Socio-economic drivers - COFFEE-TEA: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
mNo edit summary |
||
Line 1: | Line 1: | ||
Socio-economic drivers are exogenous to the TEA model. The model relies on the [https://tntcat.iiasa.ac.at/SspV2Preview/dsd?Action=htmlpage&page=10#v2 Shared Socioeconomic Pathways (SSPs) database] as a reference for the economic growth scernarios. Most applications are based on the GDP projections of the SSP2 scenario[[CiteRef::dellink2017]][[CiteRef::fricko2017]] (<xr id="fig:TEA_fig1"/>). | Socio-economic drivers are exogenous to the TEA model. The model relies on the [https://tntcat.iiasa.ac.at/SspV2Preview/dsd?Action=htmlpage&page=10#v2 Shared Socioeconomic Pathways (SSPs) database] as a reference for the economic growth and demographic scernarios. Most applications are based on the GDP and population projections of the SSP2 scenario[[CiteRef::dellink2017]][[CiteRef::fricko2017]] (<xr id="fig:TEA_fig1"/>). | ||
<figure id="fig:TEA_fig1"> | <figure id="fig:TEA_fig1"> | ||
[[File:SSP2 GDP.png|450px|thumb|SSP2 | [[File:SSP2 GDP.png|450px|thumb|SSP2 growth]] | ||
</figure> | </figure> | ||
Revision as of 15:57, 19 December 2018
Socio-economic drivers are exogenous to the TEA model. The model relies on the Shared Socioeconomic Pathways (SSPs) database as a reference for the economic growth and demographic scernarios. Most applications are based on the GDP and population projections of the SSP2 scenariodellink2017fricko2017 (<xr id="fig:TEA_fig1"/>).
<figure id="fig:TEA_fig1">
</figure>
Corresponding documentation | |
---|---|
Previous versions | |
Model information | |
Model link | |
Institution | COPPE/UFRJ (Cenergia), Brazil, http://www.cenergialab.coppe.ufrj.br/. |
Solution concept | General equilibrium (closed economy) |
Solution method | The COFFEE model is solved through Linear Programming (LP). The TEA model is formulated as a mixed complementary problem (MCP) and is solved through Mathematical Programming System for General Equilibrium -- MPSGE within GAMS using the PATH solver. |
Anticipation |