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

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  • Luc Bauwens
  • Michel Lubrano

Abstract

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).

Suggested Citation

  • Luc Bauwens & Michel Lubrano, 2007. "Bayesian Inference in Dynamic Disequilibrium Models: An Application to the Polish Credit Market," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 469-486.
  • Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:469-486
    DOI: 10.1080/07474930701220634
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    References listed on IDEAS

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    1. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-1030, November.
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    3. Sylvanus Ikhide, 2003. "Was There a Credit Crunch in Namibia Between 1996-2000?," Journal of Applied Economics, Universidad del CEMA, vol. 6, pages 269-290, November.
    4. 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.
    5. Christophe Hurlin & Rafal Kierzenkowski, 2002. "A Theoretical and Empirical Assessment of the Bank Lending Channel and Loan Market Disequilibrium in Poland," NBP Working Papers 22, Narodowy Bank Polski, Economic Research Department.
    6. 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 119-133, Suppl. De.
    7. Adolfo Barajas & Roberto Steiner, 2002. "Credit Stagnation in Latin America," IMF Working Papers 02/53, International Monetary Fund.
    8. 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.
    9. Laffont, Jean-Jacques & Garcia, Rene, 1977. "Disequilibrium Econometrics for Business Loans," Econometrica, Econometric Society, vol. 45(5), pages 1187-1204, July.
    10. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139.
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    17. Christophe Hurlin & Rafal Kierzenkowski, 2003. "Credit Market Disequilibrium in Poland: Can We Find What We Expect? Non-Stationarity and the ???Min???Condition," William Davidson Institute Working Papers Series 2003-581, William Davidson Institute at the University of Michigan.
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    19. Ginsburgh, Victor & Tishler, Asher & Zang, Israel, 1980. "Alternative estimation methods for two-regime models : A mathematical programming approach," European Economic Review, Elsevier, vol. 13(2), pages 207-228, March.
    20. 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 107-120, January.
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    Citations

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    Cited by:

    1. Claessens, Stijn & Sakho, Yaye Seynabou, 2013. "Assessing firms'financing constraints in Brazil," Policy Research Working Paper Series 6624, The World Bank.
    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. Vouldis, Angelos, 2015. "Credit market disequilibrium in Greece (2003-2011) - a Bayesian approach," Working Paper Series 1805, European Central Bank.
    4. repec:zbw:rwirep:0361 is not listed on IDEAS
    5. 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.
    6. Bofinger, Peter & Maas, Daniel & Ries, Mathias, 2017. "A model of the market for bank credit: The case of Germany," W.E.P. - Würzburg Economic Papers 98, University of Würzburg, Chair for Monetary Policy and International Economics.
    7. Schmidt, Torsten & Zwick, Lina, 2012. "In Search for a Credit Crunch in Germany," Ruhr Economic Papers 361, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

    More about this item

    Keywords

    Bayesian inference; Credit rationing; Data augmentation; Disequilibrium model; Latent variables; Poland;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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