Computable General Equilibrium (CGE) models
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CGE models calculate a vector of prices such that all the markets of the economy are in equilibrium, implying that resources are allocated efficiently. They are based on economic theory and theoretical coherence (i.e. the Walrasian representations of the economy). Therefore, parameters and coefficients are calibrated with mathematical methods and not estimated as in econometric modelling. They can be static - comparing the situation at one or more dates - or dynamic, showing developments from one period to another. CGE models require a Social Accounting Matrix that is built by combining Input-Output-tables (to model interrelations between productive sectors) with national account data.[1]
The strength of CGE models is their internal consistency; i.e. they allow for consistent comparative analysis of policy scenarios by ensuring that in all scenarios the economic system remains in general equilibrium (however, extensions to model market imperfections are possible). They integrate micro-economic mechanisms and institutional features into a consistent macro-economic framework and consider feedback mechanisms between all markets. All behavioural equations (demand and supply) are derived from microeconomic principles. Since CGE models are calibrated to a base year data set, the data requirement is limited even if the degree of disaggregation is high. This allows for the evaluation of distributional effects, across countries, economic sectors and agents. CGE models are advantageous for analysing general economic policies like public finance, taxation and social policy, and their impact on longer term structural change.[1]
The weakness of CGE models is their somewhat tautological construction (all results are implicitly linked to to the assumptions and calibration made). In contrast to macro-econometric models CGE models can be used only for simulation purposes, but not for forecasts. Another disadvantage compared to sectoral models is that, following the top-down approach, CGE models typically lack a detailed bottom-up representation of the production and supply side. Since top-down models rely on the assumption that all "best available technologies" have been already installed, the calculated cost of a specific emission reduction measure is typically higher than in bottom-up studies. A paper on possible extensions of CGE models in for impact assessment in general can be found here:
Computable General Equilibrium Models for Sustainability Impact[1]
