Bayesian inference in dynamic disequilibrium models: an application to the Polish credit market

Luc Bauwens and Michel Lubrano

No 2006050, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: We review Bayesian inference for dynamic latent variable models using the data augmentation principle. We detail the diffculties of simulating 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)
Date: 2006-06
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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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