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Asymmetry In The Link Between The Yield Spread And Industrial Production. Threshold Effects And Forecasting

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Author Info

  • Ivan Paya

    ()
    (Universidad de Alicante)

  • David A. Peel

    (University Management School)

  • Ioannis A. Venetis

    (Centre of Planning and Economic Research (KEPE))

Abstract

We analyze the nonlinear behavior of the information content in the spread for future real economic activity. The spread linearly predicts one year ahead real growth in nine industrial production sectors of the US and four of the UK over the last forty years. However, recent investigations on the spread-real activity relation have questioned both its linear nature and its time-invariant framework. Our, in-sample, empirical evidence suggests that the spread real activity relationship exhibits asymmetries that allow for different predictive power of the spread when past spread values were above or below some threshold value. We then measure the out-of-sample forecast performance of the nonlinear model using predictive accuracy tests. The results show that significant improvement in forecasting accuracy, at least for one-step ahead forecasts, can be obtained over the linear model.

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Bibliographic Info

Paper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2004-41.

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Length: 18 pages
Date of creation: Oct 2004
Date of revision:
Publication status: Published by Ivie
Handle: RePEc:ivi:wpasad:2004-41

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Keywords: industrial production; yield spread; threshold model; forecasting; predictive accuracy;

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References

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  1. Arturo Estrella & Gikas A. Hardouvelis, 1989. "The term structure as a predictor of real economic activity," Research Paper 8907, Federal Reserve Bank of New York.
  2. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, April.
  3. Galbraith, John W. & Tkacz, Greg, 2000. "Testing for asymmetry in the link between the yield spread and output in the G-7 countries," Journal of International Money and Finance, Elsevier, vol. 19(5), pages 657-672, October.
  4. Estrella, Arturo & Mishkin, Frederic S., 1997. "The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank," European Economic Review, Elsevier, vol. 41(7), pages 1375-1401, July.
  5. 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.
  6. Michael Dotsey, 1998. "The predictive content of the interest rate term spread for future economic growth," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 31-51.
  7. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
  8. Fuhrer, Jeffrey C & Moore, George R, 1995. "Monetary Policy Trade-offs and the Correlation between Nominal Interest Rates and Real Output," American Economic Review, American Economic Association, vol. 85(1), pages 219-39, March.
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Citations

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Cited by:
  1. Schrimpf, Andreas & Wang, Qingwei, 2010. "A reappraisal of the leading indicator properties of the yield curve under structural instability," International Journal of Forecasting, Elsevier, vol. 26(4), pages 836-857, October.
  2. Huseyin Kaya, 2013. "On the Predictive Power of Yield Spread for Future Growth and Recession: The Turkish Case," Working Papers 010, Bahcesehir University, Betam, revised Mar 2013.
  3. Giancarlo Bruno, 2009. "Non-linear relation between industrial production and business surveys data," ISAE Working Papers 119, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).

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