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Journal of Economic Integration 2008 June;23(2) :297-330.
DOI: https://doi.org/10.11130/jei.2008.23.2.297
Convergence and Cluster Structures in EU Area according to Fluctuations in Macroeconomic Indices
Mircea Gligor and 
Marcel Ausloos 
National College Roman Voda, University of Liege
University of Liege
Copyright ©2008 Journal of Economic Integration
ABSTRACT

Cluster analysis methods allow for a comparative study of countries through basic macroeconomic indicator fluctuations. Statistical distances between 15 EU countries are first calculated for various moving time windows. The decrease in time of the mean statistical distance is observed through the correlated fluctuations of typical macroeconomic indicators: GDP, GDP/capita, Consumption and Investments. This empirical evidence can be seen as a mark of globalization. The Moving Average Minimal Length Path algorithm indicates the existence of cluster-like structures both in the hierarchical organization of countries and their relative movements inside the hierarchy. The most strongly correlated countries with respect to GDP fluctuations can be partitioned into stable clusters. Several so correlated countries display strong correlations also in the Final Consumption Expenditure; others are strongly correlated in the Gross Capital Formation. The similarity between the classifications due to GDP and Net Exports fluctuations is pointed out through the squared sum of the correlation coefficients, a so called "country sensitivity". The structures are robust against changes in time window size. Policy implications concern the economic clusters arising in the presence of Marshallian externalities and the relationships between trade barriers, R&D incentives and growth that must be accounted for in elaborating cluster-promotion policies.

JEL classification: C1, C22, C23, O52, O57

Keywords: Statistical distances | Minimal length path | Convergence | Clustering
 
REFERENCE
1. Mehrotra, S., Biggeri, M. (2005) Can Industrial Outwork Enhance Homeworkers' Capabilities? Evidence from Clusters in South Asia, World Development, 33, 1735-1757.
2. Miskiewicz, J., Ausloos, M. (2006) An attempt to observe economy globalization: the cross correlation distance evolution of the top 19 GDP's. International Journal of Modern Physics C, 17, 317-331.
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