Bayesian Inference in Dynamic Disequilibrium Models: An Application to the Polish Credit Market
Luc Bauwens () and
Michel Lubrano ()
Econometric Reviews, 2007, vol. 26, issue 2-4, 469-486
We propose a Bayesian approach for inference in a dynamic disequilibrium model. To circumvent the difficulties raised by the Maddala and Nelson (1974) specification in the dynamic case, we analyze a dynamic extended version of the disequilibrium model of Ginsburgh et al. (1980). We develop a Gibbs sampler based on the simulation of the missing observations. The feasibility of the approach is illustrated by an empirical analysis of the Polish credit market, for which we conduct a specification search using the posterior deviance criterion of Spiegelhalter et al. (2002).
Keywords: Bayesian inference; Credit rationing; Data augmentation; Disequilibrium model; Latent variables; Poland (search for similar items in EconPapers)
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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)
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:taf:emetrv:v:26:y:2007:i:2-4:p:469-486
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