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Properties of wealth distribution in multi-agent systems of a complex network

Author

Listed:
  • Hu, Mao-Bin
  • Jiang, Rui
  • Wu, Yong-Hong
  • Wang, Ruili
  • Wu, Qing-Song

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.

Suggested Citation

  • Hu, Mao-Bin & Jiang, Rui & Wu, Yong-Hong & Wang, Ruili & Wu, Qing-Song, 2008. "Properties of wealth distribution in multi-agent systems of a complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5862-5867.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:23:p:5862-5867
    DOI: 10.1016/j.physa.2008.06.032
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    Cited by:

    1. Gogas, Periklis & Gupta, Rangan & Miller, Stephen M. & Papadimitriou, Theophilos & Sarantitis, Georgios Antonios, 2017. "Income inequality: A complex network analysis of US states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 423-437.
    2. Periklis Gogas & Rangan Gupta & Stephen M. Miller & Theophilos Papadimitriou & Georgios Antonios Sarantitis, 2015. "Income Inequality: A State-by-State Complex Network Analysis," Working Papers 201534, University of Pretoria, Department of Economics.

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