MARKOV-CHAIN MONTE-CARLO SIMULATION METHODS IN ECONOMETRICS

We present several Markov chain Monte Carlo simulation methods that ha ve been widely used in recent years in econometrics and statistics, Am ong 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 expla nation of applications to important models that are studied in econome trics, We include a discussion of some implementation issues, the use of the methods in connection with the EM algorithm, and how the method s can be helpful in model specification questions, Many of the applica tions of these methods are of particular interest to Bayesians, but we also point out ways in which frequentist statisticians may find the t echniques useful.