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Forecasting with the yield curve; level, slope, and output 1875-1997

  • Michael D. Bordo
  • Joseph G. Haubrich

Using the yield curve helps forecast real growth over the period 1875 to 1997. Using both the level and slope of the curve improves forecasts more than using either variable alone. Forecast performance changes over time and depends somewhat on whether recursive or rolling out of sample regressions are used.

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Paper provided by Federal Reserve Bank of Cleveland in its series Working Paper with number 0611.

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Date of creation: 2006
Date of revision:
Handle: RePEc:fip:fedcwp:0611
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  1. James H. Stock & Mark W. Watson, 2001. "Forecasting output and inflation: the role of asset prices," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  2. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
  3. Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City.
  4. Andrew Ang & Monika Piazzesi & Min Wei, 2004. "What Does the Yield Curve Tell us about GDP Growth?," NBER Working Papers 10672, National Bureau of Economic Research, Inc.
  5. Arturo Estrella, 2005. "Why Does the Yield Curve Predict Output and Inflation?," Economic Journal, Royal Economic Society, vol. 115(505), pages 722-744, 07.
  6. Jonathan H. Wright, 2006. "The yield curve and predicting recessions," Finance and Economics Discussion Series 2006-07, Board of Governors of the Federal Reserve System (U.S.).
  7. Joseph G. Haubrich & Ann M. Dombrosky, 1996. "Predicting real growth using the yield curve," Economic Review, Federal Reserve Bank of Cleveland, issue Q I, pages 26-35.
  8. Nathan Balke & Robert J. Gordon, 1986. "Appendix B: Historical Data," NBER Chapters, in: The American Business Cycle: Continuity and Change, pages 781-850 National Bureau of Economic Research, Inc.
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