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Turning point chronology for the Euro-Zone: A Distance Plot Approach

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  • Peter Martey Addo

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, University of Ca’ Foscari [Venice, Italy])

  • Monica Billio

    (University of Ca’ Foscari [Venice, Italy])

  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

We propose a transparent way of establishing a turning point chronology for the Euro-zone business cycle. Our analysis is achieve by exploiting the concept of recurrence plots, in this case distance plot, to characterize and detect turning points in the business cycle for any economic system. Firstly, we exploit the concept of recurrence plots on the US Industrial Production Index (IPI) series to serve as a beachmark for our analysis since there already exist reference chronology for the US business cycle, provided by the Dating Committee of the National Bureau of Economic Research (NBER). We then use this concept in constructing a turning point chronology for the Euro-zone business cycle. In particular, we show that this approach permits to detect turning points and study the business cycle without a priori assumptions on the statistical properties on the underlying economic indicator.

Suggested Citation

  • Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Turning point chronology for the Euro-Zone: A Distance Plot Approach," Post-Print halshs-00803457, HAL.
  • Handle: RePEc:hal:journl:halshs-00803457
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00803457
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    References listed on IDEAS

    as
    1. Michael ARTIS & Massimiliano MARCELLINO & Tommaso PROIETTI, 2002. "Dating the Euro Area Business Cycle," Economics Working Papers ECO2002/24, European University Institute.
    2. Claude Diebolt & Catherine Kyrtsou, 2005. "New Trends in Macroeconomics," Post-Print hal-00279607, HAL.
    3. Addo, Peter Martey & Billio, Monica & Guégan, Dominique, 2013. "Nonlinear dynamics and recurrence plots for detecting financial crisis," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 416-435.
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    5. Peter Martey Addo & Monica Billio & Dominique Guegan, 2012. "Alternative Methodology for Turning-Point Detection in Business Cycle : A Wavelet Approach," Post-Print halshs-00694420, HAL.
    6. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Understanding Exchange Rates Dynamics," Documents de travail du Centre d'Economie de la Sorbonne 13023, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
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    10. Monica Billio & Roberto Casarin, 2010. "Identifying business cycle turning points with sequential Monte Carlo methods: an online and real-time application to the Euro area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 145-167.
    11. 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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    16. Belaire-Franch, Jorge, 2004. "Testing for non-linearity in an artificial financial market: a recurrence quantification approach," Journal of Economic Behavior & Organization, Elsevier, vol. 54(4), pages 483-494, August.
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    18. Jacques Anas & Monica Billio & Laurent Ferrara & Gian Luigi Mazzi, 2008. "A System For Dating And Detecting Turning Points In The Euro Area," Manchester School, University of Manchester, vol. 76(5), pages 549-577, September.
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    1. Peter Martey Addo & Monica Billio & Dominique Guegan, 2012. "Studies in Nonlinear Dynamics and Wavelets for Business Cycle Analysis," Documents de travail du Centre d'Economie de la Sorbonne 12023r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Nov 2013.

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    More about this item

    Keywords

    points de retournement; zone euro; cycles économiques; Recurrence Plots; Euro-zone; turning points; economic cycles;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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