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Une lecture probabiliste du cycle d’affaires américain

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Author Info

  • Benoit Bellone

    (Direction de la prévision et de l'analyse économique)

Abstract

This paper explores 35 years of the American business cycle with the Hidden Markov Model (HMM) as a monitoring tool using monthly data. It exhibits ten US time series, which offer reliable information to detect recessions in real time. It also assesses the performances of different and complementary “recession models” based on Markovian processes : the “Pooled data model” and a multivariate HMM, and draws two main conclusions: simple HMM are decisive to monitor the business cycle providing that the series are proved highly reliable; models adding a multivariate dimension are useful but work marginally better than a simple summary : the inner quality of series seem to dominate their modeling. This paper introduces a new reading of the business cycle through, a favored recession model and concludes about leading and “real time detection” limitations. This paper is written in French.

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File URL: http://128.118.178.162/eps/em/papers/0407/0407002.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 0407002.

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Length: 37 pages
Date of creation: 04 Jul 2004
Date of revision: 28 Mar 2005
Handle: RePEc:wpa:wuwpem:0407002

Note: Type of Document - pdf; pages: 37. This paper introduces two new business cycle stochastic indicator of the US economy, with a foolproof recession index.
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Web page: http://128.118.178.162

Related research

Keywords: Business Cycle; Markov Switching; MSVAR; Real time data vintage; Coincident Indicators; Recession; NBER dating;

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References

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  1. Dominique Ladiray, 2002. "Conjoncture, statistique et économétrie," Économie et Statistique, Programme National Persée, vol. 359(1), pages 3-12.
  2. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
  3. Francis X. Diebold & Glenn D. Rudebusch, 1994. "Measuring Business Cycles: A Modern Perspective," NBER Working Papers 4643, National Bureau of Economic Research, Inc.
  4. Eva Andersson & David Bock & Marianne Frisén, 2004. "Detection of Turning Points in Business Cycles," Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2004(1), pages 93-108.
  5. Benoit Bellone & David Saint-Martin, 2004. "Detecting Turning Points with Many Predictors through Hidden Markov Models," Econometrics 0407001, EconWPA.
  6. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
  7. Krolzig, Hans-Martin & Hendry, David F., 2001. "Computer automation of general-to-specific model selection procedures," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 831-866, June.
  8. Marcelle Chauvet & Jeremy Piger, 2002. "Identifying business cycle turning points in real time," Working Paper 2002-27, Federal Reserve Bank of Atlanta.
  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. Ferrara, Laurent, 2003. "A three-regime real-time indicator for the US economy," Economics Letters, Elsevier, vol. 81(3), pages 373-378, December.
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  12. Harding, Don & Pagan, Adrian, 2003. "A comparison of two business cycle dating methods," Journal of Economic Dynamics and Control, Elsevier, vol. 27(9), pages 1681-1690, July.
  13. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
  14. Anas, Jacques & Ferrara, Laurent, 2002. "Un indicateur d'entrée et sortie de récession: application aux Etats-Unis
    [A start-end recession index: Application for United-States]
    ," MPRA Paper 4043, University Library of Munich, Germany.
  15. Christophe Croux & Mario Forni & Lucrezia Reichlin, 2001. "A Measure Of Comovement For Economic Variables: Theory And Empirics," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 232-241, May.
  16. Andrew J. Filardo, 1999. "How reliable are recession prediction models?," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 35-55.
  17. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
  18. 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.
  19. Nicolas Chopin, 2001. "Sequential Inference and State Number Determination for Discrete State-Space Models through Particle Filtering," Working Papers 2001-34, Centre de Recherche en Economie et Statistique.
  20. Stéphane Grégoir & Fabrice Lenglart, 1998. "Measuring the Probability of a Business Cycle Turning Point by Using a Multivariate Qualitative Hidden Markov Model," Working Papers 98-48, Centre de Recherche en Economie et Statistique.
  21. 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.
  22. Peter Reinhard Hansen, 2001. "An Unbiased and Powerful Test for Superior Predictive Ability," Working Papers 2001-06, Brown University, Department of Economics.
  23. 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.
  24. James H. Stock & Mark W. Watson, 1992. "A Procedure for Predicting Recessions With Leading Indicators: Econometric Issues and Recent Experience," NBER Working Papers 4014, National Bureau of Economic Research, Inc.
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Cited by:
  1. Benoit Bellone, 2004. "MSVARlib: a new Gauss library to estimate multivariate Hidden Markov Models," Econometrics 0406004, EconWPA.

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