PARAMETER ESTIMATION FOR A COMPUTABLE GENERAL EQUILIBRIUM MODEL: A MAXIMUM ENTROPY APPROACH
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We introduce a maximum entropy approach to parameter estimation for computable
general equilibrium (CGE) models. The approach applies information theory to
estimating a system of nonlinear simultaneous equations. It has a number of advantages.
First, it imposes all general equilibrium constraints. Second, it permits incorporation of
prior information on parameter values. Third, it can be applied in the absence of
copious data. Finally, it supplies measures of the capacity of the model to reproduce the
historical record and the statistical significance of parameter estimates. The method is
applied to estimating a CGE model of Mozambique.