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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.
Contact details of provider:
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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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  1. Marcelle Chauvet & Jeremy M. Piger, 2003. "Identifying business cycle turning points in real time," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 47-61.
  2. 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.
  3. 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.
  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. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  6. 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.
  7. Ferrara, Laurent, 2003. "A three-regime real-time indicator for the US economy," Economics Letters, Elsevier, vol. 81(3), pages 373-378, December.
  8. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  9. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
  10. 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.
  11. Francis X. Diebold & Glenn D. Rudebusch, 1994. "Measuring Business Cycles: A Modern Perspective," NBER Working Papers 4643, National Bureau of Economic Research, Inc.
  12. 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, May.
  13. Christophe Croux & Mario Forni & Lucrezia Reichlin, 2001. "A measure of co-movement for economic variables: theory and empirics," ULB Institutional Repository 2013/10139, ULB -- Universite Libre de Bruxelles.
  14. 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.
  15. Dominique Ladiray, 2002. "Conjoncture, statistique et économétrie," Économie et Statistique, Programme National Persée, vol. 359(1), pages 3-12.
  16. 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.
  17. Andrew J. Filardo, 1999. "How reliable are recession prediction models?," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 35-55.
  18. 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.
  19. Peter Reinhard Hansen, 2001. "An Unbiased and Powerful Test for Superior Predictive Ability," Working Papers 2001-06, Brown University, Department of Economics.
  20. 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.
  21. Benoit Bellone & David Saint-Martin, 2004. "Detecting Turning Points with Many Predictors through Hidden Markov Models," Econometrics 0407001, EconWPA.
  22. 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.
  23. 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.
  24. 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.
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Citations

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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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