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A New Approach to Predicting Recessions

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  • Ken Nyholm

Abstract

This paper presents a new approach to recession prediction. The methodology relies on the shape of the yield curve alone and does not incorporate macroeconomic information or other explanatory variables. This makes the modelling framework less data intensive and more intuitive than other models that have the same goal. The workhorses of the approach are (i) data transformation of observed yields with the purpose of normalizing the yield spread, and (ii) a three‐state regime‐switching version of the Nelson–Siegel parametric model of the yield curves' shape and location. In an out‐of‐sample exercise the model predicts all US NBER recessions from 1973 to 2004 at least eight months in advance of their occurrences.

Suggested Citation

  • Ken Nyholm, 2007. "A New Approach to Predicting Recessions," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 36(1), pages 27-42, February.
  • Handle: RePEc:bla:ecnote:v:36:y:2007:i:1:p:27-42
    DOI: 10.1111/j.1468-0300.2007.00176.x
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    References listed on IDEAS

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    1. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    2. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    3. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003. "How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 629-644, August.
    4. 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.
    5. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    6. Chen, Nai-Fu, 1991. "Financial Investment Opportunities and the Macroeconomy," Journal of Finance, American Finance Association, vol. 46(2), pages 529-554, June.
    7. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
    8. 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.
    9. Ivanova, Detelina & Lahiri, Kajal & Seitz, Franz, 2000. "Interest rate spreads as predictors of German inflation and business cycles," International Journal of Forecasting, Elsevier, vol. 16(1), pages 39-58.
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    Cited by:

    1. Marcelle Chauvet & Zeynep Senyuz, 2012. "A Dynamic Factor Model of the Yield Curve as a Predictor of the Economy," Finance and Economics Discussion Series 2012-32, Board of Governors of the Federal Reserve System (U.S.).
    2. Francis Bismans & Reynald Majetti, 2013. "Forecasting recessions using financial variables: the French case," Empirical Economics, Springer, vol. 44(2), pages 419-433, April.
    3. Chauvet, Marcelle & Senyuz, Zeynep, 2008. "A Joint Dynamic Bi-Factor Model of the Yield Curve and the Economy as a Predictor of Business Cycles," MPRA Paper 15076, University Library of Munich, Germany, revised Apr 2009.
    4. Chauvet, Marcelle & Senyuz, Zeynep, 2016. "A dynamic factor model of the yield curve components as a predictor of the economy," International Journal of Forecasting, Elsevier, vol. 32(2), pages 324-343.

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