IDEAS home Printed from https://ideas.repec.org/p/cor/louvrp/1918.html
   My bibliography  Save this paper

Bayesian inference in dynamic disequilibrium models: an application to the Polish credit market

Author

Listed:
  • BAUWENS, Luc
  • LUBRANO, Michel

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).
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • BAUWENS, Luc & LUBRANO, Michel, 2007. "Bayesian inference in dynamic disequilibrium models: an application to the Polish credit market," LIDAM Reprints CORE 1918, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:1918
    DOI: 10.1080/07474930701220634
    Note: In : Econometric Reviews, 26(2-4), 469-486, 2007
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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 261-278, July.
    2. Lee, Lung-Fei, 1997. "A smooth likelihood simulator for dynamic disequilibrium models," Journal of Econometrics, Elsevier, vol. 78(2), pages 257-294, June.
    3. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    4. 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.
    5. Mr. Adolfo Barajas & Mr. Roberto Steiner, 2002. "Credit Stagnation in Latin America," IMF Working Papers 2002/053, International Monetary Fund.
    6. repec:dau:papers:123456789/3410 is not listed on IDEAS
    7. Ikhide, Sylvanus, 2003. "Was There a Credit Crunch in Namibia Between 1996-2000?," Journal of Applied Economics, Universidad del CEMA, vol. 6(2), pages 1-22, November.
    8. Steven Wei, 1999. "A bayesian approach to dynamic tobit models," Econometric Reviews, Taylor & Francis Journals, vol. 18(4), pages 417-439.
    9. 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.
    10. 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.
    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. 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.
    13. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    14. 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.
    15. 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.
    16. 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.
    17. James Tobin, 1956. "Estimation of Relationships for Limited Dependent Variables," Cowles Foundation Discussion Papers 3R, Cowles Foundation for Research in Economics, Yale University.
    18. 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, October.
    19. Laffont, Jean-Jacques & Garcia, Rene, 1977. "Disequilibrium Econometrics for Business Loans," Econometrica, Econometric Society, vol. 45(5), pages 1187-1204, July.
    20. GINSBURGH, Victor & TISHLER, Asher & ZANG, Israel, 1980. "Alternative estimation methods for two-regime models," LIDAM Reprints CORE 393, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    21. Aurora Manrique & Neil Shephard, 1998. "Simulation-based likelihood inference for limited dependent processes," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 174-202.
    22. 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.
    23. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139.
    24. Lee, Lung-fei, 1999. "Estimation of dynamic and ARCH Tobit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 355-390, October.
    25. Dagenais, Marcel G., 1982. "The Tobit model with serial correlation," Economics Letters, Elsevier, vol. 10(3-4), pages 263-267.
    26. Chib, Siddhartha, 1992. "Bayes inference in the Tobit censored regression model," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 79-99.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. repec:zbw:rwirep:0361 is not listed on IDEAS
    3. Aloysius Deno Hervino, 2011. "Avoiding risk in working capital credit distribution in Indonesia," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 3(2), pages 199-210, April.
    4. Paolo Del Giovane & Andrea Nobili & Federico M. Signoretti, 2017. "Assessing the Sources of Credit Supply Tightening: Was the Sovereign Debt Crisis Different from Lehman?," International Journal of Central Banking, International Journal of Central Banking, vol. 13(2), pages 197-234, June.
    5. Karmelavičius, Jaunius & Mikaliūnaitė-Jouvanceau, Ieva & Petrokaitė, Austėja Petrokaitė, 2022. "Housing and credit misalignments in a two-market disequilibrium framework," ESRB Working Paper Series 135, European Systemic Risk Board.
    6. 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.
    7. Baird, Matthew & Daugherty, Lindsay & Kumar, Krishna B., 2019. "Improving Estimation of Labor Market Disequilibrium Using Shortage Indicators, with an Application to the Market for Anesthesiologists," IZA Discussion Papers 12129, Institute of Labor Economics (IZA).
    8. 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.
    9. 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, Department of Economics.
    10. Tamini, Arnaud & Petey, Joël, 2021. "Hoarding of reserves in the banking industry: Explaining the African paradox," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 214-225.
    11. Matthew Baird & Lindsay Daugherty & Krishna Kumar, 2017. "Improving Estimation of Labor Market Disequilibrium through Inclusion of Shortage Indicators," CINCH Working Paper Series 1701, Universitaet Duisburg-Essen, Competent in Competition and Health.
    12. 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.
    13. Vouldis, Angelos, 2015. "Credit market disequilibrium in Greece (2003-2011) - a Bayesian approach," Working Paper Series 1805, European Central Bank.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:zbw:rwirep:0361 is not listed on IDEAS
    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. 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.
    4. Poghosyan, Tigran, 2011. "Slowdown of credit flows in Jordan in the wake of the global financial crisis: Supply or demand driven?," Economic Systems, Elsevier, vol. 35(4), pages 562-573.
    5. Edwige Burdeau, 2015. "Assessing dynamics of credit supply and demand for French SMEs, an estimation based on the Bank Lending Survey," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Indicators to support monetary and financial stability analysis: data sources and statistical methodologies, volume 39, Bank for International Settlements.
    6. Xi, Yanhui & Peng, Hui & Qin, Yemei & Xie, Wenbiao & Chen, Xiaohong, 2015. "Bayesian analysis of heavy-tailed market microstructure model and its application in stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 117(C), pages 141-153.
    7. Adolfo Barajas & Enrique López & Hugo Oliveros, 2001. "¿Por qué en Colombia el Crédito al Sector Privado es tan Reducido," Borradores de Economia 185, Banco de la Republica de Colombia.
    8. Hurlin, Christophe & Kierzenkowski, Rafal, 2007. "Credit market disequilibrium in Poland: Can we find what we expect?: Non-stationarity and the short-side rule," Economic Systems, Elsevier, vol. 31(2), pages 157-183, June.
    9. Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 852-862, January.
    10. Aknouche, Abdelhakim, 2013. "Periodic autoregressive stochastic volatility," MPRA Paper 69571, University Library of Munich, Germany, revised 2015.
    11. Karmelavičius, Jaunius & Mikaliūnaitė-Jouvanceau, Ieva & Petrokaitė, Austėja Petrokaitė, 2022. "Housing and credit misalignments in a two-market disequilibrium framework," ESRB Working Paper Series 135, European Systemic Risk Board.
    12. Jun Yu & Renate Meyer, 2006. "Multivariate Stochastic Volatility Models: Bayesian Estimation and Model Comparison," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 361-384.
    13. Yu, Jun, 2005. "On leverage in a stochastic volatility model," Journal of Econometrics, Elsevier, vol. 127(2), pages 165-178, August.
    14. Jameel Ahmed, 2016. "Credit Conditions in Pakistan: Supply Constraints or Demand Deficiencies?," The Developing Economies, Institute of Developing Economies, vol. 54(2), pages 139-161, June.
    15. Vo, Minh, 2011. "Oil and stock market volatility: A multivariate stochastic volatility perspective," Energy Economics, Elsevier, vol. 33(5), pages 956-965, September.
    16. Huang, Shirley J. & Yu, Jun, 2010. "Bayesian analysis of structural credit risk models with microstructure noises," Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2259-2272, November.
    17. Abdelhakim Aknouche, 2017. "Periodic autoregressive stochastic volatility," Statistical Inference for Stochastic Processes, Springer, vol. 20(2), pages 139-177, July.
    18. Wang, Joanna J.J., 2012. "On asymmetric generalised t stochastic volatility models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(11), pages 2079-2095.
    19. Avouyi-Dovi, S. & Horny, G. & Sevestre, P., 2017. "The stability of short-term interest rates pass-through in the euro area during the financial market and sovereign debt crises," Journal of Banking & Finance, Elsevier, vol. 79(C), pages 74-94.
    20. Yu, Jun & Yang, Zhenlin & Zhang, Xibin, 2006. "A class of nonlinear stochastic volatility models and its implications for pricing currency options," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2218-2231, December.
    21. Ding, Liang & Vo, Minh, 2012. "Exchange rates and oil prices: A multivariate stochastic volatility analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 15-37.

    More about this item

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cor:louvrp:1918. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Alain GILLIS (email available below). General contact details of provider: https://edirc.repec.org/data/coreebe.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.