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The “probability of recession”: Evaluating probabilistic and non-probabilistic forecasts from probit models of U.S. recessions

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  • Ratcliff, Ryan

Abstract

This letter evaluates forecasts from probit models that use the slope of the yield curve to forecast recessions. These models give reliable non-probabilistic warnings of recessions, but the estimated probabilities do not match the conditional frequency of recession months.

Suggested Citation

  • Ratcliff, Ryan, 2013. "The “probability of recession”: Evaluating probabilistic and non-probabilistic forecasts from probit models of U.S. recessions," Economics Letters, Elsevier, vol. 121(2), pages 311-315.
    • Handle: RePEc:eee:ecolet:v:121:y:2013:i:2:p:311-315
    DOI: 10.1016/j.econlet.2013.09.002
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    References listed on IDEAS

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    1. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    2. Arturo Estrella & Anthony P. Rodrigues, 1998. "Consistent covariance matrix estimation in probit models with autocorrelated errors," Staff Reports 39, Federal Reserve Bank of New York.
    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. Heikki Kauppi & Pentti Saikkonen, 2008. "Predicting U.S. Recessions with Dynamic Binary Response Models," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 777-791, November.
    5. Henri Nyberg, 2010. "Dynamic probit models and financial variables in recession forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 215-230.
    6. Michael J. Dueker, 1997. "Strengthening the case for the yield curve as a predictor of U.S. recessions," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 41-51.
    7. 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.
    8. Edward E. Leamer, 2009. "Macroeconomic Patterns and Stories," Springer Books, Springer, number 978-3-540-46389-4, March.
    9. Heikki Kauppi, 2008. "Yield-Curve Based Probit Models for Forecasting U.S. Recessions: Stability and Dynamics," Discussion Papers 31, Aboa Centre for Economics.
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    Cited by:

    1. Seitz, Franz & Baumann, Ursel & Albuquerque, Bruno, 2015. "The information content of money and credit for US activity," Working Paper Series 1803, European Central Bank.
    2. Goodness C. Aye & Christina Christou & Luis A. Gil‐Alana & Rangan Gupta, 2019. "Forecasting the Probability of Recessions in South Africa: the Role of Decomposed Term Spread and Economic Policy Uncertainty," Journal of International Development, John Wiley & Sons, Ltd., vol. 31(1), pages 101-116, January.
    3. Albuquerque, Bruno & Baumann, Ursel & Seitz, Franz, 2016. "What does money and credit tell us about real activity in the United States?," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 328-347.
    4. repec:ecb:ecbwps:20141803 is not listed on IDEAS

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    More about this item

    Keywords

    Recession forecast; Forecast evaluation; Calibration;
    All these keywords.

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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