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Relaxation in statistical many-agent economy models

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  • Marco Patriarca
  • Anirban Chakraborti
  • Els Heinsalu
  • Guido Germano

Abstract

We review some statistical many-agent models of economic and social systems inspired by microscopic molecular models and discuss their stochastic interpretation. We apply these models to wealth exchange in economics and study how the relaxation process depends on the parameters of the system, in particular on the saving propensities that define and diversify the agent profiles.

Suggested Citation

  • Marco Patriarca & Anirban Chakraborti & Els Heinsalu & Guido Germano, 2006. "Relaxation in statistical many-agent economy models," Papers physics/0608174, arXiv.org, revised Aug 2008.
    • Handle: RePEc:arx:papers:physics/0608174
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    References listed on IDEAS

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    1. Arnab Das & Sudhakar Yarlagadda, 2003. "A distribution function analysis of wealth distribution," Papers cond-mat/0310343, arXiv.org.
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    Cited by:

    1. Kiran Sharma & Anirban Chakraborti, 2016. "Physicists' approach to studying socio-economic inequalities: Can humans be modelled as atoms?," Papers 1606.06051, arXiv.org, revised Aug 2018.
    2. Sokolov, Andrey & Melatos, Andrew & Kieu, Tien, 2010. "Laplace transform analysis of a multiplicative asset transfer model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2782-2792.
    3. Andrey Sokolov & Andrew Melatos & Tien Kieu, 2010. "Laplace transform analysis of a multiplicative asset transfer model," Papers 1004.5169, arXiv.org.
    4. Düring, Bertram & Matthes, Daniel & Toscani, Giuseppe, 2008. "A Boltzmann-type approach to the formation of wealth distribution curves," CoFE Discussion Papers 08/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    5. Rem Sadykhov & Geoffrey Goodell & Denis de Montigny & Martin Schoernig & Philip Treleaven, 2023. "Decentralized Token Economy Theory (DeTEcT)," Papers 2309.12330, arXiv.org, revised Jan 2024.
    6. Rem Sadykhov & Geoffrey Goodell & Philip Treleaven, 2024. "DeTEcT: Dynamic and Probabilistic Parameters Extension," Papers 2405.16688, arXiv.org.

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