Markov Chain Monte Carlo Simulation Methods in Econometrics
介绍了几种在计量经济学和统计学中广泛使用的马尔可夫链蒙特卡罗模拟方法，重点展示了吉布斯采样器在重要经济模型中的应用，并讨论了实施问题、与EM算法的结合以及对模型设定的帮助，对贝叶斯和频率学派统计学家均有参考价值。
We present several Markov chain Monte Carlo simulation methods that have been widely used in recent years in econometrics and statistics. Among these is the Gibbs sampler, which has been of particular interest to econometricians. Although the paper summarizes some of the relevant theoretical literature, its emphasis is on the presentation and explanation of applications to important models that are studied in econometrics. We include a discussion of some implementation issues, the use of the methods in connection with the EM algorithm, and how the methods can be helpful in model specification questions. Many of the applications of these methods are of particular interest to Bayesians, but we also point out ways in which frequentist statisticians may find the techniques useful.