Feasible estimation of firm‐specific allocative inefficiency through Bayesian numerical methods
提出一种贝叶斯数值方法，利用吉布斯抽样从条件GMM估计中获取企业及投入特定的配置低效率参数，并以智利水电站面板数据为例，发现企业间效率差异显著，而标准GMM方法几乎无法识别行业层面的配置低效率。
Abstract Both the theoretical and empirical literature on the estimation of allocative and technical inefficiency has grown enormously. To minimize aggregation bias, ideally one should estimate firm and input‐specific parameters describing allocative inefficiency. However, identifying these parameters has often proven difficult. For a panel of Chilean hydroelectric power plants, we obtain a full set of such parameters using Gibbs sampling, which draws sequentially from conditional generalized method of moments (GMM) estimates obtained via instrumental variables estimation. We find an economically significant range of firm‐specific efficiency estimates with differing degrees of precision. The standard GMM approach estimates virtually no allocative inefficiency for industry‐wide parameters. Copyright © 2009 John Wiley & Sons, Ltd.