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Identifying business cycle turning points in real time

  • Marcelle Chauvet
  • Jeremy M. Piger

This paper evaluates the ability of a statistical regime-switching model to identify turning points in U.S. economic activity in real time. The authors work with a Markov-switching model fit to real gross domestic product and employment data that, when estimated on the entire postwar sample, provides a chronology of business cycle peak and trough dates close to that produced by the National Bureau of Economic Research (NBER). Next, they investigate how accurately and quickly the model would have identified NBER-dated turning points had it been used in real time for the past 40 years. In general, the model identifies turning point dates in real time that are close to the NBER dates. For both business cycle peaks and troughs, the model provides systematic improvement over the NBER in the speed at which turning points are identified. Importantly, the model achieves this with few instances of “false positives.” Overall, the evidence suggests that the regime-switching model could be a useful supplement to the NBER Business Cycle Dating Committee for establishing turning point dates. It appears to capture the features of the NBER chronology accurately and swiftly; furthermore, the method is transparent and consistent.

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Article provided by Federal Reserve Bank of St. Louis in its journal Review.

Volume (Year): (2003)
Issue (Month): Mar ()
Pages: 47-61

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Handle: RePEc:fip:fedlrv:y:2003:i:mar:p:47-61:n:v.85no.2
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  1. Kim, C-J & Nelson, C-R, 1997. "Friedman's Plucking Model of Business Fluctuations : Tests and Estimates of Permanent and Transitory Components," Working Papers 97-06, University of Washington, Department of Economics.
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  8. Jeremy Piger & James Morley & Chang-Jin Kim, 2005. "Nonlinearity and the permanent effects of recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 291-309.
  9. 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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  11. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S61-82, Suppl. De.
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  15. 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, June.
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