Bayesian inference in dynamic disequilibrium models: an application to the Polish credit market
Luc Bauwens () and
Michel Lubrano ()
No 2006050, CORE Discussion Papers from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)
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)
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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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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2006050
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