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Predicting European Union recessions in the euro era: The yield curve as a forecasting tool of economic activity

  • Gogas, Periklis
  • Chionis, Dionisios
  • Pragkidis, Ioannis

Several studies have established the predictive power of the yield curve, ie: the difference between long and short term bond rates, in terms of real economic activity, for the U.S. and various European countries. In this paper we use data from the European Union (EU15), ranging from 1994:Q1 to 2008:Q3. The seasonally adjusted real GDP is used to extract the long run trend and the cyclical component of the European output, while the European Central Bank’s euro area government benchmark bonds of various maturities are used for the calculation of the yield spreads. We also augment the models tested with non monetary policy variables: the unemployment and a composite European stock price index constructed from the indices of the three major European stock markets of London, Frankfurt and Paris. The methodology employed in the effort to forecast recessions, is a probit model of the inverse cumulative distribution function of the standard distribution, using several formal forecasting evaluation tests. The results show that the yield curve augmented with the composite stock index has significant forecasting power in terms of the EU15 real output.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 13911.

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Date of creation: Mar 2009
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Handle: RePEc:pra:mprapa:13911
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  1. 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.
  2. Hamilton, James Douglas & Kim, Dong Heon, 2000. "A Re-examination of the Predictability of Economic Activity Using the Yield Spread," University of California at San Diego, Economics Working Paper Series qt69v8p1m9, Department of Economics, UC San Diego.
  3. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
  4. 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.
  5. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
  6. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
  7. 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.
  8. Venetis, Ioannis A. & Paya, Ivan & Peel, David A., 2003. "Re-examination of the predictability of economic activity using the yield spread: a nonlinear approach," International Review of Economics & Finance, Elsevier, vol. 12(2), pages 187-206.
  9. Kim, Kenneth A. & Limpaphayom, Piman, 1997. "The effect of economic regimes on the relation between term structure and real activity in Japan," Journal of Economics and Business, Elsevier, vol. 49(4), pages 379-392.
  10. 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.
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