Nonparametric Bayes subject to overidentified moment conditions

Research output: Contribution to journalArticlepeer-review

Abstract

Nonparametric Bayesian estimation subject to overidentified moment equations is a challenge because the support of the posterior is a manifold of lower dimension than the number of model parameters. The manifold therefore has Lebesgue measure zero thus inhibiting the use of the most commonly used Bayesian estimation method: MCMC (Markov Chain Monte Carlo). This study proposes an effective MCMC algorithm and algorithms for estimating scale and the normalizing constant. The algorithms are illustrated with two illustrative applications.

Original languageEnglish (US)
Pages (from-to)27-38
Number of pages12
JournalJournal of Econometrics
Volume228
Issue number1
DOIs
StatePublished - May 2022

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

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