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Predictions of short-term rates and the expectations hypothesis

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  • Guidolin, Massimo
  • Thornton, Daniel L.

Abstract

This paper emphasizes that traditional tests of the EH are based on two assumptions: the expectations hypothesis (EH) per se and an assumption about the expectations generating process (EGP) for the short-term rate. Arguing that conventional tests of the EH need to assume EGPs that may be significantly at odds with the true EGP, we investigate this possibility by analyzing the out-of-sample predictive performances of several models for predicting interest rates, including a few models which assume that the EH holds in its functional form that relates long- to short-term yields. Using US riskless yield data for a 1970–2016 monthly sample and testing methods that take into account the parameter uncertainty, the null hypothesis of an equal predictive accuracy of each model relative to the random walk alternative is hardly ever rejected at intermediate and long horizons. This confirms that, at least at a practical level, the main difficulty with the EH is represented by the effective prediction of short-term rates. We discuss the relevance of these findings for central banks’ use of forward guidance.

Suggested Citation

  • Guidolin, Massimo & Thornton, Daniel L., 2018. "Predictions of short-term rates and the expectations hypothesis," International Journal of Forecasting, Elsevier, vol. 34(4), pages 636-664.
  • Handle: RePEc:eee:intfor:v:34:y:2018:i:4:p:636-664
    DOI: 10.1016/j.ijforecast.2018.03.006
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    Cited by:

    1. Thornton, Daniel L., 2014. "Monetary policy: Why money matters (and interest rates don’t)," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 202-213.
    2. Clemens J. M. Kool & Daniel L. Thornton, 2015. "How Effective Is Central Bank Forward Guidance?," Review, Federal Reserve Bank of St. Louis, vol. 97(4), pages 303-322.
    3. Daniel L. Thornton, 2018. "Greenspan's Conundrum and the Fed's Ability to Affect Long‐Term Yields," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 513-543, March.
    4. Michael Wickens, 2022. "Forward Interest Rates as Predictors of Future US Spot Rates Before and After the 2008 Financial Crisis," Open Economies Review, Springer, vol. 33(3), pages 391-406, July.
    5. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    6. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Daniel L. Thornton, 2012. "The Federal Reserve’s response to the financial crisis: what it did and what it should have done," Working Papers 2012-050, Federal Reserve Bank of St. Louis.
    8. Vides, José Carlos & Golpe, Antonio A. & Iglesias, Jesús, 2021. "The impact of the term spread in US monetary policy from 1870 to 2013," Journal of Policy Modeling, Elsevier, vol. 43(1), pages 230-251.
    9. Daniel L. Thornton, 2012. "Evidence on the portfolio balance channel of quantitative easing," Working Papers 2012-015, Federal Reserve Bank of St. Louis.
    10. Peter Tulip & Stephanie Wallace, 2012. "Estimates of Uncertainty around the RBA's Forecasts," RBA Research Discussion Papers rdp2012-07, Reserve Bank of Australia.
    11. Guidolin, Massimo & Pedio, Manuela, 2019. "Forecasting and trading monetary policy effects on the riskless yield curve with regime switching Nelson–Siegel models," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    12. Schmeling, Maik & Schrimpf, Andreas & Steffensen, Sigurd A.M., 2022. "Monetary policy expectation errors," Journal of Financial Economics, Elsevier, vol. 146(3), pages 841-858.
    13. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    14. Vides, José Carlos & Golpe, Antonio A. & Iglesias, Jesús, 2020. "The EHTS and the persistence in the spread reconsidered. A fractional cointegration approach," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 124-137.
    15. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.

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    17. Backus, David & Foresi, Silverio & Mozumdar, Abon & Wu, Liuren, 2001. "Predictable changes in yields and forward rates," Journal of Financial Economics, Elsevier, vol. 59(3), pages 281-311, March.
    18. Hautsch, Nikolaus & Ou, Yangguoyi, 2012. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 2988-3007.
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