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How reliable are recession prediction models?

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  • Andrew J. Filardo

Abstract

The U.S. economy continues to advance briskly, defying forecasts of more moderate growth. Beginning in March 1991, the current expansion has become the longest peacetime expansion on record and is less than a year away from becoming the longest in U.S. history. To the surprise of some observers, economic growth has been particularly robust late in the expansion. In fact, over the last three years growth has averaged 4 percent annually, and indicators of growth for the first half of 1999 show no signs of significant slowing.> Despite these positive signs, few analysts believe the expansion can go on forever. As the expansion continues to age, economists will increasingly be called on to predict the next recession. Recession prediction models may help them gauge the likelihood of imminent recession.> Filardo examines the reliability of five popular recession prediction models. He concludes that these models have demonstrated some ability in the past to predict recessions. When judiciously interpreted, the models can help resolve uncertainty about the possibility of future recession.

Suggested Citation

  • Andrew J. Filardo, 1999. "How reliable are recession prediction models?," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 35-55.
  • Handle: RePEc:fip:fedker:y:1999:i:qii:p:35-55:n:v.84no.2
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    1. Victor Zarnowitz & Phillip Braun, 1993. "Twenty-two Years of the NBER-ASA Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance," NBER Chapters,in: Business Cycles, Indicators and Forecasting, pages 11-94 National Bureau of Economic Research, Inc.
    2. Victor Zarnowitz, 1992. "Business Cycles: Theory, History, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number zarn92-1, June.
    3. Geoffrey H. Moore, 1983. "Business Cycles, Inflation, and Forecasting, 2nd edition," NBER Books, National Bureau of Economic Research, Inc, number moor83-1, June.
    4. Geoffrey H. Moore, 1983. "Introductory pages to "Business Cycles, Inflation, and Forecasting, 2nd edition"," NBER Chapters,in: Business Cycles, Inflation, and Forecasting, 2nd edition, pages -25 National Bureau of Economic Research, Inc.
    5. Kling, John L, 1987. "Predicting the Turning Points of Business and Economic Time Series," The Journal of Business, University of Chicago Press, vol. 60(2), pages 201-238, April.
    6. Wecker, William E, 1979. "Predicting the Turning Points of a Time Series," The Journal of Business, University of Chicago Press, vol. 52(1), pages 35-50, January.
    7. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters,in: Business Cycles, Indicators and Forecasting, pages 95-156 National Bureau of Economic Research, Inc.
    8. Geoffrey H. Moore, 1983. "Appendices to "Business Cycles, Inflation, and Forecasting, 2nd edition"," NBER Chapters,in: Business Cycles, Inflation, and Forecasting, 2nd edition, pages 453-473 National Bureau of Economic Research, Inc.
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    Cited by:

    1. Sergey V. Smirnov & Nikolai V. Kondrashov & Anna V. Petronevich, 2016. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," HSE Working papers WP BRP 122/EC/2016, National Research University Higher School of Economics.
    2. Österholm, Pär, 2012. "The limited usefulness of macroeconomic Bayesian VARs when estimating the probability of a US recession," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 76-86.
    3. McNown, Robert & Seip, Knut Lehre, 2011. "Periods and structural breaks in US economic history 1959-2007," Journal of Policy Modeling, Elsevier, vol. 33(2), pages 169-182, March.
    4. Qi, Min, 2001. "Predicting US recessions with leading indicators via neural network models," International Journal of Forecasting, Elsevier, vol. 17(3), pages 383-401.
    5. Kajal Lahiri & J. George Wang, 2007. "The value of probability forecasts as predictors of cyclical downturns," Applied Economics Letters, Taylor & Francis Journals, vol. 14(1), pages 11-14.
    6. Khurshid Kiani, 2011. "Fluctuations in Economic and Activity and Stabilization Policies in the CIS," Computational Economics, Springer;Society for Computational Economics, vol. 37(2), pages 193-220, February.
    7. Benoit Bellone, 2004. "Une lecture probabiliste du cycle d’affaires américain," Econometrics 0407002, EconWPA, revised 28 Mar 2005.
    8. Mili, Mehdi & Sahut, Jean-Michel & Teulon, Frédéric, 2012. "Non linear and asymmetric linkages between real growth in the Euro area and global financial market conditions: New evidence," Economic Modelling, Elsevier, vol. 29(3), pages 734-741.
    9. Maximo Camacho & Gabriel Perez-Quiros, 2002. "This is what the leading indicators lead," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(1), pages 61-80.
    10. Ahrens, R., 2002. "Predicting recessions with interest rate spreads: a multicountry regime-switching analysis," Journal of International Money and Finance, Elsevier, vol. 21(4), pages 519-537, August.
    11. Sergey Smirnov, 2011. "Those Unpredictable Recessions," HSE Working papers WP BRP 02/EC/2011, National Research University Higher School of Economics.
    12. Marco Del Negro, 2001. "Turn, turn, turn: Predicting turning points in economic activity," Economic Review, Federal Reserve Bank of Atlanta, issue Q2, pages 1-12.
    13. Seip, Knut Lehre & McNown, Robert, 2007. "The timing and accuracy of leading and lagging business cycle indicators: A new approach," International Journal of Forecasting, Elsevier, vol. 23(2), pages 277-287.

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    Keywords

    Recessions ; Forecasting;

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