IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v594y2022ics0378437122000802.html
   My bibliography  Save this article

Constructing games on networks for controlling the inequalities in the capital distribution

Author

Listed:
  • Miszczak, Jarosław Adam

Abstract

The inequality in capital or resource distribution is among the important phenomena observed in populations. The sources of inequality and methods for controlling it are of practical interest. To study this phenomenon, we introduce a model of interaction between agents in the network designed for the purpose of reducing the inequality in the distribution of capital. To achieve the effect of inequality reduction we interpret the outcome of the elementary game played in the network such that the wining the game is translated into the reduction of the inequality. We study different interpretations of the introduced scheme and their impact on the behaviour of agents in the terms of the capital distribution and we provide examples based on the capital dependent Parrondo’s paradox. The results presented in this study provide insight into the mechanics of the inequality formation in the society.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:594:y:2022:i:c:s0378437122000802
    DOI: 10.1016/j.physa.2022.126997
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122000802
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2022.126997?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. A. Szolnoki & M. Perc & G. Szabó, 2008. "Diversity of reproduction rate supports cooperation in the prisoner's dilemma game on complex networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 61(4), pages 505-509, February.
    2. 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.
    3. Francisco C. Santos & Marta D. Santos & Jorge M. Pacheco, 2008. "Social diversity promotes the emergence of cooperation in public goods games," Nature, Nature, vol. 454(7201), pages 213-216, July.
    4. Cowell, Frank, 2011. "Measuring Inequality," OUP Catalogue, Oxford University Press, edition 3, number 9780199594047.
    5. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
    6. Ye, Ye & Zhang, Xin-shi & Liu, Lin & Xie, Neng-Gang, 2021. "Effects of group interactions on the network Parrondo’s games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    7. Gregory P. Harmer & Derek Abbott, 1999. "Losing strategies can win by Parrondo's paradox," Nature, Nature, vol. 402(6764), pages 864-864, December.
    8. George Deltas, 2003. "The Small-Sample Bias of the Gini Coefficient: Results and Implications for Empirical Research," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 226-234, February.
    9. Karataieva, Tatiana & Koshmanenko, Volodymyr & Krawczyk, Małgorzata J. & Kułakowski, Krzysztof, 2019. "Mean field model of a game for power," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 535-547.
    10. Derek De Solla Price, 1976. "A general theory of bibliometric and other cumulative advantage processes," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 27(5), pages 292-306, September.
    11. Victor M. Yakovenko & J. Barkley Rosser, 2009. "Colloquium: Statistical mechanics of money, wealth, and income," Papers 0905.1518, arXiv.org, revised Dec 2009.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Xiaoliang & Zhou, Peng, 2022. "Wealth inequality and social mobility: A simulation-based modelling approach," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 307-329.
    2. Max Greenberg & H. Oliver Gao, 2024. "Twenty-five years of random asset exchange modeling," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(6), pages 1-27, June.
    3. Costas Efthimiou & Adam Wearne, 2016. "Household Income Distribution in the USA," Papers 1602.06234, arXiv.org.
    4. Ngo-Hoang, Dai-Long, 2019. "A research paper of Hossein Sabzian (2019), Theories and Practice of Agent based Modeling: Some practical Implications for Economic Planners, ArXiv, 54p," AgriXiv xutyz_v1, Center for Open Science.
    5. Miguel A. Márquez & Elena Lasarte & Marcelo Lufin, 2019. "The Role of Neighborhood in the Analysis of Spatial Economic Inequality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 245-273, January.
    6. Venkatasubramanian, Venkat & Luo, Yu & Sethuraman, Jay, 2015. "How much inequality in income is fair? A microeconomic game theoretic perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 435(C), pages 120-138.
    7. Liang, Rizhou & Zhang, Jiqiang & Zheng, Guozhong & Chen, Li, 2021. "Social hierarchy promotes the cooperation prevalence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    8. Lorenzo Pareschi & Giuseppe Toscani, 2014. "Wealth distribution and collective knowledge. A Boltzmann approach," Papers 1401.4550, arXiv.org.
    9. Fan, Ruguo & Zhang, Yingqing & Luo, Ming & Zhang, Hongjuan, 2017. "Promotion of cooperation induced by heterogeneity of both investment and payoff allocation in spatial public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 454-463.
    10. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.
    11. Smerlak, Matteo, 2016. "Thermodynamics of inequalities: From precariousness to economic stratification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 40-50.
    12. Mimkes, Jürgen, 2010. "Stokes integral of economic growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1665-1676.
    13. Tatjana Miljkovic & Ying-Ju Chen, 2021. "A new computational approach for estimation of the Gini index based on grouped data," Computational Statistics, Springer, vol. 36(3), pages 2289-2311, September.
    14. Stein, Julian Alexander Cornelius & Braun, Dieter, 2019. "Stability of a time-homogeneous system of money and antimoney in an agent-based random economy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 232-249.
    15. Hossein Sabzian & Mohammad Ali Shafia & Ali Maleki & Seyeed Mostapha Seyeed Hashemi & Ali Baghaei & Hossein Gharib, 2019. "Theories and Practice of Agent based Modeling: Some practical Implications for Economic Planners," Papers 1901.08932, arXiv.org.
    16. Tao, Yong, 2015. "Universal laws of human society’s income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 435(C), pages 89-94.
    17. Yu, Fengyuan & Wang, Jianwei & Chen, Wei & He, Jialu, 2023. "Increased cooperation potential and risk under suppressed strategy differentiation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
    18. Deng, Zheng-Hong & Huang, Yi-Jie & Gu, Zhi-Yang & Liu, Dan & Gao, Li, 2018. "Multi-games on interdependent networks and the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 83-90.
    19. Kaldasch, Joachim, 2012. "Evolutionary model of the personal income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5628-5642.
    20. Park, Ji-Won & Kim, Chae Un & Isard, Walter, 2012. "Permit allocation in emissions trading using the Boltzmann distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4883-4890.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:594:y:2022:i:c:s0378437122000802. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.