IAMC-Documentation - User contributions [en]

WITCH

2020-05-13T12:25:44Z

Laurent Drouet:

{{ModelTemplate}}
{{ModelInfoTemplate
|Name=WITCH
|Version=5.0
|participation=full
|processState=published
}}
{{ScopeMethodTemplate
|Objective=WITCH evaluates the impacts of climate policies on global and regional economic systems and provides information on the optimal responses of these economies to climate change. The model considers the positive externalities from leaning-by-doing and learning-by-researching in the technological change.
|SolutionConceptOption=General equilibrium (closed economy)
|SolutionHorizon=inter-temporal (foresight);
|SolutionMethodOption=Optimization
|BaseYear=2005
|TimeSteps=5
|Horizon=2150
|Nr=17
|PoliciesOption=Emission tax; Emission pricing; Cap and trade; Fuel taxes; Fuel subsidies; Capacity targets; Emission standards
|Concept=Hybrid: Economic optimal growth model, including a bottom-up energy sector and a simple climate model, embedded in a `game theory` framework.
|PolicyImplementation=Quantitative climate targets (temperature, radiative forcing, concentration), carbon budgets, emissions profiles as optimization constraints.
Carbon taxes.
Allocation and trading of emission permits, banking and borrowing.
Subsidies, taxes and penalty on energies sources.
}}
{{Socio-economicTemplate
|PopulationOption=Yes (exogenous)
|PopulationAgeStructureOption=Yes (exogenous)
|EducationLevelOption=Yes (exogenous)
|UrbanizationRateOption=Yes (exogenous)
|GDPOption=Yes (endogenous)
|TotalFactorProductivityOption=Yes (exogenous)
|AutonomousEnergyEfficiencyImprovementsOption=Yes (exogenous)
|ExogenousDriverOption=Total Factor Productivity; Labour Productivity; Capital Technical progress
}}
{{Macro-economyTemplate
|TradeOption=Coal; Oil; Gas; Uranium; Electricity; Bioenergy crops; Capital; Emissions permits; Non-energy goods
|CostMeasureOption=GDP loss; Welfare loss; Consumption loss; Energy system cost mark-up
|CoalRUOption=Yes (supply curve)
|ConventionalOilRUOption=Yes (process model)
|UnconventionalOilRUOption=Yes (process model)
|ConventionalGasRUOption=Yes (fixed)
|Unconventional GasRUOption=Yes (fixed)
|UraniumRUOption=Yes (fixed)
|BioenergyRUOption=Yes (supply curve)
|EconomicSector=other;
|EconomicSectorText=A single economy sector is represented. Production inputs are capital, labor and energy services, accounting for the Energy sector split into 8 energy technologies sectors (coal, oil, gas, wind&solar, nuclear, electricity and biofuels).
|EnergyEnd-useTCOption=Endogenous technological change
|AgricultureTCOption=Exogenous technological change
|EconomicSectorOption=Energy
}}
{{EnergyTemplate
|EnergyTechnologyChoiceOption=No discrete technology choices
|EnergyTechnologySubstitutabilityOption=Mostly high substitutability
|EnergyTechnologyDeploymentOption=Expansion and decline constraints; System integration constraints
|ElectricityTechnologyOption=Coal w/o CCS; Coal w/ CCS; Gas w/o CCS; Gas w/ CCS; Oil w/o CCS; Oil w/ CCS; Bioenergy w/o CCS; Bioenergy w/ CCS; Nuclear power; Solar power; Solar power-central PV; Solar power-CSP; Wind power; Wind power-onshore; Wind power-offshore; Hydroelectric power; Solar power-distributed PV
|ElectricityGIOption=Yes (aggregate)
|PassengerTransportationOption=Light Duty Vehicles (LDVs); Electric LDVs; Hybrid LDVs; Diesel LDVs
|ResourceUseOption=Coal; Oil; Gas; Uranium; Biomass
|GridInfrastructureOption=Electricity; CO2
|TechnologySubstitutionOption=Expansion and decline constraints; System integration constraints
|EnergyServiceSectorOption=Transportation
}}
{{Land-useTemplate
|LandCoverOption=Cropland; Forest; Pasture; Cropland irrigated
|Land-use=Cropland; Forest;
|Land-useText=Bioenergy related cost and emissions are obtained by an soft linking with the GLOBIOM model.
}}
{{EmissionClimateTemplate
|GHGOption=HFCs; CO2 fossil fuels; CO2 land use; CH4 energy; CH4 land use; CH4 other; N2O energy; N2O land use; N2O other
|PollutantOption=CO energy; CO land use; CO other; NOx energy; NOx land use; NOx other; VOC energy; VOC land use; VOC other; SO2 energy; SO2 land use; SO2 other; BC energy; BC land use; BC other; OC energy; OC land use; OC other; NH3 energy; NH3 land use; NH3 other
|ClimateIndicatorOption=Temperature change; Concentration: CO2; Concentration: CH4; Concentration: N2O; Concentration: Kyoto gases; Radiative forcing: CO2; Radiative forcing: CH4; Radiative forcing: N2O; Radiative forcing: F-gases; Radiative forcing: Kyoto gases; Radiative forcing: aerosols; Radiative forcing: land albedo; Radiative forcing: AN3A; Radiative forcing: total
|CarbonDioxideRemovalOption=Bioenergy with CCS; Reforestation; Afforestation; Direct air capture
|ClimateChangeImpactsOption=Economic output
|Co-LinkagesOption=Air pollution & health: Source-based aerosol emissions; Air pollution & health: Health impacts of air Pollution
}}
{{InstitutionTemplate
|abbr=RFF-CMCC EIEE
|institution=European Institute on Economics and the Environment
|link=http://www.eiee.org
|country=Italy
}}

WITCH

2020-03-12T10:55:28Z

Laurent Drouet:

2016-10-11T14:00:55Z

Laurent Drouet:

WITCH

2016-10-11T13:57:29Z

Laurent Drouet:

WITCH

2016-10-11T13:55:25Z

Laurent Drouet:

2016-08-30T12:37:19Z

Laurent Drouet: /* General Framework */

{{ModelDocumentationTemplate
|IsDocumentationOf=WITCH
|DocumentationCategory=Model concept, solver and details
|IsEmpty=No
}}
== General Framework ==

WITCH (World Induced Technical Change Hybrid) is an optimal growth model of the world economy that integrates in a unified framework the sources and the consequences of climate change. A climate module links GHG emissions produced by economic activities to their accumulation in the atmosphere and the oceans. The effect of these GHG concentrations on the global mean temperature is derived. A damage function explicitly accounts for the effects of temperature increases on the economic system.

Regions interact with each other because of the presence of economic (technology, exhaustible natural resources) and environmental global externalities. For each region a forward-looking agent maximizes its own inter-temporal social welfare function, strategically and simultaneously to other regions. The inter-temporal equilibrium is calculated as an open-loop Nash equilibrium, or, a cooperative solution can also be solved by aggregating the welfare of each regions. More precisely, the Nash equilibrium is the outcome of a non-cooperative, simultaneous, open membership game with full information. Through the optimization process regions choose the optimal dynamic path of a set of control variables, namely investments in key economic variables.

WITCH is a hard-link hybrid model because the energy sector is fully integrated with the rest of the economy and therefore investments and the quantity of resources for energy generation are chosen optimally, together with the other macroeconomic variables. The model can be defined hybrid because the energy sector features a bottom-up characterization. A broad range of different fuels and technologies can be used in the generation of energy. The energy sector endogenously accounts for technological change, with considerations for the positive externalities stemming from Learning-By-Doing and Learning-By-Researching. Overall, the economy of each region consists of eight sectors: one final good, which can be used for consumption or investments, and seven energy sectors (or technologies): coal, oil, gas, wind & solar, nuclear, electricity, and bio-fuels.

== Non-cooperative solution ==

The game theoretic setup makes it possible to capture the non-cooperative nature of international relationships. Free-riding behaviors and strategic inaction induced by the presence of a global externality are explicitly accounted for in the model. Climate change is the major global externality, as GHG emissions produced by each region indirectly impact on all other regions through the effect on global concentrations and thus global average temperature.

The model features other economic externalities that provide additional channels of interaction. Energy prices depend on the extraction of fossil fuels, which in turn is affected by consumption patterns of all regions in the world. International knowledge and experience spillovers are two additional sources of externalities. By investing in energy R&D, each region accumulates a stock of knowledge that augments energy efficiency and reduces the cost of specific energy technologies.

The effect of knowledge is not confined to the inventor region but it can spread to other regions. Finally, the diffusion of knowledge embodied in wind&solar experience is represented by learning curves linking investment costs with world, and not regional, cumulative capacity. Increasing capacity thus reduces investment costs for all regions. These externalities provide incentives to adopt strategic behaviours, both with respect to the environment (e.g. GHG emissions) and with respect to investments in knowledge and carbon-free but costly technologies.

Two different solutions can be produced: a cooperative one that is globally optimal and a decentralised, non-cooperative one that is strategically optimal for each given region (Nash equilibrium). In the cooperative solution all externalities are internalised and therefore it can be interpreted as a first-best solution. The Nash equilibrium instead can be seen as a second-best solution. Intermediate degree of cooperation, both in terms of externalities addressed and participation can also be simulated.