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The Rich Are Different!: Pareto Law from asymmetric interactions in asset exchange models

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  • Sitabhra Sinha

Abstract

It is known that asset exchange models with symmetric interaction between agents show either a Gibbs/log-normal distribution of assets among the agents or condensation of the entire wealth in the hands of a single agent, depending upon the rules of exchange. Here we explore the effects of introducing asymmetry in the interaction between agents with different amounts of wealth (i.e., the rich behave differently from the poor). This can be implemented in several ways: e.g., (1) in the net amount of wealth that is transferred from one agent to another during an exchange interaction, or (2) the probability of gaining vs. losing a net amount of wealth from an exchange interaction. We propose that, in general, the introduction of asymmetry leads to Pareto-like power law distribution of wealth.

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  • Sitabhra Sinha, 2005. "The Rich Are Different!: Pareto Law from asymmetric interactions in asset exchange models," Papers physics/0504197, arXiv.org.
    • Handle: RePEc:arx:papers:physics/0504197
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    References listed on IDEAS

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    Cited by:

    1. Guy Katriel, 2015. "The Immediate Exchange model: an analytical investigation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(1), pages 1-6, January.
    2. Derzsy, N. & Néda, Z. & Santos, M.A., 2012. "Income distribution patterns from a complete social security database," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5611-5619.
    3. Néda, Zoltán & Gere, István & Biró, Tamás S. & Tóth, Géza & Derzsy, Noemi, 2020. "Scaling in income inequalities and its dynamical origin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    4. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.
    5. Willis, Geoff, 2011. "Why money trickles up – wealth & income distributions," MPRA Paper 30851, University Library of Munich, Germany.
    6. Hegyi, Géza & Néda, Zoltán & Augusta Santos, Maria, 2007. "Wealth distribution and Pareto's law in the Hungarian medieval society," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 271-277.
    7. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    8. N. Derzsy & Z. Neda & M. A. Santos, 2012. "Income distribution patterns from a complete social security database," Papers 1203.1880, arXiv.org.
    9. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 9, Edward Elgar Publishing.
    10. Zoltan Neda & Istvan Gere & Tamas S. Biro & Geza Toth & Noemi Derzsy, 2019. "Scaling in Income Inequalities and its Dynamical Origin," Papers 1911.02449, arXiv.org, revised Mar 2020.
    11. Lux, Thomas, 2008. "Applications of statistical physics in finance and economics," Kiel Working Papers 1425, Kiel Institute for the World Economy (IfW Kiel).
    12. Vázquez-Montejo, J. & Huerta-Quintanilla, R. & Rodríguez-Achach, M., 2010. "Wealth condensation in a Barabasi–Albert network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1464-1470.

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