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Identifying business cycle turning points in real time

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Author Info
Marcelle Chauvet
Jeremy M. Piger

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Abstract

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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Keywords: Forecasting ; Economic conditions ; Business cycles;

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References listed on IDEAS
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. 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. [Downloadable!] (restricted)
  2. Boldin, Michael D, 1994. "Dating Turning Points in the Business Cycle," Journal of Business, University of Chicago Press, vol. 67(1), pages 97-131, January. [Downloadable!] (restricted)
  3. 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.
  4. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February. [Downloadable!] (restricted)
    Other versions:
  5. 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)
  6. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November. [Downloadable!] (restricted)
    Other versions:
  7. 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.
  8. Kim, Chang-Jin & Nelson, Charles R, 1999. "Friedman's Plucking Model of Business Fluctuations: Tests and Estimates of Permanent and Transitory Components," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 31(3), pages 317-34, August.
  9. Beaudry, Paul & Koop, Gary, 1993. "Do recessions permanently change output?," Journal of Monetary Economics, Elsevier, vol. 31(2), pages 149-163, April. [Downloadable!] (restricted)
  10. 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, issue Nov. [Downloadable!]
  11. Friedman, Milton, 1993. "The "Plucking Model" of Business Fluctuations Revisited," Economic Inquiry, Oxford University Press, vol. 31(2), pages 171-77, April.
  12. 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. [Downloadable!]
  13. Chang-Jin Kim & James Morley & Jeremy Piger, 2003. "Nonlinearity and the permanent effects of recessions," Working Papers 2002-014, Federal Reserve Bank of St. Louis. [Downloadable!]
    Other versions:
Full references

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. Harm Bandholz & Michael Funke, 2003. "Die Konstruktion und Schätzung eines Frühindikators für die Konjunkturentwicklung in der Freien und Hansestadt Hamburg," Quantitative Macroeconomics Working Papers 20305, Hamburg University, Department of Economics. [Downloadable!]
  2. Benoit Bellone, 2004. "Une lecture probabiliste du cycle d’affaires américain," Econometrics 0407002, EconWPA, revised 28 Mar 2005. [Downloadable!]
  3. Adanero-Donderis , M. & Darné, O. & Ferrara, L., 2007. "Deux indicateurs probabilistes de retournement cyclique pour l’économie française," Documents de Travail 187, Banque de France. [Downloadable!]
  4. Don Harding & Adrian Pagan, 2006. "Measurement of Business Cycles," Department of Economics - Working Papers Series 966, The University of Melbourne. [Downloadable!]
  5. Viv B. Hall & C. John McDermott, 2006. "The New Zealand Business Cycle: Return To Golden Days?," CAMA Working Papers 2006-21, Australian National University, Centre for Applied Macroeconomic Analysis. [Downloadable!]
  6. Ferrara, Laurent & Guégan, Dominique, 2005. "Detection of the industrial business cycle using SETAR models," MPRA Paper 4389, University Library of Munich, Germany. [Downloadable!]
    Other versions:
  7. Vincent, BODART & Konstantin, KHOLODILIN & Fati, SHADMAN-MEHTA, 2005. "Identifying and Forecasting the Turning Points of the Belgian Business Cycle with Regime-Switching and Logit Models," Discussion Papers (ECON - Département des Sciences Economiques) 2005006, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
  8. Kevin L. Kliesen, 2003. "The 2001 recession: how was it different and what developments may have caused it?," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 23-38. [Downloadable!]
  9. Ana Beatriz C. Galvao, 2006. "Structural break threshold VARs for predicting US recessions using the spread," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 463-487. [Downloadable!]
    Other versions:
  10. Benoit Bellone, 2004. "MSVARlib: a new Gauss library to estimate multivariate Hidden Markov Models," Econometrics 0406004, EconWPA. [Downloadable!]
  11. Michael T. Owyang & Jeremy M. Piger & Howard J. Wall, 2004. "Business cycle phases in U.S. states," Working Papers 2003-011, Federal Reserve Bank of St. Louis. [Downloadable!]
    Other versions:
  12. Darné, O. & Ferrara, L., 2009. "Identification of slowdowns and accelerations for the euro area economy," Documents de Travail 239, Banque de France. [Downloadable!]
  13. Michael T. Owyang & Jeremy M. Piger & Howard J. Wall, 2005. "The 2001 recession and the states of the Eighth Federal Reserve District," Regional Economic Development, Federal Reserve Bank of St. Louis, issue Nov, pages 3-16. [Downloadable!]
    Other versions:
  14. Ferrara, Laurent, 2006. "A real-time recession indicator for the Euro area," MPRA Paper 4042, University Library of Munich, Germany. [Downloadable!]
  15. Marcelle Chauvet & Jeremy M. Piger, 2005. "A comparison of the real-time performance of business cycle dating methods," Working Papers 2005-021, Federal Reserve Bank of St. Louis. [Downloadable!]
    Other versions:
  16. Benoit Bellone & David Saint-Martin, 2004. "Detecting Turning Points with Many Predictors through Hidden Markov Models," Econometrics 0407001, EconWPA. [Downloadable!]
  17. 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!]
  18. Vincent, BODART & Konstantin A., KHOLODILIN & Fati, SHADMAN-MEHTA, 2003. "Dating and Forecasting the Belgian Business Cycle," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2003018, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES). [Downloadable!]
  19. Dean Croushore, 2008. "Frontiers of real-time data analysis," Working Papers 08-4, Federal Reserve Bank of Philadelphia. [Downloadable!]
  20. Döpke, Jörg, 2004. "Real-time data and business cycle analysis in Germany," Discussion Paper Series 1: Economic Studies 2004,11, Deutsche Bundesbank, Research Centre. [Downloadable!]
  21. James Morley & Jeremy M. Piger, 2005. "The importance of nonlinearity in reproducing business cycle features," Working Papers 2004-032, Federal Reserve Bank of St. Louis. [Downloadable!]
  22. Konstantin A. Kholodilin, 2005. "Forecasting the Turns of German Business Cycle: Dynamic Bi-factor Model with Markov Switching," Discussion Papers of DIW Berlin 494, DIW Berlin, German Institute for Economic Research. [Downloadable!]
  23. Monica Billio & Roberto Casarin, 2008. "Identifying Business Cycle Turning Points with Sequential Monte Carlo Methods," Working Papers 0815, University of Brescia, Department of Economics. [Downloadable!]
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This page was last updated on 2009-11-18.

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