https://www.iamcdocumentation.eu/api.php?action=feedcontributions&feedformat=atom&user=Celine+GuivarchIAMC-Documentation - User contributions [en]2026-05-07T16:08:43ZUser contributionsMediaWiki 1.39.15https://www.iamcdocumentation.eu/index.php?title=Macro-economy_-_IMACLIM&diff=5289Macro-economy - IMACLIM2016-10-04T11:16:01Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Macro-economy<br />
}}<br />
== A general equilibrium with rigidities ==<br />
<br />
The representation of the economy in Imaclim-R is a multi-sector (12 sectors), multi-region (12 regions) general equilibrium framework. In each region, there are 14 economic agents: one representative household, one representative firm per sector (hence 12 representative firms) and the public administration. Households receive revenues from labor and capital and from transfers from public administrations and save part of their revenues. They chose their consumptions of goods and services depending on relative prices and they pay taxes to the public administrations. Productive sectors chose their production levels to meet demand, earn profits, pay wages and dividends to households and pay taxes to public administrations. Public administrations collect taxes, make public expenditures and invest in public infrastructures, and organize transfers. Regions are linked through international markets for goods and services, and capital. <xr id="fig:imaclim_3"/> outlines these interrelationships.<br />
<br />
<figure id="fig:imaclim_3"><br />
[[File:36405263.png|none|600px|thumb|<caption> Sectoral interaction in the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
=== Households ===<br />
<br />
Each year, households maximize their current utility under constraints of both revenue received and of their time spent in transport. They save an exogenous share of their revenues. For detailed descriptions of demand formation mechanisms refer to the [[Economic_activity_-_IMACLIM|section on demand representation]].<br />
<br />
=== Public administrations ===<br />
<br />
Public administrations collect taxes, make public expenditures including investment in public infrastructures and organize transfers.<br />
<br />
Tax rates (and/or subsidies) are calibrated to their values for the model calibration year (2001). Taxes (and/or subsidies) impact upon energy, labor, revenues, added value, production, imports and exports. In the default setting of the model, tax rates are kept constant throughout the modelling period (except for in scenarios that model the introduction of a carbon tax ) although alternative assumption on tax rates can also be tested. In a scenario where a carbon tax is introduced, alternative assumptions on the use of the corresponding revenues can be modelled i.e. they are given to households via transfers, used to reduce other pre-existing tax rates or used to finance a subsidy.<br />
<br />
In the default setting public expenditures in each region are assumed to follow GDP growth rates, Alternative assumptions on the evolution of public expenditures can also be tested.<br />
<br />
Transfers are determined such that the public administration budget is at equilibrium each year. Public debt is not accounted for.<br />
<br />
=== Productive sectors ===<br />
<br />
A start point for IMACLIM is the recognition that it is almost impossible to find mathematical functions that can handle large departures from a reference equilibrium over a time period of one century and are flexible enough to encompass different scenarios of structural change resulting from the interplay between consumption styles, technologies and localization patterns (Hourcade, 1993)[[CiteRef::hourcade1993modelling]].<br />
<br />
==== Beyond the classical production function, or reconciling bottom-up and top-down approaches ====<br />
<br />
In IMACLIM-R, there is no production function, such as a constant elasticity of substitution function, to represent evolutions in production techniques (substitutions between production factors). Instead, evolutions in production techniques are represented in a recursive structure by an exchange of information between static and dynamic modules described as follows: <br />
<br />
* An annual static equilibrium module, in which the production function mimics the Leontief specification, with fixed equipment stocks and fixed intensity of labor, energy and other intermediary inputs, but with a flexible utilization rate. Solving this equilibrium at time, ''t'', provides a snapshot of the economy at this date showing a set of information about relative prices, levels of output, physical flows and profitability rates for each sector and allocation of investments among sectors.<br />
<br />
* Dynamic modules, including demography, capital dynamics and sector-specific reduced forms of technology-rich models, which take into account the economic values of the previous static equilibrium, assess the reaction of technical systems and send back this information to the static module in the form of new input-output coefficients for calculating the equilibrium at time, 't' + 1. Each year, technical choices are flexible but they modify only at the margin the input-output coefficients and labor productivity embodied in the existing equipment that result from past technical choices. This general putty-clay assumption is critical to represent the inertia in technical systems and the role of volatility in economic signals.<br />
<br />
This modelling approach allows for abandoning standard aggregate production functions, which have intrinsic limitations in cases of large departures from the reference equilibrium (Frondel et al., 2002)[[CiteRef::frondel2002capital]] and sea changes of production frontiers over several decades.<br />
<br />
As we move away from using a traditional production function, it becomes possible to highlight the influence of factors other than price on decisions affecting the allocation of resources. The use of this modeling approach requires however a comprehensive description of the temporally evolving technical characteristics of each sector.<br />
<br />
At each point in time, producers are assumed to operate under constraint of a fixed production capacity ''Cap<sub>k,i</sub>'', defined as the maximum level of physical output achievable with their installed equipment.<br />
<br />
However, the model allows short-run adjustments to market conditions through the modification of the utilization rate ''Q<sub>k,i</sub>/Cap<sub>k,i</sub>''. This represents a different approach from standard production specifications, since in Imaclim the 'capital' factor is not always fully utilized. Supply cost curves in Imaclim-R thus show static decreasing returns: production costs increase when the utilization rate of equipment approaches 1 (100 %) (See <xr id="fig:imaclim_4"/>). In principle, these decreasing returns affect all intermediary inputs and labor. However, for the sake of simplicity and because of the order of magnitude of the correlation between utilization rates and prices (Corrado and Mattey, 1997)[[CiteRef::corrado1997capacity]], we assume that the primary cause of higher production costs is higher labor costs due to overtime operations with lower productivity, costly night work and increased maintenance works. We thus set (i) fixed input-output coefficients representing that, with the current set of embodied techniques, producing one unit of good ''i'' in region ''k'' requires the fixed physical amount ''IC<sub>j,i,k</sub>'' of intermediate goods j and ''l<sub>k,i</sub>''of labor; (ii) a decreasing return parameter ''Ω<sub>k,i</sub>= Ω(Q<sub>k,i</sub>/Cap<sub>k,i</sub>)'' on wages only, at the sector level. The treatment of the cost of crude oil production is an exception. The increasing factor weighs on the mark-up rate, to convey the fact that oligopolistic producers can take advantage of capacity shortages by increasing their differential rent.<br />
<br />
This solution actually comes back to earlier works on the existence of short-run flexibility of production systems at the sectoral level with putty-clay technologies (Marshall, 1890)[[CiteRef::marshallpoe]], (Johansen, 1959)[[CiteRef::johansen1959substitution]] demonstrating that this flexibility comes less from input substitution than from variations in differentiated capacity utilization rates.<br />
<br />
<figure id="fig:imaclim_4"><br />
[[File:36405273.png|none|600px|thumb|<caption> Sectoral interaction in the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
===== Equations =====<br />
<br />
We derive an expression of mean production costs ''Cm<sub>k,i</sub>'', that depends on the prices of intermediate goods ''pIC<sub>j,i,k</sub>'', input-ouput coefficients ''IC<sub>j,i,k</sub>'' and ''l<sub>k,i</sub>'', wages ''w<sub>k,i</sub>'', and production levels through the decreasing return factor ''Ω<sub>k,i</sub>'' applied to labor costs (including payroll taxes).<br />
<br />
[[File:36405274.png]]<br />
<br />
Market prices and associated profits depend on assumptions regarding the degree of market competition in each sector (e.g. perfect competition or monopoly). Unless otherwise stated, perfect competition is assumed in every production sector, with the market price equal to the marginal production cost.<br />
<br />
Producer prices are equal to the sum of mean production costs and mean profits. In the current version of the model, all sectors apply a constant sector-specific mark-up rate ''p<sub>k,i</sub>'' so that the producer price is given by equation (2). This constant mark-up corresponds to a standard profit-maximization for producers whose mean production costs follow equation (1) and who are price-takers, provided that the decreasing return factor can be approximated by an exponential function of utilization rate.<br />
<br />
[[File:36405275.png]]<br />
<br />
This equation is an inverse supply curve: it shows how a representative producer decides their level of output ''Q<sub>k,i</sub>'' (which is included in the ''Ω<sub>k,i</sub>''factor) as a function of all prices and real wages.<br />
<br />
From equation (2) we derive wages and profits in each sector:<br />
<br />
[[File:36405276.png]]<br />
<br />
The cost function shows fixed technical coefficients and therefore does not allow for substitution between production factors when relative prices change within the new static equilibrium. Only the level of output ''Q<sub>k,i </sub>'' can be adjusted according to these price changes.<br />
<br />
=== Markets ===<br />
<br />
==== Markets of goods and services ====<br />
<br />
In the Imaclim-R model, all intermediate and final goods are internationally tradable and total demand for each good (the sum of households' consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports (see section on international trade XXXXXXXXXXXXXXXXX). Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices calculated in the static equilibrium such that demand and supply are equal.<br />
<br />
'''Price'''<br />
<br />
In each region ''k'' and sector ''i'', the price equation is:<br />
<br />
[[File:36405277.png]]'''(5)'''<br />
<br />
where ''π<sub>k,i</sub>'' is a markup, ''IC<sub>j,i,k</sub>'' are intermediate consumption of good ''j'' in sector ''i'' in region ''k'', and ''Ω<sub>k,i</sub>'' is an increasing cost (or decreasing returns) function of the productive capacities utilization rate. This function is applied to labor costs (which include wages w<sub>k,i</sub> and labor taxes tax<sub>k,i</sub>).<br />
<br />
'' The functional form for Ω'' is:<br />
<br />
[[File:36405278.png]]'''(6)'''<br />
<br />
Regional prices thus correspond to the addition of average regional production costs and a margin. This markup, which is fixed in the static equilibrium, encapsulates Ricardian and scarcity rents at the same time and increases with the utilization rate of production capacities in the oil sector.<br />
<br />
A further parameter for the oil sector is that Middle-Eastern producers are considered 'swing producers' who are free to strategically set their investment decisions and, until they reach their depletion constraints, to control oil prices through the utilization rate of their production capacities (Kaufmann et al, 2004)[[CiteRef::kaufmann2004does]]. This possibility is justified by the temporary reinforcement of their market power due to the stagnation and decline of conventional oil in the rest of the world. They can in particular decide to slow the development of production capacities below its maximum rate in order to adjust the oil price according to their rent-seeking objectives. They anticipate the level of capacities that will make it possible for them to reach their goals, on the basis of projections of total oil demand and production in other regions.<br />
<br />
==== Capital markets ====<br />
<br />
A share (''shareExpK'') of gross domestic savings (GRB) is internationally tradable, and distributed via an international capital pool. Each regions receives a share of the international pool (''shareImpK)''. In the default model setting, both shares (''shareExpK and shareImpK'') are exogenous: ''shareExpK'' is exponentially reduced such that international financial imbalances disappear by 2050 and ''shareImpK'' remains constant throughout the simulation period.<br />
<br />
The remaining share of domestic savings and imported capital (NRB) are then invested in each region respectively.<br />
<br />
[[File:36405279.png]] ''' (7,8,9)'''<br />
<br />
The total amount of money ''InvFin<sub>k,i</sub>'' available for investment in sector ''i'' in the region ''k'' allows new capacities ''DCap<sub>k,i</sub>'' to be constructed at a cost ''pCap<sub>k,i</sub>'' (equation 9-3-5). The cost ''pCap<sub>k,i</sub>'' depends on the quantities ''β<sub>j,i,k</sub>'' and the prices ''pI<sub>k,j</sub>'' of goods ''j'' required by the construction of a new unit of capacity in sector ''i'' and in region ''k''. Coefficient ''β<sub>j,i,k</sub>'' is the amount of good ''j'' necessary to constuct the equipment corresponding to one new unit of production capacity in sector i of the region k. Finally, in each region, the total demand for goods for building new capacities is given by the last equation below.<br />
<br />
[[File:36405280.png]]''' (10,11,12)'''<br />
<br />
Each sector anticipates future production levels through an anticipation of future prices and demand and formulates the corresponding investment demand. Total available investment ''I<sub>k,j</sub>'' is then distributed among sectors according to their demand.<br />
<br />
==== Labour markets ====<br />
<br />
At each time step, producers operate in static equilibria with a fixed input of labor per unit of output. This labor input, corresponding to labor productivity, evolves between two yearly equilibria following exogenous trends in labor productivity.<br />
<br />
Three of the model features explain the possibility of under-utilization of labor as a factor of production, and thus unemployment. First, rigidity of real wages, represented by a wage curve can prevent wages falling to their market-clearing level. Put another way, instantaneous adjustment of wages to the economic context in the static equilibrium does not occur in an optimal manner. Second, in the static equilibrium, the fixed technologies (Leontief coefficients even for labor input) prevent substitution among production factors in the short run. And third, the installed productive capital is not mobile across sectors, which creates rigidities in the reallocations of production between sectors when relative prices change.<br />
<br />
In each region ''k'', each sector employs the labor force ''l<sub>k,i</sub><sup>.</sup>Q<sub>k,i</sub>'', where ''l<sub>k,i</sub>'' is the unitary labor input (in hours worked) and Q<sub>k,i</sub> the production. The underutilization of the labor force, equivalently referred to as the 'unemployment rate' [2] in the following, ''_z<sub>k</sub>'' is therefore equal to one minus the ratio of the employed labor force across all sectors over ''L<sub>k</sub>'', the total labor force:<br />
<br />
[[File:36405281.png]] ''' (13)'''<br />
<br />
Obviously, this definition of the unemployment rate is a limitation of the current calibration of the model. Future developments will look into the possibility to differentiate labor markets per regions. However, one important difficulty lies in the lack of reliable data on the underutilization of the labor forces in all regions, in particular due to informal economy, very diverse accounting rules for unemployment rates and variations in hours worked per person across countries. No endogenous mobility of workers between regions is accounted for in the model. Thus twelve separate labor markets are represented.<br />
<br />
We chose to model labor market imperfections through an aggregate regional ''wage curve'' that links real wage levels to the unemployment rate. This representation is based on labor theories developed in the 1980s and early 1990s in which an aggregate wage curve, or ''wage setting curve'', is the primary distinguishing feature (an overview can be found in Layard et al., 2005[[CiteRef::layard2005unemployment]]; Lindbeck, 1993[[CiteRef::lindbeck1993unemployment]]; or Phelps, 1992[[CiteRef::phelps1992consumer]]). The novel approach of these models, when introduced, was to replace the conventional labor supply curve with a negatively-sloped curve linking the level of wages to the level of unemployment. The interpretation of this wage curve is given either by the bargaining approach (Layard and Nickell, 1986)[[CiteRef::layard1986unemployment]] or the wage-efficiency approach (Shapiro and Stiglitz, 1984)[[CiteRef::shapiro1984equilibrium]]. Both interpretations rely on the fact that unemployment represents an outside threat that leads workers to accept lower wages the greater the threat. The bargaining approach emphasizes the role of workers' (or union) power in the wage setting negotiations, power that is weakened when unemployment is high. The wage-efficiency approach takes the firms' point of view and assumes that firms set wage levels so as to discourage shirking; this level is lower when the threat of not finding a job after being caught shirking gets higher. The wage curve specification allows the theories to be consistent with both involuntary unemployment and the fact that real wages fluctuate less than the theory of the conventional flexible labor supply curve predicts. Microeconometric evidence for such formulations was given in a seminal contribution by (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]].<br />
<br />
In practice, the wage curve for each region k in our model is implemented through the relation:<br />
<br />
[[File:36405282.png]]''' (14)'''<br />
<br />
where ''w'' is the hourly nominal wage level, ''pind'' the consumption price index, ''z'' the unemployment rate, ''ref'' indexes represent the values of the variables at the calibration date, ''pindref'' is derived from the final consumption prices and volumes at the calibration date, ''wref'' is calibrated from the total salaries per sector in the GTAP 6 database (Reference?) and the shares of labor force per sector are taken from International Labor Organisation statistics. By default, ''aw'' is calibrated to 1 and evolves in parallel to labor productivity so that unitary real wages are indexed on labor productivity. ''zref'' represents the underutilization of the labor force at the calibration date. ''f'' is a function equal to one when the unemployment rate is equal to its calibration level, and is negatively sloped, representing a negative elasticity of wages level to unemployment [3]. Choosing a functional form and calibrating the function is particularly tricky, notably due to the lack of reliable data to fully inform the functioning of the labor markets worldwide. We chose a function of the form a.(1-tanh(c.z)), and calibrate the parameters a and c so as to have the desired value and elasticity at the calibration point.<br />
<br />
By default, we assume all regions' labor markets to be identical and set the underutilization of the labor force at 10% (Contrary to the definition by the U.S. Bureau of Labor Statistics, the level of unemployment is expressed here in terms of worked hours and not in terms of persons)[4] and the wage curve elasticity at -0.1 for all regions (This is a value emerging from many econometric studies, e.g. (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]], (Blanchflower and Oswald 2005). [http://halshs.archives-ouvertes.fr/docs/00/72/44/87/PDF/Guivarch_et_al_2011_Costs_climate_policies_second_best_world_labour_market_imperfections.pdf Guivarch et al. (2011)][[CiteRef::guivarch2011costs]] analyzes the critical role of labour markets imperfections, and in particular of the value of the wage curve elasticity, on the formation of climate stabilization costs.<br />
<br />
=== International Trade ===<br />
<br />
For each good, exports from all world regions are blended into an international variety, which is then imported by each region based on its specific terms-of-trade measured between the price of the aggregate international variety, and the production price of the domestic good.<br />
<br />
International trade is treated 'upstream': the competition of the domestic and imported varieties of each good is settled in an aggregate manner, not at the level of each domestic agent.<br />
<br />
A well-known modelling issue is then to avoid 'knife-edge' solutions, ''i.e.'' to prevent cheaper goods systematically winning market shares over more expensive ones. We follow the most common approach to addressing this issue, the Armington (1969)[[CiteRef::sassi2010im]] specification, which assumes that the domestic and imported varieties of the same good aggregate in a common quantity index, although in an imperfectly substitutable way which is typically derived from assuming that the two varieties combine through a constant elasticity of substitution (CES) function. This allows representing markets in which both domestic production and imports have a share, despite the fact that they are priced differently.<br />
<br />
Despite its straightforward treatment of imperfect product competition, the Armington specification has the major drawback of introducing aggregate volumes that do not sum up the volumes of imported and domestic varieties. While this shortcoming can be ignored for non-descript 'composite' goods, where quantity units are indexes of no direct significance to the economy-energy-environment interactions, it is not compatible with the obvious need to track energy balances expressed in real physical units. Competition between energy goods is thus settled through simplified specifications. In the case of national models, the hypothesis of a constant elasticity of substitution is retained, but the construction of a composite index is dropped. Imports and domestic production are simply summed up to form the resource that is available to the importing economy. For the multi-regional version of Imaclim, a market-sharing formula is implemented. The international market buys energy exports at different prices and sells them at a single average world price to importers; shares of exporters on the international market and regional shares of domestic ''vs.'' imported energy goods dependent on relative prices, export and import taxes, and market fragmentation parameters that are calibrated to reproduce the existing markets structure.<br />
<br />
For all goods, export prices include the producer prices, export taxes or subsidies, and average transportation costs. This allows the model to take into account that increasing energy prices would impact on transportation costs and eventually on commercial flows and industrial location patterns.<br />
<br />
''Armington goods'' [[File:36405284.png]]''' (15,16,17)'''<br />
[[File:36405285.png]]''' (18,19,20)'''<br />
[[File:36405286.png]]''' (21,22)'''<br />
<br />
''Energy goods''<br />
<br />
[[File:36405287.png]]''' (23,24,25)'''<br />
[[File:36405288.png]]''' (26,27,28)'''<br />
[[File:36405289.png]]''' (29,30,31)'''<br />
<br />
<br />
-----<br />
<br />
[1] The treatment of the cost of crude oil production is an exception. The increasing factor weighs on the mark-up rate, to convey the fact that oligopolistic producers can take advantage of capacity shortages by increasing their differential rent.<br />
<br />
[2] Obviously, this is a limitation of the current calibration of the model. Future developments will look into the possibility to differentiate labor markets per regions. However, one important difficulty lies in the lack of reliable data on the underutilization of the labor forces in all regions, in particular due to informal economy, very diverse accounting rules for unemployment rates and variations in hours worked per person across countries.<br />
<br />
[3] Choosing a functional form and calibrating the function is particularly tricky, notably due to the lack of reliable data to fully inform the functioning of the labor markets worldwide. We chose a function of the form a.(1-tanh(c.z)), and calibrate the parameters a and c so as to have the desired value and elasticity at the calibration point.<br />
<br />
[4] Contrary to the definition by the U.S. Bureau of Labor Statistics, the level of unemployment is expressed here in terms of worked hours and not in terms of persons.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Macro-economy_-_IMACLIM&diff=5265Macro-economy - IMACLIM2016-09-29T16:51:51Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Macro-economy<br />
}}<br />
== A general equilibrium with rigidities ==<br />
<br />
The representation of the economy in Imaclim-R is a multi-sector (12 sectors), multi-region (12 regions) general equilibrium framework. In each region, there are 14 economic agents: one representative household, one representative firm per sector (hence 12 representative firms) and the public administration. Households receive revenues from labor and capital and from transfers from public administrations and save part of their revenues. They chose their consumptions of goods and services depending on relative prices and they pay taxes to the public administrations. Productive sectors chose their production levels to meet demand, earn profits, pay wages and dividends to households and pay taxes to public administrations. Public administrations collect taxes, make public expenditures and invest in public infrastructures, and organize transfers. Regions are linked through international markets for goods and services, and capital. <xr id="fig:imaclim_3"/> outlines these interrelationships.<br />
<br />
<figure id="fig:imaclim_3"><br />
[[File:36405263.png|none|600px|thumb|<caption> Sectoral interaction in the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
=== Households ===<br />
<br />
Each year, households maximize their current utility under constraints of both revenue received and of their time spent in transport. They save an exogenous share of their revenues. For detailed descriptions of demand formation mechanisms refer to the [[Economic_activity_-_IMACLIM|section on demand representation]].<br />
<br />
=== Public administrations ===<br />
<br />
Public administrations collect taxes, make public expenditures including investment in public infrastructures and organize transfers.<br />
<br />
Tax rates (and/or subsidies) are calibrated to their values for the model calibration year (2001). Taxes (and/or subsidies) impact upon energy, labor, revenues, added value, production, imports and exports. In the default setting of the model, tax rates are kept constant throughout the modelling period (except for in scenarios that model the introduction of a carbon tax ) although alternative assumption on tax rates can also be tested. In a scenario where a carbon tax is introduced, alternative assumptions on the use of the corresponding revenues can be modelled i.e. they are given to households via transfers, used to reduce other pre-existing tax rates or used to finance a subsidy.<br />
<br />
In the default setting public expenditures in each region are assumed to follow GDP growth rates, Alternative assumptions on the evolution of public expenditures can also be tested.<br />
<br />
Transfers are determined such that the public administration budget is at equilibrium each year. Public debt is not accounted for.<br />
<br />
=== Productive sectors ===<br />
<br />
A start point for IMACLIM is the recognition that it is almost impossible to find mathematical functions that can handle large departures from a reference equilibrium over a time period of one century and are flexible enough to encompass different scenarios of structural change resulting from the interplay between consumption styles, technologies and localization patterns (Hourcade, 1993)[[CiteRef::hourcade1993modelling]].<br />
<br />
==== Beyond the classical production function, or reconciling bottom-up and top-down approaches ====<br />
<br />
In IMACLIM-R, there is no production function, such as a constant elasticity of substitution function, to represent evolutions in production techniques (substitutions between production factors). Instead, evolutions in production techniques are represented in a recursive structure by an exchange of information between static and dynamic modules described as follows: <br />
<br />
* An annual static equilibrium module, in which the production function mimics the Leontief specification, with fixed equipment stocks and fixed intensity of labor, energy and other intermediary inputs, but with a flexible utilization rate. Solving this equilibrium at time, ''t'', provides a snapshot of the economy at this date showing a set of information about relative prices, levels of output, physical flows and profitability rates for each sector and allocation of investments among sectors.<br />
<br />
* Dynamic modules, including demography, capital dynamics and sector-specific reduced forms of technology-rich models, which take into account the economic values of the previous static equilibrium, assess the reaction of technical systems and send back this information to the static module in the form of new input-output coefficients for calculating the equilibrium at time, 't' + 1. Each year, technical choices are flexible but they modify only at the margin the input-output coefficients and labor productivity embodied in the existing equipment that result from past technical choices. This general putty-clay assumption is critical to represent the inertia in technical systems and the role of volatility in economic signals.<br />
<br />
This modelling approach allows for abandoning standard aggregate production functions, which have intrinsic limitations in cases of large departures from the reference equilibrium (Frondel et al., 2002)[[CiteRef::frondel2002capital]] and sea changes of production frontiers over several decades.<br />
<br />
As we move away from using a traditional production function, it becomes possible to highlight the influence of factors other than price on decisions affecting the allocation of resources. The use of this modeling approach requires however a comprehensive description of the temporally evolving technical characteristics of each sector.<br />
<br />
At each point in time, producers are assumed to operate under constraint of a fixed production capacity ''Cap<sub>k,i</sub>'', defined as the maximum level of physical output achievable with their installed equipment.<br />
<br />
However, the model allows short-run adjustments to market conditions through the modification of the utilization rate ''Q<sub>k,i</sub>/Cap<sub>k,i</sub>''. This represents a different approach from standard production specifications, since in Imaclim the 'capital' factor is not always fully utilized. Supply cost curves in Imaclim-R thus show static decreasing returns: production costs increase when the utilization rate of equipment approaches 1 (100 %) (See <xr id="fig:imaclim_4"/>). In principle, these decreasing returns affect all intermediary inputs and labor. However, for the sake of simplicity and because of the order of magnitude of the correlation between utilization rates and prices (Corrado and Mattey, 1997)[[CiteRef::corrado1997capacity]], we assume that the primary cause of higher production costs is higher labor costs due to overtime operations with lower productivity, costly night work and increased maintenance works. We thus set (i) fixed input-output coefficients representing that, with the current set of embodied techniques, producing one unit of good ''i'' in region ''k'' requires the fixed physical amount ''IC<sub>j,i,k</sub>'' of intermediate goods j and ''l<sub>k,i</sub>''of labor; (ii) a decreasing return parameter ''Ω<sub>k,i</sub>= Ω(Q<sub>k,i</sub>/Cap<sub>k,i</sub>)'' on wages only, at the sector level [1].<br />
<br />
This solution actually comes back to earlier works on the existence of short-run flexibility of production systems at the sectoral level with putty-clay technologies (Marshall, 1890)[[CiteRef::marshallpoe]], (Johansen, 1959)[[CiteRef::johansen1959substitution]] demonstrating that this flexibility comes less from input substitution than from variations in differentiated capacity utilization rates.<br />
<br />
<figure id="fig:imaclim_4"><br />
[[File:36405273.png|none|600px|thumb|<caption> Sectoral interaction in the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
===== Equations =====<br />
<br />
We derive an expression of mean production costs ''Cm<sub>k,i</sub>'', that depends on the prices of intermediate goods ''pIC<sub>j,i,k</sub>'', input-ouput coefficients ''IC<sub>j,i,k</sub>'' and ''l<sub>k,i</sub>'', wages ''w<sub>k,i</sub>'', and production levels through the decreasing return factor ''Ω<sub>k,i</sub>'' applied to labor costs (including payroll taxes).<br />
<br />
[[File:36405274.png]]<br />
<br />
Market prices and associated profits depend on assumptions regarding the degree of market competition in each sector (e.g. perfect competition or monopoly). Unless otherwise stated, perfect competition is assumed in every production sector, with the market price equal to the marginal production cost.<br />
<br />
Producer prices are equal to the sum of mean production costs and mean profits. In the current version of the model, all sectors apply a constant sector-specific mark-up rate ''p<sub>k,i</sub>'' so that the producer price is given by equation (2). This constant mark-up corresponds to a standard profit-maximization for producers whose mean production costs follow equation (1) and who are price-takers, provided that the decreasing return factor can be approximated by an exponential function of utilization rate.<br />
<br />
[[File:36405275.png]]<br />
<br />
This equation is an inverse supply curve: it shows how a representative producer decides their level of output ''Q<sub>k,i</sub>'' (which is included in the ''Ω<sub>k,i</sub>''factor) as a function of all prices and real wages.<br />
<br />
From equation (2) we derive wages and profits in each sector:<br />
<br />
[[File:36405276.png]]<br />
<br />
The cost function shows fixed technical coefficients and therefore does not allow for substitution between production factors when relative prices change within the new static equilibrium. Only the level of output ''Q<sub>k,i </sub>'' can be adjusted according to these price changes.<br />
<br />
=== Markets ===<br />
<br />
==== Markets of goods and services ====<br />
<br />
In the Imaclim-R model, all intermediate and final goods are internationally tradable and total demand for each good (the sum of households' consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports (see section on international trade XXXXXXXXXXXXXXXXX). Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices calculated in the static equilibrium such that demand and supply are equal.<br />
<br />
'''Price'''<br />
<br />
In each region ''k'' and sector ''i'', the price equation is:<br />
<br />
[[File:36405277.png]]'''(5)'''<br />
<br />
where ''π<sub>k,i</sub>'' is a markup, ''IC<sub>j,i,k</sub>'' are intermediate consumption of good ''j'' in sector ''i'' in region ''k'', and ''Ω<sub>k,i</sub>'' is an increasing cost (or decreasing returns) function of the productive capacities utilization rate. This function is applied to labor costs (which include wages w<sub>k,i</sub> and labor taxes tax<sub>k,i</sub>).<br />
<br />
'' The functional form for Ω'' is:<br />
<br />
[[File:36405278.png]]'''(6)'''<br />
<br />
Regional prices thus correspond to the addition of average regional production costs and a margin. This markup, which is fixed in the static equilibrium, encapsulates Ricardian and scarcity rents at the same time and increases with the utilization rate of production capacities in the oil sector.<br />
<br />
A further parameter for the oil sector is that Middle-Eastern producers are considered 'swing producers' who are free to strategically set their investment decisions and, until they reach their depletion constraints, to control oil prices through the utilization rate of their production capacities (Kaufmann et al, 2004)[[CiteRef::kaufmann2004does]]. This possibility is justified by the temporary reinforcement of their market power due to the stagnation and decline of conventional oil in the rest of the world. They can in particular decide to slow the development of production capacities below its maximum rate in order to adjust the oil price according to their rent-seeking objectives. They anticipate the level of capacities that will make it possible for them to reach their goals, on the basis of projections of total oil demand and production in other regions.<br />
<br />
==== Capital markets ====<br />
<br />
A share (''shareExpK'') of gross domestic savings (GRB) is internationally tradable, and distributed via an international capital pool. Each regions receives a share of the international pool (''shareImpK)''. In the default model setting, both shares (''shareExpK and shareImpK'') are exogenous: ''shareExpK'' is exponentially reduced such that international financial imbalances disappear by 2050 and ''shareImpK'' remains constant throughout the simulation period.<br />
<br />
The remaining share of domestic savings and imported capital (NRB) are then invested in each region respectively.<br />
<br />
[[File:36405279.png]] ''' (7,8,9)'''<br />
<br />
The total amount of money ''InvFin<sub>k,i</sub>'' available for investment in sector ''i'' in the region ''k'' allows new capacities ''DCap<sub>k,i</sub>'' to be constructed at a cost ''pCap<sub>k,i</sub>'' (equation 9-3-5). The cost ''pCap<sub>k,i</sub>'' depends on the quantities ''β<sub>j,i,k</sub>'' and the prices ''pI<sub>k,j</sub>'' of goods ''j'' required by the construction of a new unit of capacity in sector ''i'' and in region ''k''. Coefficient ''β<sub>j,i,k</sub>'' is the amount of good ''j'' necessary to constuct the equipment corresponding to one new unit of production capacity in sector i of the region k. Finally, in each region, the total demand for goods for building new capacities is given by the last equation below.<br />
<br />
[[File:36405280.png]]''' (10,11,12)'''<br />
<br />
Each sector anticipates future production levels through an anticipation of future prices and demand and formulates the corresponding investment demand. Total available investment ''I<sub>k,j</sub>'' is then distributed among sectors according to their demand.<br />
<br />
==== Labour markets ====<br />
<br />
At each time step, producers operate in static equilibria with a fixed input of labor per unit of output. This labor input, corresponding to labor productivity, evolves between two yearly equilibria following exogenous trends in labor productivity.<br />
<br />
Three of the model features explain the possibility of under-utilization of labor as a factor of production, and thus unemployment. First, rigidity of real wages, represented by a wage curve can prevent wages falling to their market-clearing level. Put another way, instantaneous adjustment of wages to the economic context in the static equilibrium does not occur in an optimal manner. Second, in the static equilibrium, the fixed technologies (Leontief coefficients even for labor input) prevent substitution among production factors in the short run. And third, the installed productive capital is not mobile across sectors, which creates rigidities in the reallocations of production between sectors when relative prices change.<br />
<br />
In each region ''k'', each sector employs the labor force ''l<sub>k,i</sub><sup>.</sup>Q<sub>k,i</sub>'', where ''l<sub>k,i</sub>'' is the unitary labor input (in hours worked) and Q<sub>k,i</sub> the production. The underutilization of the labor force, equivalently referred to as the 'unemployment rate' [2] in the following, ''_z<sub>k</sub>'' is therefore equal to one minus the ratio of the employed labor force across all sectors over ''L<sub>k</sub>'', the total labor force:<br />
<br />
[[File:36405281.png]] ''' (13)'''<br />
<br />
No endogenous mobility of workers between regions is accounted for in the model. Thus twelve separate labor markets are represented.<br />
<br />
We chose to model labor market imperfections through an aggregate regional ''wage curve'' that links real wage levels to the unemployment rate. This representation is based on labor theories developed in the 1980s and early 1990s in which an aggregate wage curve, or ''wage setting curve'', is the primary distinguishing feature (an overview can be found in Layard et al., 2005[[CiteRef::layard2005unemployment]]; Lindbeck, 1993[[CiteRef::lindbeck1993unemployment]]; or Phelps, 1992[[CiteRef::phelps1992consumer]]). The novel approach of these models, when introduced, was to replace the conventional labor supply curve with a negatively-sloped curve linking the level of wages to the level of unemployment. The interpretation of this wage curve is given either by the bargaining approach (Layard and Nickell, 1986)[[CiteRef::layard1986unemployment]] or the wage-efficiency approach (Shapiro and Stiglitz, 1984)[[CiteRef::shapiro1984equilibrium]]. Both interpretations rely on the fact that unemployment represents an outside threat that leads workers to accept lower wages the greater the threat. The bargaining approach emphasizes the role of workers' (or union) power in the wage setting negotiations, power that is weakened when unemployment is high. The wage-efficiency approach takes the firms' point of view and assumes that firms set wage levels so as to discourage shirking; this level is lower when the threat of not finding a job after being caught shirking gets higher. The wage curve specification allows the theories to be consistent with both involuntary unemployment and the fact that real wages fluctuate less than the theory of the conventional flexible labor supply curve predicts. Microeconometric evidence for such formulations was given in a seminal contribution by (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]].<br />
<br />
In practice, the wage curve for each region k in our model is implemented through the relation:<br />
<br />
[[File:36405282.png]]''' (14)'''<br />
<br />
where ''w'' is the hourly nominal wage level, ''pind'' the consumption price index, ''z'' the unemployment rate, ''ref'' indexes represent the values of the variables at the calibration date, ''pindref'' is derived from the final consumption prices and volumes at the calibration date, ''wref'' is calibrated from the total salaries per sector in the GTAP 6 database (Reference?) and the shares of labor force per sector are taken from International Labor Organisation statistics. By default, ''aw'' is calibrated to 1 and evolves in parallel to labor productivity so that unitary real wages are indexed on labor productivity. ''zref'' represents the underutilization of the labor force at the calibration date. ''f'' is a function equal to one when the unemployment rate is equal to its calibration level, and is negatively sloped, representing a negative elasticity of wages level to unemployment [3].<br />
<br />
By default, we assume all regions' labor markets to be identical and set the underutilization of the labor force at 10% [4] and the wage curve elasticity at -0.1 for all regions (This is a value emerging from many econometric studies, e.g. (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]], (Blanchflower and Oswald 2005). [http://halshs.archives-ouvertes.fr/docs/00/72/44/87/PDF/Guivarch_et_al_2011_Costs_climate_policies_second_best_world_labour_market_imperfections.pdf Guivarch et al. (2011)][[CiteRef::guivarch2011costs]] analyzes the critical role of labour markets imperfections, and in particular of the value of the wage curve elasticity, on the formation of climate stabilization costs.<br />
<br />
=== International Trade ===<br />
<br />
For each good, exports from all world regions are blended into an international variety, which is then imported by each region based on its specific terms-of-trade measured between the price of the aggregate international variety, and the production price of the domestic good.<br />
<br />
International trade is treated 'upstream': the competition of the domestic and imported varieties of each good is settled in an aggregate manner, not at the level of each domestic agent.<br />
<br />
A well-known modelling issue is then to avoid 'knife-edge' solutions, ''i.e.'' to prevent cheaper goods systematically winning market shares over more expensive ones. We follow the most common approach to addressing this issue, the Armington (1969)[[CiteRef::sassi2010im]] specification, which assumes that the domestic and imported varieties of the same good aggregate in a common quantity index, although in an imperfectly substitutable way which is typically derived from assuming that the two varieties combine through a constant elasticity of substitution (CES) function. This allows representing markets in which both domestic production and imports have a share, despite the fact that they are priced differently.<br />
<br />
Despite its straightforward treatment of imperfect product competition, the Armington specification has the major drawback of introducing aggregate volumes that do not sum up the volumes of imported and domestic varieties. While this shortcoming can be ignored for non-descript 'composite' goods, where quantity units are indexes of no direct significance to the economy-energy-environment interactions, it is not compatible with the obvious need to track energy balances expressed in real physical units. Competition between energy goods is thus settled through simplified specifications. In the case of national models, the hypothesis of a constant elasticity of substitution is retained, but the construction of a composite index is dropped. Imports and domestic production are simply summed up to form the resource that is available to the importing economy. For the multi-regional version of Imaclim, a market-sharing formula is implemented. The international market buys energy exports at different prices and sells them at a single average world price to importers; shares of exporters on the international market and regional shares of domestic ''vs.'' imported energy goods dependent on relative prices, export and import taxes, and market fragmentation parameters that are calibrated to reproduce the existing markets structure.<br />
<br />
For all goods, export prices include the producer prices, export taxes or subsidies, and average transportation costs. This allows the model to take into account that increasing energy prices would impact on transportation costs and eventually on commercial flows and industrial location patterns.<br />
<br />
''Armington goods'' [[File:36405284.png]]''' (15,16,17)'''<br />
[[File:36405285.png]]''' (18,19,20)'''<br />
[[File:36405286.png]]''' (21,22)'''<br />
<br />
''Energy goods''<br />
<br />
[[File:36405287.png]]''' (23,24,25)'''<br />
[[File:36405288.png]]''' (26,27,28)'''<br />
[[File:36405289.png]]''' (29,30,31)'''<br />
<br />
<br />
-----<br />
<br />
[1] The treatment of the cost of crude oil production is an exception. The increasing factor weighs on the mark-up rate, to convey the fact that oligopolistic producers can take advantage of capacity shortages by increasing their differential rent.<br />
<br />
[2] Obviously, this is a limitation of the current calibration of the model. Future developments will look into the possibility to differentiate labor markets per regions. However, one important difficulty lies in the lack of reliable data on the underutilization of the labor forces in all regions, in particular due to informal economy, very diverse accounting rules for unemployment rates and variations in hours worked per person across countries.<br />
<br />
[3] Choosing a functional form and calibrating the function is particularly tricky, notably due to the lack of reliable data to fully inform the functioning of the labor markets worldwide. We chose a function of the form a.(1-tanh(c.z)), and calibrate the parameters a and c so as to have the desired value and elasticity at the calibration point.<br />
<br />
[4] Contrary to the definition by the U.S. Bureau of Labor Statistics, the level of unemployment is expressed here in terms of worked hours and not in terms of persons.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Macro-economy_-_IMACLIM&diff=5264Macro-economy - IMACLIM2016-09-29T16:39:39Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Macro-economy<br />
}}<br />
== A general equilibrium with rigidities ==<br />
<br />
The representation of the economy in Imaclim-R is a multi-sector (12 sectors), multi-region (12 regions) general equilibrium framework. In each region, there are 14 economic agents: one representative household, one representative firm per sector (hence 12 representative firms) and the public administration. Households receive revenues from labor and capital and from transfers from public administrations and save part of their revenues. They chose their consumptions of goods and services depending on relative prices and they pay taxes to the public administrations. Productive sectors chose their production levels to meet demand, earn profits, pay wages and dividends to households and pay taxes to public administrations. Public administrations collect taxes, make public expenditures and invest in public infrastructures, and organize transfers. Regions are linked through international markets for goods and services, and capital. <xr id="fig:imaclim_3"/> outlines these interrelationships.<br />
<br />
<figure id="fig:imaclim_3"><br />
[[File:36405263.png|none|600px|thumb|<caption> Sectoral interaction in the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
=== Households ===<br />
<br />
Each year, households maximize their current utility under constraints of both revenue received and of their time spent in transport. They save an exogenous share of their revenues. For detailed descriptions of demand formation mechanisms refer to the [[Economic_activity_-_IMACLIM|section on demand representation]].<br />
<br />
=== Public administrations ===<br />
<br />
Public administrations collect taxes, make public expenditures including investment in public infrastructures and organize transfers.<br />
<br />
Tax rates (and/or subsidies) are calibrated to their values for the model calibration year (2001). Taxes (and/or subsidies) impact upon energy, labor, revenues, added value, production, imports and exports. In the default setting of the model, tax rates are kept constant throughout the modelling period (except for in scenarios that model the introduction of a carbon tax ) although alternative assumption on tax rates can also be tested. In a scenario where a carbon tax is introduced, alternative assumptions on the use of the corresponding revenues can be modelled i.e. they are given to households via transfers, used to reduce other pre-existing tax rates or used to finance a subsidy.<br />
<br />
In the default setting public expenditures in each region are assumed to follow GDP growth rates, Alternative assumptions on the evolution of public expenditures can also be tested.<br />
<br />
Transfers are determined such that the public administration budget is at equilibrium each year. Public debt is not accounted for.<br />
<br />
=== Productive sectors ===<br />
<br />
A start point for IMACLIM is the recognition that it is almost impossible to find mathematical functions that can handle large departures from a reference equilibrium over a time period of one century and are flexible enough to encompass different scenarios of structural change resulting from the interplay between consumption styles, technologies and localization patterns (Hourcade, 1993)[[CiteRef::hourcade1993modelling]].<br />
<br />
==== Beyond the classical production function, or reconciling bottom-up and top-down approaches ====<br />
<br />
In IMACLIM-R, there is no production function, such as a constant elasticity of substitution function, to represent evolutions in production techniques (substitutions between production factors). Instead, evolutions in production techniques are represented in a recursive structure by an exchange of information between static and dynamic modules described as follows: <br />
<br />
* An annual static equilibrium module, in which the production function mimics the Leontief specification, with fixed equipment stocks and fixed intensity of labor, energy and other intermediary inputs, but with a flexible utilization rate. Solving this equilibrium at time, ''t'', provides a snapshot of the economy at this date showing a set of information about relative prices, levels of output, physical flows and profitability rates for each sector and allocation of investments among sectors.<br />
<br />
* Dynamic modules, including demography, capital dynamics and sector-specific reduced forms of technology-rich models, which take into account the economic values of the previous static equilibrium, assess the reaction of technical systems and send back this information to the static module in the form of new input-output coefficients for calculating the equilibrium at time, ""t"" + 1. Each year, technical choices are flexible but they modify only at the margin the input-output coefficients and labor productivity embodied in the existing equipment that result from past technical choices. This general putty-clay assumption is critical to represent the inertia in technical systems and the role of volatility in economic signals.<br />
<br />
This modelling approach allows for abandoning standard aggregate production functions, which have intrinsic limitations in cases of large departures from the reference equilibrium (Frondel et al., 2002)[[CiteRef::frondel2002capital]] and sea changes of production frontiers over several decades.<br />
<br />
As we move away from using a traditional production function, it becomes possible to highlight the influence of factors other than price on decisions affecting the allocation of resources. The use of this modeling approach requires however a comprehensive description of the temporally evolving technical characteristics of each sector.<br />
<br />
At each point in time, producers are assumed to operate under constraint of a fixed production capacity ''Cap<sub>k,i</sub>'', defined as the maximum level of physical output achievable with their installed equipment.<br />
<br />
However, the model allows short-run adjustments to market conditions through the modification of the utilization rate ''Q<sub>k,i</sub>/Cap<sub>k,i</sub>''. This represents a different approach from standard production specifications, since in Imaclim the 'capital' factor is not always fully utilized. Supply cost curves in Imaclim-R thus show static decreasing returns: production costs increase when the utilization rate of equipment approaches 1 (100 %) (See <xr id="fig:imaclim_4"/>). In principle, these decreasing returns affect all intermediary inputs and labor. However, for the sake of simplicity and because of the order of magnitude of the correlation between utilization rates and prices (Corrado and Mattey, 1997)[[CiteRef::corrado1997capacity]], we assume that the primary cause of higher production costs is higher labor costs due to overtime operations with lower productivity, costly night work and increased maintenance works. We thus set (i) fixed input-output coefficients representing that, with the current set of embodied techniques, producing one unit of good ''i'' in region ''k'' requires the fixed physical amount ''IC<sub>j,i,k</sub>'' of intermediate goods j and ''l<sub>k,i</sub>''of labor; (ii) a decreasing return parameter ''Ω<sub>k,i</sub>= Ω(Q<sub>k,i</sub>/Cap<sub>k,i</sub>)'' on wages only, at the sector level [1].<br />
<br />
This solution actually comes back to earlier works on the existence of short-run flexibility of production systems at the sectoral level with putty-clay technologies (Marshall, 1890)[[CiteRef::marshallpoe]], (Johansen, 1959)[[CiteRef::johansen1959substitution]] demonstrating that this flexibility comes less from input substitution than from variations in differentiated capacity utilization rates.<br />
<br />
<figure id="fig:imaclim_4"><br />
[[File:36405273.png|none|600px|thumb|<caption> Sectoral interaction in the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
===== Equations =====<br />
<br />
We derive an expression of mean production costs ''Cm<sub>k,i</sub>'', that depends on the prices of intermediate goods ''pIC<sub>j,i,k</sub>'', input-ouput coefficients ''IC<sub>j,i,k</sub>'' and ''l<sub>k,i</sub>'', wages ''w<sub>k,i</sub>'', and production levels through the decreasing return factor ''?<sub>k,i</sub>'' applied to labor costs (including payroll taxes).<br />
<br />
[[File:36405274.png]]'''(1)'''<br />
<br />
Market prices and associated profits depend on assumptions regarding the degree of market competition in each sector (e.g. perfect competition or monopoly). Unless otherwise stated, perfect competition is assumed in every production sector, with the market price equal to the marginal production cost.<br />
<br />
Producer prices are equal to the sum of mean production costs and mean profits. In the current version of the model, all sectors apply a constant sector-specific mark-up rate ''p<sub>k,i</sub>'' so that the producer price is given by equation (2). This constant mark-up corresponds to a standard profit-maximization for producers whose mean production costs follow equation (1) and who are price-takers, provided that the decreasing return factor can be approximated by an exponential function of utilization rate.<br />
<br />
[[File:36405275.png]]'''(2)'''<br />
<br />
This equation is an inverse supply curve: it shows how a representative producer decides their level of output ''Q<sub>k,i</sub>'' (which is included in the ''?<sub>k,i</sub>''factor) as a function of all prices and real wages.<br />
<br />
From equation (2) we derive wages and profits in each sector:<br />
<br />
[[File:36405276.png]]'''(3,4)'''<br />
<br />
The cost function shows fixed technical coefficients and therefore does not allow for substitution between production factors when relative prices change within the new static equilibrium. Only the level of output ''Q<sub>k,i </sub>'' can be adjusted according to these price changes.<br />
<br />
=== Markets ===<br />
<br />
==== Markets of goods and services ====<br />
<br />
In the Imaclim-R model, all intermediate and final goods are internationally tradable and total demand for each good (the sum of households' consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports (see section on international trade). Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices calculated in the static equilibrium such that demand and supply are equal.<br />
<br />
'''Price'''<br />
<br />
In each region ''k'' and sector ''i'', the price equation is:<br />
<br />
[[File:36405277.png]]'''(5)'''<br />
<br />
where ''π<sub>k,i</sub>'' is a markup, ''IC<sub>j,i,k</sub>'' are intermediate consumption of good ''j'' in sector ''i'' in region ''k'', and ''Ω<sub>k,i</sub>'' is an increasing cost (or decreasing returns) function of the productive capacities utilization rate. This function is applied to labor costs (which include wages w<sub>k,i</sub> and labor taxes tax<sub>k,i</sub>).<br />
<br />
'' The functional form for Ω'' is:<br />
<br />
[[File:36405278.png]]'''(6)'''<br />
<br />
Regional prices thus correspond to the addition of average regional production costs and a margin. This markup, which is fixed in the static equilibrium, encapsulates Ricardian and scarcity rents at the same time and increases with the utilization rate of production capacities in the oil sector.<br />
<br />
A further parameter for the oil sector is that Middle-Eastern producers are considered 'swing producers' who are free to strategically set their investment decisions and, until they reach their depletion constraints, to control oil prices through the utilization rate of their production capacities (Kaufmann et al, 2004)[[CiteRef::kaufmann2004does]]. This possibility is justified by the temporary reinforcement of their market power due to the stagnation and decline of conventional oil in the rest of the world. They can in particular decide to slow the development of production capacities below its maximum rate in order to adjust the oil price according to their rent-seeking objectives. They anticipate the level of capacities that will make it possible for them to reach their goals, on the basis of projections of total oil demand and production in other regions.<br />
<br />
==== Capital markets ====<br />
<br />
A share (''shareExpK'') of gross domestic savings (GRB) is internationally tradable, and distributed via an international capital pool. Each regions receives a share of the international pool (''shareImpK)''. In the default model setting, both shares (''shareExpK and shareImpK'') are exogenous: ''shareExpK'' is exponentially reduced such that international financial imbalances disappear by 2050 and ''shareImpK'' remains constant throughout the simulation period.<br />
<br />
The remaining share of domestic savings and imported capital (NRB) are then invested in each region respectively.<br />
<br />
[[File:36405279.png]] ''' (7,8,9)'''<br />
<br />
* *The total amount of money ''InvFin<sub>k,i</sub>'' available for investment in sector ''i'' in the region ''k'' allows new capacities ''DCap<sub>k,i</sub>'' to be constructed at a cost ''pCap<sub>k,i</sub>'' (equation 9-3-5). The cost ''pCap<sub>k,i</sub>'' depends on the quantities ''?<sub>j,i,k</sub>'' and the prices ''pI<sub>k,j</sub>'' of goods ''j'' required by the construction of a new unit of capacity in sector ''i'' and in region ''k''. Coefficient ''?<sub>j,i,k</sub>'' is the amount of good ''j'' necessary to constuct the equipment corresponding to one new unit of production capacity in sector i of the region k. Finally, in each region, the total demand for goods for building new capacities is given by the last equation below.<br />
<br />
[[File:36405280.png]]''' (10,11,12)'''<br />
<br />
Each sector anticipates future production levels through an anticipation of future prices and demand and formulates the corresponding investment demand. Total available investment ''I<sub>k,j</sub>'' is then distributed among sectors according to their demand.<br />
<br />
==== Labour markets ====<br />
<br />
At each time step, producers operate in static equilibria with a fixed input of labor per unit of output. This labor input, corresponding to labor productivity, evolves between two yearly equilibria following exogenous trends in labor productivity.<br />
<br />
Three of the model features explain the possibility of under-utilization of labor as a factor of production, and thus unemployment. First, rigidity of real wages, represented by a wage curve can prevent wages falling to their market-clearing level. Put another way, instantaneous adjustment of wages to the economic context in the static equilibrium does not occur in an optimal manner. Second, in the static equilibrium, the fixed technologies (Leontief coefficients even for labor input) prevent substitution among production factors in the short run. And third, the installed productive capital is not mobile across sectors, which creates rigidities in the reallocations of production between sectors when relative prices change.<br />
<br />
In each region ''k'', each sector employs the labor force ''l<sub>k,i</sub><sup>.</sup>Q<sub>k,i</sub>'', where ''l<sub>k,i</sub>'' is the unitary labor input (in hours worked) and Q<sub>k,i</sub> the production. The underutilization of the labor force, equivalently referred to as the 'unemployment rate' [2] in the following, ''_z<sub>k</sub>'' is therefore equal to one minus the ratio of the employed labor force across all sectors over ''L<sub>k</sub>'', the total labor force:<br />
<br />
[[File:36405281.png]] ''' (13)'''<br />
<br />
No endogenous mobility of workers between regions is accounted for in the model. Thus twelve separate labor markets are represented.<br />
<br />
We chose to model labor market imperfections through an aggregate regional ''wage curve'' that links real wage levels to the unemployment rate. This representation is based on labor theories developed in the 1980s and early 1990s in which an aggregate wage curve, or ''wage setting curve'', is the primary distinguishing feature (an overview can be found in Layard et al., 2005[[CiteRef::layard2005unemployment]]; Lindbeck, 1993[[CiteRef::lindbeck1993unemployment]]; or Phelps, 1992[[CiteRef::phelps1992consumer]]). The novel approach of these models, when introduced, was to replace the conventional labor supply curve with a negatively-sloped curve linking the level of wages to the level of unemployment. The interpretation of this wage curve is given either by the bargaining approach (Layard and Nickell, 1986)[[CiteRef::layard1986unemployment]] or the wage-efficiency approach (Shapiro and Stiglitz, 1984)[[CiteRef::shapiro1984equilibrium]]. Both interpretations rely on the fact that unemployment represents an outside threat that leads workers to accept lower wages the greater the threat. The bargaining approach emphasizes the role of workers? (or unions?) power in the wage setting negotiations, power that is weakened when unemployment is high. The wage-efficiency approach takes the firms? point of view and assumes that firms set wage levels so as to discourage shirking; this level is lower when the threat of not finding a job after being caught shirking gets higher. The wage curve specification allows the theories to be consistent with both involuntary unemployment and the fact that real wages fluctuate less than the theory of the conventional flexible labor supply curve predicts. Microeconometric evidence for such formulations was given in a seminal contribution by (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]].<br />
<br />
In practice, the wage curve for each region k in our model is implemented through the relation:<br />
<br />
[[File:36405282.png]]''' (14)'''<br />
<br />
where ''w'' is the hourly nominal wage level, ''pind'' the consumption price index, ''z'' the unemployment rate, ''ref'' indexes represent the values of the variables at the calibration date, ''pindref'' is derived from the final consumption prices and volumes at the calibration date, ''wref'' is calibrated from the total salaries per sector in the GTAP 6 database (Reference?) and the shares of labor force per sector are taken from International Labor Organisation statistics. By default, ''aw'' is calibrated to 1 and evolves in parallel to labor productivity so that unitary real wages are indexed on labor productivity. ''zref'' represents the underutilization of the labor force at the calibration date. ''f'' is a function equal to one when the unemployment rate is equal to its calibration level, and is negatively sloped, representing a negative elasticity of wages level to unemployment [3].<br />
<br />
By default, we assume all regions' labor markets to be identical and set the underutilization of the labor force at 10% [4] and the wage curve elasticity at -0.1 for all regions (This is a value emerging from many econometric studies, e.g. (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]], (Blanchflower and Oswald 2005). [http://halshs.archives-ouvertes.fr/docs/00/72/44/87/PDF/Guivarch_et_al_2011_Costs_climate_policies_second_best_world_labour_market_imperfections.pdf Guivarch et al. (2011)][[CiteRef::guivarch2011costs]] analyzes the critical role of labour markets imperfections, and in particular of the value of the wage curve elasticity, on the formation of climate stabilization costs.<br />
<br />
=== International Trade ===<br />
<br />
For each good, exports from all world regions are blended into an international variety, which is then imported by each region based on its specific terms-of-trade measured between the price of the aggregate international variety, and the production price of the domestic good.<br />
<br />
International trade is treated 'upstream': the competition of the domestic and imported varieties of each good is settled in an aggregate manner, not at the level of each domestic agent.<br />
<br />
A well-known modelling issue is then to avoid ?knife-edge? solutions, ''i.e.'' to prevent cheaper goods systematically winning market shares over more expensive ones We follow the most common approach to addressing this issue, the Armington (1969)[[CiteRef::sassi2010im]] specification, which assumes that the domestic and imported varieties of the same good aggregate in a common quantity index, although in an imperfectly substitutable way which is typically derived from assuming that the two varieties combine through a constant elasticity of substitution (CES) function. This allows representing markets in which both domestic production and imports have a share, despite the fact that they are priced differently.<br />
<br />
Despite its straightforward treatment of imperfect product competition, the Armington specification has the major drawback of introducing aggregate volumes that do not sum up the volumes of imported and domestic varieties. While this shortcoming can be ignored for non-descript 'composite' goods, where quantity units are indexes of no direct significance to the economy-energy-environment interactions, it is not compatible with the obvious need to track energy balances expressed in real physical units. Competition between energy goods is thus settled through simplified specifications. In the case of national models, the hypothesis of a constant elasticity of substitution is retained, but the construction of a composite index is dropped. Imports and domestic production are simply summed up to form the resource that is available to the importing economy. For the multi-regional version of Imaclim, a market-sharing formula is implemented. The international market buys energy exports at different prices and sells them at a single average world price to importers; shares of exporters on the international market and regional shares of domestic ''vs.'' imported energy goods dependent on relative prices, export and import taxes, and market fragmentation parameters that are calibrated to reproduce the existing markets structure.<br />
<br />
For all goods, export prices include the producer prices, export taxes or subsidies, and average transportation costs. This allows the model to take into account that increasing energy prices would impact on transportation costs and eventually on commercial flows and industrial location patterns.<br />
<br />
''Armington goods'' [[File:36405284.png]]''' (15,16,17)'''<br />
[[File:36405285.png]]''' (18,19,20)'''<br />
[[File:36405286.png]]''' (21,22)'''<br />
<br />
''Energy goods''<br />
<br />
[[File:36405287.png]]''' (23,24,25)'''<br />
[[File:36405288.png]]''' (26,27,28)'''<br />
[[File:36405289.png]]''' (29,30,31)'''<br />
<br />
<br />
-----<br />
<br />
[1] The treatment of the cost of crude oil production is an exception. The increasing factor weighs on the mark-up rate, to convey the fact that oligopolistic producers can take advantage of capacity shortages by increasing their differential rent.<br />
<br />
[2] Obviously, this is a limitation of the current calibration of the model. Future developments will look into the possibility to differentiate labor markets per regions. However, one important difficulty lies in the lack of reliable data on the underutilization of the labor forces in all regions, in particular due to informal economy, very diverse accounting rules for unemployment rates and variations in hours worked per person across countries.<br />
<br />
[3] Choosing a functional form and calibrating the function is particularly tricky, notably due to the lack of reliable data to fully inform the functioning of the labor markets worldwide. We chose a function of the form a.(1-tanh(c.z)), and calibrate the parameters a and c so as to have the desired value and elasticity at the calibration point.<br />
<br />
[4] Contrary to the definition by the U.S. Bureau of Labor Statistics, the level of unemployment is expressed here in terms of worked hours and not in terms of persons.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Macro-economy_-_IMACLIM&diff=5263Macro-economy - IMACLIM2016-09-29T16:13:28Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Macro-economy<br />
}}<br />
== A general equilibrium with rigidities ==<br />
<br />
The representation of the economy in Imaclim-R is a multi-sector (12 sectors), multi-region (12 regions) general equilibrium framework. In each region, there are 14 economic agents: one representative household, one representative firm per sector (hence 12 representative firms) and the public administration. Households receive revenues from labor and capital and from transfers from public administrations and save part of their revenues. They chose their consumptions of goods and services depending on relative prices and they pay taxes to the public administrations. Productive sectors chose their production levels to meet demand, earn profits, pay wages and dividends to households and pay taxes to public administrations. Public administrations collect taxes, make public expenditures and invest in public infrastructures, and organize transfers. Regions are linked through international markets for goods and services, and capital. <xr id="fig:imaclim_3"/> outlines these interrelationships.<br />
<br />
<figure id="fig:imaclim_3"><br />
[[File:36405263.png|none|600px|thumb|<caption> Sectoral interaction in the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
=== Households ===<br />
<br />
Each year, households maximize their current utility under constraints of both revenue received and of their time spent in transport. They save an exogenous share of their revenues. For detailed descriptions of demand formation mechanisms refer to the [[Economic_activity_-_IMACLIM:section on demand representation]].<br />
<br />
=== Public administrations ===<br />
<br />
Public administrations collect taxes, make public expenditures including investment in public infrastructures and organize transfers.<br />
<br />
Tax rates (and/or subsidies) are calibrated to their values for the model calibration year (2001). Taxes (and/or subsidies) impact upon energy, labor, revenues, added value, production, imports and exports. In the default setting of the model, tax rates are kept constant throughout the modelling period (except for in scenarios that model the introduction of a carbon tax ) although alternative assumption on tax rates can also be tested. In a scenario where a carbon tax is introduced, alternative assumptions on the use of the corresponding revenues can be modelled i.e. they are given to households via transfers, used to reduce other pre-existing tax rates or used to finance a subsidy.<br />
<br />
In the default setting public expenditures in each region are assumed to follow GDP growth rates, Alternative assumptions on the evolution of public expenditures can also be tested.<br />
<br />
Transfers are determined such that the public administration budget is at equilibrium each year. Public debt is not accounted for.<br />
<br />
=== Productive sectors ===<br />
<br />
A start point for IMACLIM is the recognition that it is almost impossible to find mathematical functions that can handle large departures from a reference equilibrium over a time period of one century and are flexible enough to encompass different scenarios of structural change resulting from the interplay between consumption styles, technologies and localization patterns (Hourcade, 1993)[[CiteRef::hourcade1993modelling]].<br />
<br />
==== Beyond the classical production function, or reconciling bottom-up and top-down approaches ====<br />
<br />
In IMACLIM-R, there is no production function, such as a constant elasticity of substitution function, to represent evolutions in production techniques (substitutions between production factors). Instead, evolutions in production techniques are represented in a recursive structure by an exchange of information between static and dynamic modules described as follows: <br />
<br />
* An annual static equilibrium module, in which the production function mimics the Leontief specification, with fixed equipment stocks and fixed intensity of labor, energy and other intermediary inputs, but with a flexible utilization rate. Solving this equilibrium at time, ''t'', provides a snapshot of the economy at this date showing a set of information about relative prices, levels of output, physical flows and profitability rates for each sector and allocation of investments among sectors.<br />
<br />
* Dynamic modules, including demography, capital dynamics and sector-specific reduced forms of technology-rich models, which take into account the economic values of the previous static equilibrium, assess the reaction of technical systems and send back this information to the static module in the form of new input-output coefficients for calculating the equilibrium at time, ""t + 1"". Each year, technical choices are flexible but they modify only at the margin the input-output coefficients and labor productivity embodied in the existing equipment that result from past technical choices. This general putty-clay assumption is critical to represent the inertia in technical systems and the role of volatility in economic signals.<br />
<br />
This modelling approach allows for abandoning standard aggregate production functions, which have intrinsic limitations in cases of large departures from the reference equilibrium (Frondel et al., 2002)[[CiteRef::frondel2002capital]] and sea changes of production frontiers over several decades.<br />
<br />
As we move away from using a traditional production function, it becomes possible to highlight the influence of factors other than price on decisions affecting the allocation of resources. The use of this modeling approach requires however a comprehensive description of the temporally evolving technical characteristics of each sector.<br />
<br />
At each point in time, producers are assumed to operate under constraint of a fixed production capacity ''Cap<sub>k,i</sub>'', defined as the maximum level of physical output achievable with their installed equipment.<br />
<br />
However, the model allows short-run adjustments to market conditions through the modification of the utilization rate ''Q<sub>k,i</sub>/Cap<sub>k,i</sub>''. This represents a different approach from standard production specifications, since in Imaclim the ?capital? factor is not always fully utilized. Supply cost curves in Imaclim-R thus show static decreasing returns: production costs increase when the utilization rate of equipment approaches 1 (100 %) (Figure below). In principle, these decreasing returns affect all intermediary inputs and labor. However, for the sake of simplicity and because of the order of magnitude of the correlation between utilization rates and prices (Corrado and Mattey, 1997)[[CiteRef::corrado1997capacity]], we assume that the primary cause of higher production costs is higher labor costs due to overtime operations with lower productivity, costly night work and increased maintenance works. We thus set (i) fixed input-output coefficients representing that, with the current set of embodied techniques, producing one unit of good ''i'' in region ''k'' requires the fixed physical amount ''IC<sub>j,i,k</sub>'' of intermediate goods j and ''l<sub>k,i</sub>''of labor; (ii) a decreasing return parameter ''?<sub>k,i</sub>= ? (Q<sub>k,i</sub>/Cap<sub>k,i</sub>)'' on wages only, at the sector level [1].<br />
<br />
This solution actually comes back to earlier works on the existence of short-run flexibility of production systems at the sectoral level with putty-clay technologies (Marshall, 1890)[[CiteRef::marshallpoe]], (Johansen, 1959)[[CiteRef::johansen1959substitution]] demonstrating that this flexibility comes less from input substitution than from variations in differentiated capacity utilization rates.<br />
<br />
[[File:36405273.png]]<br />
<br />
===== Equations =====<br />
<br />
We derive an expression of mean production costs ''Cm<sub>k,i</sub>'', that depends on the prices of intermediate goods ''pIC<sub>j,i,k</sub>'', input-ouput coefficients ''IC<sub>j,i,k</sub>'' and ''l<sub>k,i</sub>'', wages ''w<sub>k,i</sub>'', and production levels through the decreasing return factor ''?<sub>k,i</sub>'' applied to labor costs (including payroll taxes).<br />
<br />
[[File:36405274.png]]<br />
<br />
Market prices and associated profits depend on assumptions regarding the degree of market competition in each sector (e.g. perfect competition or monopoly). Unless otherwise stated, perfect competition is assumed in every production sector, with the market price equal to the marginal production cost.<br />
<br />
Producer prices are equal to the sum of mean production costs and mean profits. In the current version of the model, all sectors apply a constant sector-specific mark-up rate ''p<sub>k,i</sub>'' so that the producer price is given by equation (2). This constant mark-up corresponds to a standard profit-maximization for producers whose mean production costs follow equation (1) and who are price-takers, provided that the decreasing return factor can be approximated by an exponential function of utilization rate.<br />
<br />
[[File:36405275.png]]<br />
<br />
This equation is an inverse supply curve: it shows how a representative producer decides their level of output ''Q<sub>k,i</sub>'' (which is included in the ''?<sub>k,i</sub>''factor) as a function of all prices and real wages.<br />
<br />
From equation (2) we derive wages and profits in each sector:<br />
<br />
[[File:36405276.png]]<br />
<br />
The cost function shows fixed technical coefficients and therefore does not allow for substitution between production factors when relative prices change within the new static equilibrium. Only the level of output ''Q<sub>k,i </sub>'' can be adjusted according to these price changes.<br />
<br />
=== Markets ===<br />
<br />
==== Markets of goods and services ====<br />
<br />
In the Imaclim-R model, all intermediate and final goods are internationally tradable and total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports (see section on international trade). Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices calculated in the static equilibrium such that demand and supply are equal.<br />
<br />
'''Price'''<br />
<br />
In each region ''k'' and sector ''i'', the price equation is:<br />
<br />
[[File:36405277.png]]'''(5)'''<br />
<br />
where ''?<sub>k,i</sub>'' is a markup, ''IC<sub>j,i,k</sub>'' are intermediate consumption of good ''j'' in sector ''i'' in region ''k'', and ''?<sub>k,i</sub>'' is an increasing cost (or decreasing returns) function of the productive capacities utilization rate. This function is applied to labor costs (which include wages w<sub>k,i</sub> and labor taxes tax<sub>k,i</sub>).<br />
<br />
'' _The functional form for _?'' is:<br />
<br />
[[File:36405278.png]]'''(6)'''<br />
<br />
Regional prices thus correspond to the addition of average regional production costs and a margin. This markup, which is fixed in the static equilibrium, encapsulates Ricardian and scarcity rents at the same time and increases with the utilization rate of production capacities in the oil sector.<br />
<br />
A further parameter for the oil sector is that Middle-Eastern producers are considered ?swing producers? who are free to strategically set their investment decisions and, until they reach their depletion constraints, to control oil prices through the utilization rate of their production capacities (Kaufmann et al, 2004)[[CiteRef::kaufmann2004does]]. This possibility is justified by the temporary reinforcement of their market power due to the stagnation and decline of conventional oil in the rest of the world. They can in particular decide to slow the development of production capacities below its maximum rate in order to adjust the oil price according to their rent-seeking objectives. They anticipate the level of capacities that will make it possible for them to reach their goals, on the basis of projections of total oil demand and production in other regions.<br />
<br />
==== Capital markets ====<br />
<br />
A share (''shareExpK'') of gross domestic savings (GRB) is internationally tradable, and distributed via an international capital pool. Each regions receives a share of the international pool (''shareImpK)''. In the default model setting, both shares (''shareExpK and shareImpK'') are exogenous: ''shareExpK'' is exponentially reduced such that international financial imbalances disappear by 2050 and ''shareImpK'' remains constant throughout the simulation period.<br />
<br />
The remaining share of domestic savings and imported capital (NRB) are then invested in each region respectively.<br />
<br />
[[File:36405279.png]] ''' (7,8,9)'''<br />
<br />
* *The total amount of money ''InvFin<sub>k,i</sub>'' available for investment in sector ''i'' in the region ''k'' allows new capacities ''DCap<sub>k,i</sub>'' to be constructed at a cost ''pCap<sub>k,i</sub>'' (equation 9-3-5). The cost ''pCap<sub>k,i</sub>'' depends on the quantities ''?<sub>j,i,k</sub>'' and the prices ''pI<sub>k,j</sub>'' of goods ''j'' required by the construction of a new unit of capacity in sector ''i'' and in region ''k''. Coefficient ''?<sub>j,i,k</sub>'' is the amount of good ''j'' necessary to constuct the equipment corresponding to one new unit of production capacity in sector i of the region k. Finally, in each region, the total demand for goods for building new capacities is given by the last equation below.<br />
<br />
[[File:36405280.png]]''' (10,11,12)'''<br />
<br />
Each sector anticipates future production levels through an anticipation of future prices and demand and formulates the corresponding investment demand. Total available investment ''I<sub>k,j</sub>'' is then distributed among sectors according to their demand.<br />
<br />
==== Labour markets ====<br />
<br />
At each time step, producers operate in static equilibria with a fixed input of labor per unit of output. This labor input, corresponding to labor productivity, evolves between two yearly equilibria following exogenous trends in labor productivity.<br />
<br />
Three of the model features explain the possibility of under-utilization of labor as a factor of production, and thus unemployment. First, rigidity of real wages, represented by a wage curve can prevent wages falling to their market-clearing level. Put another way, instantaneous adjustment of wages to the economic context in the static equilibrium does not occur in an optimal manner. Second, in the static equilibrium, the fixed technologies (Leontief coefficients even for labor input) prevent substitution among production factors in the short run. And third, the installed productive capital is not mobile across sectors, which creates rigidities in the reallocations of production between sectors when relative prices change.<br />
<br />
In each region ''k'', each sector employs the labor force ''l<sub>k,i</sub><sup>.</sup>Q<sub>k,i</sub>'', where ''l<sub>k,i</sub>'' is the unitary labor input (in hours worked) and Q<sub>k,i</sub> the production. The underutilization of the labor force, equivalently referred to as the ?unemployment rate? [2] in the following, ''_z<sub>k</sub>'' is therefore equal to one minus the ratio of the employed labor force across all sectors over ''L<sub>k</sub>'', the total labor force:<br />
<br />
[[File:36405281.png]] ''' (13)'''<br />
<br />
No endogenous mobility of workers between regions is accounted for in the model. Thus twelve separate labor markets are represented.<br />
<br />
We chose to model labor market imperfections through an aggregate regional ''wage curve'' that links real wage levels to the unemployment rate. This representation is based on labor theories developed in the 1980s and early 1990s in which an aggregate wage curve, or ''wage setting curve'', is the primary distinguishing feature (an overview can be found in Layard et al., 2005[[CiteRef::layard2005unemployment]]; Lindbeck, 1993[[CiteRef::lindbeck1993unemployment]]; or Phelps, 1992[[CiteRef::phelps1992consumer]]). The novel approach of these models, when introduced, was to replace the conventional labor supply curve with a negatively-sloped curve linking the level of wages to the level of unemployment. The interpretation of this wage curve is given either by the bargaining approach (Layard and Nickell, 1986)[[CiteRef::layard1986unemployment]] or the wage-efficiency approach (Shapiro and Stiglitz, 1984)[[CiteRef::shapiro1984equilibrium]]. Both interpretations rely on the fact that unemployment represents an outside threat that leads workers to accept lower wages the greater the threat. The bargaining approach emphasizes the role of workers? (or unions?) power in the wage setting negotiations, power that is weakened when unemployment is high. The wage-efficiency approach takes the firms? point of view and assumes that firms set wage levels so as to discourage shirking; this level is lower when the threat of not finding a job after being caught shirking gets higher. The wage curve specification allows the theories to be consistent with both involuntary unemployment and the fact that real wages fluctuate less than the theory of the conventional flexible labor supply curve predicts. Microeconometric evidence for such formulations was given in a seminal contribution by (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]].<br />
<br />
In practice, the wage curve for each region k in our model is implemented through the relation:<br />
<br />
[[File:36405282.png]]''' (14)'''<br />
<br />
where ''w'' is the hourly nominal wage level, ''pind'' the consumption price index, ''z'' the unemployment rate, ''ref'' indexes represent the values of the variables at the calibration date, ''pindref'' is derived from the final consumption prices and volumes at the calibration date, ''wref'' is calibrated from the total salaries per sector in the GTAP 6 database (Reference?) and the shares of labor force per sector are taken from International Labor Organisation statistics. By default, ''aw'' is calibrated to 1 and evolves in parallel to labor productivity so that unitary real wages are indexed on labor productivity. ''zref'' represents the underutilization of the labor force at the calibration date. ''f'' is a function equal to one when the unemployment rate is equal to its calibration level, and is negatively sloped, representing a negative elasticity of wages level to unemployment [3].<br />
<br />
By default, we assume all regions' labor markets to be identical and set the underutilization of the labor force at 10% [4] and the wage curve elasticity at -0.1 for all regions (This is a value emerging from many econometric studies, e.g. (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]], (Blanchflower and Oswald 2005). [http://halshs.archives-ouvertes.fr/docs/00/72/44/87/PDF/Guivarch_et_al_2011_Costs_climate_policies_second_best_world_labour_market_imperfections.pdf Guivarch et al. (2011)][[CiteRef::guivarch2011costs]] analyzes the critical role of labour markets imperfections, and in particular of the value of the wage curve elasticity, on the formation of climate stabilization costs.<br />
<br />
=== International Trade ===<br />
<br />
For each good, exports from all world regions are blended into an international variety, which is then imported by each region based on its specific terms-of-trade measured between the price of the aggregate international variety, and the production price of the domestic good.<br />
<br />
International trade is treated ?upstream?: the competition of the domestic and imported varieties of each good is settled in an aggregate manner, not at the level of each domestic agent.<br />
<br />
A well-known modelling issue is then to avoid ?knife-edge? solutions, ''i.e.'' to prevent cheaper goods systematically winning market shares over more expensive ones We follow the most common approach to addressing this issue, the Armington (1969)[[CiteRef::sassi2010im]] specification, which assumes that the domestic and imported varieties of the same good aggregate in a common quantity index, although in an imperfectly substitutable way which is typically derived from assuming that the two varieties combine through a constant elasticity of substitution (CES) function. This allows representing markets in which both domestic production and imports have a share, despite the fact that they are priced differently.<br />
<br />
Despite its straightforward treatment of imperfect product competition, the Armington specification has the major drawback of introducing aggregate volumes that do not sum up the volumes of imported and domestic varieties. While this shortcoming can be ignored for non-descript ?composite? goods, where quantity units are indexes of no direct significance to the economy-energy-environment interactions, it is not compatible with the obvious need to track energy balances expressed in real physical units. Competition between energy goods is thus settled through simplified specifications. In the case of national models, the hypothesis of a constant elasticity of substitution is retained, but the construction of a composite index is dropped. Imports and domestic production are simply summed up to form the resource that is available to the importing economy. For the multi-regional version of Imaclim, a market-sharing formula is implemented. The international market buys energy exports at different prices and sells them at a single average world price to importers; shares of exporters on the international market and regional shares of domestic ''vs.'' imported energy goods dependent on relative prices, export and import taxes, and market fragmentation parameters that are calibrated to reproduce the existing markets structure.<br />
<br />
For all goods, export prices include the producer prices, export taxes or subsidies, and average transportation costs. This allows the model to take into account that increasing energy prices would impact on transportation costs and eventually on commercial flows and industrial location patterns.<br />
<br />
''Armington goods'' [[File:36405284.png]]''' (15,16,17)'''<br />
[[File:36405285.png]]''' (18,19,20)'''<br />
[[File:36405286.png]]''' (21,22)'''<br />
<br />
''Energy goods''<br />
<br />
[[File:36405287.png]]''' (23,24,25)'''<br />
[[File:36405288.png]]''' (26,27,28)'''<br />
[[File:36405289.png]]''' (29,30,31)'''<br />
<br />
<br />
-----<br />
<br />
[1] The treatment of the cost of crude oil production is an exception. The increasing factor weighs on the mark-up rate, to convey the fact that oligopolistic producers can take advantage of capacity shortages by increasing their differential rent.<br />
<br />
[2] Obviously, this is a limitation of the current calibration of the model. Future developments will look into the possibility to differentiate labor markets per regions. However, one important difficulty lies in the lack of reliable data on the underutilization of the labor forces in all regions, in particular due to informal economy, very diverse accounting rules for unemployment rates and variations in hours worked per person across countries.<br />
<br />
[3] Choosing a functional form and calibrating the function is particularly tricky, notably due to the lack of reliable data to fully inform the functioning of the labor markets worldwide. We chose a function of the form a.(1-tanh(c.z)), and calibrate the parameters a and c so as to have the desired value and elasticity at the calibration point.<br />
<br />
[4] Contrary to the definition by the U.S. Bureau of Labor Statistics, the level of unemployment is expressed here in terms of worked hours and not in terms of persons.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Macro-economy_-_IMACLIM&diff=5262Macro-economy - IMACLIM2016-09-29T16:03:27Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Macro-economy<br />
}}<br />
== A general equilibrium with rigidities ==<br />
<br />
The representation of the economy in Imaclim-R is a multi-sector (12 sectors), multi-region (12 regions) general equilibrium framework. In each region, there are 14 economic agents: one representative household, one representative firm per sector (hence 12 representative firms) and the public administration. Households receive revenues from labor and capital and from transfers from public administrations and save part of their revenues. They chose their consumptions of goods and services depending on relative prices and they pay taxes to the public administrations. Productive sectors chose their production levels to meet demand, earn profits, pay wages and dividends to households and pay taxes to public administrations. Public administrations collect taxes, make public expenditures and invest in public infrastructures, and organize transfers. Regions are linked through international markets for goods and services, and capital. <xr id="fig:imaclim_3"/> outlines these interrelationships.<br />
<br />
<figure id="fig:imaclim_3"><br />
[[File:36405263.png|none|800px|thumb|<caption> The recursive and modular architecture of the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
=== Households ===<br />
<br />
Each year, households maximize their current utility under constraints of both revenue received and of their time spent in transport. They save an exogenous share of their revenues. For detailed descriptions of demand formation mechanisms refer to the [/x/3JUMAg section on demand representation].<br />
<br />
=== Public administrations ===<br />
<br />
Public administrations collect taxes; make public expenditures including investment in public infrastructures; and organize transfers.<br />
<br />
Tax rates (and/or subsidies) are calibrated to their values at the calibration year (2001). Taxes (and/or subsidies) impact upon energy, labor, revenues, added value, production, imports and exports. In the default setting of the model, tax rates are kept constant throughout the modelling period (except for scenarios that model the introduction of a carbon tax ); although alternative assumption on tax rates can also be tested. In a scenario wherea carbon tax is introduced, alternative assumptions on the use of the corresponding revenues can be modelled: i.e. they are given to households via transfers, used to reduce other pre-existing tax rates or used to finance a subsidy.<br />
<br />
In the default setting public expenditures in each region are assumed to follow GDP growth rates, Alternative assumptions on evolutions in public expenditures can also be tested.<br />
<br />
Transfers are determined such that the public administration budget is at equilibrium each year. Public debt is not accounted for.<br />
<br />
=== Productive sectors ===<br />
<br />
A start point for IMACLIM is the recognition that it is almost impossible to find mathematical functions that can handle large departures from a reference equilibrium over a time period of one century and are flexible enough to encompass different scenarios of structural change resulting from the interplay between consumption styles, technologies and localization patterns (Hourcade, 1993)[[CiteRef::hourcade1993modelling]].<br />
<br />
==== Beyond the classical production function, or reconciling bottom-up and top-down approaches ====<br />
<br />
In IMACLIM-R, there is no production function, such as a constant elasticity of substitution function, to represent evolutions in production techniques (substitutions between production factors). Instead, evolutions in production techniques are represented in a recursive structure by an exchange of information between static and dynamic modules described as follows: <br />
<br />
* An annual static equilibrium module, in which the production function mimics the Leontief specification, with fixed equipment stocks and fixed intensity of labor, energy and other intermediary inputs, but with a flexible utilization rate. Solving this equilibrium at t provides a snapshot of the economy at this date showing a set of information about relative prices, levels of output, physical flows and profitability rates for each sector and allocation of investments among sectors.<br />
<br />
* Dynamic modules, including demography, capital dynamics and sector-specific reduced forms of technology-rich models, which take into account the economic values of the previous static equilibrium, assess the reaction of technical systems and send back this information to the static module in the form of new input-output coefficients for calculating the equilibrium at t + 1. Each year, technical choices are flexible but they modify only at the margin the input-output coefficients and labor productivity embodied in the existing equipment that result from past technical choices. This general putty-clay assumption is critical to represent the inertia in technical systems and the role of volatility in economic signals.<br />
<br />
This modelling approach allows for abandoning standard aggregate production functions, which have intrinsic limitations in cases of large departures from the reference equilibrium (Frondel et al., 2002)[[CiteRef::frondel2002capital]] and sea changes of production frontiers over several decades.<br />
<br />
As we move away from using a traditional production function, it becomes possible to highlight the influence of factors other than price on decisions affecting the allocation of resources. The use of this modeling approach requires however a comprehensive description of the temporally evolving technical characteristics of each sector.<br />
<br />
At each point in time, producers are assumed to operate under constraint of a fixed production capacity ''Cap<sub>k,i</sub>'', defined as the maximum level of physical output achievable with their installed equipment.<br />
<br />
However, the model allows short-run adjustments to market conditions through the modification of the utilization rate ''Q<sub>k,i</sub>/Cap<sub>k,i</sub>''. This represents a different approach from standard production specifications, since in Imaclim the ?capital? factor is not always fully utilized. Supply cost curves in Imaclim-R thus show static decreasing returns: production costs increase when the utilization rate of equipment approaches 1 (100 %) (Figure below). In principle, these decreasing returns affect all intermediary inputs and labor. However, for the sake of simplicity and because of the order of magnitude of the correlation between utilization rates and prices (Corrado and Mattey, 1997)[[CiteRef::corrado1997capacity]], we assume that the primary cause of higher production costs is higher labor costs due to overtime operations with lower productivity, costly night work and increased maintenance works. We thus set (i) fixed input-output coefficients representing that, with the current set of embodied techniques, producing one unit of good ''i'' in region ''k'' requires the fixed physical amount ''IC<sub>j,i,k</sub>'' of intermediate goods j and ''l<sub>k,i</sub>''of labor; (ii) a decreasing return parameter ''?<sub>k,i</sub>= ? (Q<sub>k,i</sub>/Cap<sub>k,i</sub>)'' on wages only, at the sector level [1].<br />
<br />
This solution actually comes back to earlier works on the existence of short-run flexibility of production systems at the sectoral level with putty-clay technologies (Marshall, 1890)[[CiteRef::marshallpoe]], (Johansen, 1959)[[CiteRef::johansen1959substitution]] demonstrating that this flexibility comes less from input substitution than from variations in differentiated capacity utilization rates.<br />
<br />
[[File:36405273.png]]<br />
<br />
===== Equations =====<br />
<br />
We derive an expression of mean production costs ''Cm<sub>k,i</sub>'', that depends on the prices of intermediate goods ''pIC<sub>j,i,k</sub>'', input-ouput coefficients ''IC<sub>j,i,k</sub>'' and ''l<sub>k,i</sub>'', wages ''w<sub>k,i</sub>'', and production levels through the decreasing return factor ''?<sub>k,i</sub>'' applied to labor costs (including payroll taxes).<br />
<br />
[[File:36405274.png]]<br />
<br />
Market prices and associated profits depend on assumptions regarding the degree of market competition in each sector (e.g. perfect competition or monopoly). Unless otherwise stated, perfect competition is assumed in every production sector, with the market price equal to the marginal production cost.<br />
<br />
Producer prices are equal to the sum of mean production costs and mean profits. In the current version of the model, all sectors apply a constant sector-specific mark-up rate ''p<sub>k,i</sub>'' so that the producer price is given by equation (2). This constant mark-up corresponds to a standard profit-maximization for producers whose mean production costs follow equation (1) and who are price-takers, provided that the decreasing return factor can be approximated by an exponential function of utilization rate.<br />
<br />
[[File:36405275.png]]<br />
<br />
This equation is an inverse supply curve: it shows how a representative producer decides their level of output ''Q<sub>k,i</sub>'' (which is included in the ''?<sub>k,i</sub>''factor) as a function of all prices and real wages.<br />
<br />
From equation (2) we derive wages and profits in each sector:<br />
<br />
[[File:36405276.png]]<br />
<br />
The cost function shows fixed technical coefficients and therefore does not allow for substitution between production factors when relative prices change within the new static equilibrium. Only the level of output ''Q<sub>k,i </sub>'' can be adjusted according to these price changes.<br />
<br />
=== Markets ===<br />
<br />
==== Markets of goods and services ====<br />
<br />
In the Imaclim-R model, all intermediate and final goods are internationally tradable and total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports (see section on international trade). Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices calculated in the static equilibrium such that demand and supply are equal.<br />
<br />
'''Price'''<br />
<br />
In each region ''k'' and sector ''i'', the price equation is:<br />
<br />
[[File:36405277.png]]'''(5)'''<br />
<br />
where ''?<sub>k,i</sub>'' is a markup, ''IC<sub>j,i,k</sub>'' are intermediate consumption of good ''j'' in sector ''i'' in region ''k'', and ''?<sub>k,i</sub>'' is an increasing cost (or decreasing returns) function of the productive capacities utilization rate. This function is applied to labor costs (which include wages w<sub>k,i</sub> and labor taxes tax<sub>k,i</sub>).<br />
<br />
'' _The functional form for _?'' is:<br />
<br />
[[File:36405278.png]]'''(6)'''<br />
<br />
Regional prices thus correspond to the addition of average regional production costs and a margin. This markup, which is fixed in the static equilibrium, encapsulates Ricardian and scarcity rents at the same time and increases with the utilization rate of production capacities in the oil sector.<br />
<br />
A further parameter for the oil sector is that Middle-Eastern producers are considered ?swing producers? who are free to strategically set their investment decisions and, until they reach their depletion constraints, to control oil prices through the utilization rate of their production capacities (Kaufmann et al, 2004)[[CiteRef::kaufmann2004does]]. This possibility is justified by the temporary reinforcement of their market power due to the stagnation and decline of conventional oil in the rest of the world. They can in particular decide to slow the development of production capacities below its maximum rate in order to adjust the oil price according to their rent-seeking objectives. They anticipate the level of capacities that will make it possible for them to reach their goals, on the basis of projections of total oil demand and production in other regions.<br />
<br />
==== Capital markets ====<br />
<br />
A share (''shareExpK'') of gross domestic savings (GRB) is internationally tradable, and distributed via an international capital pool. Each regions receives a share of the international pool (''shareImpK)''. In the default model setting, both shares (''shareExpK and shareImpK'') are exogenous: ''shareExpK'' is exponentially reduced such that international financial imbalances disappear by 2050 and ''shareImpK'' remains constant throughout the simulation period.<br />
<br />
The remaining share of domestic savings and imported capital (NRB) are then invested in each region respectively.<br />
<br />
[[File:36405279.png]] ''' (7,8,9)'''<br />
<br />
* *The total amount of money ''InvFin<sub>k,i</sub>'' available for investment in sector ''i'' in the region ''k'' allows new capacities ''DCap<sub>k,i</sub>'' to be constructed at a cost ''pCap<sub>k,i</sub>'' (equation 9-3-5). The cost ''pCap<sub>k,i</sub>'' depends on the quantities ''?<sub>j,i,k</sub>'' and the prices ''pI<sub>k,j</sub>'' of goods ''j'' required by the construction of a new unit of capacity in sector ''i'' and in region ''k''. Coefficient ''?<sub>j,i,k</sub>'' is the amount of good ''j'' necessary to constuct the equipment corresponding to one new unit of production capacity in sector i of the region k. Finally, in each region, the total demand for goods for building new capacities is given by the last equation below.<br />
<br />
[[File:36405280.png]]''' (10,11,12)'''<br />
<br />
Each sector anticipates future production levels through an anticipation of future prices and demand and formulates the corresponding investment demand. Total available investment ''I<sub>k,j</sub>'' is then distributed among sectors according to their demand.<br />
<br />
==== Labour markets ====<br />
<br />
At each time step, producers operate in static equilibria with a fixed input of labor per unit of output. This labor input, corresponding to labor productivity, evolves between two yearly equilibria following exogenous trends in labor productivity.<br />
<br />
Three of the model features explain the possibility of under-utilization of labor as a factor of production, and thus unemployment. First, rigidity of real wages, represented by a wage curve can prevent wages falling to their market-clearing level. Put another way, instantaneous adjustment of wages to the economic context in the static equilibrium does not occur in an optimal manner. Second, in the static equilibrium, the fixed technologies (Leontief coefficients even for labor input) prevent substitution among production factors in the short run. And third, the installed productive capital is not mobile across sectors, which creates rigidities in the reallocations of production between sectors when relative prices change.<br />
<br />
In each region ''k'', each sector employs the labor force ''l<sub>k,i</sub><sup>.</sup>Q<sub>k,i</sub>'', where ''l<sub>k,i</sub>'' is the unitary labor input (in hours worked) and Q<sub>k,i</sub> the production. The underutilization of the labor force, equivalently referred to as the ?unemployment rate? [2] in the following, ''_z<sub>k</sub>'' is therefore equal to one minus the ratio of the employed labor force across all sectors over ''L<sub>k</sub>'', the total labor force:<br />
<br />
[[File:36405281.png]] ''' (13)'''<br />
<br />
No endogenous mobility of workers between regions is accounted for in the model. Thus twelve separate labor markets are represented.<br />
<br />
We chose to model labor market imperfections through an aggregate regional ''wage curve'' that links real wage levels to the unemployment rate. This representation is based on labor theories developed in the 1980s and early 1990s in which an aggregate wage curve, or ''wage setting curve'', is the primary distinguishing feature (an overview can be found in Layard et al., 2005[[CiteRef::layard2005unemployment]]; Lindbeck, 1993[[CiteRef::lindbeck1993unemployment]]; or Phelps, 1992[[CiteRef::phelps1992consumer]]). The novel approach of these models, when introduced, was to replace the conventional labor supply curve with a negatively-sloped curve linking the level of wages to the level of unemployment. The interpretation of this wage curve is given either by the bargaining approach (Layard and Nickell, 1986)[[CiteRef::layard1986unemployment]] or the wage-efficiency approach (Shapiro and Stiglitz, 1984)[[CiteRef::shapiro1984equilibrium]]. Both interpretations rely on the fact that unemployment represents an outside threat that leads workers to accept lower wages the greater the threat. The bargaining approach emphasizes the role of workers? (or unions?) power in the wage setting negotiations, power that is weakened when unemployment is high. The wage-efficiency approach takes the firms? point of view and assumes that firms set wage levels so as to discourage shirking; this level is lower when the threat of not finding a job after being caught shirking gets higher. The wage curve specification allows the theories to be consistent with both involuntary unemployment and the fact that real wages fluctuate less than the theory of the conventional flexible labor supply curve predicts. Microeconometric evidence for such formulations was given in a seminal contribution by (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]].<br />
<br />
In practice, the wage curve for each region k in our model is implemented through the relation:<br />
<br />
[[File:36405282.png]]''' (14)'''<br />
<br />
where ''w'' is the hourly nominal wage level, ''pind'' the consumption price index, ''z'' the unemployment rate, ''ref'' indexes represent the values of the variables at the calibration date, ''pindref'' is derived from the final consumption prices and volumes at the calibration date, ''wref'' is calibrated from the total salaries per sector in the GTAP 6 database (Reference?) and the shares of labor force per sector are taken from International Labor Organisation statistics. By default, ''aw'' is calibrated to 1 and evolves in parallel to labor productivity so that unitary real wages are indexed on labor productivity. ''zref'' represents the underutilization of the labor force at the calibration date. ''f'' is a function equal to one when the unemployment rate is equal to its calibration level, and is negatively sloped, representing a negative elasticity of wages level to unemployment [3].<br />
<br />
By default, we assume all regions' labor markets to be identical and set the underutilization of the labor force at 10% [4] and the wage curve elasticity at -0.1 for all regions (This is a value emerging from many econometric studies, e.g. (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]], (Blanchflower and Oswald 2005). [http://halshs.archives-ouvertes.fr/docs/00/72/44/87/PDF/Guivarch_et_al_2011_Costs_climate_policies_second_best_world_labour_market_imperfections.pdf Guivarch et al. (2011)][[CiteRef::guivarch2011costs]] analyzes the critical role of labour markets imperfections, and in particular of the value of the wage curve elasticity, on the formation of climate stabilization costs.<br />
<br />
=== International Trade ===<br />
<br />
For each good, exports from all world regions are blended into an international variety, which is then imported by each region based on its specific terms-of-trade measured between the price of the aggregate international variety, and the production price of the domestic good.<br />
<br />
International trade is treated ?upstream?: the competition of the domestic and imported varieties of each good is settled in an aggregate manner, not at the level of each domestic agent.<br />
<br />
A well-known modelling issue is then to avoid ?knife-edge? solutions, ''i.e.'' to prevent cheaper goods systematically winning market shares over more expensive ones We follow the most common approach to addressing this issue, the Armington (1969)[[CiteRef::sassi2010im]] specification, which assumes that the domestic and imported varieties of the same good aggregate in a common quantity index, although in an imperfectly substitutable way which is typically derived from assuming that the two varieties combine through a constant elasticity of substitution (CES) function. This allows representing markets in which both domestic production and imports have a share, despite the fact that they are priced differently.<br />
<br />
Despite its straightforward treatment of imperfect product competition, the Armington specification has the major drawback of introducing aggregate volumes that do not sum up the volumes of imported and domestic varieties. While this shortcoming can be ignored for non-descript ?composite? goods, where quantity units are indexes of no direct significance to the economy-energy-environment interactions, it is not compatible with the obvious need to track energy balances expressed in real physical units. Competition between energy goods is thus settled through simplified specifications. In the case of national models, the hypothesis of a constant elasticity of substitution is retained, but the construction of a composite index is dropped. Imports and domestic production are simply summed up to form the resource that is available to the importing economy. For the multi-regional version of Imaclim, a market-sharing formula is implemented. The international market buys energy exports at different prices and sells them at a single average world price to importers; shares of exporters on the international market and regional shares of domestic ''vs.'' imported energy goods dependent on relative prices, export and import taxes, and market fragmentation parameters that are calibrated to reproduce the existing markets structure.<br />
<br />
For all goods, export prices include the producer prices, export taxes or subsidies, and average transportation costs. This allows the model to take into account that increasing energy prices would impact on transportation costs and eventually on commercial flows and industrial location patterns.<br />
<br />
''Armington goods'' [[File:36405284.png]]''' (15,16,17)'''<br />
[[File:36405285.png]]''' (18,19,20)'''<br />
[[File:36405286.png]]''' (21,22)'''<br />
<br />
''Energy goods''<br />
<br />
[[File:36405287.png]]''' (23,24,25)'''<br />
[[File:36405288.png]]''' (26,27,28)'''<br />
[[File:36405289.png]]''' (29,30,31)'''<br />
<br />
<br />
-----<br />
<br />
[1] The treatment of the cost of crude oil production is an exception. The increasing factor weighs on the mark-up rate, to convey the fact that oligopolistic producers can take advantage of capacity shortages by increasing their differential rent.<br />
<br />
[2] Obviously, this is a limitation of the current calibration of the model. Future developments will look into the possibility to differentiate labor markets per regions. However, one important difficulty lies in the lack of reliable data on the underutilization of the labor forces in all regions, in particular due to informal economy, very diverse accounting rules for unemployment rates and variations in hours worked per person across countries.<br />
<br />
[3] Choosing a functional form and calibrating the function is particularly tricky, notably due to the lack of reliable data to fully inform the functioning of the labor markets worldwide. We chose a function of the form a.(1-tanh(c.z)), and calibrate the parameters a and c so as to have the desired value and elasticity at the calibration point.<br />
<br />
[4] Contrary to the definition by the U.S. Bureau of Labor Statistics, the level of unemployment is expressed here in terms of worked hours and not in terms of persons.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Economic_activity_-_IMACLIM&diff=5261Economic activity - IMACLIM2016-09-29T15:58:17Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=Economic activity<br />
}}<br />
<br />
== Modelling economic growth ==<br />
<br />
=== An exogenous growth engine composed of demography and labour productivity growth ===<br />
<br />
The IMACLIM-R model growth engine is composed of exogenous demographic trends ([[Population_-_IMACLIM|See section on Population]]) and exogenous trends in labor productivity, as proposed in Solow's neoclassical model of economic growth (Solow 1956)[[CiteRef::solow1956contribution]]. To build these labor productivity trends we draw on stylized facts from the literature, in particular the convergence assumption (Barro and Sala-i-Martin 1992)[[CiteRef::barro1992convergence]] and two empirical analyses on economic convergence, one investigating past trends by Maddison (1995)[[CiteRef::maddison1995monitoring]], and another by Martins and al. (2005)[[CiteRef::oliveira2005impact]] looking at future trends. In the default parameterization of the model, we retain a 'leader', the US, whose labor productivity growth trend lies between 2% in the short run and 1.65% in the long run. The trends in labor productivity of the other regions catch up with that of the leader over time, i.e. their growth in labor productivity is higher the further their level of absolute labor productivity is from the leader's. All sectors within one region exhibit the same growth in labor productivity, while the respective initial levels are sector and region specific<br />
<br />
The two sets of assumptions on demography and labor productivity growth describe natural growth (Phelps, 1961)[[CiteRef::phelps1961golden]], i.e. the growth rate that an aggregated one-sector economy would follow under full employment of factors of production.<br />
<br />
=== Realized GDP growth is endogenous ===<br />
<br />
In this multi-sectoral framework of Imaclim-R, with partial use of factors of production, the effective economic growth rate may depart from the exogenous natural growth rate trend. The structure and rate of realized growth are endogenously determined by: (i) the allocation of labor force across sectors, which is itself governed by the final demand of these sectors, and (ii) the evolution in unemployment rates, which also result from the final demand of these sectors and the constraints of installed productive capacities and their technical characteristics.<br />
<br />
First, the twelve production sectors have different productivities, captured by unitary labor requirements for a unit of production. Therefore the effective labor productivity of the economy depends on the allocation of the labor force among production sectors. For instance, the overall productivity of labor increases through structural changes that favour the reallocation of labor towards highly productive sectors. In that case, realized economic growth can be higher than the natural growth rate. Second, exogenous labor productivity gains may not be transformed into actual growth if unemployment increases due to demand shortage or constraints on installed productive capacities.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Population_-_IMACLIM&diff=5260Population - IMACLIM2016-09-29T15:55:57Z<p>Celine Guivarch: Replaced content with "{{ModelDocumentationTemplate |IsDocumentationOf=IMACLIM |DocumentationCategory=Population }} In IMACLIM-R model population growth is taken from exogenous demographic tren..."</p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=Population<br />
}}<br />
<br />
In IMACLIM-R model population growth is taken from exogenous demographic trends (by default, UN World Population Prospects, medium scenario, United Nations, 2005)[[CiteRef::united2005world]].</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Economic_activity_-_IMACLIM&diff=5259Economic activity - IMACLIM2016-09-29T15:54:32Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=Economic activity<br />
}}<br />
<br />
== Modelling economic growth ==<br />
<br />
=== An exogenous growth engine composed of demography and labour productivity growth ===<br />
<br />
The IMACLIM-R model growth engine is composed of exogenous demographic trends (see section on PopulationXXX) and exogenous trends in labor productivity, as proposed in Solow's neoclassical model of economic growth (Solow 1956)[[CiteRef::solow1956contribution]]. To build these labor productivity trends we draw on stylized facts from the literature, in particular the convergence assumption (Barro and Sala-i-Martin 1992)[[CiteRef::barro1992convergence]] and two empirical analyses on economic convergence, one investigating past trends by Maddison (1995)[[CiteRef::maddison1995monitoring]], and another by Martins and al. (2005)[[CiteRef::oliveira2005impact]] looking at future trends. In the default parameterization of the model, we retain a 'leader', the US, whose labor productivity growth trend lies between 2% in the short run and 1.65% in the long run. The trends in labor productivity of the other regions catch up with that of the leader over time, i.e. their growth in labor productivity is higher the further their level of absolute labor productivity is from the leader's. All sectors within one region exhibit the same growth in labor productivity, while the respective initial levels are sector and region specific<br />
<br />
The two sets of assumptions on demography and labor productivity growth describe natural growth (Phelps, 1961)[[CiteRef::phelps1961golden]], i.e. the growth rate that an aggregated one-sector economy would follow under full employment of factors of production.<br />
<br />
=== Realized GDP growth is endogenous ===<br />
<br />
In this multi-sectoral framework of Imaclim-R, with partial use of factors of production, the effective economic growth rate may depart from the exogenous natural growth rate trend. The structure and rate of realized growth are endogenously determined by: (i) the allocation of labor force across sectors, which is itself governed by the final demand of these sectors, and (ii) the evolution in unemployment rates, which also result from the final demand of these sectors and the constraints of installed productive capacities and their technical characteristics.<br />
<br />
First, the twelve production sectors have different productivities, captured by unitary labor requirements for a unit of production. Therefore the effective labor productivity of the economy depends on the allocation of the labor force among production sectors. For instance, the overall productivity of labor increases through structural changes that favour the reallocation of labor towards highly productive sectors. In that case, realized economic growth can be higher than the natural growth rate. Second, exogenous labor productivity gains may not be transformed into actual growth if unemployment increases due to demand shortage or constraints on installed productive capacities.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Economic_activity_-_IMACLIM&diff=5258Economic activity - IMACLIM2016-09-29T15:51:06Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=Economic activity<br />
}}<br />
<br />
== Modelling economic growth - Realized GDP growth is endogenous ===<br />
<br />
In this multi-sectoral framework of Imaclim-R, with partial use of factors of production, the effective economic growth rate may depart from the exogenous natural growth rate trend. The structure and rate of realized growth are endogenously determined by: (i) the allocation of labor force across sectors, which is itself governed by the final demand of these sectors, and (ii) the evolution in unemployment rates, which also result from the final demand of these sectors and the constraints of installed productive capacities and their technical characteristics.<br />
<br />
First, the twelve production sectors have different productivities, captured by unitary labor requirements for a unit of production. Therefore the effective labor productivity of the economy depends on the allocation of the labor force among production sectors. For instance, the overall productivity of labor increases through structural changes that favour the reallocation of labor towards highly productive sectors. In that case, realized economic growth can be higher than the natural growth rate. Second, exogenous labor productivity gains may not be transformed into actual growth if unemployment increases due to demand shortage or constraints on installed productive capacities.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Population_-_IMACLIM&diff=5257Population - IMACLIM2016-09-29T15:49:45Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=Population<br />
}}<br />
== Modelling economic growth ==<br />
<br />
=== An exogenous growth engine composed of demography and labour productivity growth ===<br />
<br />
The IMACLIM-R model growth engine is composed of exogenous demographic trends (by default, UN World Population Prospects, medium scenario, United Nations, 2005)[[CiteRef::united2005world]] and exogenous trends in labor productivity, as proposed in Solow's neoclassical model of economic growth (Solow 1956)[[CiteRef::solow1956contribution]]. To build these labor productivity trends we draw on stylized facts from the literature, in particular the convergence assumption (Barro and Sala-i-Martin 1992)[[CiteRef::barro1992convergence]] and two empirical analyses on economic convergence, one investigating past trends by Maddison (1995)[[CiteRef::maddison1995monitoring]], and another by Martins and al. (2005)[[CiteRef::oliveira2005impact]] looking at future trends. In the default parameterization of the model, we retain a 'leader', the US, whose labor productivity growth trend lies between 2% in the short run and 1.65% in the long run. The trends in labor productivity of the other regions catch up with that of the leader over time, i.e. their growth in labor productivity is higher the further their level of absolute labor productivity is from the leader's. All sectors within one region exhibit the same growth in labor productivity, while the respective initial levels are sector and region specific<br />
<br />
The two sets of assumptions on demography and labor productivity growth describe natural growth (Phelps, 1961)[[CiteRef::phelps1961golden]], i.e. the growth rate that an aggregated one-sector economy would follow under full employment of factors of production.<br />
<br />
=== Realized GDP growth is endogenous ===<br />
<br />
In this multi-sectoral framework of Imaclim-R, with partial use of factors of production, the effective economic growth rate may depart from the exogenous natural growth rate trend. The structure and rate of realized growth are endogenously determined by: (i) the allocation of labor force across sectors, which is itself governed by the final demand of these sectors, and (ii) the evolution in unemployment rates, which also result from the final demand of these sectors and the constraints of installed productive capacities and their technical characteristics.<br />
<br />
First, the twelve production sectors have different productivities, captured by unitary labor requirements for a unit of production. Therefore the effective labor productivity of the economy depends on the allocation of the labor force among production sectors. For instance, the overall productivity of labor increases through structural changes that favour the reallocation of labor towards highly productive sectors. In that case, realized economic growth can be higher than the natural growth rate. Second, exogenous labor productivity gains may not be transformed into actual growth if unemployment increases due to demand shortage or constraints on installed productive capacities.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5256Model concept, solver and details - IMACLIM2016-09-29T15:43:25Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess 'sustainability- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging 'hybrid' models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities (v). On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria as depicted in <xr id="fig:imaclim_2"/>.<br />
<br />
<figure id="fig:imaclim_2"><br />
[[File:35815505.png|none|800px|thumb|<caption> The recursive and modular architecture of the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
For each annual static equilibrium, domestic and international markets (besides markets for ''factors'' such as capital and labour) are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as is common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''<sub>k,i</sub>, defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''<sub>j,i,k</sub> of intermediate goods ''j'' and of labour ''l''<sub>k,i</sub>. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''<sub>k,i</sub>/''Cap''<sub>k,i</sub> according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation. Following (Corrado and Mattey, 1997[[CiteRef::corrado1997capacity]]), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition. The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal). This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the 'capital' factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households' consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports. For non-energy goods, we adopt Armington specifications (Armington, 1969[[CiteRef::armington1969theory]]) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities. The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents' decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents' microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966[[CiteRef::ahmad1966theory]]). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959[[CiteRef::johansen1959substitution]]).<br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006[[CiteRef::hourcade2006hybrid]]). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954[[CiteRef::arrow1954existence]]), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5255Model concept, solver and details - IMACLIM2016-09-29T15:35:08Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess 'sustainability- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging 'hybrid' models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities (v). On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria as depicted in <xr id="fig:imaclim_2"/>.<br />
<br />
<figure id="fig:imaclim_2"><br />
[[File:35815505.png|none|800px|thumb|<caption> The recursive and modular architecture of the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
For each annual static equilibrium, domestic and international markets (besides markets for ''factors'' such as capital and labour) are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as is common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''<sub>k,i</sub>, defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''<sub>j,i,k</sub> of intermediate goods ''j'' and of labour ''l''<sub>k,i</sub>. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''<sub>k,i</sub>/''Cap''<sub>k,i</sub> according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation <ref>Following (Corrado and Mattey, 1997[[CiteRef::corrado1997capacity]]), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.</ref>. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition <ref>The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).</ref>. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households' consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports <ref>For non-energy goods, we adopt Armington specifications (Armington, 1969[[CiteRef::armington1969theory]]) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.</ref>. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities <ref>The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</ref>.<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966[[CiteRef::ahmad1966theory]]). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959[[CiteRef::johansen1959substitution]]).<br />
<br />
<references /><br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006[[CiteRef::hourcade2006hybrid]]). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954[[CiteRef::arrow1954existence]]), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] <br />
<br />
[2] <br />
<br />
[3] <br />
<br />
[4]</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5254Model concept, solver and details - IMACLIM2016-09-29T15:30:21Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess 'sustainability- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging 'hybrid' models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities (v). On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria as depicted in <xr id="fig:"/>.<br />
<br />
<figure id="fig:imaclim_2"><br />
[[File:35815505.png|none|800px|thumb|<caption> The recursive and modular architecture of the Imaclim-R hybrid model</caption>]]<br />
</figure><br />
<br />
For each annual static equilibrium, domestic and international markets (besides markets for ''factors'' such as capital and labour) are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as is common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation <ref>Following (Corrado and Mattey, 1997[[CiteRef::corrado1997capacity]]), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.</ref>. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition <ref>The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).</ref>. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports <ref>For non-energy goods, we adopt Armington specifications (Armington, 1969[[CiteRef::armington1969theory]]) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.</ref>. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities <ref>The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</ref>.<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966[[CiteRef::ahmad1966theory]]). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959[[CiteRef::johansen1959substitution]]).<br />
<br />
<references /><br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006[[CiteRef::hourcade2006hybrid]]). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954[[CiteRef::arrow1954existence]]), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] <br />
<br />
[2] <br />
<br />
[3] <br />
<br />
[4]</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Macro-economy_-_IMACLIM&diff=5253Macro-economy - IMACLIM2016-09-29T15:11:07Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Macro-economy<br />
}}<br />
== A general equilibrium with rigidities ==<br />
<br />
The representation of the economy in Imaclim-R is a multi-sector (12 sectors), multi-region (12 regions) general equilibrium framework. In each region, there are 14 economic agents: one representative household, one representative firm per sector (hence 12 representative firms) and the public administrations. Households receive revenues from labor and capital and from transfers from public administrations; they save part of their revenues; they chose their consumptions of goods and services depending on relative prices; they pay taxes to the public administrations. Productive sectors chose their production levels to meet demand, earn profits, pay wages and dividends to households and pay taxes to public administrations. Public administrations collect taxes, make public expenditures and invest in public infrastructures, and organize transfers. Regions are linked through international markets for goods and services, and capital.<br />
<br />
[[File:36405263.png]]<br />
<br />
=== Households ===<br />
<br />
Each year, households maximize their current utility under constraints of both revenue received and of their time spent in transport. They save an exogenous share of their revenues. For detailed descriptions of demand formation mechanisms refer to the [/x/3JUMAg section on demand representation].<br />
<br />
=== Public administrations ===<br />
<br />
Public administrations collect taxes; make public expenditures including investment in public infrastructures; and organize transfers.<br />
<br />
Tax rates (and/or subsidies) are calibrated to their values at the calibration year (2001). Taxes (and/or subsidies) impact upon energy, labor, revenues, added value, production, imports and exports. In the default setting of the model, tax rates are kept constant throughout the modelling period (except for scenarios that model the introduction of a carbon tax ); although alternative assumption on tax rates can also be tested. In a scenario wherea carbon tax is introduced, alternative assumptions on the use of the corresponding revenues can be modelled: i.e. they are given to households via transfers, used to reduce other pre-existing tax rates or used to finance a subsidy.<br />
<br />
In the default setting public expenditures in each region are assumed to follow GDP growth rates, Alternative assumptions on evolutions in public expenditures can also be tested.<br />
<br />
Transfers are determined such that the public administration budget is at equilibrium each year. Public debt is not accounted for.<br />
<br />
=== Productive sectors ===<br />
<br />
A start point for IMACLIM is the recognition that it is almost impossible to find mathematical functions that can handle large departures from a reference equilibrium over a time period of one century and are flexible enough to encompass different scenarios of structural change resulting from the interplay between consumption styles, technologies and localization patterns (Hourcade, 1993)[[CiteRef::hourcade1993modelling]].<br />
<br />
==== Beyond the classical production function, or reconciling bottom-up and top-down approaches ====<br />
<br />
In IMACLIM-R, there is no production function, such as a constant elasticity of substitution function, to represent evolutions in production techniques (substitutions between production factors). Instead, evolutions in production techniques are represented in a recursive structure by an exchange of information between static and dynamic modules described as follows: <br />
<br />
* An annual static equilibrium module, in which the production function mimics the Leontief specification, with fixed equipment stocks and fixed intensity of labor, energy and other intermediary inputs, but with a flexible utilization rate. Solving this equilibrium at t provides a snapshot of the economy at this date showing a set of information about relative prices, levels of output, physical flows and profitability rates for each sector and allocation of investments among sectors.<br />
<br />
* Dynamic modules, including demography, capital dynamics and sector-specific reduced forms of technology-rich models, which take into account the economic values of the previous static equilibrium, assess the reaction of technical systems and send back this information to the static module in the form of new input-output coefficients for calculating the equilibrium at t + 1. Each year, technical choices are flexible but they modify only at the margin the input-output coefficients and labor productivity embodied in the existing equipment that result from past technical choices. This general putty-clay assumption is critical to represent the inertia in technical systems and the role of volatility in economic signals.<br />
<br />
This modelling approach allows for abandoning standard aggregate production functions, which have intrinsic limitations in cases of large departures from the reference equilibrium (Frondel et al., 2002)[[CiteRef::frondel2002capital]] and sea changes of production frontiers over several decades.<br />
<br />
As we move away from using a traditional production function, it becomes possible to highlight the influence of factors other than price on decisions affecting the allocation of resources. The use of this modeling approach requires however a comprehensive description of the temporally evolving technical characteristics of each sector.<br />
<br />
At each point in time, producers are assumed to operate under constraint of a fixed production capacity ''Cap<sub>k,i</sub>'', defined as the maximum level of physical output achievable with their installed equipment.<br />
<br />
However, the model allows short-run adjustments to market conditions through the modification of the utilization rate ''Q<sub>k,i</sub>/Cap<sub>k,i</sub>''. This represents a different approach from standard production specifications, since in Imaclim the ?capital? factor is not always fully utilized. Supply cost curves in Imaclim-R thus show static decreasing returns: production costs increase when the utilization rate of equipment approaches 1 (100 %) (Figure below). In principle, these decreasing returns affect all intermediary inputs and labor. However, for the sake of simplicity and because of the order of magnitude of the correlation between utilization rates and prices (Corrado and Mattey, 1997)[[CiteRef::corrado1997capacity]], we assume that the primary cause of higher production costs is higher labor costs due to overtime operations with lower productivity, costly night work and increased maintenance works. We thus set (i) fixed input-output coefficients representing that, with the current set of embodied techniques, producing one unit of good ''i'' in region ''k'' requires the fixed physical amount ''IC<sub>j,i,k</sub>'' of intermediate goods j and ''l<sub>k,i</sub>''of labor; (ii) a decreasing return parameter ''?<sub>k,i</sub>= ? (Q<sub>k,i</sub>/Cap<sub>k,i</sub>)'' on wages only, at the sector level [1].<br />
<br />
This solution actually comes back to earlier works on the existence of short-run flexibility of production systems at the sectoral level with putty-clay technologies (Marshall, 1890)[[CiteRef::marshallpoe]], (Johansen, 1959)[[CiteRef::johansen1959substitution]] demonstrating that this flexibility comes less from input substitution than from variations in differentiated capacity utilization rates.<br />
<br />
[[File:36405273.png]]<br />
<br />
===== Equations =====<br />
<br />
We derive an expression of mean production costs ''Cm<sub>k,i</sub>'', that depends on the prices of intermediate goods ''pIC<sub>j,i,k</sub>'', input-ouput coefficients ''IC<sub>j,i,k</sub>'' and ''l<sub>k,i</sub>'', wages ''w<sub>k,i</sub>'', and production levels through the decreasing return factor ''?<sub>k,i</sub>'' applied to labor costs (including payroll taxes).<br />
<br />
[[File:36405274.png]]<br />
<br />
Market prices and associated profits depend on assumptions regarding the degree of market competition in each sector (e.g. perfect competition or monopoly). Unless otherwise stated, perfect competition is assumed in every production sector, with the market price equal to the marginal production cost.<br />
<br />
Producer prices are equal to the sum of mean production costs and mean profits. In the current version of the model, all sectors apply a constant sector-specific mark-up rate ''p<sub>k,i</sub>'' so that the producer price is given by equation (2). This constant mark-up corresponds to a standard profit-maximization for producers whose mean production costs follow equation (1) and who are price-takers, provided that the decreasing return factor can be approximated by an exponential function of utilization rate.<br />
<br />
[[File:36405275.png]]<br />
<br />
This equation is an inverse supply curve: it shows how a representative producer decides their level of output ''Q<sub>k,i</sub>'' (which is included in the ''?<sub>k,i</sub>''factor) as a function of all prices and real wages.<br />
<br />
From equation (2) we derive wages and profits in each sector:<br />
<br />
[[File:36405276.png]]<br />
<br />
The cost function shows fixed technical coefficients and therefore does not allow for substitution between production factors when relative prices change within the new static equilibrium. Only the level of output ''Q<sub>k,i </sub>'' can be adjusted according to these price changes.<br />
<br />
=== Markets ===<br />
<br />
==== Markets of goods and services ====<br />
<br />
In the Imaclim-R model, all intermediate and final goods are internationally tradable and total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports (see section on international trade). Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices calculated in the static equilibrium such that demand and supply are equal.<br />
<br />
'''Price'''<br />
<br />
In each region ''k'' and sector ''i'', the price equation is:<br />
<br />
[[File:36405277.png]]'''(5)'''<br />
<br />
where ''?<sub>k,i</sub>'' is a markup, ''IC<sub>j,i,k</sub>'' are intermediate consumption of good ''j'' in sector ''i'' in region ''k'', and ''?<sub>k,i</sub>'' is an increasing cost (or decreasing returns) function of the productive capacities utilization rate. This function is applied to labor costs (which include wages w<sub>k,i</sub> and labor taxes tax<sub>k,i</sub>).<br />
<br />
'' _The functional form for _?'' is:<br />
<br />
[[File:36405278.png]]'''(6)'''<br />
<br />
Regional prices thus correspond to the addition of average regional production costs and a margin. This markup, which is fixed in the static equilibrium, encapsulates Ricardian and scarcity rents at the same time and increases with the utilization rate of production capacities in the oil sector.<br />
<br />
A further parameter for the oil sector is that Middle-Eastern producers are considered ?swing producers? who are free to strategically set their investment decisions and, until they reach their depletion constraints, to control oil prices through the utilization rate of their production capacities (Kaufmann et al, 2004)[[CiteRef::kaufmann2004does]]. This possibility is justified by the temporary reinforcement of their market power due to the stagnation and decline of conventional oil in the rest of the world. They can in particular decide to slow the development of production capacities below its maximum rate in order to adjust the oil price according to their rent-seeking objectives. They anticipate the level of capacities that will make it possible for them to reach their goals, on the basis of projections of total oil demand and production in other regions.<br />
<br />
==== Capital markets ====<br />
<br />
A share (''shareExpK'') of gross domestic savings (GRB) is internationally tradable, and distributed via an international capital pool. Each regions receives a share of the international pool (''shareImpK)''. In the default model setting, both shares (''shareExpK and shareImpK'') are exogenous: ''shareExpK'' is exponentially reduced such that international financial imbalances disappear by 2050 and ''shareImpK'' remains constant throughout the simulation period.<br />
<br />
The remaining share of domestic savings and imported capital (NRB) are then invested in each region respectively.<br />
<br />
[[File:36405279.png]] ''' (7,8,9)'''<br />
<br />
* *The total amount of money ''InvFin<sub>k,i</sub>'' available for investment in sector ''i'' in the region ''k'' allows new capacities ''DCap<sub>k,i</sub>'' to be constructed at a cost ''pCap<sub>k,i</sub>'' (equation 9-3-5). The cost ''pCap<sub>k,i</sub>'' depends on the quantities ''?<sub>j,i,k</sub>'' and the prices ''pI<sub>k,j</sub>'' of goods ''j'' required by the construction of a new unit of capacity in sector ''i'' and in region ''k''. Coefficient ''?<sub>j,i,k</sub>'' is the amount of good ''j'' necessary to constuct the equipment corresponding to one new unit of production capacity in sector i of the region k. Finally, in each region, the total demand for goods for building new capacities is given by the last equation below.<br />
<br />
[[File:36405280.png]]''' (10,11,12)'''<br />
<br />
Each sector anticipates future production levels through an anticipation of future prices and demand and formulates the corresponding investment demand. Total available investment ''I<sub>k,j</sub>'' is then distributed among sectors according to their demand.<br />
<br />
==== Labour markets ====<br />
<br />
At each time step, producers operate in static equilibria with a fixed input of labor per unit of output. This labor input, corresponding to labor productivity, evolves between two yearly equilibria following exogenous trends in labor productivity.<br />
<br />
Three of the model features explain the possibility of under-utilization of labor as a factor of production, and thus unemployment. First, rigidity of real wages, represented by a wage curve can prevent wages falling to their market-clearing level. Put another way, instantaneous adjustment of wages to the economic context in the static equilibrium does not occur in an optimal manner. Second, in the static equilibrium, the fixed technologies (Leontief coefficients even for labor input) prevent substitution among production factors in the short run. And third, the installed productive capital is not mobile across sectors, which creates rigidities in the reallocations of production between sectors when relative prices change.<br />
<br />
In each region ''k'', each sector employs the labor force ''l<sub>k,i</sub><sup>.</sup>Q<sub>k,i</sub>'', where ''l<sub>k,i</sub>'' is the unitary labor input (in hours worked) and Q<sub>k,i</sub> the production. The underutilization of the labor force, equivalently referred to as the ?unemployment rate? [2] in the following, ''_z<sub>k</sub>'' is therefore equal to one minus the ratio of the employed labor force across all sectors over ''L<sub>k</sub>'', the total labor force:<br />
<br />
[[File:36405281.png]] ''' (13)'''<br />
<br />
No endogenous mobility of workers between regions is accounted for in the model. Thus twelve separate labor markets are represented.<br />
<br />
We chose to model labor market imperfections through an aggregate regional ''wage curve'' that links real wage levels to the unemployment rate. This representation is based on labor theories developed in the 1980s and early 1990s in which an aggregate wage curve, or ''wage setting curve'', is the primary distinguishing feature (an overview can be found in Layard et al., 2005[[CiteRef::layard2005unemployment]]; Lindbeck, 1993[[CiteRef::lindbeck1993unemployment]]; or Phelps, 1992[[CiteRef::phelps1992consumer]]). The novel approach of these models, when introduced, was to replace the conventional labor supply curve with a negatively-sloped curve linking the level of wages to the level of unemployment. The interpretation of this wage curve is given either by the bargaining approach (Layard and Nickell, 1986)[[CiteRef::layard1986unemployment]] or the wage-efficiency approach (Shapiro and Stiglitz, 1984)[[CiteRef::shapiro1984equilibrium]]. Both interpretations rely on the fact that unemployment represents an outside threat that leads workers to accept lower wages the greater the threat. The bargaining approach emphasizes the role of workers? (or unions?) power in the wage setting negotiations, power that is weakened when unemployment is high. The wage-efficiency approach takes the firms? point of view and assumes that firms set wage levels so as to discourage shirking; this level is lower when the threat of not finding a job after being caught shirking gets higher. The wage curve specification allows the theories to be consistent with both involuntary unemployment and the fact that real wages fluctuate less than the theory of the conventional flexible labor supply curve predicts. Microeconometric evidence for such formulations was given in a seminal contribution by (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]].<br />
<br />
In practice, the wage curve for each region k in our model is implemented through the relation:<br />
<br />
[[File:36405282.png]]''' (14)'''<br />
<br />
where ''w'' is the hourly nominal wage level, ''pind'' the consumption price index, ''z'' the unemployment rate, ''ref'' indexes represent the values of the variables at the calibration date, ''pindref'' is derived from the final consumption prices and volumes at the calibration date, ''wref'' is calibrated from the total salaries per sector in the GTAP 6 database (Reference?) and the shares of labor force per sector are taken from International Labor Organisation statistics. By default, ''aw'' is calibrated to 1 and evolves in parallel to labor productivity so that unitary real wages are indexed on labor productivity. ''zref'' represents the underutilization of the labor force at the calibration date. ''f'' is a function equal to one when the unemployment rate is equal to its calibration level, and is negatively sloped, representing a negative elasticity of wages level to unemployment [3].<br />
<br />
By default, we assume all regions' labor markets to be identical and set the underutilization of the labor force at 10% [4] and the wage curve elasticity at -0.1 for all regions (This is a value emerging from many econometric studies, e.g. (Blanchflower and Oswald 1995)[[CiteRef::blanchflower1994introduction]], (Blanchflower and Oswald 2005). [http://halshs.archives-ouvertes.fr/docs/00/72/44/87/PDF/Guivarch_et_al_2011_Costs_climate_policies_second_best_world_labour_market_imperfections.pdf Guivarch et al. (2011)][[CiteRef::guivarch2011costs]] analyzes the critical role of labour markets imperfections, and in particular of the value of the wage curve elasticity, on the formation of climate stabilization costs.<br />
<br />
=== International Trade ===<br />
<br />
For each good, exports from all world regions are blended into an international variety, which is then imported by each region based on its specific terms-of-trade measured between the price of the aggregate international variety, and the production price of the domestic good.<br />
<br />
International trade is treated ?upstream?: the competition of the domestic and imported varieties of each good is settled in an aggregate manner, not at the level of each domestic agent.<br />
<br />
A well-known modelling issue is then to avoid ?knife-edge? solutions, ''i.e.'' to prevent cheaper goods systematically winning market shares over more expensive ones We follow the most common approach to addressing this issue, the Armington (1969)[[CiteRef::sassi2010im]] specification, which assumes that the domestic and imported varieties of the same good aggregate in a common quantity index, although in an imperfectly substitutable way which is typically derived from assuming that the two varieties combine through a constant elasticity of substitution (CES) function. This allows representing markets in which both domestic production and imports have a share, despite the fact that they are priced differently.<br />
<br />
Despite its straightforward treatment of imperfect product competition, the Armington specification has the major drawback of introducing aggregate volumes that do not sum up the volumes of imported and domestic varieties. While this shortcoming can be ignored for non-descript ?composite? goods, where quantity units are indexes of no direct significance to the economy-energy-environment interactions, it is not compatible with the obvious need to track energy balances expressed in real physical units. Competition between energy goods is thus settled through simplified specifications. In the case of national models, the hypothesis of a constant elasticity of substitution is retained, but the construction of a composite index is dropped. Imports and domestic production are simply summed up to form the resource that is available to the importing economy. For the multi-regional version of Imaclim, a market-sharing formula is implemented. The international market buys energy exports at different prices and sells them at a single average world price to importers; shares of exporters on the international market and regional shares of domestic ''vs.'' imported energy goods dependent on relative prices, export and import taxes, and market fragmentation parameters that are calibrated to reproduce the existing markets structure.<br />
<br />
For all goods, export prices include the producer prices, export taxes or subsidies, and average transportation costs. This allows the model to take into account that increasing energy prices would impact on transportation costs and eventually on commercial flows and industrial location patterns.<br />
<br />
''Armington goods'' [[File:36405284.png]]''' (15,16,17)'''<br />
[[File:36405285.png]]''' (18,19,20)'''<br />
[[File:36405286.png]]''' (21,22)'''<br />
<br />
''Energy goods''<br />
<br />
[[File:36405287.png]]''' (23,24,25)'''<br />
[[File:36405288.png]]''' (26,27,28)'''<br />
[[File:36405289.png]]''' (29,30,31)'''<br />
<br />
<br />
-----<br />
<br />
[1] The treatment of the cost of crude oil production is an exception. The increasing factor weighs on the mark-up rate, to convey the fact that oligopolistic producers can take advantage of capacity shortages by increasing their differential rent.<br />
<br />
[2] Obviously, this is a limitation of the current calibration of the model. Future developments will look into the possibility to differentiate labor markets per regions. However, one important difficulty lies in the lack of reliable data on the underutilization of the labor forces in all regions, in particular due to informal economy, very diverse accounting rules for unemployment rates and variations in hours worked per person across countries.<br />
<br />
[3] Choosing a functional form and calibrating the function is particularly tricky, notably due to the lack of reliable data to fully inform the functioning of the labor markets worldwide. We chose a function of the form a.(1-tanh(c.z)), and calibrate the parameters a and c so as to have the desired value and elasticity at the calibration point.<br />
<br />
[4] Contrary to the definition by the U.S. Bureau of Labor Statistics, the level of unemployment is expressed here in terms of worked hours and not in terms of persons.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Population_-_IMACLIM&diff=5252Population - IMACLIM2016-09-29T14:18:03Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=Population<br />
}}<br />
== Modelling economic growth ==<br />
<br />
=== An exogenous growth engine composed of demography and labour productivity growth ===<br />
<br />
The IMACLIM-R model growth engine is composed of exogenous demographic trends (by default, UN World Population Prospects, medium scenario, United Nations, 2005)[[CiteRef::united2005world]] and exogenous trends in labor productivity, as proposed in Solow's neoclassical model of economic growth (Solow 1956)[[CiteRef::solow1956contribution]]. To build these labor productivity trends we draw on stylized facts from the literature, in particular the convergence assumption (Barro and Sala-i-Martin 1992)[[CiteRef::barro1992convergence]] and two empirical analyses on economic convergence, one investigating the past trends by Maddison (1995)[[CiteRef::maddison1995monitoring]], and another one by Martins and al. (2005)[[CiteRef::oliveira2005impact]] looking at future trends. In the default parameterization of the model, we retain a 'leader', the US, whose labor productivity growth trend lies between 2% in the short run and 1.65% in the long run. The trends in labor productivity of the other regions catch up with the leader?s over time, i.e. their growth in labor productivity is higher the further their level of absolute labor productivity is from the leader's. All sectors within one region exhibit the same growth in labor productivity, while the respective initial levels are sector and region specific<br />
<br />
The two sets of assumptions on demography and labor productivity growth describe natural growth (Phelps, 1961)[[CiteRef::phelps1961golden]], i.e. the growth rate that an aggregated one-sector economy would follow under full employment of factors of production.<br />
<br />
=== Realized GDP growth is endogenous ===<br />
<br />
In this multi-sectoral framework of Imaclim-R, with partial use of factors of production, the effective economic growth rate may depart from the exogenous natural growth rate trend. The structure and rate of realized growth are endogenously determined by: (i) the allocation of labor force across sectors,which is itself governed by the final demand of these sectors, and (ii) the evolution in unemployment rates, which also results from the final demand of these sectors and the constraints of installed productive capacities and their technical characteristics.<br />
<br />
First, the twelve production sectors have different productivities, captured by unitary labor requirements for a unit of production. Therefore the effective labor productivity of the economy therefore depends on the allocation of the labor force among production sectors. For instance, the overall productivity of labor increases through structural changes that favour the reallocation of labor towards highly productive sectors. In that case, realized economic growth can be higher than the natural growth rate. Second, exogenous labor productivity gains may not be transformed into actual growth if unemployment increases due to demand shortage or constraints on installed productive capacities.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5251References - IMACLIM2016-09-29T14:15:26Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
blanchflower1994introduction;<br />
corrado1997capacity;<br />
frondel2002capital;<br />
guivarch2011costs;<br />
hourcade1993modelling;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
kaufmann2004does;<br />
layard2005unemployment;<br />
layard1986unemployment;<br />
lindbeck1993unemployment;<br />
maddison1995monitoring;<br />
marshallpoe;<br />
oliveira2005impact;<br />
phelps1961golden;<br />
phelps1992consumer;<br />
sassi2010im;<br />
shapiro1984equilibrium;<br />
solow1956contribution;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{blanchflower1994introduction,<br />
title={An introduction to the wage curve},<br />
author={Blanchflower, David and Oswald, Andrew J},<br />
journal={The Journal of Economic Perspectives},<br />
pages={153-167},<br />
year={1995},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{frondel2002capital,<br />
title={The capital-energy controversy: an artifact of cost shares?},<br />
author={Frondel, Manuel and Schmidt, Christoph M},<br />
journal={The Energy Journal},<br />
pages={53-79},<br />
year={2002},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{guivarch2011costs,<br />
title={The costs of climate policies in a second-best world with labour market imperfections},<br />
author={Guivarch, Céline and Crassous, Renaud and Sassi, Olivier and Hallegatte, Stéphane},<br />
journal={Climate Policy},<br />
volume={11},<br />
number={1},<br />
pages={768-788},<br />
year={2011},<br />
publisher={Taylor & Francis}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade1993modelling,<br />
title={Modelling long-run scenarios: methodology lessons from a prospective study on a low CO2 intensive country},<br />
author={Hourcade, Jean-Charles},<br />
journal={Energy Policy},<br />
volume={21},<br />
number={3},<br />
pages={309-326},<br />
year={1993},<br />
publisher={Elsevier}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{kaufmann2004does,<br />
title={Does OPEC matter? An econometric analysis of oil prices},<br />
author={Kaufmann, Robert K and Dees, Stephane and Karadeloglou, Pavlos and Sanchez, Marcelo},<br />
journal={The Energy Journal},<br />
pages={67-90},<br />
year={2004},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{layard2005unemployment,<br />
title={Unemployment: macroeconomic performance and the labour market},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
year={2005},<br />
publisher={Oxford University Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{layard1986unemployment,<br />
title={Unemployment in Britain},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
journal={Economica},<br />
volume={53},<br />
number={210},<br />
pages={121-169},<br />
year={1991}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{lindbeck1993unemployment,<br />
title={Unemployment and macroeconomics},<br />
author={Lindbeck, Assar},<br />
year={1993},<br />
publisher={MIT Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy: 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={OECD, Paris, France}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{marshallpoe,<br />
title={Principles of Economics},<br />
author={Marshall, Alfred},<br />
year={1890},<br />
publisher={London: Macmillan}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund S},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638-643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1992consumer,<br />
title={Consumer demand and equilibrium unemployment in a working model of the customer-market incentive-wage economy},<br />
author={Phelps, Edmund S},<br />
journal={The Quarterly Journal of Economics},<br />
pages={1003--1032},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{shapiro1984equilibrium,<br />
title={Equilibrium unemployment as a worker discipline device},<br />
author={Shapiro, Carl and Stiglitz, Joseph E},<br />
journal={The American Economic Review},<br />
volume={74},<br />
number={3},<br />
pages={433-444},<br />
year={1984},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{solow1956contribution,<br />
title={A contribution to the theory of economic growth},<br />
author={Solow, Robert M},<br />
journal={The quarterly journal of economics},<br />
pages={65-94},<br />
year={1956},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Spatial_dimension_-_IMACLIM&diff=5250Spatial dimension - IMACLIM2016-09-29T14:05:40Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Spatial dimension<br />
}}<br />
<br />
Imaclim-R is a global model of the world economy, divided into the following 12 regions and shown in <xr id="fig:imaclim_1"/>:<br />
<br />
*USA<br />
*Canada<br />
*Europe<br />
*OECD Pacific<br />
*Former Soviet Union<br />
*China<br />
*India<br />
*Brazil<br />
*Middle East<br />
*Africa<br />
*Rest of Asia<br />
*Rest of Latin America<br />
<br />
<figure id="fig:imaclim_1"><br />
[[File:35815647.png|none|600px|thumb|<caption> Regional disaggregation of Imaclim-R model. OECD Pacific includes Australia, New Zealand, Japan and South Korea. FSU = Former Soviet Union, Rest of LAM = Rest of Latin America</caption>]]<br />
</figure></div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Spatial_dimension_-_IMACLIM&diff=5249Spatial dimension - IMACLIM2016-09-29T14:04:32Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Spatial dimension<br />
}}<br />
<br />
There are some new features in the Media Wiki:<br />
*Creating Tables <br />
*Creating Equations <br />
*Dynamic referencing to Figures, Tables and Equations<br />
*Dynamic referencing to Citations<br />
<br />
Imaclim-R is a global model of the world economy, divided into 12 regions as shown in <xr id="fig:imaclim_1"/>:<br />
<br />
*USA<br />
*Canada<br />
*Europe<br />
*OECD Pacific<br />
*Former Soviet Union<br />
*China<br />
*India<br />
*Brazil<br />
*Middle East<br />
*Africa<br />
*Rest of Asia<br />
*Rest of Latin America<br />
<br />
<figure id="fig:imaclim_1"><br />
[[File:35815647.png|none|600px|thumb|<caption> Regional disaggregation of Imaclim-R model. OECD Pacific includes Australia, New Zealand, Japan and South Korea. FSU = Former Soviet Union, Rest of LAM = Rest of Latin America</caption>]]<br />
</figure></div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Spatial_dimension_-_IMACLIM&diff=5248Spatial dimension - IMACLIM2016-09-29T13:56:46Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=Spatial dimension<br />
}}<br />
<br />
Imaclim-R is a global model of the world economy, divided into 12 regions as shown in <xr id="fig:imaclim_1"/>:<br />
<br />
*USA<br />
*Canada<br />
*Europe<br />
*OECD Pacific<br />
*Former Soviet Union<br />
*China<br />
*India<br />
*Brazil<br />
*Middle East<br />
*Africa<br />
*Rest of Asia<br />
*Rest of Latin America<br />
<br />
<figure id="fig:imaclim_1"><br />
[[File:35815647.png|none|600px|thumb|<caption> Regional disaggregation of Imaclim-R model. OECD Pacific includes Australia, New Zealand, Japan and South Korea. FSU = Former Soviet Union, Rest of LAM = Rest of Latin America</caption>]]<br />
</figure></div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Spatial_dimension_-_IMACLIM&diff=5247Spatial dimension - IMACLIM2016-09-29T13:49:10Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=Spatial dimension<br />
}}<br />
<br />
Imaclim-R is a global model of the world economy, divided into 12 regions:<br />
<br />
*USA<br />
*Canada<br />
*Europe<br />
*OECD Pacific<br />
*Former Soviet Union<br />
*China<br />
*India<br />
*Brazil<br />
*Middle East<br />
*Africa<br />
*Rest of Asia<br />
*Rest of Latin America<br />
<br />
<br />
[[File:35815647.png]]</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Spatial_dimension_-_IMACLIM&diff=5246Spatial dimension - IMACLIM2016-09-29T13:44:52Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=Spatial dimension<br />
}}<br />
<br />
Imaclim-R is a global model of the world economy, divided into 12 regions:<br />
<br />
*USA<br />
*Canada<br />
*Europe<br />
*OECD Pacific<br />
*Former Soviet Union<br />
*China<br />
*India<br />
*Brazil<br />
*Middle East<br />
*Africa<br />
*Rest of Asia<br />
*Rest of Latin America</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5245Model concept, solver and details - IMACLIM2016-09-29T13:29:47Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation <ref>Following (Corrado and Mattey, 1997[[CiteRef::corrado1997capacity]]), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.</ref>. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition <ref>The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).</ref>. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports <ref>For non-energy goods, we adopt Armington specifications (Armington, 1969[[CiteRef::armington1969theory]]) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.</ref>. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities <ref>The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</ref>.<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966[[CiteRef::ahmad1966theory]]). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959[[CiteRef::johansen1959substitution]]).<br />
<br />
<references /><br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006[[CiteRef::hourcade2006hybrid]]). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954[[CiteRef::arrow1954existence]]), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] <br />
<br />
[2] <br />
<br />
[3] <br />
<br />
[4]</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5244Model concept, solver and details - IMACLIM2016-09-29T13:27:33Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation <ref>Following (Corrado and Mattey, 1997[[CiteRef::corrado1997capacity]]), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.</ref>. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition <ref>The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).</ref>. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports <ref>For non-energy goods, we adopt Armington specifications (Armington, 1969[[CiteRef::armington1969theory]]) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.</ref>. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities <ref>The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</ref>.<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966[[CiteRef::ahmad1966theory]]). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959[[CiteRef::johansen1959substitution]]).<br />
<br />
<Footnotes/><br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006[[CiteRef::hourcade2006hybrid]]). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954[[CiteRef::arrow1954existence]]), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] <br />
<br />
[2] <br />
<br />
[3] <br />
<br />
[4]</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5243Model concept, solver and details - IMACLIM2016-09-29T13:23:15Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation <pre><ref>Following (Corrado and Mattey, 1997[[CiteRef::corrado1997capacity]]), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.</ref></pre>. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition <pre><ref>The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).</ref></pre>.. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports <pre><ref>For non-energy goods, we adopt Armington specifications (Armington, 1969[[CiteRef::armington1969theory]]) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.</ref>.</pre> All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities <pre><ref>The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</ref></pre>.<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966[[CiteRef::ahmad1966theory]]). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959[[CiteRef::johansen1959substitution]]).<br />
<br />
<pre><Footnotes/></pre><br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006[[CiteRef::hourcade2006hybrid]]). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954[[CiteRef::arrow1954existence]]), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] <br />
<br />
[2] <br />
<br />
[3] <br />
<br />
[4]</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5242Model concept, solver and details - IMACLIM2016-09-29T13:18:53Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation <pre><ref>Following (Corrado and Mattey, 1997[[CiteRef::corrado1997capacity]]), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.</ref></pre>. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition <pre><ref>The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).</ref></pre>.. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports <ref>For non-energy goods, we adopt Armington specifications (Armington, 1969[[CiteRef::armington1969theory]]) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.</ref>. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities <pre><ref>The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</ref></pre>..<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966[[CiteRef::ahmad1966theory]]). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959[[CiteRef::johansen1959substitution]]).<br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006[[CiteRef::hourcade2006hybrid]]). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954[[CiteRef::arrow1954existence]]), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] <br />
<br />
[2] <br />
<br />
[3] <br />
<br />
[4]</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5241Model concept, solver and details - IMACLIM2016-09-29T13:14:23Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation <pre><ref>Following (Corrado and Mattey, 1997[[CiteRef::corrado1997capacity]]), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.</ref></pre>. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition <pre><ref>The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).</ref></pre>.. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports <pre><ref>For non-energy goods, we adopt Armington specifications (Armington, 1969[[CiteRef::armington1969theory]]) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.</ref></pre>.. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities <pre><ref>The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</ref></pre>..<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966[[CiteRef::ahmad1966theory]]). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959[[CiteRef::johansen1959substitution]]).<br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006[[CiteRef::hourcade2006hybrid]]). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954[[CiteRef::arrow1954existence]]), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] <br />
<br />
[2] <br />
<br />
[3] <br />
<br />
[4]</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5240Model concept, solver and details - IMACLIM2016-09-29T13:07:41Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation [1]. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition [2]. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports [3]. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities [4].<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966[[CiteRef::ahmad1966theory]]). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959[[CiteRef::johansen1959substitution]]).<br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006[[CiteRef::hourcade2006hybrid;]]). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954[[CiteRef::arrow1954existence]]), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] Following (Corrado and Mattey, 1997[[CiteRef::corrado1997capacity]]), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.<br />
<br />
[2] The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).<br />
<br />
[3] For non-energy goods, we adopt Armington specifications (Armington, 1969[[CiteRef::armington1969theory]]) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.<br />
<br />
[4] The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5239References - IMACLIM2016-09-28T14:56:26Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
blanchflower1994introduction;<br />
corrado1997capacity;<br />
frondel2002capital;<br />
guivarch2011costs;<br />
hourcade1993modelling;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
kaufmann2004does;<br />
layard2005unemployment;<br />
layard1986unemployment;<br />
lindbeck1993unemployment;<br />
maddison1995monitoring;<br />
marshallpoe;<br />
oliveira2005impact;<br />
phelps1961golden;<br />
phelps1992consumer;<br />
sassi2010im;<br />
shapiro1984equilibrium;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{blanchflower1994introduction,<br />
title={An introduction to the wage curve},<br />
author={Blanchflower, David and Oswald, Andrew J},<br />
journal={The Journal of Economic Perspectives},<br />
pages={153-167},<br />
year={1995},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{frondel2002capital,<br />
title={The capital-energy controversy: an artifact of cost shares?},<br />
author={Frondel, Manuel and Schmidt, Christoph M},<br />
journal={The Energy Journal},<br />
pages={53-79},<br />
year={2002},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{guivarch2011costs,<br />
title={The costs of climate policies in a second-best world with labour market imperfections},<br />
author={Guivarch, Céline and Crassous, Renaud and Sassi, Olivier and Hallegatte, Stéphane},<br />
journal={Climate Policy},<br />
volume={11},<br />
number={1},<br />
pages={768-788},<br />
year={2011},<br />
publisher={Taylor & Francis}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade1993modelling,<br />
title={Modelling long-run scenarios: methodology lessons from a prospective study on a low CO2 intensive country},<br />
author={Hourcade, Jean-Charles},<br />
journal={Energy Policy},<br />
volume={21},<br />
number={3},<br />
pages={309-326},<br />
year={1993},<br />
publisher={Elsevier}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{kaufmann2004does,<br />
title={Does OPEC matter? An econometric analysis of oil prices},<br />
author={Kaufmann, Robert K and Dees, Stephane and Karadeloglou, Pavlos and Sanchez, Marcelo},<br />
journal={The Energy Journal},<br />
pages={67-90},<br />
year={2004},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{layard2005unemployment,<br />
title={Unemployment: macroeconomic performance and the labour market},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
year={2005},<br />
publisher={Oxford University Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{layard1986unemployment,<br />
title={Unemployment in Britain},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
journal={Economica},<br />
volume={53},<br />
number={210},<br />
pages={121-169},<br />
year={1991}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{lindbeck1993unemployment,<br />
title={Unemployment and macroeconomics},<br />
author={Lindbeck, Assar},<br />
year={1993},<br />
publisher={MIT Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy: 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={OECD, Paris, France}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{marshallpoe,<br />
title={Principles of Economics},<br />
author={Marshall, Alfred},<br />
year={1890},<br />
publisher={London: Macmillan}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund S},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638-643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1992consumer,<br />
title={Consumer demand and equilibrium unemployment in a working model of the customer-market incentive-wage economy},<br />
author={Phelps, Edmund S},<br />
journal={The Quarterly Journal of Economics},<br />
pages={1003--1032},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{shapiro1984equilibrium,<br />
title={Equilibrium unemployment as a worker discipline device},<br />
author={Shapiro, Carl and Stiglitz, Joseph E},<br />
journal={The American Economic Review},<br />
volume={74},<br />
number={3},<br />
pages={433-444},<br />
year={1984},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5238References - IMACLIM2016-09-28T14:53:37Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
blanchflower1994introduction;<br />
corrado1997capacity;<br />
frondel2002capital;<br />
guivarch2011costs;<br />
hourcade1993modelling;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
kaufmann2004does;<br />
layard2005unemployment;<br />
layard1986unemployment;<br />
lindbeck1993unemployment;<br />
maddison1995monitoring;<br />
marshallpoe;<br />
oliveira2005impact;<br />
phelps1961golden;<br />
phelps1992consumer;<br />
sassi2010im;<br />
shapiro1984equilibrium;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{blanchflower1994introduction,<br />
title={An introduction to the wage curve},<br />
author={Blanchflower, David and Oswald, Andrew J},<br />
journal={The Journal of Economic Perspectives},<br />
pages={153-167},<br />
year={1995},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{frondel2002capital,<br />
title={The capital-energy controversy: an artifact of cost shares?},<br />
author={Frondel, Manuel and Schmidt, Christoph M},<br />
journal={The Energy Journal},<br />
pages={53--79},<br />
year={2002},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{guivarch2011costs,<br />
title={The costs of climate policies in a second-best world with labour market imperfections},<br />
author={Guivarch, Céline and Crassous, Renaud and Sassi, Olivier and Hallegatte, Stéphane},<br />
journal={Climate Policy},<br />
volume={11},<br />
number={1},<br />
pages={768-788},<br />
year={2011},<br />
publisher={Taylor & Francis}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade1993modelling,<br />
title={Modelling long-run scenarios: methodology lessons from a prospective study on a low CO2 intensive country},<br />
author={Hourcade, Jean-Charles},<br />
journal={Energy Policy},<br />
volume={21},<br />
number={3},<br />
pages={309--326},<br />
year={1993},<br />
publisher={Elsevier}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{kaufmann2004does,<br />
title={Does OPEC matter? An econometric analysis of oil prices},<br />
author={Kaufmann, Robert K and Dees, Stephane and Karadeloglou, Pavlos and Sanchez, Marcelo},<br />
journal={The Energy Journal},<br />
pages={67-90},<br />
year={2004},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{layard2005unemployment,<br />
title={Unemployment: macroeconomic performance and the labour market},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
year={2005},<br />
publisher={Oxford University Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{layard1986unemployment,<br />
title={Unemployment in Britain},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
journal={Economica},<br />
volume={53},<br />
number={210},<br />
pages={121-169},<br />
year={1991}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{lindbeck1993unemployment,<br />
title={Unemployment and macroeconomics},<br />
author={Lindbeck, Assar},<br />
year={1993},<br />
publisher={MIT Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy: 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={OECD, Paris, France}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{marshallpoe,<br />
title={Principles of Economics},<br />
author={Marshall, Alfred},<br />
year={1890},<br />
publisher={London: Macmillan}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund S},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638-643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1992consumer,<br />
title={Consumer demand and equilibrium unemployment in a working model of the customer-market incentive-wage economy},<br />
author={Phelps, Edmund S},<br />
journal={The Quarterly Journal of Economics},<br />
pages={1003--1032},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{shapiro1984equilibrium,<br />
title={Equilibrium unemployment as a worker discipline device},<br />
author={Shapiro, Carl and Stiglitz, Joseph E},<br />
journal={The American Economic Review},<br />
volume={74},<br />
number={3},<br />
pages={433-444},<br />
year={1984},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5237References - IMACLIM2016-09-28T14:47:57Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
blanchflower1994introduction;<br />
corrado1997capacity;<br />
guivarch2011costs;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
kaufmann2004does;<br />
layard2005unemployment;<br />
layard1986unemployment;<br />
lindbeck1993unemployment;<br />
maddison1995monitoring;<br />
marshallpoe;<br />
oliveira2005impact;<br />
phelps1961golden;<br />
phelps1992consumer;<br />
sassi2010im;<br />
shapiro1984equilibrium;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{blanchflower1994introduction,<br />
title={An introduction to the wage curve},<br />
author={Blanchflower, David and Oswald, Andrew J},<br />
journal={The Journal of Economic Perspectives},<br />
pages={153-167},<br />
year={1995},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{frondel2002capital,<br />
title={The capital-energy controversy: an artifact of cost shares?},<br />
author={Frondel, Manuel and Schmidt, Christoph M},<br />
journal={The Energy Journal},<br />
pages={53--79},<br />
year={2002},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{guivarch2011costs,<br />
title={The costs of climate policies in a second-best world with labour market imperfections},<br />
author={Guivarch, Céline and Crassous, Renaud and Sassi, Olivier and Hallegatte, Stéphane},<br />
journal={Climate Policy},<br />
volume={11},<br />
number={1},<br />
pages={768-788},<br />
year={2011},<br />
publisher={Taylor & Francis}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade1993modelling,<br />
title={Modelling long-run scenarios: methodology lessons from a prospective study on a low CO2 intensive country},<br />
author={Hourcade, Jean-Charles},<br />
journal={Energy Policy},<br />
volume={21},<br />
number={3},<br />
pages={309--326},<br />
year={1993},<br />
publisher={Elsevier}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{kaufmann2004does,<br />
title={Does OPEC matter? An econometric analysis of oil prices},<br />
author={Kaufmann, Robert K and Dees, Stephane and Karadeloglou, Pavlos and Sanchez, Marcelo},<br />
journal={The Energy Journal},<br />
pages={67-90},<br />
year={2004},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{layard2005unemployment,<br />
title={Unemployment: macroeconomic performance and the labour market},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
year={2005},<br />
publisher={Oxford University Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{layard1986unemployment,<br />
title={Unemployment in Britain},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
journal={Economica},<br />
volume={53},<br />
number={210},<br />
pages={121-169},<br />
year={1991}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{lindbeck1993unemployment,<br />
title={Unemployment and macroeconomics},<br />
author={Lindbeck, Assar},<br />
year={1993},<br />
publisher={MIT Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy: 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={OECD, Paris, France}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{marshallpoe,<br />
title={Principles of Economics},<br />
author={Marshall, Alfred},<br />
year={1890},<br />
publisher={London: Macmillan}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638-643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1992consumer,<br />
title={Consumer demand and equilibrium unemployment in a working model of the customer-market incentive-wage economy},<br />
author={Phelps, Edmund S},<br />
journal={The Quarterly Journal of Economics},<br />
pages={1003--1032},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{shapiro1984equilibrium,<br />
title={Equilibrium unemployment as a worker discipline device},<br />
author={Shapiro, Carl and Stiglitz, Joseph E},<br />
journal={The American Economic Review},<br />
volume={74},<br />
number={3},<br />
pages={433-444},<br />
year={1984},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5236References - IMACLIM2016-09-28T14:43:50Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
blanchflower1994introduction;<br />
corrado1997capacity;<br />
guivarch2011costs;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
kaufmann2004does;<br />
layard2005unemployment;<br />
layard1986unemployment;<br />
lindbeck1993unemployment;<br />
maddison1995monitoring;<br />
marshallpoe;<br />
oliveira2005impact;<br />
phelps1961golden;<br />
phelps1992consumer;<br />
sassi2010im;<br />
shapiro1984equilibrium;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{blanchflower1994introduction,<br />
title={An introduction to the wage curve},<br />
author={Blanchflower, David and Oswald, Andrew J},<br />
journal={The Journal of Economic Perspectives},<br />
pages={153-167},<br />
year={1995},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{frondel2002capital,<br />
title={The capital-energy controversy: an artifact of cost shares?},<br />
author={Frondel, Manuel and Schmidt, Christoph M},<br />
journal={The Energy Journal},<br />
pages={53--79},<br />
year={2002},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{guivarch2011costs,<br />
title={The costs of climate policies in a second-best world with labour market imperfections},<br />
author={Guivarch, Céline and Crassous, Renaud and Sassi, Olivier and Hallegatte, Stéphane},<br />
journal={Climate Policy},<br />
volume={11},<br />
number={1},<br />
pages={768-788},<br />
year={2011},<br />
publisher={Taylor & Francis}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade1993modelling,<br />
title={Modelling long-run scenarios: methodology lessons from a prospective study on a low CO2 intensive country},<br />
author={Hourcade, Jean-Charles},<br />
journal={Energy Policy},<br />
volume={21},<br />
number={3},<br />
pages={309--326},<br />
year={1993},<br />
publisher={Elsevier}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{kaufmann2004does,<br />
title={Does OPEC matter? An econometric analysis of oil prices},<br />
author={Kaufmann, Robert K and Dees, Stephane and Karadeloglou, Pavlos and Sanchez, Marcelo},<br />
journal={The Energy Journal},<br />
pages={67-90},<br />
year={2004},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{layard2005unemployment,<br />
title={Unemployment: macroeconomic performance and the labour market},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
year={2005},<br />
publisher={Oxford University Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{layard1986unemployment,<br />
title={Unemployment in Britain},<br />
author={Layard R, Nickell S, Jackman R},<br />
journal={Economica},<br />
volume={53},<br />
number={210},<br />
pages={121-169},<br />
year={1991}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{lindbeck1993unemployment,<br />
title={Unemployment and macroeconomics},<br />
author={Lindbeck, Assar},<br />
year={1993},<br />
publisher={MIT Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy: 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={OECD, Paris, France}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{marshallpoe,<br />
title={Principles of Economics},<br />
author={Marshall, Alfred},<br />
year={1890},<br />
publisher={London: Macmillan}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638-643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1992consumer,<br />
title={Consumer demand and equilibrium unemployment in a working model of the customer-market incentive-wage economy},<br />
author={Phelps, Edmund S},<br />
journal={The Quarterly Journal of Economics},<br />
pages={1003--1032},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{shapiro1984equilibrium,<br />
title={Equilibrium unemployment as a worker discipline device},<br />
author={Shapiro, Carl and Stiglitz, Joseph E},<br />
journal={The American Economic Review},<br />
volume={74},<br />
number={3},<br />
pages={433-444},<br />
year={1984},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5235References - IMACLIM2016-09-28T14:37:13Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
blanchflower1994introduction;<br />
corrado1997capacity;<br />
guivarch2011costs;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
kaufmann2004does;<br />
layard2005unemployment;<br />
layard1986unemployment;<br />
lindbeck1993unemployment;<br />
maddison1995monitoring;<br />
marshallpoe;<br />
oliveira2005impact;<br />
phelps1961golden;<br />
phelps1992consumer;<br />
sassi2010im;<br />
shapiro1984equilibrium;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{blanchflower1994introduction,<br />
title={An introduction to the wage curve},<br />
author={Blanchflower, David and Oswald, Andrew J and others},<br />
year={1994},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{frondel2002capital,<br />
title={The capital-energy controversy: an artifact of cost shares?},<br />
author={Frondel, Manuel and Schmidt, Christoph M},<br />
journal={The Energy Journal},<br />
pages={53--79},<br />
year={2002},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{guivarch2011costs,<br />
title={The costs of climate policies in a second-best world with labour market imperfections},<br />
author={Guivarch, Céline and Crassous, Renaud and Sassi, Olivier and Hallegatte, Stéphane},<br />
journal={Climate Policy},<br />
volume={11},<br />
number={1},<br />
pages={768--788},<br />
year={2011},<br />
publisher={Taylor & Francis}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade1993modelling,<br />
title={Modelling long-run scenarios: methodology lessons from a prospective study on a low CO2 intensive country},<br />
author={Hourcade, Jean-Charles},<br />
journal={Energy Policy},<br />
volume={21},<br />
number={3},<br />
pages={309--326},<br />
year={1993},<br />
publisher={Elsevier}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{kaufmann2004does,<br />
title={Does OPEC matter? An econometric analysis of oil prices},<br />
author={Kaufmann, Robert K and Dees, Stephane and Karadeloglou, Pavlos and Sanchez, Marcelo},<br />
journal={The Energy Journal},<br />
pages={67-90},<br />
year={2004},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{layard2005unemployment,<br />
title={Unemployment: macroeconomic performance and the labour market},<br />
author={Layard, P Richard G and Nickell, Stephen J and Jackman, Richard},<br />
year={2005},<br />
publisher={Oxford University Press on Demand}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{layard1986unemployment,<br />
title={Unemployment in Britain},<br />
author={Layard R, Nickell S, Jackman R },<br />
journal={Economica},<br />
volume={53},<br />
number={210},<br />
pages={121-169},<br />
year={1991}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{lindbeck1993unemployment,<br />
title={Unemployment and macroeconomics},<br />
author={Lindbeck, Assar},<br />
volume={3},<br />
year={1993},<br />
publisher={MIT Press}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy: 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={OECD, Paris, France}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{marshallpoe,<br />
title={Principles of Economics},<br />
author={Marshall, Alfred},<br />
year={1890},<br />
publisher={London: Macmillan}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638-643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1992consumer,<br />
title={Consumer demand and equilibrium unemployment in a working model of the customer-market incentive-wage economy},<br />
author={Phelps, Edmund S},<br />
journal={The Quarterly Journal of Economics},<br />
pages={1003--1032},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{shapiro1984equilibrium,<br />
title={Equilibrium unemployment as a worker discipline device},<br />
author={Shapiro, Carl and Stiglitz, Joseph E},<br />
journal={The American Economic Review},<br />
volume={74},<br />
number={3},<br />
pages={433--444},<br />
year={1984},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5234References - IMACLIM2016-09-28T14:17:51Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
corrado1997capacity;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
maddison1995monitoring;<br />
marshallpoe;<br />
oliveira2005impact;<br />
phelps1961golden;<br />
sassi2010im;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{frondel2002capital,<br />
title={The capital-energy controversy: an artifact of cost shares?},<br />
author={Frondel, Manuel and Schmidt, Christoph M},<br />
journal={The Energy Journal},<br />
pages={53--79},<br />
year={2002},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade1993modelling,<br />
title={Modelling long-run scenarios: methodology lessons from a prospective study on a low CO2 intensive country},<br />
author={Hourcade, Jean-Charles},<br />
journal={Energy Policy},<br />
volume={21},<br />
number={3},<br />
pages={309--326},<br />
year={1993},<br />
publisher={Elsevier}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy: 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={OECD, Paris, France}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{marshallpoe,<br />
title={Principles of Economics},<br />
author={Marshall, Alfred},<br />
year={1890},<br />
publisher={London: Macmillan}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638-643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
volume={2},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5233References - IMACLIM2016-09-28T14:08:25Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
corrado1997capacity;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
maddison1995monitoring;<br />
oliveira2005impact;<br />
phelps1961golden;<br />
sassi2010im;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy: 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={OECD, Paris, France}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638-643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
volume={2},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5232References - IMACLIM2016-09-28T14:05:22Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
corrado1997capacity;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
maddison1995monitoring;<br />
oliveira2005impact;<br />
phelps1961golden;<br />
sassi2010im;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy, 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={Paris (France) OECD}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638-643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
volume={2},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5231References - IMACLIM2016-09-28T13:54:17Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
barro1992convergence;<br />
corrado1997capacity;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
maddison1995monitoring;<br />
oliveira2005impact;<br />
phelps1961golden<br />
sassi2010im;<br />
united2005world;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{barro1992convergence,<br />
title={Convergence},<br />
author={Barro, Robert J and Sala-i-Martin, Xavier},<br />
journal={Journal of political Economy},<br />
pages={223--251},<br />
year={1992},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{maddison1995monitoring,<br />
title={Monitoring the world economy, 1820-1992},<br />
author={Maddison, Angus},<br />
year={1995},<br />
publisher={Paris (France) OECD}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{oliveira2005impact,<br />
title={The impact of ageing on demand, factor markets and growth},<br />
author={Oliveira Martins, Joaquim and Gonand, Frédéric and Antolin, Pablo and De la Maisonneuve, Christine and Yoo, Kwang-Yeol},<br />
year={2005},<br />
publisher={OECD Economics Department Working Paper}<br />
}<br />
}}<br />
<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{phelps1961golden,<br />
title={The golden rule of accumulation: a fable for growthmen},<br />
author={Phelps, Edmund},<br />
journal={The American Economic Review},<br />
volume={51},<br />
number={4},<br />
pages={638--643},<br />
year={1961},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@book{united2005world,<br />
title={World Population Prospects: Sex and age distribution of the world population},<br />
author={United Nations. Department of Economic},<br />
volume={2},<br />
year={2005},<br />
publisher={United Nations Publications}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5230References - IMACLIM2016-09-28T13:44:35Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
armington1969theory;<br />
arrow1954existence;<br />
corrado1997capacity;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
sassi2010im;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{armington1969theory,<br />
title={A theory of demand for products distinguished by place of production},<br />
author={Armington, Paul S},<br />
journal={Staff Papers},<br />
volume={16},<br />
number={1},<br />
pages={159--178},<br />
year={1969},<br />
publisher={Springer}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5229References - IMACLIM2016-09-28T13:41:55Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=<br />
ahmad1966theory;<br />
arrow1954existence;<br />
corrado1997capacity;<br />
hourcade2006hybrid;<br />
johansen1959substitution;<br />
sassi2010im;<br />
waisman2012th;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Frédéric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5228References - IMACLIM2016-09-28T13:37:16Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=waisman2012th;<br />
sassi2010im;ahmad1966theory;johansen1959substitution;hourcade2006hybrid;arrow1954existence;corrado1997capacity;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{arrow1954existence,<br />
title={Existence of an equilibrium for a competitive economy},<br />
author={Arrow, Kenneth J and Debreu, Gerard},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={265-290},<br />
year={1954},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{corrado1997capacity,<br />
title={Capacity utilization},<br />
author={Corrado, Carol and Mattey, Joe},<br />
journal={The Journal of Economic Perspectives},<br />
volume={11},<br />
number={1},<br />
pages={151-167},<br />
year={1997},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{hourcade2006hybrid,<br />
title={Hybrid Modeling: New Answers to Old Challenges Introduction to the Special Issue of" The Energy Journal"},<br />
author={Hourcade, Jean-Charles and Jaccard, Mark and Bataille, Chris and Ghersi, Fr{\'e}d{\'e}ric},<br />
journal={The Energy Journal},<br />
pages={1-11},<br />
year={2006},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5227References - IMACLIM2016-09-28T13:32:12Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=waisman2012th;<br />
sassi2010im;ahmad1966theory;johansen1959substitution;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344-357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{johansen1959substitution,<br />
title={Substitution versus fixed production coefficients in the theory of economic growth: a synthesis},<br />
author={Johansen, Leif},<br />
journal={Econometrica: Journal of the Econometric Society},<br />
pages={157-176},<br />
year={1959},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5226References - IMACLIM2016-09-28T13:27:21Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=waisman2012th;<br />
sassi2010im;ahmad1966theory;<br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344--357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5225References - IMACLIM2016-09-28T13:26:10Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=waisman2012th;<br />
sassi2010im; <br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
{{#scite:<br />
|bibtex=<br />
@article{ahmad1966theory,<br />
title={On the theory of induced invention},<br />
author={Ahmad, Syed},<br />
journal={The Economic Journal},<br />
volume={76},<br />
number={302},<br />
pages={344--357},<br />
year={1966},<br />
publisher={JSTOR}<br />
}<br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5224Model concept, solver and details - IMACLIM2016-09-26T14:59:17Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation [1]. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition [2]. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports [3]. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities [4].<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959).<br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] Following (Corrado and Mattey, 1997), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.<br />
<br />
[2] The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).<br />
<br />
[3] For non-energy goods, we adopt Armington specifications (Armington, 1969) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.<br />
<br />
[4] The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5223Model concept, solver and details - IMACLIM2016-09-26T14:58:36Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010 [[CiteRef::sassi2010im]]; Waisman et al., 2012[[CiteRef::waisman2012th]), is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation [1]. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition [2]. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports [3]. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities [4].<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959).<br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] Following (Corrado and Mattey, 1997), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.<br />
<br />
[2] The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).<br />
<br />
[3] For non-energy goods, we adopt Armington specifications (Armington, 1969) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.<br />
<br />
[4] The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5222Model concept, solver and details - IMACLIM2016-09-26T14:57:15Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010; Waisman et al., 2012)[[CiteRef::waisman2012th],[[CiteRef::sassi2010im]] is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation [1]. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition [2]. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports [3]. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities [4].<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959).<br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] Following (Corrado and Mattey, 1997), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.<br />
<br />
[2] The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).<br />
<br />
[3] For non-energy goods, we adopt Armington specifications (Armington, 1969) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.<br />
<br />
[4] The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=Model_concept,_solver_and_details_-_IMACLIM&diff=5221Model concept, solver and details - IMACLIM2016-09-26T14:50:24Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsDocumentationOf=IMACLIM<br />
|IsEmpty=No<br />
|DocumentationCategory=Model concept, solver and details<br />
}}<br />
The Imaclim-R model (Sassi et al., 2010; Waisman et al., 2012)[[CiteRef::waisman2012th;sassi2010im]] is a multi-region and multi-sector model of the world economy. It combines a Computable General Equilibrium (CGE) framework with bottom-up sectoral modules in a hybrid and recursive dynamic architecture. Furthermore, it describes growth patterns in second best worlds with market imperfections, partial uses of production factors and imperfect expectations.<br />
<br />
== A hybrid modelling structure to study the interactions between the evolutions of energy systems and economic growth ==<br />
<br />
Assessing the intertwined evolution of technical systems, energy demand behaviors and economic growth, as well as the costs and benefits of transitions to low carbon economies is a major challenge for economic modeling. Ideally, models should (i) be framed in a consistent macroeconomic framework, (ii) include the relevant technical constraints in each sector, such as views about the direction of technical change, (iii) capture the key relationships between economic activity and the environment, e.g., energy and natural resources consumption or greenhouse gases emissions, (iv) have a horizon long enough to assess ?sustainability?- a long-term horizon which also implies, incidentally, that the model must be able to represent structural and technical change, yet (v) recognize short-term economic processes critical for assessing transition pathways, such as market imbalance and rigidities.<br />
<br />
No model in existence today meets all of these specifications. In fact, current models can be classified along two major fault lines: bottom-up vs. top-down, and long-term vs. short-term.<br />
<br />
By design, computable general equilibrium (CGE) models which are classed as top-down, provide a comprehensive macroeconomic framework (i); but they typically adopt oversimplified representations of technical constraints and then fail to explicitly include their interactions with growth trajectories. Conversely, bottom-up engineering models provide a detailed account of technical potentials and limitations (ii), but their macro-engine, if existing at all, is most often rudimentary. Emerging ?hybrid? models developed in the context of climate policy assessment are steps towards addressing these drawbacks. A similar dichotomy occurs with regard to the time horizon. Growth models in the ''Solow'' tradition are designed to capture key features of long-term development paths (iv), but they do not include short- or medium-term economic processes such as market rigidities. On the other hand, short-term models (econometric or structural) will meet requirement (v) but are not designed to project far into the future. Emerging models thus include short/medium-term processes into their analysis of growth in the long-run, although this remains an open research field.<br />
<br />
The IMACLIM modelling platform, developed at CIRED, is a step towards the five-point specification outlined above. It comprises a hybrid structure that combines a multi-sectorial top-down macroeconomic framework with a bottom-up modules for each sector. A key feature of IMACLIM is its dual representation of economic flows in monetary flows (e.g., euros or dollars) and in physical quantities (e.g., MToe for energy, passenger.km for mobility). This dual representation allows for explicit representation of the material and technological content of economic activity and endogenization of the interactions between these technical dimensions and growth trajectories: the projected economy is supported by a realistic technical background (in the engineering sense) and, conversely, that projected technical systems are bounded by realistic economic flows and consistent sets of prices. This modeling principle facilitates interaction between technical and economic considerations and allows in particular a detailed representation of sectorial characteristics.<br />
<br />
== A recursive and modular simulation architecture capturing inertias and imperfect foresight ==<br />
<br />
IMACLIM-R models the evolution of the economy over the period 2001-2100, in one year time steps.<br />
<br />
Technically, the model can be labelled as a recursive dynamic simulation framework, since it generates an energy-economy trajectory by solving a sequence of yearly static equilibria of the economy, interlinked by dynamic modules. The recursive structure organizes a systematic exchange of information between a top-down annual static equilibrium providing a snapshot of the economy, and bottom-up dynamic modules providing information on the evolution of technical parameters between each annual equilibria (Figure 1.1.1).<br />
<br />
[[File:35815505.png]]<br />
<br />
Figure 1.1.1 The recursive and modular architecture of the Imaclim-R hybrid model.<br />
<br />
For each annual static equilibrium, domestic and international markets ? besides markets for ''factors'' such as capital and labour ? are fully cleared by a unique set of relative prices that depend on the behaviours of representative agents (producers, households, states) on the demand and supply sides. The calculation of this annual equilibrium determines the following variables: relative prices, wages, labour, quantities of goods and services including energy, value flows, physical flows and capacity utilization.<br />
<br />
Households choose their consumption of goods and services to maximize their current utility under both income and time constraints; the former is the sum of wages, capital returns and transfers whereas the latter controls the total time spent in transportation.<br />
<br />
The behaviour of producers is not represented by a flexible production function allowing for substitution between factors, as it is in common practice. Instead, these substitutions occur between two equilibria in sector-specific dynamic modules. Producers are therefore assumed to operate under short-run constraints of (i) a fixed maximal production capacity ''Cap''''<sub>k,i</sub>'', defined as the maximum level of physical output achievable with the equipment installed, and (ii) fixed input-output coefficients representing that with the current set of installed technologies, producing one unit of a good ''i'' in region ''k'' requires fixed physical amounts ''IC''''<sub>j,i,k</sub>'' of intermediate goods ''j'' and of labour ''l''''<sub>k,i</sub>''. In this context, the only room for manouvre producers have is to adjust the utilisation rate ''Q''''<sub>k,i</sub>''''/Cap''''<sub>k,i</sub>'' according to the relative market prices of inputs and output, taking into account decreasing static returns when capacity utilization approaches saturation [1]. Producers determine their prices using a marginal rate over and above production costs (mark-up) to capture the effect of imperfect competition [2]. This represents a different paradigm from usual production specifications e,g, with constant elasticity of substitution KLEM production functions, since the ?capital? factor is not always fully utilized.<br />
<br />
Total demand for each good (the sum of households? consumption, public and private investments and intermediate uses) is satisfied by a mix of domestic production and imports [3]. All intermediate and final goods are internationally tradable. Domestic as well as international markets for all goods are cleared (i.e. no stock is allowed) by a unique set of relative prices and this determines the utilization rate of production capacities [4].<br />
<br />
Between annual equilibria, dedicated modules describe the investments choices and the evolution of preferences, techniques and land uses; thereby updating the next equilibrium parameters at t+1 (installed production capacities, households equipment, the installed technologies represented by the input-output coefficients?).<br />
<br />
The equilibrium values of all variables from previous equilibria serve as signals for agents? decisions represented in the dynamic modules. Therefore decisions are taken with no perfect foresight of future values.<br />
<br />
Within the dynamic modules, technical choices are available, however only marginal changes in the input-output coefficients embodied in existing equipment vintages (arising from past technical choices) are possible/allowed.<br />
<br />
The dynamic modules represent the evolution of technical coefficients resulting from agents? microeconomic decisions on technological choices, under the limits imposed by the ''innovation possibility frontier,'' IPF, (Ahmad, 1966). They embed a) sectoral level information on economies of scale, learning-by-doing mechanisms and saturation in efficiency progress, and b) expert views about the asymptotes of ultimate technical potentials, the impact of incentive systems, and the role of market or institutional imperfections. The new investment choices and technical coefficients are then sent back to the static module in the form of updated production capacities and input-output coefficients to calculate the t+1 equilibrium.<br />
<br />
This general putty-clay representation with fixed technical content of installed capital, is critical to the representation of inertia in technical systems. It allows for distinction between short-term rigidities and long-term flexibilities (Johansen, 1959).<br />
<br />
== Summary ==<br />
<br />
The IMACLIM-R model endogenizes the rate and direction of technical change by representing the bottom-up impact of investment decisions on the deployment of technical systems. The consistency of the top-down/bottom-up communication is guaranteed by a hybrid structure representing the economy in money values and physical quantities (Hourcade et al, 2006). This dual accounting, following the Arrow-Debreu framework (Arrow and Debreu, 1954), ensures that the projected economy is supported by a realistic technical background and, conversely, that projected technical systems correspond to realistic economic flows and consistent sets of relative prices.<br />
<br />
= Practical implementation =<br />
<br />
Imaclim-R is implemented in Scilab, and uses a C solver to solve the static equilibrium system of non-linear equations.<br />
<br />
<br />
-----<br />
<br />
[1] Following (Corrado and Mattey, 1997), decreasing returns reflect the higher labor costs associated to overtime extra-hour, costly night work and increasing maintenance works when capacity utilization approaches saturation.<br />
<br />
[2] The mark-ups are exogenous except in the energy sector where they are endogenous to reflect (a) the market power of fossil fuel producers, (b) specific pricing principles in the power sector (e.g., mean cost pricing), and (c) the different margins over the three inputs for liquid fuels production (oil, biomass, coal).<br />
<br />
[3] For non-energy goods, we adopt Armington specifications (Armington, 1969) to capture the partial substitutability between domestic and foreign goods, while for energy goods (in MToe) physical accounting makes them fully substitutable.<br />
<br />
[4] The partial utilization rate of production capacities allows the represention of operational flexibility through early retirement of those capacities which, although installed, are not used for actual production because they are not competitive in current economic conditions.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5220References - IMACLIM2016-09-26T14:25:21Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=waisman2012th;<br />
sassi2010im; <br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|number=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|number=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5219References - IMACLIM2016-09-26T14:22:57Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=waisman2012th;<br />
sassi2010im; <br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|issue=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change|+sep=; <br />
|issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|issue=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; <br />
|issn=1466-6650;1741-5136|+sep=; <br />
}}<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5218References - IMACLIM2016-09-26T14:20:03Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=waisman2012th;<br />
sassi2010im; <br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade<br />
|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|issue=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change<br />
|+sep=; <br />
|issn=0165-0009;1573-1480<br />
|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch<br />
|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|issue=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law<br />
|+sep=; <br />
|issn=1466-6650;1741-5136<br />
|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=sassi2010im |type=journal-article |title=IMACLIM-R: a modelling framework to simulate sustainable development pathways |author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch|+sep=; |journal=International Journal of Global Environmental Issues |publisher=Inderscience Publishers |year=2010 |volume=10 |issue=1/2 |pages=5 |doi=10.1504/ijgenvi.2010.030566 |subject=Geography, Planning and Development;Management, Monitoring, Policy and Law|+sep=; |issn=1466-6650;1741-5136|+sep=; }}<br />
<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarchhttps://www.iamcdocumentation.eu/index.php?title=References_-_IMACLIM&diff=5217References - IMACLIM2016-09-26T14:17:44Z<p>Celine Guivarch: </p>
<hr />
<div>{{ModelDocumentationTemplate<br />
|IsEmpty=No<br />
|IsDocumentationOf=IMACLIM<br />
|DocumentationCategory=References<br />
}}<br />
References are divided into three categories as follows:<br />
<br />
# References describing the structure and results obtained with the Imaclim-R Global model<br />
# References to models comparison exercises in which Imaclim-R Global model has participated<br />
# References to economic theory, data sources, or other energy system modelling used in the model description presented in this WIKI<br />
<br />
The references are presented in accordence to the above categorisation. References corresponding to the first two categories are also listed in the Table below. Further information on the the Imaclim suite of models is also available on the [http://www.imaclim.centre-cired.fr/ Imaclim homepage]. <br />
<br />
{| class="wikitable"<br />
|width="33%"| <br />
|width="33%"|Description of Imaclim-R structure and results<br />
|width="33%"|Models comparison (including Imaclim-R)<br />
|-<br />
|Technologies<br />
<br />
|Bibas and Méjean (2014) (bioenergy)<br />
<br />
|Kim et al. (2014) (nuclear)<br />
<br />
Koelbl et al. (2014) (CCS)<br />
<br />
Krey et al. (2014)<br />
<br />
Kriegler et al. (2014)<br />
<br />
Luderer et al. (2014) (renewables)<br />
<br />
Rose et al. (2014) (bioenergy)<br />
<br />
Tavoni et al. (2012)<br />
|-<br />
|Energy efficiency<br />
|Bibas et al. (2015)<br />
|Sugiyama et al. (2014)<br />
|-<br />
|Fossil fuels<br />
|Rozenberg et al. (2010)<br />
<br />
Waisman et al. (2012)<br />
<br />
Waisman et al. (2013a)<br />
|Bauer et al. (2015)<br />
<br />
MCCollum et al. (2014)<br />
|-<br />
|Transport<br />
|Waisman et al. (2013b)<br />
| <br />
|-<br />
|Macroeconomy<br />
|Crassous et al. (2006) (endogenous structural change)<br />
<br />
Guivarch et al. (2011) (labor markets)<br />
| <br />
|-<br />
|Evaluation of model<br />
|Guivarch et al. (2009) (backcasting)<br />
|Kriegler et al. (2015b) (diagnostics)<br />
|-<br />
|Scenarios<br />
|Guivarch and Mathy (2012)<br />
<br />
Hamdi-Cherif et al. (2011)<br />
<br />
Mathy and Guivarch (2010)<br />
<br />
Rozenberg et al. (2014)<br />
<br />
Waisman et al. (2014)<br />
|Blanford et al. (2014)<br />
<br />
Kriegler et al. (2015)<br />
<br />
Luderer et al. (2012a)<br />
<br />
Luderer et al. (2012b)<br />
<br />
Riahi et al. (2015)<br />
|}<br />
<br />
{{#referencelist:<br />
|references=waisman2012th <br />
|+sep=;<br />
|listtype=ol<br />
|browselinks=yes<br />
|columns=2<br />
|toc=yes<br />
|header=All references<br />
}}<br />
<br />
{{#scite: |reference=waisman2012th <br />
|type=journal-article <br />
|title=The Imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight |author=Henri Waisman;Céline Guivarch;Fabio Grazi;Jean Charles Hourcade|+sep=; <br />
|journal=Climatic Change <br />
|publisher=Springer Science + Business Media <br />
|year=2012 <br />
|volume=114 <br />
|issue=1 <br />
|pages=101-120 <br />
|doi=10.1007/s10584-011-0387-z <br />
|subject=Atmospheric Science;Global and Planetary Change<br />
|+sep=; |issn=0165-0009;1573-1480|+sep=; <br />
}}<br />
<br />
{{#scite: |reference=sassi2010im <br />
|type=journal-article <br />
|title=IMACLIM-R: a modelling framework to simulate sustainable development pathways <br />
|author=Olivier Sassi;Renaud Crassous;Jean Charles Hourcade;Vincent Gitz;Henri Waisman;Celine Guivarch<br />
|+sep=; <br />
|journal=International Journal of Global Environmental Issues <br />
|publisher=Inderscience Publishers <br />
|year=2010 <br />
|volume=10 <br />
|issue=1/2 <br />
|pages=5 <br />
|doi=10.1504/ijgenvi.2010.030566 <br />
|subject=Geography, Planning and Development;Management, Monitoring, Policy and Law<br />
|+sep=; <br />
|issn=1466-6650;1741-5136<br />
|+sep=; <br />
}}<br />
<br />
<br />
== ''' 1. Description of Imaclim-R structure and results''' ==<br />
<br />
Bibas R., and A. Méjean (2014). Potential and limitations of bioenergy for low carbon transitions. ''Climatic Change'', 123(3-4) 731-761<br />
<br />
Bibas, R., Méjean, A., Hamdi-Cherif, M., 2015. Energy efficiency policies and the timing of action: An assessment of climate mitigation costs. ''Technological Forecasting and Social Change'' 90 (part A), 137-152.<br />
<br />
Crassous, R., J. C Hourcade, et O. Sassi. 2006. « Endogenous structural change and climate targets modeling experiments with Imaclim-R ». ''Energy Journal'' 27: 259?76.<br />
<br />
Guivarch, Céline, Stéphane Hallegatte, et Renaud Crassous. 2009. « The resilience of the Indian economy to rising oil prices as a validation test for a global energy?environment?economy CGE model ». ''Energy Policy'' 37 (11): 4259?66.<br />
<br />
Guivarch, C., Crassous, R., Sassi, O., Hallegatte, S. 2011. ?The costs of climate policies in a second best world with labour market imperfections?. ''Climate Policy'' 11 : 768?788.<br />
<br />
Guivarch, C., Mathy, S. 2012. ?Energy-GDP decoupling in a second best world?a case study on India? ''Climatic Change,'' Volume 113, Number 2, 339-356.<br />
<br />
Hamdi-Cherif, M., Guivarch, C., Quirion, P. 2011. ?Sectoral targets for developing countries: Combining ?Common but differentiated responsibilities? with ?Meaningful participation??,''Climate Policy'' 11: 731?751.<br />
<br />
Mathy, S., Guivarch, C. 2010. ?Climate policies in a second-best world - A case study on India?, ''Energy Policy'' 38:3, 1519-1528.<br />
<br />
Rozenberg, Julie, Stéphane Hallegatte, Adrien Vogt-Schilb, Olivier Sassi, Céline Guivarch, Henri Waisman, et Jean-Charles Hourcade. 2010. « Climate policies as a hedge against the uncertainty on future oil supply ». ''Climatic Change'' 101 (3): 663?68.<br />
<br />
Rozenberg, J., Guivarch, C., Lempert, R., Hallegatte, S. 2014. Building SSPs for climate policy analysis: a scenario elicitation methodology to map the space of possible future challenges to mitigation and adaptation. ''Climatic Change'' 122(3), pp 509-522.<br />
<br />
Waisman, Henri, Julie Rozenberg, Olivier Sassi, et Jean-Charles Hourcade. 2012. « Peak Oil profiles through the lens of a general equilibrium assessment ». ''Energy Policy'', Special Section: Frontiers of Sustainability, 48: 744?53.<br />
<br />
Waisman, Henri, Julie Rozenberg, et Jean Charles Hourcade. 2013. « Monetary compensations in climate policy through the lens of a general equilibrium assessment: The case of oil-exporting countries ». ''Energy Policy'' 63: 951?61.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. ?The transportation sector and low-carbon growth pathways? ''Climate Policy'' 13(1): 106?129.<br />
<br />
Waisman Henri-David, Cassen Chritophe, Hamdi-Cherif Meriem and Hourcade Jean-Charles, 2014. Sustainability, Globalization, and the Energy Sector - Europe in a Global Perspective. ''Journal of Environment and Development'', Volume 23 (1), 101-132.<br />
<br />
== ''' 2. Model comparisons in which Imaclim-R has been used''' ==<br />
<br />
Bauer, Nico, Valentina Bosetti, Meriem Hamdi-Cherif, Alban Kitous, David McCollum, Aurélie Méjean, Shilpa Rao, Hal Turton, Leonidas Paroussos, et Shuichi Ashina. 2015. CO2 emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies. ''Technological Forecasting and Social Change'' 90 (Part A), 243-256.<br />
<br />
Blanford, Geoffrey J., Elmar Kriegler, et Massimo Tavoni. 2014. « Harmonization vs. fragmentation: overview of climate policy scenarios in EMF27 ». ''Climatic Change'' 123 (3-4), 383?96.<br />
<br />
Kim, Son H., Kenichi Wada, Atsushi Kurosawa, et Matthew Roberts. 2014. « Nuclear energy response in the EMF27 study ». ''Climatic Change'' 123 (3-4): 443?60.<br />
<br />
Koelbl, Barbara Sophia, Machteld A. van den Broek, André PC Faaij, et Detlef P. van Vuuren. 2014. « Uncertainty in Carbon Capture and Storage (CCS) deployment projections: a cross-model comparison exercise ». ''Climatic Change'' 123 (3-4): 461?76.<br />
<br />
Krey, Volker, Gunnar Luderer, Leon Clarke, et Elmar Kriegler. 2014. « Getting from here to there?energy technology transformation pathways in the EMF27 scenarios ». ''Climatic Change'' 123 (3-4), 369?82.<br />
<br />
Kriegler, Elmar, John P. Weyant, Geoffrey J. Blanford, Volker Krey, Leon Clarke, Jae Edmonds, Allen Fawcett, et al. 2014. « The Role of Technology for Achieving Climate Policy Objectives: Overview of the EMF 27 Study on Global Technology and Climate Policy Strategies ». ''Climatic Change'' 123 (3-4), 353?67.<br />
<br />
Kriegler E., K. Riahi, N. Bauer, V.J. Schanitz, N. Petermann, V. Bosetti, A. Marcucci, S. Otto, L. Paroussos, and et al. (2015a). Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy. ''Technological Forecasting and Social Change'' 90 (Part A), 24-44.<br />
<br />
Kriegler, Elmar, Nils Petermann, Volker Krey, Valeria Jana Schwanitz, Gunnar Luderer, Shuichi Ashina, Valentina Bosetti, Jiyong Eom, Alban Kitous, et Aurélie Méjean. 2015b. Diagnostic indicators for integrated assessment models of climate policy. ''Technological Forecasting and Social Change''. 90 (Part A), 45-61.<br />
<br />
Luderer G, DeCian E, Hourcade JC, Leimbach M, Waisman H et Edenhofer O (2012a). ? On the regional distribution of mitigation costs in a global cap-and-trade regime?, ''Climatic Change'' 114 (1), 59-78.<br />
<br />
Luderer G, Bosetti V, Jakob M, Steckel J, Waisman H et Edenhofer O (2012b). ?The Economics of GHG Emissions Reductions ? results and insights from the RECIPE model intercomparison?, ''Climatic Change'' 114 (1), 9-37.<br />
<br />
Luderer, Gunnar, Volker Krey, Katherine Calvin, James Merrick, Silvana Mima, Robert Pietzcker, Jasper Van Vliet, et Kenichi Wada. 2014. « The role of renewable energy in climate stabilization: results from the EMF27 scenarios ». ''Climatic Change'' 123 (3-4): 427?41.<br />
<br />
McCollum, David, Nico Bauer, Katherine Calvin, Alban Kitous, et Keywan Riahi. 2014. « Fossil resource and energy security dynamics in conventional and carbon-constrained worlds ». ''Climatic Change'' 123 (3-4): 413?26.<br />
<br />
Riahi K., E. Kriegler, N. Johnson, C. Bertram, M. Den Elzen, J. Eom, M. Schaeffer, J. Edmonds, and et al. (2015). Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals. ''Technological Forecasting and Social Change'' 90 (Part A), 8-23.<br />
<br />
Rose, Steven K., Elmar Kriegler, Ruben Bibas, Katherine Calvin, Alexander Popp, Detlef P. van Vuuren, et John Weyant. 2014. « Bioenergy in energy transformation and climate management ». ''Climatic Change'' 123 (3-4): 477?93.<br />
<br />
Sugiyama, Masahiro, Osamu Akashi, Kenichi Wada, Amit Kanudia, Jun Li, et John Weyant. 2014. « Energy Efficiency Potentials for Global Climate Change Mitigation ». ''Climatic Change'' 123 (3-4): 397?411.<br />
<br />
Tavoni M, DeCian E, Luderer G, Steckel JC et Waisman H (2012). ?The value of technology and of its evolution towards a low carbon economy?, ''Climatic Change'' 114 (1), 39-57.<br />
<br />
== '''3. References cited in Model Description''' ==<br />
<br />
Ahmad, S (1966). On the theory of induced innovation. Economic Journal 76: 344-357.<br />
<br />
Alexandratos, N. and Bruinsma, J. (2012). World agriculture towards 2030/2050. the 2012 revision. Technical report, FAO. ESA Working paper No. 12-03.<br />
<br />
Amigues, J.-P., Favard, P., Gaudet, G., Moreaux, M., 1998. On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited. ''Journal of Economic Theory'' 80 (1) 153-170.<br />
<br />
Ambrosi, P., J.C. Hourcade, S. Hallegatte, F. Lecocq, P. Dumas, Ha-Duong, M. (2003) Optimal Control Models and Elicitation of Attitudes towards Climate Damages. Environmental Modeling and Assessment 8(3): 135-147.<br />
<br />
Armington PS (1969). A Theory of Demand for Products Distinguished by Place of Production. IMF, International Monetary Fund Staff Papers 16: 170-201.<br />
<br />
Arrow K.J., and Debreu G., 1954. Existence of an equilibrium for a competitive economy. Econometrica 22:265-290.<br />
<br />
Barro, R. J., and X. Sala-i-Martin. 1992. Convergence. ''Journal of Political Economy'' 100, no. 2: 223.<br />
<br />
Bentley, R.W.,Mannan,S.,Wheeler,S.,2007.Assessing the date of the global oil peak: the need to use 2P reserves. Energy Policy 35(12), 6364--6382.<br />
<br />
Blanchflower, D. G, and A. J Oswald. 1995. An introduction to the wage curve. ''The Journal of Economic Perspectives'': 153-167.<br />
<br />
Blanchflower, David G., and Andrew J. Oswald. 2005. The Wage Curve Reloaded. ''National Bureau of Economic Research Working Paper Series'' No. 11338.<br />
<br />
Bondeau, A., Smith, P. C., Saehle, S., Schaphoff, S., Lucht,W., Cramer, W., Gerten, D., Lotze-Campen, H., Müller, C., Reichstein, M., and Smith, B.: Modelling the role of agriculture for the 20th century global terrestrial carbon balance, Glob. Change Biol., 13, 679--706, doi:10.1111/j.1365-2486.2006.01305.x, 2007.<br />
<br />
Bozbas, K., 2008. Biodiesel as an alternative motor fuel: Production and policies in the European Union. ''Renewable and Sustainable Energy Reviews'' 12 (2) 542-552.<br />
<br />
Bouwman, A., der Hoek, K. V., Eickhout, B., and Soenario, I.: Exploring changes in world ruminant production systems, Agr. Systems, 84, 121--153, doi:10.1016/j.agsy.2004.05.006, 2005.Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle, B., Goss Eng, A., Lucht, W., Mapako, M., Masera Cerutti, O., McIntyre, T., Minowa, T., Pingoud, K.., 2011. Bioenergy. In: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Matschoss, P., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S, von Stechow, C. (eds) ''IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation''. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.<br />
<br />
Chavas, J.P.: On the economics of agricultural production, Aust. J. Agr. Resour. Econom., 52, 365-380, 2008.<br />
<br />
Clarke JF, Edmonds JA (1993) Modelling energy technologies in a competitive market. Energy Economics 15(2):123129<br />
<br />
P. Conforti and M. Giampietro, Fossil energy use in agriculture: an international comparison, Agriculture, ecosystems &amp; environment, 65 (1997), pp. 231--243.<br />
<br />
Corrado C and Mattey J (1997). Capacity Utilization. Journal of Economic Perspectives 11(1): 151-167.<br />
<br />
Dees S, Karadeloglou P, Kaufmann RK, Sanchez M (2007) Modelling the world oil market: Assessment of a quarterly econometric model. Energy Policy 35(1): 178-191.<br />
<br />
Dorin, B.: Agribiom Caloric Balance Sheets, updated estimates from Paillard et al. 2011, 25--65, 2011.<br />
<br />
Edmonds, J.A., Pitcher, H.M., Sands, R.D., 2004. Second generation model 2004: an overview. Pacific Northwest National Laboratory, PNNL-14916.<br />
<br />
FAO (2013). Food and agriculture organisation of the united nations: Statistical database. (last access: 6 Mars 2013).<br />
<br />
Fattouh B (2007) The drivers of oil prices: The usefulness and limitations of Non-Structural model, the Demand-Supply framework and informal approaches. OIES WORKING PAPERS WPM 32.<br />
<br />
Frondel, M., Schmidt, C., 2002. The Capital-Energy Controversy: an artifact of cost shares? ''The Energy Journal'' 23 (3) 53-80.<br />
<br />
Fulton L, Eads G (2004) IEA/SMP model documentation and reference case projection. Tech. rep.,URL [http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf http://www.wbcsd.org/web/publications/mobility/smp-model-document.pdf]<br />
<br />
Greene DL, Hopson JL, Li J (2006) Have we run out of oil yet? oil peaking analysis from an optimist's perspective. Energy Policy 34(5): 515-531.<br />
<br />
Grubler A, Nakicenovi N, Nordhaus W (2002) Technological change and the environment. Washington DC<br />
<br />
Guivarch, C., Crassous, R., Sassi, O. and Hallegatte, S. 2010. The costs of climate policies in a second best world with labour market imperfections. Climate Policy 11, 1 : 768--788.<br />
<br />
Gulen G (1996) Is OPEC a cartel? evidence from cointegration and causality tests. Energy Journal 17: 43-58.<br />
<br />
Hairault, Jean-Olivier, et Hubert Kempf, éd. 2002. A Long---Term Model for the World Economy. In ''Market Imperfections and Macroeconomic Dynamics'', 51?73. Springer US.<br />
<br />
Holland, S.,2008. Modeling Peak Oil. The Energy Journal 29(2), 61--80.<br />
<br />
Holland, S.,2003.Extraction capacity and the optimal order of extraction. Journal of Environmental Economics and Management 45(3),569--588.<br />
<br />
Hotelling H (1931) The economics of exhaustible resources. The Journal of Energy and Development 39(2):137-175.<br />
<br />
Hourcade J.-C., 1993. Modelling long-run scenarios: Methodology lessons from a prospective study on a low CO2 intensive country. ''Energy Policy'' 21 (3) 309-326.<br />
<br />
Hourcade J.C., Jaccard M., Bataille C. and Ghersi F., 2006. Hybrid Modeling : New Answers to Old Challenges. In: Hybrid Modeling of Energy-Environment Policies: reconciling Bottom-up and Top- down. The Energy Journal (Special Issue 2): 1-12.<br />
<br />
IEA (2007) World energy outlook. Tech. rep., IEA/OECD, Paris, France<br />
<br />
International Energy Agency (IEA), 2008. World Energy Outlook 2008, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006a. World Energy Outlook. Technical report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006b. Coal-to-liquids Workshop report, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2006c. Energy Technology Perspectives 2006 - Scenarios &amp; Strategies to 2050, IEA/OECD, Paris, France.<br />
<br />
International Energy Agency (IEA), 2004. Biofuels for transport, IEA/OECD, Paris, France.<br />
<br />
Johansen L (1959). Substitution versus Fixed Production Coefficients in the Theory of Growth: A synthesis. Econometrica 27: 157-176.<br />
<br />
Kaufmann, R.K., S. Dees, P. Karadeloglou, M. Sanchez, 2004. Does OPEC matter? An econometric analysis of oil prices. The Energy Journal, 25 (4), pp. 67--90.<br />
<br />
Kemp, M.C.,Van Long, N.,1980. On two folk theorems concerning the extraction of exhaustible resources. Econometrica 48(3), 663--673.<br />
<br />
Krautkraemer JA (1998) Nonrenewable resource scarcity. Journal of Economic Literature 36(4): 2065-2107.<br />
<br />
Labriet M, Loulou R, Kanudia A, Vaillancourt K (2004) The advanced world markal model: Description of the inputs. Les Cahiers du GERAD<br />
<br />
Layard, R., S. Nickell, and R. Jackman. 2005. ''Unemployment''.<br />
<br />
Layard, R., and S. Nickell. 1986. Unemployment in Britain. ''Economica'' 53, no. 210. New Series: S121-S169.<br />
<br />
Lindbeck, A. 1993. ''Unemployment and macroeconomics''.<br />
<br />
LEPII-EPE (2006) The POLES model, POLES State of the Art. Institut d'économie et de Politique de l'énergie, Grenoble, France.<br />
<br />
Maddison, A. 1995. ''Monitoring the world economy: 1820-1992''. OECD Development Center, ISSN 1563-4310 ; 1995 . Paris: OECD.<br />
<br />
Marshall, A., 1890. ''Principles of Economics''. London: Macmillan and Co., Ltd., 1920: Eighth edition.<br />
<br />
Martins, J. Oliveira, F. Gonand, P. Antolin, C. De La Maisonneuve, and Kwang-Yeol Yoo. 2005. The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers 420.<br />
<br />
Malcolm G. and Truong P., 1999. The Process of Incorporating Energy Data into GTAP, Draft GTAP Technical Paper, Center for Global Trade Analysis, PurdueUniversity, WestLafayette, Indiana, USA.<br />
<br />
A. McDonald and L. Schrattenholzer, Learning rates for energy technologies, Energy policy, 29 (2001), pp. 255--261.<br />
<br />
L. Neij, Cost development of future technologies for power generation - A study based on experience curves and complementary bottom-up assessments, Energy policy, 36 (2008), pp. 2200--2211.<br />
<br />
Nordhaus, W. D., Boyer, J. (2010) Warming the World: Economics Models of Global Warming. Cambridge, MA: MIT Press.<br />
<br />
Paltsev S, Reilly J, Jacoby H, Eckaux R, McFarland J, Sarofim M, Asasoorian M, Babiker M (2005). The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4, Report no. 125. Joint Program on the Science and Policy of Global Change, MIT, Cambridge, MA<br />
<br />
Paillard, S., Treyer, S., and Dorin, B. (Eds.): Agrimonde, Scenarios and Challenges for Feeding the World in 2050, Quae, Versailles, 2011.<br />
<br />
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer,S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993--1010, doi:10.5194/gmd-4-993-2011, 2011.<br />
<br />
E. Phelps, The golden rule of accumulation: a fable for growthmen, The American Economic Review, 51 (1961), p. 638--643.<br />
<br />
Phelps, E. S. 1992. Consumer Demand and Equilibrium Unemployment in a Working Model of the Customer-Market Incentive-Wage Economy. ''The Quarterly Journal of Economics'' 107, no. 3: 1003-1032.<br />
<br />
Ramankutty, N. and Foley, J. A. (1999). Estimating historical changes in global land cover: croplands from 1700 to 1992. Global Biogeochemical Cycles, 13(4):997-1027.<br />
<br />
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, doi:10.1029/2007GB002952, 2008.<br />
<br />
Ricardo, D.: On the principles of political economy and taxation,1817.<br />
<br />
Rao S, Keppo I, Riahi K (2006) Importance of technological change and spillovers in long-term climate policy. The Energy Journal pp 105-122<br />
<br />
Rehrl T, Friedrich R (2006) Modelling long-term oil price and extraction with a hubbert approach: The LOPEX model. Energy Policy 34(15): 2413-2428.<br />
<br />
Reynolds, D.B.,1999. The mineral economy: how prices and costs can falsely signal decreasing scarcity. Ecological Economics 31(1),155-166.<br />
<br />
Rogner H (1997) An assessment of world hydrocarbon resources. Annual review of energy and the environment 22: 217-262.<br />
<br />
Sands R.D., Miller S. and Kim M.K., 2005. The Second Generation Model: Comparison of SGM and GTAP Approaches to Data Development, Pacific Northwest National Labouratory, PNNL-15467, 2005.<br />
<br />
Sassi O., Crassous R., Hourcade J.C.,Gitz V., Waisman H., Guivarch C., 2010. ?[http://inderscience.metapress.com/content/e81p5m067q218t62/ Imaclim-R: a modelling framework to simulate sustainable development pathways]?, International Journal of Global Environmental Issues, Special Issue on Models for Sustainable Development for Resolving Global Environmental Issues: Vol. 10, Nos. 1/2, pp. 5-24. [http://hal.archives-ouvertes.fr/docs/00/56/62/90/PDF/Sassi_et_al_2010_ImaclimR_a_modelling_framework_to_simulate_sustainable_development_pathways.pdf Working Paper version.]<br />
<br />
Schneider, S. H., Thompson, S. L. (1981) Atmospheric CO<sub>2</sub> and Climate: Importance of the Transient Response. Journal of Geophysical Research 86(4): 3135--47.<br />
<br />
Shapiro, C., and J E. Stiglitz. 1984. Equilibrium Unemployment as a Worker Discipline Device. ''The American Economic Review'' 74, no. 3: 433-444.<br />
<br />
Sims REH, Schock RN, Adegbululgbe A, Fenhann J, Konstantinaviciute I, et al (2007) Energy supply. Climate change pp 251-322<br />
<br />
Storchmann, K., 2005. Long-Run Gasoline demand for passenger cars: the role of income distribution. Energy Economics 27: 25--58.<br />
<br />
Solow, R. M. 1956. A contribution to the theory of economic growth. ''The Quarterly Journal of Economics'': 65-94.<br />
<br />
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R., Müller, C., and Bondeau, A. (2012). The nexus land-use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use. Geoscientic Model Development, 5(5):1297-1322.<br />
<br />
United Nations. 2005. ''World population prospects: the 2004 revision''. United Nations Publications.<br />
<br />
USGS (2000) World petroleum assessment 2000. Tech. rep., United States Geological Survey, USA, Washington.<br />
<br />
Uhler, R.S.,1976.Costs and supply in petroleum exploration: the case of alberta. Canadian Journal of Economics 19, 72--90.<br />
<br />
Waisman, H.D., Guivarch, C., Grazi, F., Hourcade, J.C. 2012. ?[http://www.springerlink.com/content/22jk123872580154/ The Imaclim-R Model: Infrastructures, Technical Inertia and the Costs of Low Carbon Futures under Imperfect Foresight.]? Climatic Change, Volume 114, Number 1, 101-120.<br />
<br />
Waisman, H.D., Guivarch, C., Lecocq, C. 2013. [http://www.tandfonline.com/doi/abs/10.1080/14693062.2012.735916 ?The transportation sector and low-carbon growth pathways?] Climate Policy 13(1): 106--129. [http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf http://hal.archives-ouvertes.fr/docs/00/79/91/19/PDF/WAISMAN_et_al._-_Transport_and_LCS_FINAL_HAL.pdf]<br />
<br />
Zahavi, Y., Talvitie, A., 1980, ?Regularities in Travel Time and Money Expenditures?,''Transportation Research Record,'' 750, 13-19.</div>Celine Guivarch