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)
JournalJournal of Econometrics
DOIs
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

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