Parameter Estimation for a Computable General Equilibrium Model: A Maximum Entropy Approach
Publikation: Working paper › Forskning
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Parameter Estimation for a Computable General Equilibrium Model : A Maximum Entropy Approach. / Arndt, Channing; Robinson, Sherman; Tarp, Finn.
Washington, D.C. : International Food Policy Research Institute (IFPRI), 1999.Publikation: Working paper › Forskning
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TY - UNPB
T1 - Parameter Estimation for a Computable General Equilibrium Model
T2 - A Maximum Entropy Approach
AU - Arndt, Channing
AU - Robinson, Sherman
AU - Tarp, Finn
N1 - JEL Classification: C51, C68
PY - 1999
Y1 - 1999
N2 - 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
AB - 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
M3 - Working paper
BT - Parameter Estimation for a Computable General Equilibrium Model
PB - International Food Policy Research Institute (IFPRI)
CY - Washington, D.C.
ER -
ID: 45480