Clusters in weighted macroeconomic networks: the EU case. Introducing the overlapping index of GDP/capita fluctuation correlations

GDP/capita correlations are investigated in various time windows (TW), for the time interval 1990–2005. The target group of countries is the set of 25 EU members, 15 till 2004 plus the 10 countries which joined EU later on. The TW-means of the statistical correlation coefficients are taken as the weights (links) of a fully connected network having the countries as nodes. Thereafter we define and introduce the overlapping index of weighted network nodes. A cluster structure of EU countries is derived from the statistically relevant eigenvalues and eigenvectors of the adjacency matrix. This may be considered to yield some information about the structure, stability and evolution of the EU country clusters in a macroeconomic sense.

[1]  Rolf Aaberge,et al.  Income Inequality and Income Mobility in the Scandinavian Countries Compared to the United States , 2002 .

[2]  Rocco Huang,et al.  Distance and Trade: Disentangling unfamiliarity effects and transport cost effects , 2006 .

[3]  Andrew G. Glen,et al.  APPL , 2001 .

[4]  M. Ausloos,et al.  Clusters or networks of economies? A macroeconomy study through Gross Domestic Product , 2007 .

[5]  A. Barabasi,et al.  Evolution of the social network of scientific collaborations , 2001, cond-mat/0104162.

[6]  Marcel Ausloos,et al.  Hierarchical structures in the Gross Domestic Product per capita fluctuation in Latin American countries , 2009 .

[7]  H. Kaiser The Application of Electronic Computers to Factor Analysis , 1960 .

[8]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[9]  Evidencing European regional convergence clubs with optimal grouping criteria , 2005 .

[10]  R. Cattell The Scree Test For The Number Of Factors. , 1966, Multivariate behavioral research.

[11]  M. Newman Analysis of weighted networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  M. Browne A comparison of factor analytic techniques , 1968, Psychometrika.

[13]  J. McCauley,et al.  Martingales, nonstationary increments, and the efficient market hypothesis , 2008 .

[14]  S. Thurner Statistical Mechanics of Complex Networks , 2009 .

[15]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[16]  M. Ausloos,et al.  Cluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations , 2006 .

[17]  A. Vespignani,et al.  The architecture of complex weighted networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.