Abstract
We present a simple model for examining the wealth distribution with agents playing evolutionary games (the Prisoners' Dilemma and the Snowdrift Game) on complex networks. Pareto's power law distribution of wealth (from 1897) is reproduced on a scale-free network, and the Gibbs or log-normal distribution for a low income population is reproduced on a random graph. The Pareto exponents of a scale-free network are in agreement with empirical observations. The Gini coefficient of an ER random graph shows a sudden increment with game parameters. We suggest that the social network of a high income group is scale-free, whereas it is more like a random graph for a low income group.
Original language | English |
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Pages (from-to) | 5862-5867 |
Number of pages | 6 |
Journal | Physica A: Statistical Mechanics and its Applications |
Volume | 387 |
Issue number | 23 |
DOIs | |
Publication status | Published - 1 Oct 2008 |
Externally published | Yes |
Keywords
- Complex networks
- Gini coefficient
- Pareto exponent
- Wealth distribution
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Statistics and Probability