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Dating Business Cycle Turning Points

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Author Info
Marcelle Chauvet
James D. Hamilton

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Abstract

This paper discusses formal quantitative algorithms that can be used to identify business cycle turning points. An intuitive, graphical derivation of these algorithms is presented along with a description of how they can be implemented making very minimal distributional assumptions. We also provide the intuition and detailed description of these algorithms for both simple parametric univariate inference as well as latent-variable multiple-indicator inference using a state-space Markov-switching approach. We illustrate the promise of this approach by reconstructing the inferences that would have been generated if parameters had to be estimated and inferences drawn based on data as they were originally released at each historical date. Waiting until one extra quarter of GDP growth is reported or one extra month of the monthly indicators released before making a call of a business cycle turning point helps reduce the risk of misclassification. We introduce two new measures for dating business cycle turning points, which we call the %u201Cquarterly real-time GDP-based recession probability index%u201D and the %u201Cmonthly real-time multiple-indicator recession probability index%u201D that incorporate these principles. Both indexes perform quite well in simulation with real-time data bases. We also discuss some of the potential complicating factors one might want to consider for such an analysis, such as the reduced volatility of output growth rates since 1984 and the changing cyclical behavior of employment. Although such refinements can improve the inference, we nevertheless find that the simpler specifications perform very well historically and may be more robust for recognizing future business cycle turning points of unknown character.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 11422.

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Date of creation: Jun 2005
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Handle: RePEc:nbr:nberwo:11422

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E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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References listed on IDEAS
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    Other versions:
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  5. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November. [Downloadable!] (restricted)
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  8. 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. [Downloadable!] (restricted)
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  10. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22. [Downloadable!] (restricted)
  11. 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.
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    Other versions:
  13. Chinhui Juhn & Simon Potter, 1999. "Explaining the recent divergence in payroll and household employment growth," Current Issues in Economics and Finance, Federal Reserve Bank of New York, issue Dec. [Downloadable!]
  14. 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. [Downloadable!] (restricted)
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Cited by:
(explanations, 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.)

  1. McKay, Alisdair & Reis, Ricardo, 2006. "The Brevity and Violence of Contractions and Expansions," CEPR Discussion Papers 5756, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  2. Darné, O. & Ferrara, L., 2009. "Identification of slowdowns and accelerations for the euro area economy," Documents de Travail 239, Banque de France. [Downloadable!]
  3. Frédérick Demers & Ryan Macdonald, 2007. "The Canadian Business Cycle: A Comparison of Models," Working Papers 07-38, Bank of Canada. [Downloadable!]
  4. Minakshy Iyer, 2006. "An Index of Uncertainty for Business Cycle Leading Indicators," Working Papers id:751, esocialsciences.com. [Downloadable!]
  5. Troy Davig, 2008. "Detecting recessions in the Great Moderation: a real-time analysis," Economic Review, Federal Reserve Bank of Kansas City, issue Q IV, pages 5-33. [Downloadable!]
  6. Marcelle, Chauvet & Simon, Potter, 2007. "Monitoring Business Cycles with Structural Breaks," MPRA Paper 15097, University Library of Munich, Germany, revised 31 Apr 2009. [Downloadable!]
  7. Willem Boshoff, 2005. "The properties of cycles in South African financial variables and their relation to the business cycle," Working Papers 02/2005, Stellenbosch University, Department of Economics. [Downloadable!]
  8. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators Under Real-Time Conditions," Kiel Working Papers 1397, Kiel Institute for the World Economy. [Downloadable!]
    Other versions:
  9. Michael J. Dueker & Martin Sola, 2008. "Multivariate Markov switching with weighted regime determination: giving France more weight than Finland," Working Papers 2008-001, Federal Reserve Bank of St. Louis. [Downloadable!]
  10. Jeremy J. Nalewaik, 2006. "Estimating probabilities of recession in real time using GDP and GDI," Finance and Economics Discussion Series 2007-07, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  11. Edward E. Leamer, 2008. "What's a Recession, Anyway?," NBER Working Papers 14221, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  12. David N. DeJong & Hariharan Dharmarajan & Roman Liesenfeld & Jean-Francois Richard, 2008. "Exploiting Non-Linearities in GDP Growth for Forecasting and Anticipating Regime Changes," Working Papers 367, University of Pittsburgh, Department of Economics, revised Sep 2008. [Downloadable!]
  13. Munechika Katayama, . "Declining Effects of Oil-Price Shocks," Departmental Working Papers 2009-02, Department of Economics, Louisiana State University. [Downloadable!]
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