• Media type: E-Book
  • Title: Bayesian Inference in Dynamic Disequilibrium Models : An Application to the Polish Credit Market
  • Contributor: Bauwens, Luc [Author]; Lubrano, Michel [Other]
  • Published: [S.l.]: SSRN, [2006]
  • Published in: CORE Discussion Paper ; No. 2006/50
  • Extent: 1 Online-Ressource (24 p)
  • Language: Not determined
  • DOI: 10.2139/ssrn.925677
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 2006 erstellt
  • Description: 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
  • Access State: Open Access