Stochastic frontier models with random coefficients
提出一种随机系数随机前沿模型，用于分离企业的技术无效率与技术差异，并基于贝叶斯方法和吉布斯抽样进行推断，通过实证示例说明该方法的实用性。
Abstract The paper proposes a stochastic frontier model with random coefficients to separate technical inefficiency from technological differences across firms, and free the frontier model from the restrictive assumption that all firms must share exactly the same technological possibilities. Inference procedures for the new model are developed based on Bayesian techniques, and computations are performed using Gibbs sampling with data augmentation to allow finite‐sample inference for underlying parameters and latent efficiencies. An empirical example illustrates the procedure. Copyright © 2002 John Wiley & Sons, Ltd.