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The Yield Curve as a Predictor of Growth: Long-Run Evidence, 1875-1997

Author

Listed:
  • Michael D. Bordo

    (Rutgers University and NBER)

  • Joseph G. Haubrich

    (Federal Reserve Bank of Cleveland)

Abstract

This paper brings historical evidence to bear on the stylized fact that the yield curve predicts future growth. The spread between corporate bonds and commercial paper reliably predicts future growth over the period 1875-1997. This predictability varies over time, however, and has been strongest in the post-World War II period. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Michael D. Bordo & Joseph G. Haubrich, 2008. "The Yield Curve as a Predictor of Growth: Long-Run Evidence, 1875-1997," The Review of Economics and Statistics, MIT Press, vol. 90(1), pages 182-185, February.
    • Handle: RePEc:tpr:restat:v:90:y:2008:i:1:p:182-185
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    Citations

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    Cited by:

    1. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    2. Kevin Lee & Nilss Olekalns & Kalvinder Shields, 2008. "Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real Time Data are Available," Discussion Papers in Economics 08/17, Division of Economics, School of Business, University of Leicester.
    3. Kevin Aretz & David A. Peel, 2010. "Spreads versus professional forecasters as predictors of future output change," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(6), pages 517-522.
    4. Roberto Santis, 2015. "Quantity theory is alive: the role of international portfolio shifts," Empirical Economics, Springer, vol. 49(4), pages 1401-1430, December.
    5. Nilss Olekalns & Kalvinder Shields, 2008. "Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real Time Data are Available," Department of Economics - Working Papers Series 1040, The University of Melbourne.
    6. Antonello D'Agostino & Paolo Surico, 2012. "A Century of Inflation Forecasts," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1097-1106, November.
    7. Bordo, Michael D. & Haubrich, Joseph G., 2024. "Low interest rates and the predictive content of the yield curve," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    8. Hännikäinen, Jari, 2017. "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1044-1064.
    9. Hännikäinen, Jari, 2015. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," Review of Financial Economics, Elsevier, vol. 26(C), pages 47-54.
    10. Junttila, Juha & Vataja, Juuso, 2018. "Economic policy uncertainty effects for forecasting future real economic activity," Economic Systems, Elsevier, vol. 42(4), pages 569-583.
    11. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    12. Gebka, Bartosz & Wohar, Mark E., 2018. "The predictive power of the yield spread for future economic expansions: Evidence from a new approach," Economic Modelling, Elsevier, vol. 75(C), pages 181-195.
    13. De Santis, Roberto A., 2012. "Quantity theory is alive: the role of international portfolio shifts," Working Paper Series 1435, European Central Bank.
    14. Aitor Erce & Xu Jiang & Diana Zigraiova, 2020. "Quantifying Risks to Sovereign Market Access: Methods and Challenges," Globalization Institute Working Papers 377, Federal Reserve Bank of Dallas.
    15. Rockoff, Hugh & White, Eugene N., 2012. "Monetary Regimes and Policy on a Global Scale: The Oeuvre of Michael D. Bordo," MPRA Paper 49672, University Library of Munich, Germany, revised May 2013.
    16. Evgenidis, Anastasios & Papadamou, Stephanos & Siriopoulos, Costas, 2020. "The yield spread's ability to forecast economic activity: What have we learned after 30 years of studies?," Journal of Business Research, Elsevier, vol. 106(C), pages 221-232.
    17. Morell, Joseph, 2018. "The decline in the predictive power of the US term spread: A structural interpretation," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 314-331.
    18. Michael D. Bordo & Joseph G. Haubrich, 2020. "Low Interest Rates and the Predictive Content of the Yield Curve," Working Papers 20-24R, Federal Reserve Bank of Cleveland, revised 21 Dec 2021.
    19. Kao, Yi-Cheng & Kuan, Chung-Ming & Chen, Shikuan, 2013. "Testing the predictive power of the term structure without data snooping bias," Economics Letters, Elsevier, vol. 121(3), pages 546-549.
    20. 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.
    21. Petri Kuosmanen & Juuso Vataja, 2017. "The return of financial variables in forecasting GDP growth in the G-7," Economic Change and Restructuring, Springer, vol. 50(3), pages 259-277, August.
    22. Gozluklu, Arie & Morin, Annaïg, 2019. "Stock vs. Bond yields and demographic fluctuations," Journal of Banking & Finance, Elsevier, vol. 109(C).

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