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Deux indicateurs probabilistes de retournement cyclique pour l’économie française

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  • Adanero-Donderis , M.
  • Darné, O.
  • Ferrara, L.

Abstract

This paper proposes two new coincident probabilistic cyclical indicators developed by the Bank of France in order to follow, on a monthly basis, the French economic activity. The first one is an indicator which aims at detecting the turning points of the acceleration cycle while the second one is dedicated to the follow-up of recession phases in the industrial sector. Both indicators are based on the methodology of Markov-Switching models and use only for input the Bank of France monthly business survey. An historical validation since 1998 points out to the interest and the complementarity of both indicators for the short-term economic diagnosis. This kind of indicators provides with an original and additional conjonctural qualitative information by comparison with more classical quantitative tools aiming at estimating the GDP growth rate.

Suggested Citation

  • Adanero-Donderis , M. & Darné, O. & Ferrara, L., 2007. "Deux indicateurs probabilistes de retournement cyclique pour l’économie française," Working papers 187, Banque de France.
    • Handle: RePEc:bfr:banfra:187
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    1. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
    2. Olivier Bandt & Heinz Herrmann & Giuseppe Parigi, 2006. "Convergence or Divergence in Europe?," Springer Books, Springer, number 978-3-540-32611-3, January.
    3. Sichel, Daniel E, 1994. "Inventories and the Three Phases of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 269-277, July.
    4. Clements, Michael P & Krolzig, Hans-Martin, 2003. "Business Cycle Asymmetries: Characterization and Testing Based on Markov-Switching Autoregressions," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 196-211, January.
    5. Stéphane Gregoir & Fabrice Lenglart, 1998. "Un nouvel indicateur pour saisir les retournements de conjoncture," Économie et Statistique, Programme National Persée, vol. 314(1), pages 39-60.
    6. Marcelle Chauvet & Jeremy M. Piger, 2003. "Identifying business cycle turning points in real time," Review, Federal Reserve Bank of St. Louis, vol. 85(Mar), pages 47-61.
    7. Zarnowitz, Victor & Ozyildirim, Ataman, 2006. "Time series decomposition and measurement of business cycles, trends and growth cycles," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1717-1739, October.
    8. Benoît Bellone & Erwan Gautier & Sébastien Le Coent, 2006. "Les marchés financiers anticipent-ils les retournements conjoncturels ?," Economie & Prévision, La Documentation Française, vol. 172(1), pages 83-99.
    9. Jean-Philippe Cotis & Jonathan Coppel, 2005. "Business Cycle Dynamics in OECD Countries: Evidence, Causes and Policy Implications," RBA Annual Conference Volume (Discontinued), in: Christopher Kent & David Norman (ed.),The Changing Nature of the Business Cycle, Reserve Bank of Australia.
    10. Hans-Martin Krolzig & Juan Toro, 2004. "Classical and modern business cycle measurement: The European case," Spanish Economic Review, Springer;Spanish Economic Association, vol. 7(1), pages 1-21, January.
    11. Stéphane Grégoir & Fabrice Lenglart, 1998. "Measuring the Probability of a Business Cycle Turning Point by Using a Multivariate Qualitative Hidden Markov Model," Working Papers 98-48, Center for Research in Economics and Statistics.
    12. Riccardo Cristadoro & Giovanni Veronese, 2006. "Tracking the Economy in the Largest Euro Area Countries: a Large Datasets Approach," Springer Books, in: Convergence or Divergence in Europe?, pages 63-93, Springer.
    13. Durland, J Michael & McCurdy, Thomas H, 1994. "Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 279-288, July.
    14. Benoit Bellone, 2005. "Classical Estimation of Multivariate Markov-Switching Models using MSVARlib," Econometrics 0508017, University Library of Munich, Germany.
    15. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    16. Ferrara, Laurent, 2003. "A three-regime real-time indicator for the US economy," Economics Letters, Elsevier, vol. 81(3), pages 373-378, December.
    17. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
    18. Layton, Allan P. & Smith, Daniel R., 2007. "Business cycle dynamics with duration dependence and leading indicators," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 855-875, December.
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    Cited by:

    1. Ferrara, L., 2008. "The contribution of cyclical turning point indicators to business cycle analysis," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 13, pages 49-61, Autumn.

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    More about this item

    Keywords

    Business cycle ; Acceleration cycle ; Probabilistic indicator ; Markov-Switching models ; Surveys.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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