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Cluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations

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Author Info

  • M. Gligor

    ()

  • M. Ausloos

    ()

Abstract

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x 1), Final Consumption Expenditure (x 2), Gross Capital Formation (x 3), Net Exports (x 4), Consumer Price Index (y 1), Rates of Interest of the Central Banks (y 2), Labour Force (z 1), Unemployment (z 2), GDP/hour worked (z 3), GDP/capita (w 1) and Gini coefficient (w 2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007

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File URL: http://hdl.handle.net/10.1140/epjb/e2007-00132-5
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Bibliographic Info

Article provided by Springer in its journal The European Physical Journal B.

Volume (Year): 57 (2007)
Issue (Month): 2 (05)
Pages: 139-146

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Handle: RePEc:spr:eurphb:v:57:y:2007:i:2:p:139-146

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Web page: http://www.springer.com/economics/journal/10051

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Related research

Keywords: 89.65.Gh Economics; econophysics; financial markets; business and management; 89.75.Fb Structures and organization in complex systems; 05.45.Tp Time series analysis;

References

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  1. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906.
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Cited by:
  1. Maharaj, Elizabeth Ann & D’Urso, Pierpaolo, 2010. "A coherence-based approach for the pattern recognition of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3516-3537.
  2. Redelico, Francisco O. & Proto, Araceli N. & Ausloos, Marcel, 2009. "Hierarchical structures in the Gross Domestic Product per capita fluctuation in Latin American countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3527-3535.
  3. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2011. "The Japanese economy in crises: A time series segmentation study," Economics Discussion Papers 2011-24, Kiel Institute for the World Economy.
  4. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2012. "The Japanese economy in crises: A time series segmentation study," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 6(5), pages 1-81.

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