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Turning point chronology for the euro area: A distance plot approach

Author

Listed:
  • 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)

  • 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)

Abstract

We propose a transparent way of establishing a turning point chronology for the euro area business cycle. Our analysis is achieved by exploiting the concept of recurrence plots, in particular distance plots, to characterise and detect turning points of the business cycle. Firstly, we apply the concept of recurrence plots on the US Industrial Production Index (IPI) series; this serves as a benchmark for our analysis since it already contains a reference chronology for the US business cycle, as provided by the Dating Committee of the National Bureau of Economic Research (NBER). We then use this concept to construct a turning point chronology for the euro area business cycle. In particular, we show that this approach detects turning points and helps with the study of the business cycle without a priori assumptions on the statistical properties of the underlying economic indicator.

Suggested Citation

  • Peter Martey Addo & Monica Billio & Dominique Guegan, 2014. "Turning point chronology for the euro area: A distance plot approach," PSE-Ecole d'économie de Paris (Postprint) hal-01310533, HAL.
    • Handle: RePEc:hal:pseptp:hal-01310533
    DOI: 10.1787/19952899
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    Cited by:

    1. Peter Martey Addo & Philippe De Peretti, 2014. "Detection and quantification of causal dependencies in multivariate time series: a novel information theoretic approach to understanding systemic risk," Documents de travail du Centre d'Economie de la Sorbonne 14069, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Peter Martey Addo, 2015. "Insights to the European debt crisis using recurrence quantification and network analysis," Documents de travail du Centre d'Economie de la Sorbonne 15035, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. Peter Martey Addo, 2015. "Insights to the European debt crisis using recurrence quantification and network analysis," Post-Print halshs-01164025, HAL.

    More about this item

    Keywords

    economic cycles; euro area; recurrence plots; turning points;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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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