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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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  • Gogas, Periklis & Chionis, Dionisios & Pragkidis, Ioannis, 2009. "Predicting European Union recessions in the euro era: The yield curve as a forecasting tool of economic activity," MPRA Paper 13911, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:13911

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    References listed on IDEAS

    1. 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.
    2. Hamilton, James D & Kim, Dong Heon, 2002. "A Reexamination of the Predictability of Economic Activity Using the Yield Spread," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 340-360, May.
    3. 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.
    4. 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.
    5. 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.
    6. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    7. 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.
    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. Estrella, Arturo & Hardouvelis, Gikas A, 1991. " The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    10. 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.
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    Cited by:

    1. Periklis Gogas & Ioannis Pragidis, 2012. "GDP trend deviations and the yield spread: the case of eight E.U. countries," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 226-237, January.
    2. Periklis Gogas & Theophilos Papadimitriou & Maria Matthaiou & Efthymia Chrysanthidou, 2015. "Yield Curve and Recession Forecasting in a Machine Learning Framework," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 635-645, April.
    3. Schock, Matthias, 2014. "Do Eurozone yield spreads predict recessions?," Hannover Economic Papers (HEP) dp-532, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    4. Goodness C. Aye & Christina Christou & Luis A. Gil-Alana & Rangan Gupta, 2016. "Forecasting the Probability of Recessions in South Africa: The Role of Decomposed Term-Spread and Economic Policy Uncertainty," Working Papers 201680, University of Pretoria, Department of Economics.
    5. Pirschel, Inske, 2015. "Forecasting Euro Area Recessions in real-time with a mixed-frequency Bayesian VAR," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113031, Verein für Socialpolitik / German Economic Association.
    6. Gogas, Periklis & Pragidis, Ioannis, 2010. "GDP Trend Deviations and the Yield Spread: the Case of Five E.U. Countries," DUTH Research Papers in Economics 2-2010, Democritus University of Thrace, Department of Economics.

    More about this item


    forecasting; yield spread; recession; probit; term structure; monetary policy; real growth;

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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