期刊名称：Discussion Paper / Département des Sciences Économiques de l'Université Catholique de Louvain
印刷版ISSN：1379-244X
出版年度：2006
卷号：1
出版社：Université catholique de Louvain
摘要：We review Bayesian inference for dynamic latent variable models using the data augmentation principle. We detail the difficulties of stimulating dynamic latent variables in a Gibbs sampler. We propose an alternative specification of the dynamic disequilibrium model which leads to a simple simulation procedure and renders Bayesian inference fully operational. Identification issues are discussed. We conduct a specification search using the posterior deviance criterion of Spiegelhalter, Best, Carlin, and van der Linde (2002) for a disequilibrium model of the Polish credit market.
