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Forecasting recessions using financial variables: the French case

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  • Francis Bismans

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  • Reynald Majetti

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    Abstract

    In this article, we focus on the ability of two financial variables—the yield curve spread and the euro–US dollar exchange rate—to predict French recessions over the period 1979–2010. First, we propose a turning point chronology for the French business cycle based on a classical conception of economic cycles and a non-parametric dating algorithm applied to the real GDP series. Second, static and dynamic probit models are developed and estimated to produce the recession probabilities. In-sample results show that the dynamic specification performs better than the static one and, above all, that the exchange rate has a stronger predictive power than the yield curve. Out-of-sample results finally confirm the predominant role assigned to the exchange rate in predicting the latest recession occurred in 2008. Copyright Springer-Verlag 2013

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    Bibliographic Info

    Article provided by Springer in its journal Empirical Economics.

    Volume (Year): 44 (2013)
    Issue (Month): 2 (April)
    Pages: 419-433

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    Handle: RePEc:spr:empeco:v:44:y:2013:i:2:p:419-433

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    Related research

    Keywords: French business cycle; Dynamic probit; Recession forecasts; Term spread; EUR/USD exchange rate; C22; C25; E32; E37;

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    References

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    1. Marco Del Negro, 2001. "Turn, turn, turn: Predicting turning points in economic activity," Economic Review, Federal Reserve Bank of Atlanta, issue Q2, pages 1-12.
    2. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1 National Bureau of Economic Research, Inc.
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    15. Eichengreen, Barry & Watson, Mark W & Grossman, Richard S, 1985. "Bank Rate Policy under the Interwar Gold Standard: A Dynamic Probit Model," Economic Journal, Royal Economic Society, vol. 95(379), pages 725-45, September.
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