Bayesian Inference in Dynamic Disequilibrium Models: an Application to the Polish Credit Market

Luc Bauwens and Michel Lubrano

No 2006027, Discussion Papers (ECON - Département des Sciences Economiques) from Université catholique de Louvain, Département des Sciences Economiques

Abstract: 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.

Keywords: Latent variables; Disequilibrium models; Bayesian inference; Gibbs sampler; Credit rationing (search for similar items in EconPapers)
JEL-codes: C11 C32 C34 E51 (search for similar items in EconPapers)
Pages: 26
Date: 2006-05-01
New Economics Papers: this item is included in nep-ecm and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Bayesian Inference in Dynamic Disequilibrium Models: An Application to the Polish Credit Market (2007)
Working Paper: Bayesian inference in dynamic disequilibrium models: an application to the Polish credit market (2007)
Working Paper: Bayesian inference in dynamic disequilibrium models: an application to the Polish credit market (2006)
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