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Bayesian Inference in Dynamic Disequilibrium Models: An Application to the Polish Credit Market

  • Luc Bauwens
  • Michel Lubrano

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).

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Article provided by Taylor & Francis Journals in its journal Econometric Reviews.

Volume (Year): 26 (2007)
Issue (Month): 2-4 ()
Pages: 469-486

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Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:469-486
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  4. Sylvanus Ikhide, 2003. "Was There a Credit Crunch in Namibia Between 1996-2000?," Journal of Applied Economics, Universidad del CEMA, vol. 0, pages 269-290, November.
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  8. James Tobin, 1956. "Estimation of Relationships for Limited Dependent Variables," Cowles Foundation Discussion Papers 3R, Cowles Foundation for Research in Economics, Yale University.
  9. Kim, Hyun E., 1999. "Was the credit channel a key monetary transmission mechanism following the recent financial crisis in the Republic of Korea?," Policy Research Working Paper Series 2103, The World Bank.
  10. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
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  17. Berg, Andreas & Meyer, Renate & Yu, Jun, 2004. "Deviance Information Criterion for Comparing Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 107-20, January.
  18. Sneessens, Henri R., 1985. "Two alternative stochastic specification and estimation methods for quantity rationing models : A Monte-Carlo comparison," European Economic Review, Elsevier, vol. 29(1), pages 111-136.
  19. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika van der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639.
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