Bayesian Estimation of Regional Production for CGE Modeling
针对CGE模型参数依赖外部来源的批评，采用贝叶斯方法估计区域CGE模型中的超越对数生产函数参数，并用马尔可夫链蒙特卡洛模拟进行估计，最后对比了柯布-道格拉斯与估计的超越对数方程的政策响应差异。
Abstract 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.