A unified framework for the pareto law and Matthew effect using scale-free networks
- 134 Downloads
We investigate the accumulated wealth distribution by adopting evolutionary games taking place on scale-free networks. The system self-organizes to a critical Pareto distribution (1897) of wealth P(m)∼m-(v+1) with 1.6 < v <2.0 (which is in agreement with that of U.S. or Japan). Particularly, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which is consistent with the Matthew Effect present in society, economy, science and so on. Though our model is simple, it provides a good representation of cooperation and profit accumulation behavior in economy, and it combines the network theory with econophysics.
PACS.87.23.Ge Dynamics of social systems 89.75.Hc Networks and genealogical trees 05.10.-a Computational methods in statistical physics and nonlinear dynamics 89.75.-k Complex systems
Unable to display preview. Download preview PDF.
- V. Pareto, Le Cours d'Économie Politique (Macmillan, Lausanne, Paris, 1987) Google Scholar
- S. Moss de Oliveira, P.M.C. de Oliveira, D. Stauer, Evolution, Money, War and Computers, edited by B.G. Tuebner (Stuttgart, Leipzig, 1999) Google Scholar
- Econophysics of Wealth Distributions, edited by A. Chatterjee, S. Yarlagadda, B.K. Chakrabarti (Springer-Verlag, Milan, 2005) Google Scholar
- A.L. Barabási, H. Jeong, E. Ravasz, Z. Néda, A. Schubert, T. Vicsek, preprint arXiv:cond-mat/0104162 (2001) Google Scholar
- H. Gintis, Game Theory Evolving (Princeton University, Princeton, NJ, 2000) Google Scholar
- A.M. Colman, Game Theory and its Applications in the Social and Biological Sciences (Butterworth-Heinemann, Oxford, 1995) Google Scholar
- D.F. Brewer, Physics Today 44, 154 (1991); Google Scholar