Socio-economic drivers - REMIND-MAgPIE: Difference between revisions
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Population and GDP are main drivers of future energy demand and, thus, GHG emissions in REMIND. We base population and GDP inputs on the Shared Socio-economic Pathway (SSP) scenarios. REMIND’s default population projections (both total population as well as working age population) are based on IIASA (KC and Lutz 2016) (and the GDP scenarios from the OECD (Dellink et al. 2015). Both Population and GDP scenario data are available at https://secure.iiasa.ac.at/web-apps/ene/SspDb/dsd?Action=htmlpage&page=about. These projections are available for all five different SSP scenarios (O’Neill et al. 2014). For default scenarios, we use SSP2 scenario data as they represent a middle-of-the road scenario. To calibrate GDP, which is an endogenous result of the growth engine in REMIND, we calibrate labor productivity parameters in an iterative procedure so as to reproduce the OECD's GDP reference scenarios. Within REMIND GDP is measured in market exchange rates (MER). | Population and GDP are main drivers of future energy demand and, thus, GHG emissions in REMIND. We base population and GDP inputs on the Shared Socio-economic Pathway (SSP) scenarios. REMIND’s default population projections (both total population as well as working age population) are based on IIASA (KC and Lutz 2016) (and the GDP scenarios from the OECD (Dellink et al. 2015). Both Population and GDP scenario data are available at https://secure.iiasa.ac.at/web-apps/ene/SspDb/dsd?Action=htmlpage&page=about. These projections are available for all five different SSP scenarios (O’Neill et al. 2014). For default scenarios, we use SSP2 scenario data as they represent a middle-of-the road scenario. To calibrate GDP, which is an endogenous result of the growth engine in REMIND, we calibrate labor productivity parameters in an iterative procedure so as to reproduce the OECD's GDP reference scenarios. Within REMIND GDP is measured in market exchange rates (MER). | ||
<figure id="fig:REMIND_3"> | |||
[[File: Figure Socio-economic drivers - REMIND.JPG]] | [[File: Figure Socio-economic drivers - REMIND.JPG]] | ||
</figure> | |||
Figure 3. Projections of (a) population and (b) GDP used in the REMIND SSP2 (“Middle-of-the-Road”) scenario. | Figure 3. Projections of (a) population and (b) GDP used in the REMIND SSP2 (“Middle-of-the-Road”) scenario. | ||
Revision as of 12:22, 1 February 2017
| Corresponding documentation | |
|---|---|
| Previous versions | |
| Model information | |
| Model link | |
| Institution | Potsdam Institut für Klimafolgenforschung (PIK), Germany, https://www.pik-potsdam.de. |
| Solution concept | General equilibrium (closed economy)MAgPIE: partial equilibrium model of the agricultural sector; |
| Solution method | OptimizationMAgPIE: cost minimization; |
| Anticipation | |
Population and GDP are main drivers of future energy demand and, thus, GHG emissions in REMIND. We base population and GDP inputs on the Shared Socio-economic Pathway (SSP) scenarios. REMIND’s default population projections (both total population as well as working age population) are based on IIASA (KC and Lutz 2016) (and the GDP scenarios from the OECD (Dellink et al. 2015). Both Population and GDP scenario data are available at https://secure.iiasa.ac.at/web-apps/ene/SspDb/dsd?Action=htmlpage&page=about. These projections are available for all five different SSP scenarios (O’Neill et al. 2014). For default scenarios, we use SSP2 scenario data as they represent a middle-of-the road scenario. To calibrate GDP, which is an endogenous result of the growth engine in REMIND, we calibrate labor productivity parameters in an iterative procedure so as to reproduce the OECD's GDP reference scenarios. Within REMIND GDP is measured in market exchange rates (MER).
<figure id="fig:REMIND_3"> File:Figure Socio-economic drivers - REMIND.JPG </figure>
Figure 3. Projections of (a) population and (b) GDP used in the REMIND SSP2 (“Middle-of-the-Road”) scenario.