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

Bauwens, Luc;Lubrano, Michel
(2006)

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  • Bauwens, Lucorcid-logoUCLouvain
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  • Lubrano, Michel
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Abstract
We review Bayesian inference for dynamic latent variable models using the data augmentation principle. We detail the difficulties 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.
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Bauwens, L., & Lubrano, M. (2006). Bayesian inference in dynamic disequilibrium models: an application to the Polish credit market (ECON Discussion Papers 2006/27). https://hdl.handle.net/2078.5/128455