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

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  • Luc, BAUWENS

    (UNIVERSITE CATHOLIQUE DE LOUVAIN, Department of Economics)

  • Michel, LUBRANO

Abstract

We review Bayesian inference for dynamic latent variable models using the data augmentation principle. We detail the difficulties of stimulating 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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Bibliographic Info

Paper provided by Université catholique de Louvain, Département des Sciences Economiques in its series Discussion Papers (ECON - Département des Sciences Economiques) with number 2006027.

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Length: 26
Date of creation: 01 May 2006
Date of revision:
Handle: RePEc:ctl:louvec:2006027

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Keywords: Latent variables; Disequilibrium models; Bayesian inference; Gibbs sampler; Credit rationing;

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  1. Victor Ginsburgh & Asher Tishler & ISRAEL Zang, 1980. "Alternative estimation methods for two regime models: a mathematical programming approach," ULB Institutional Repository 2013/1771, ULB -- Universite Libre de Bruxelles.
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  7. Dagenais, Marcel G., 1982. "The Tobit model with serial correlation," Economics Letters, Elsevier, vol. 10(3-4), pages 263-267.
  8. 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.
  9. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-30, November.
  10. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139, October.
  11. 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.
  12. 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.
  13. 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.
  14. Lee, Lung-fei, 1999. "Estimation of dynamic and ARCH Tobit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 355-390, October.
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  16. Laroque, Guy & Salanie, B, 1993. "Simulation-Based Estimation of Models with Lagged Latent Variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S119-33, Suppl. De.
  17. Shen, Chung-Hua, 2002. "Credit Rationing for Bad Companies in Bad Years: Evidence from Bank Loan Transaction Data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 7(3), pages 261-78, July.
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  19. 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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  21. Adolfo Barajas & Roberto Steiner, 2002. "Credit Stagnation in Latin America," IMF Working Papers 02/53, International Monetary Fund.
  22. Chib, Siddhartha, 1992. "Bayes inference in the Tobit censored regression model," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 79-99.
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Cited by:
  1. Carpenter, Seth & Demiralp, Selva & Eisenschmidt, Jens, 2014. "The effectiveness of non-standard monetary policy in addressing liquidity risk during the financial crisis: The experiences of the Federal Reserve and the European Central Bank," Journal of Economic Dynamics and Control, Elsevier, vol. 43(C), pages 107-129.
  2. Torsten Schmidt & Lina Zwick, 2012. "In Search for a Credit Crunch in Germany," Ruhr Economic Papers 0361, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
  3. Claessens, Stijn & Sakho, Yaye Seynabou, 2013. "Assessing firms'financing constraints in Brazil," Policy Research Working Paper Series 6624, The World Bank.

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