Clusters or networks of economies? A macroeconomy study through Gross Domestic Product

Physica A: Statistical Mechanics and its Applications

Volumn 382, Issue 1, 2007, Pages 16-21

  Ausloos, M ^a   Lambiotte, R ^a  

^a UNIVERSITY OF LIÈGE   (Belgium)

Author keywords

Correlations; Directed network; Distance; Econophysics; GDP; Patterns; Theil index; Time delay

Indexed keywords

ECONOMIC ANALYSIS; STATISTICAL MECHANICS; TIME DELAY;

DIRECTED NETWORK; ECONOPHYSICS; THEIL INDEX;

CORRELATION THEORY;

EID: 34249905233     PISSN: 03784371     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.physa.2007.02.005     Document Type: Article

References (17)

1. Miskiewicz J., and Ausloos M. Correlations between the most developed (G7) countries. A moving average window size optimization, Acta Phys. Pol. B 36 (2005) 2477-2486
2. Miskiewicz J., and Ausloos M. An attempt to observe economy globalization: the cross correlation distance evolution of the top 19 GDP's. Int. J. Mod. Phys. C 17 (2006) 317-332
3. Miskiewicz J., and Ausloos M. G7 country Gross Domestic Product (GDP) time correlations-A graph network analysis. In: Takayasu H. (Ed). Practical Fruits of Econophysics (2006), Springer, Tokyo 312-316
4. Miskiewicz J., and Ausloos M. Influence of information flow in the formation of economic cycles. In: Ausloos M., and Dirickx M. (Eds). The Logistic Map and the Route to Chaos (2006), Springer, Berlin 223-238
5. Gligor M., and Ausloos M. Eur Phys J B 56 (2007) 1434-6028
6. Serrano M.A., and Boguna M. Topology of the world trade web. Phys. Rev. E 68 (2003) 015101R
7. Garlaschelli D., and Loffredo M.I. Fitness-dependent topological properties of the world trade web. Phys. Rev. Lett. 93 (2004) 188701
8. D. Garlaschelli, T. Di Matteo, T. Aste, G. Caldarelli, M.I. Loffredo, Interplay between topology and dynamics in the world trade web, Proceedings of WEHIA 2006.
9. Di Matteo T., and Aste T. How does the Eurodollar Interest Rate behave?. Int. J. Theor. Appl. Fin. 5 (2002) 107-122
10. G. Fagiolo, Question raised at the end of the oral presentation.
11. Long J.B., and Plosser C.I. Real business cycles. J. Polit. Econ. 91 (1983) 39-69
12. Basu S., and Taylor A.M. Business cycles in international historical perspective. J. Econom. Perspect. 13 (1999) 45-68
13. P. Glansdorff, I. Prigogine, Structure, Stabilité et Fluctuations, Masson, Paris, 1971.
14. Lambiotte R., and Ausloos M. Uncovering collective listening habits and music genres in bipartite networks. Phys. Rev. E 72 (2005) 066107
15. An anonymous referee commented that the noise inherent to such small sample invalidates any possible outcome of the analysis. Moreover temporal series of fluctuations in economy are usually autocorrelated, like when two such series are correlated with a common process, e.g. traders in the stock market all influenced by the same inputs, such as news or index markets, or countries within the EU who follow common european policies. Under these conditions, it is easy to see that both series are cross correlated at different time lags; this fact does not imply that one series is driving the other one. We quote In fact, one finds cross correlation for positive and negative lags and therefore it is not possible to say who is influencing who. We do not disagree; in fact we claim that the networks generated in this paper might not reflect the real (if any) pattern of influences among countries. However the clustering can be accepted if one accepts economy (empirical) theoreticians that globalization exists. In summary, we believe that our possible interpretation of the results is meaningful.
16. Mora T. Evidencing European regional convergence clubs with optimal grouping criteria. Appl. Econ. Lett. 12 (2005) 937-940
17. E.C. Angelini, F. Farina, The size of redistribution in OECD countries: does it influence wave inequality? Paper for International Conference in Memory of Two Eminent Social Scientists: C. Gini and M. O. Lorenz, Siena, Italy, 23-26 May, 2005.