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Simulating the wealth distribution with a Richest-Following strategy on scale-free network

Author

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

Abstract

In this paper, we investigate the wealth distribution with agents playing evolutionary games on a scale-free social network adopting the Richest-Following strategy. Pareto's power-law distribution (1897) of wealth is demonstrated with power factor in agreement with that of US or Japan. Moreover, 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 agrees with the Matthew Effect.

Suggested Citation

  • Hu, Mao-Bin & Jiang, Rui & Wu, Qing-Song & Wu, Yong-Hong, 2007. "Simulating the wealth distribution with a Richest-Following strategy on scale-free network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 467-472.
    • Handle: RePEc:eee:phsmap:v:381:y:2007:i:c:p:467-472
    DOI: 10.1016/j.physa.2007.03.021
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    Citations

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    Cited by:

    1. Yongkui Liu & Xiaojie Chen & Lin Zhang & Long Wang & Matjaž Perc, 2012. "Win-Stay-Lose-Learn Promotes Cooperation in the Spatial Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    2. Miszczak, Jarosław Adam, 2022. "Constructing games on networks for controlling the inequalities in the capital distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    3. Victor M. Yakovenko, 2007. "Econophysics, Statistical Mechanics Approach to," Papers 0709.3662, arXiv.org, revised Aug 2008.
    4. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
    5. Zanin, Massimiliano & Papo, David & Romance, Miguel & Criado, Regino & Moral, Santiago, 2016. "The topology of card transaction money flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 134-140.
    6. Hua, Mingzhuang & Chen, Xuewu & Chen, Jingxu & Huang, Di & Cheng, Long, 2022. "Large-scale dockless bike sharing repositioning considering future usage and workload balance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    7. Geng, Yini & Liu, Yifan & Lu, Yikang & Shen, Chen & Shi, Lei, 2022. "Reinforcement learning explains various conditional cooperation," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    8. Stefan, F.M. & Atman, A.P.F., 2023. "Asymmetric rate of returns and wealth distribution influenced by the introduction of technical analysis into a behavioral agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    9. Tomson Ogwang, 2011. "Power laws in top wealth distributions: evidence from Canada," Empirical Economics, Springer, vol. 41(2), pages 473-486, October.
    10. Sanz Nogales, Jose M. & Zazo, S., 2020. "Replicator based on imitation for finite and arbitrary networked communities," Applied Mathematics and Computation, Elsevier, vol. 378(C).
    11. Massimiliano Zanin & David Papo & Miguel Romance & Regino Criado & Santiago Moral, 2016. "The topology of card transaction money flows," Papers 1605.04938, arXiv.org.
    12. Ogwang, Tomson, 2013. "Is the wealth of the world’s billionaires Paretian?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 757-762.
    13. Li, Jun-fang & Zhang, Bu-han & Liu, Yi-fang & Wang, Kui & Wu, Xiao-shan, 2012. "Spatial evolution character of multi-objective evolutionary algorithm based on self-organized criticality theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5490-5499.
    14. Liu, Yongkui & Chen, Xiaojie & Zhang, Lin & Tao, Fei & Wang, Long, 2012. "Does migration cost influence cooperation among success-driven individuals?," Chaos, Solitons & Fractals, Elsevier, vol. 45(11), pages 1301-1308.

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