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Identifying business cycle turning points in real time

  • Marcelle Chauvet
  • Jeremy 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 Markov-switching models of real GDP and employment that, when estimated on the entire post-war sample, provide a chronology of business cycle peak and trough dates very close to that produced by the National Bureau of Economic Research (NBER). Next, they investigate how accurately and quickly the models would have identified turning points had they been used in real-time for the past forty years. In general, the models identify turning point dates in real-time that are close to the NBER dates. For both business cycle peaks and troughs, the models provide systematic improvement over the NBER in the speed at which turning points are identified. Importantly, the models achieve 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. The model appears to capture the features of the NBER chronology in an accurate, timely way, and does so in a transparent and consistent fashion.

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Paper provided by Federal Reserve Bank of Atlanta in its series Working Paper with number 2002-27.

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Date of creation: 2002
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Handle: RePEc:fip:fedawp:2002-27
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  1. Beaudry, Paul & Koop, Gary, 1993. "Do recessions permanently change output?," Journal of Monetary Economics, Elsevier, vol. 31(2), pages 149-163, April.
  2. Layton, Allan P., 1996. "Dating and predicting phase changes in the U.S. business cycle," International Journal of Forecasting, Elsevier, vol. 12(3), pages 417-428, September.
  3. Kim, C-J & Nelson, C-R, 1997. "Friedman's Plucking Model of Business Fluctuations : Tests and Estimates of Permanent and Transitory Components," Discussion Papers in Economics at the University of Washington 97-06, Department of Economics at the University of Washington.
  4. 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.
  5. 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.
  6. 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.
  7. Francis X. Diebold & Glenn D. Rudebusch, 1994. "Measuring Business Cycles: A Modern Perspective," NBER Working Papers 4643, National Bureau of Economic Research, Inc.
  8. Margaret M. McConnell, 1998. "Rethinking the value of initial claims as a forecasting tool," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 4(Nov).
  9. 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.
  10. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
  11. Boldin, Michael D, 1994. "Dating Turning Points in the Business Cycle," The Journal of Business, University of Chicago Press, vol. 67(1), pages 97-131, January.
  12. Friedman, Milton, 1993. "The "Plucking Model" of Business Fluctuations Revisited," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 171-77, April.
  13. 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.
  14. William T. Gavin & Kevin L. Kliesen, 2002. "Unemployment insurance claims and economic activity," Review, Federal Reserve Bank of St. Louis, issue May, pages 15-28.
  15. 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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