Markov Chain Monte Carlo Simulation Methods in Econometrics

Siddhartha Chib and Edward Greenberg
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Siddhartha Chib: Washington University

Econometrics from University Library of Munich, Germany

Abstract: 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.

JEL-codes: C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 1994-08-22, Revised 1995-02-23
Note: This is a slightly revised version of that posted earlier. It is a postscript file.
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Citations: View citations in EconPapers (6)

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Related works:
Journal Article: Markov Chain Monte Carlo Simulation Methods in Econometrics (1996)
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:9408001

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