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Clustering eurozone cycles

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  • Chee-Heong Quah

Abstract

Firstly, the study draws out symmetrical subsets of 27 member countries of the European Union (EU27) countries according to their extents of business cycle symmetry with the whole of EA12, quantified by correlations of cycles between the countries’ GDP components and the EA12s GDP. The objective is to evaluate the obtained country groupings against the EA12 countries, the initial members of the euro club. This exercise is implemented using hierarchical cluster analysis for pre- and post-euro periods. As a robustness check, a principal component analysis is applied. Secondly, the analysis deploys a discriminant technique on the cluster analysis solutions to identify the GDP component whose cycle synchronicity contributes most to separation of the countries. In a nutshell, the findings suggest a significant rise in fragmentation within EU27 and within EA12 after euroization and that cycle synchronization involving the GDP component of private investment as a more important determinant to country classifications. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Chee-Heong Quah, 2014. "Clustering eurozone cycles," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3447-3462, November.
  • Handle: RePEc:spr:qualqt:v:48:y:2014:i:6:p:3447-3462
    DOI: 10.1007/s11135-013-9966-6
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    References listed on IDEAS

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    1. António Afonso & Ana Sequeira, 2010. "Revisiting business cycle synchronisation in the European Union," Working Papers Department of Economics 2010/22, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    2. Mark Mink & Jan P.A.M. Jacobs & Jakob de Haan, 2007. "Measuring Synchronicity And Co-Movement Of Business Cycles With An Application To The Euro Area," CAMA Working Papers 2007-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Chee‐Heong Quah & Patrick M. Crowley, 2010. "Monetary Integration in East Asia: A Hierarchical Clustering Approach," International Finance, Wiley Blackwell, vol. 13(2), pages 283-309, August.
    4. D. Furceri & G. Karras, 2008. "Business-cycle synchronization in the EMU," Applied Economics, Taylor & Francis Journals, vol. 40(12), pages 1491-1501.
    5. Christian Gayer, 2007. "A fresh look at business cycle synchronisation in the euro area," European Economy - Economic Papers 2008 - 2015 287, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    6. Mark Mink & Jan P.A.M. Jacobs & Jakob de Haan, 2012. "Measuring coherence of output gaps with an application to the euro area," Oxford Economic Papers, Oxford University Press, vol. 64(2), pages 217-236, April.
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    Cited by:

    1. Chee-Heong Quah, 2017. "Exchange Rate Fixation between US, China, Japan and Eurozone," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 11(2), pages 99-120, May.
    2. Chee-Heong Quah, 2016. "Germany versus the United States: Monetary Dominance in the Eurozone," Economies, MDPI, vol. 4(2), pages 1-16, April.
    3. Jian Zhou & Qina Wang & Chih-Cheng Hung & Fan Yang, 2017. "Credibilistic clustering algorithms via alternating cluster estimation," Journal of Intelligent Manufacturing, Springer, vol. 28(3), pages 727-738, March.
    4. Ahlborn, Markus & Wortmann, Marcus, 2018. "The core‒periphery pattern of European business cycles: A fuzzy clustering approach," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 12-27.

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