Improved marginal likelihood estimation via power posteriors and importance sampling

DOI10.1016/j.jeconom.2021.11.009OpenAlexW2965951690MaRDI QIDQ2697973

Yanyan Li

Publication date: 14 April 2023

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2021.11.009

zbMATH Keywords

importance samplingMarkov chain Monte CarloBayes factormarginal likelihoodmodel choicepower posteriors

Mathematics Subject Classification ID

Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Uses Software

• WinBUGS
• BayesDA

Cites Work

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• Striated Metropolis-Hastings sampler for high-dimensional models
• On priors and Bayes factors
• The Bernstein-von Mises theorem under misspecification
• Deviance information criterion for latent variable models and misspecified models
• Thermodynamic integration and steppingstone sampling methods for estimating Bayes factors: a tutorial
• Risk of Bayesian Inference in Misspecified Models, and the Sandwich Covariance Matrix
• Bayesian Estimation of DSGE Models
• Marginal Likelihood Estimation via Power Posteriors
• Asymptotic Statistics
• Computing Bayes Factors by Combining Simulation and Asymptotic Approximations
• Bayes Factors

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