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Identifying and Forecasting the Turning Points of the Belgian Business Cycle with Regime-Switching and Logit Models

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Author Info

  • Vincent, BODART

    (UNIVERSITE CATHOLIQUE DE LOUVAIN, Department of Economics)

  • Konstantin, KHOLODILIN
  • Fati, SHADMAN-MEHTA

    (UNIVERSITE CATHOLIQUE DE LOUVAIN, Department of Economics)

Abstract

This paper seeks to elaborate econometric models that can be used to forecast the turning points of the Belgian business cycle. We begin by suggesting three reference cycle, which we hope will fill the void of an official reference chronology for Belgium. We then construct two different types of model to estimate the probabilities of recession : Markov-switching models, and Logit models. We apply each approach to a limited set of data, which are a good representation of the economy, are available early and are subject to only minor revisions. We then select the best performing model for each chronology and type of approach. The out-of-sample results show that the models provide useful indicators of business cycle turning points. They are however far from perfect forecasting tools, especially when it comes to forecasting periods of classical recession.

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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 2005006.

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Length: 40
Date of creation: 01 Mar 2005
Date of revision:
Handle: RePEc:ctl:louvec:2005006

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Related research

Keywords: Refrence chronologies; Markov-Switching and Logit models; forecasting business cycle turning points;

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References

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  1. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-96, November.
  2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  3. Diebold & Rudebusch, . "Measuring Business Cycle: A Modern Perspective," Home Pages _061, University of Pennsylvania.
  4. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 95-156 National Bureau of Economic Research, Inc.
  5. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
  6. Marcelle Chauvet & Jeremy Piger, 2002. "Identifying business cycle turning points in real time," Working Paper 2002-27, Federal Reserve Bank of Atlanta.
  7. Arturo Estrella & Frederic S. Mishkin, 1996. "Predicting U.S. recessions: financial variables as leading indicators," Research Paper 9609, Federal Reserve Bank of New York.
  8. Francis X. Diebold & Glenn D. Rudebusch, 1987. "Scoring the leading indicators," Special Studies Papers 206, Board of Governors of the Federal Reserve System (U.S.).
  9. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  10. Kim, C-J., 1991. "Dynamic Linear Models with Markov-Switching," Papers 91-8, York (Canada) - Department of Economics.
  11. Allan P. Layton & Anirvan Banerji, 2001. "What Is A Recession?: A Reprise," School of Economics and Finance Discussion Papers and Working Papers Series 095, School of Economics and Finance, Queensland University of Technology.
  12. Harding, Don & Pagan, Adrian, 2001. "Extracting, Using and Analysing Cyclical Information," MPRA Paper 15, University Library of Munich, Germany.
  13. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, July.
  14. Bertrand Candelon & Vincent Bodart, 2000. "Appréhender la conjoncture à l'aide de la méthode de Stock-Watson : une application à l'économie belge," Économie et Prévision, Programme National Persée, vol. 146(5), pages 141-153.
  15. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
  16. Layton, Allan P. & Katsuura, Masaki, 2001. "Comparison of regime switching, probit and logit models in dating and forecasting US business cycles," International Journal of Forecasting, Elsevier, vol. 17(3), pages 403-417.
  17. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
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Cited by:
  1. Bruno, Giancarlo & Otranto, Edoardo, 2008. "Models to date the business cycle: The Italian case," Economic Modelling, Elsevier, vol. 25(5), pages 899-911, September.

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