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

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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.

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Paper provided by Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne in its series Documents de travail du Centre d'Economie de la Sorbonne with number 13025.

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Length: 10 pages
Date of creation: Mar 2013
Date of revision:
Handle: RePEc:mse:cesdoc:13025

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Keywords: Recurrence Plots; economic cycles; turning points; Euro-zone.;

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References

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  1. Michael ARTIS & Massimiliano MARCELLINO & Tommaso PROIETTI, 2002. "Dating the Euro Area Business Cycle," Economics Working Papers ECO2002/24, European University Institute.
  2. Artis, Michael J & Marcellino, Massimiliano & Proietti, Tommaso, 2004. "Characterizing the Business Cycle for Accession Countries," CEPR Discussion Papers 4457, C.E.P.R. Discussion Papers.
  3. Jacques Anas & Laurent Ferrara, 2004. "Detecting Cyclical Turning Points: The ABCD Approach and Two Probabilistic Indicators," Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2004(2), pages 193-225.
  4. 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.
  5. 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 357-84, March.
  6. Peter McAdam, 2007. "USA, Japan and the Euro Area: Comparing Business-Cycle Features," International Review of Applied Economics, Taylor & Francis Journals, vol. 21(1), pages 135-156.
  7. 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.
  8. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, July.
  9. 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.
  10. 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.
  11. 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, 09.
  12. Fagan, Gabriel & Henry, Jérôme & Mestre, Ricardo, 2001. "An area-wide model (AWM) for the euro area," Working Paper Series 0042, European Central Bank.
  13. Peter Martey Addo & Monica Billio & Dominique Guegan, 2012. "Alternative Methodology for Turning-Point Detection in Business Cycle: A Wavelet Approach," Documents de travail du Centre d'Economie de la Sorbonne 12023, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  14. Pilar Bengoechea & Gabriel Pérez-Quirós, 2004. "A useful tool to identify recessions in the euro-area," Banco de Espa�a Working Papers 0419, Banco de Espa�a.
  15. Monica Billio & Jacques Anas & Laurent Ferrara & Marco Lo Duca, 2007. "A turning point chronology for the Euro-zone," Working Papers 2007_33, Department of Economics, University of Venice "Ca' Foscari".
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Cited by:
  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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