Premium
Bayesian Estimation of Regional Production for CGE Modeling
Author(s) -
Adkins Lee C.,
Rickman Dan S.,
Hameed Abid
Publication year - 2003
Publication title -
journal of regional science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.171
H-Index - 79
eISSN - 1467-9787
pISSN - 0022-4146
DOI - 10.1111/j.0022-4146.2003.00314.x
Subject(s) - computable general equilibrium , stylized fact , econometrics , markov chain monte carlo , production (economics) , bayesian probability , economics , production function , estimation , prior probability , markov chain , function (biology) , bayes estimator , econometric model , computer science , mathematics , statistics , macroeconomics , management , evolutionary biology , biology
Computable general equilibrium (CGE) models are often criticized for using restrictive functional forms and relying on external sources for parameter values in their calibration. CGE modelers argue that in many instances reliable econometric estimates of important model parameters are unavailable because they must be estimated using small numbers of time‐series observations. To address these criticisms, this paper uses a Bayesian approach to estimate the parameters of a translog production function in a regional computable general equilibrium model. Using priors from more reliable national estimates, and parameter restrictions required by neoclassical production theory, estimation is done by Markov chain Monte Carlo simulation. A stylized regional CGE model is then used to contrast policy responses of a Cobb‐Douglas specification with those from the estimated translog equation.