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Predicting Recession Using the Yield Curve: An Artificial Intelligence and Econometric Comparison

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  • Mohamad Shaaf

    (University of Central Oklahoma)

Abstract

Normally the yield curve has an upward slope and is slightly convex. There are times when the curve becomes flat or slopes downward, which signals an approaching economic slowdown soon. Although simple, the yield curve has often been more successful at predicting recession than larger and/or more complex econometric models. Using an artificial intelligence methodology called "neural networks" and quarterly data from 1959 to 1997, the purpose of this study was to use the yield curve for forecasting recessions. The results confirm earlier findings that used econometric modelling, and suggest that the yield curve is a very useful tool for the prediction of recession. Furthermore, the results of the out-of-sample simulation imply that the forecast of the artificial intelligence method is more accurate than that of the traditional econometric model.

Suggested Citation

  • Mohamad Shaaf, 2000. "Predicting Recession Using the Yield Curve: An Artificial Intelligence and Econometric Comparison," Eastern Economic Journal, Eastern Economic Association, vol. 26(2), pages 171-190, Spring.
    • Handle: RePEc:eej:eeconj:v:26:y:2000:i:2:p:171-190
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    File URL: http://web.holycross.edu/RePEc/eej/Archive/Volume26/V26N2P171_190.pdf
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    References listed on IDEAS

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    1. John Y. Campbell, 1995. "Some Lessons from the Yield Curve," Journal of Economic Perspectives, American Economic Association, vol. 9(3), pages 129-152, Summer.
    2. Mishkin, Frederic S., 1990. "What does the term structure tell us about future inflation?," Journal of Monetary Economics, Elsevier, vol. 25(1), pages 77-95, January.
    3. 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.
    4. Harvey, Campbell R., 1988. "The real term structure and consumption growth," Journal of Financial Economics, Elsevier, vol. 22(2), pages 305-333, December.
    5. Fisher, Irving, 1907. "The Rate of Interest," History of Economic Thought Books, McMaster University Archive for the History of Economic Thought, number fisher1907.
    6. 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.
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    Cited by:

    1. David C. Wheelock & Mark E. Wohar, 2009. "Can the term spread predict output growth and recessions? a survey of the literature," Review, Federal Reserve Bank of St. Louis, vol. 91(Sep), pages 419-440.
    2. Fabio Moneta, 2005. "Does the Yield Spread Predict Recessions in the Euro Area?," International Finance, Wiley Blackwell, vol. 8(2), pages 263-301, August.

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    More about this item

    Keywords

    Econometrics; Neural Networks; Neural;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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