Model concept, solver and details - COFFEE-TEA: Difference between revisions

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TEA (Total Economy Assessment) is a multi-regional and multi-sectorial CGE model that tracks the production and distribution of goods in a dynamic recursive setup for the global economy. The model is based on the MIT EPPA model<ref>[[yang1996miteppa]]
TEA (Total Economy Assessment) is a multi-regional and multi-sectorial CGE model that tracks the production and distribution of goods in a dynamic recursive setup for the global economy. The model is based on the MIT EPPA model<ref>yang1996miteppa
</ref><ref>paltsev2005emissions</ref> and on GTAPinGAMS<ref>rutherford1997gtapingams</ref>.
</ref><ref>paltsev2005emissions</ref> and on GTAPinGAMS<ref>rutherford1997gtapingams</ref>.



Revision as of 17:54, 13 December 2018

TEA (Total Economy Assessment) is a multi-regional and multi-sectorial CGE model that tracks the production and distribution of goods in a dynamic recursive setup for the global economy. The model is based on the MIT EPPA model[1][2] and on GTAPinGAMS[3].

The model is formulated as mixed complementary problem (MCP) and is solved through Mathematical Programming System for General Equilibrium -- MPSGE[4] within GAMS using the PATH solver. It assumes total market clearance (through commodity price equilibrium), zero profit condition for producers (with constant-returns-to-scale) and perfect competition to reach general equilibrium.

Alert-warning.png Note: The documentation of COFFEE-TEA is 'under review' and is not yet 'published'!

Model Documentation - COFFEE-TEA

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
    1. yang1996miteppa
    2. paltsev2005emissions
    3. rutherford1997gtapingams
    4. rutherford1999applied