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Asymmetry in the link between the yield spread and industrial production: threshold effects and forecasting

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  • Ioannis A. Venetis

    (Centre of Planning and Economic Research (KEPE), Athens, Greece)

  • David A. Peel

    (Lancaster University Management School, UK)

  • Ivan Paya

    (Departamento Fundamentos Analisis Economico, University of Alicante, Spain)

Abstract

We analyse the nonlinear behaviour 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 USA and four of the UK over the last 40 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. Copyright © 2004 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.921
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 23 (2004)
Issue (Month): 5 ()
Pages: 373-384

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Handle: RePEc:jof:jforec:v:23:y:2004:i:5:p:373-384

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
  7. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
  8. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2000. "How stable is the predictive power of the yield curve? evidence from Germany and the United States," Staff Reports 113, Federal Reserve Bank of New York.
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Cited by:
  1. Bruno, Giancarlo, 2009. "Non-linear relation between industrial production and business surveys data," MPRA Paper 42337, University Library of Munich, Germany.
  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. 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.

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