IDEAS home Printed from https://ideas.repec.org/a/fip/fedker/y1999iqiip35-55nv.84no.2.html
   My bibliography  Save this article

How reliable are recession prediction models?

Author

Listed:
  • 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, vol. 84(Q II), pages 35-55.
    • Handle: RePEc:fip:fedker:y:1999:i:qii:p:35-55:n:v.84no.2
    as

    Download full text from publisher

    File URL: https://www.kansascityfed.org/documents/1184/1999-How%20Reliable%20Are%20Recession%20Prediction%20Models%3F.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David E. Runkle, 1998. "Revisionist history: how data revisions distort economic policy research," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 22(Fall), pages 3-12.
    2. 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.
    3. Victor Zarnowitz, 1992. "Business Cycles: Theory, History, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number zarn92-1.
    4. Geoffrey H. Moore, 1983. "Business Cycles, Inflation, and Forecasting, 2nd edition," NBER Books, National Bureau of Economic Research, Inc, number moor83-1.
    5. 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.
    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 357-384, March.
    7. Stephen K. McNees, 1987. "Forecasting cyclical turning points: the record in the past three recessions," New England Economic Review, Federal Reserve Bank of Boston, issue Mar, pages 31-40.
    8. 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.
    9. 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.
    10. John C. Robertson & Ellis W. Tallman, 1998. "Data vintages and measuring forecast model performance," Economic Review, Federal Reserve Bank of Atlanta, vol. 83(Q 4), pages 4-20.
    11. Chan Guk Huh, 1991. "Recession probability indexes: a survey," Economic Review, Federal Reserve Bank of San Francisco, issue Fall, pages 31-40.
    12. James H. Stock & Mark W. Watson, 1993. "Business Cycles, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number stoc93-1.
    13. Stock, James H. & Watson, Mark W. (ed.), 1993. "Business Cycles, Indicators, and Forecasting," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226774886, August.
    14. Saul H. Hymans, 1973. "On the Use of Leading Indicators to Predict Cyclical Turning Points," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 4(2), pages 339-384.
    15. 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.
    16. Sharon Kozicki, 1997. "Predicting real growth and inflation with the yield spread," Economic Review, Federal Reserve Bank of Kansas City, vol. 82(Q IV), pages 39-57.
    17. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sergey V. Smirnov & Nikolay V. Kondrashov & Anna V. Petronevich, 2017. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(1), pages 53-73, May.
    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, University Library of Munich, Germany, revised 28 Mar 2005.
    8. 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.
    9. 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.
    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. Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
    13. Marco Del Negro, 2001. "Turn, turn, turn: Predicting turning points in economic activity," Economic Review, Federal Reserve Bank of Atlanta, vol. 86(Q2), pages 1-12.
    14. 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.
    15. Huiwen Lai & Eric C. Y. Ng, 2020. "On business cycle forecasting," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-26, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gregory R. Duffee & Stephen D. Prowse, "undated". "What's Good for GM...? Using Auto Industry Stock Returns to Forecast Business Cycles and Test the Q-Theory of Investment," Finance and Economics Discussion Series 1996-38, Board of Governors of the Federal Reserve System (U.S.), revised 04 Dec 2019.
    2. Andrew Filardo, 2004. "The 2001 US recession: what did recession prediction models tell us?," BIS Working Papers 148, Bank for International Settlements.
    3. Carriero, Andrea & Marcellino, Massimiliano, 2007. "A comparison of methods for the construction of composite coincident and leading indexes for the UK," International Journal of Forecasting, Elsevier, vol. 23(2), pages 219-236.
    4. Carriero, Andrea & Marcellino, Massimiliano, 2007. "A comparison of methods for the construction of composite coincident and leading indexes for the UK," International Journal of Forecasting, Elsevier, vol. 23(2), pages 219-236.
    5. Sergey V. Smirnov & Nikolay V. Kondrashov & Anna V. Petronevich, 2017. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(1), pages 53-73, May.
    6. 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.
    7. Morais, Igor Alexandre C. & Chauvet, Marcelle, 2011. "Leading Indicators for the Capital Goods Industry," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 31(1), March.
    8. Peláez, Rolando F., 2015. "Market-timing the business cycle," Review of Financial Economics, Elsevier, vol. 26(C), pages 55-64.
    9. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.
    10. Duo Qin, 2010. "Econometric Studies of Business Cycles in the History of Econometrics," Working Papers 669, Queen Mary University of London, School of Economics and Finance.
    11. 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.
    12. Chan Guk Huh, 1998. "Forecasting industrial production using models with business cycle asymmetry," Economic Review, Federal Reserve Bank of San Francisco, pages 29-41.
    13. DAVID E. ALLEN & MICHAEL McALEER & ROBERT J. POWELL & ABHAY K. SINGH, 2018. "Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-23, June.
    14. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    15. Chris Birchenhall & Denise Osborn & Marianne Sensier, 2001. "Predicting UK Business Cycle Regimes," Scottish Journal of Political Economy, Scottish Economic Society, vol. 48(2), pages 179-195, May.
    16. Rolando F. Peláez, 2015. "A recession‐and‐state forecasting model," Southern Economic Journal, John Wiley & Sons, vol. 81(4), pages 1025-1039, April.
    17. Allan P. Layton, 1994. "Further on the Nature of the Australian Business Cycle," The Economic Record, The Economic Society of Australia, vol. 70(208), pages 12-18, March.
    18. Dimitrios Papastamos & Fotis Mouzakis & Simon Stevenson, 2014. "Rationality and Momentum in Real Estate Investment Forecasts," Real Estate & Planning Working Papers rep-wp2014-07, Henley Business School, University of Reading.
    19. Victor Zarnowitz, 1999. "Has the Business Cycle Been Abolished?," NBER Working Papers 6367, National Bureau of Economic Research, Inc.
    20. Engemann, Kristie M. & Kliesen, Kevin L. & Owyang, Michael T., 2011. "Do Oil Shocks Drive Business Cycles? Some U.S. And International Evidence," Macroeconomic Dynamics, Cambridge University Press, vol. 15(S3), pages 498-517, November.

    More about this item

    Keywords

    Recessions; Forecasting;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedker:y:1999:i:qii:p:35-55:n:v.84no.2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Zach Kastens (email available below). General contact details of provider: https://edirc.repec.org/data/frbkcus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.