IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v415y2014icp514-524.html

Agent based models for wealth distribution with preference in interaction

Author

Listed:
  • Goswami, Sanchari
  • Sen, Parongama

Abstract

We propose a set of conservative models in which agents exchange wealth with a preference in the choice of interacting agents in different ways. The common feature in all the models is that the temporary values of financial status of agents is a deciding factor for interaction. Other factors which may play important role are past interactions and wealth possessed by individuals. Wealth distribution, network properties and activity are the main quantities which have been studied. Evidence of phase transitions and other interesting features are presented. The results show that certain observations of the real economic system can be reproduced by the models.

Suggested Citation

  • Goswami, Sanchari & Sen, Parongama, 2014. "Agent based models for wealth distribution with preference in interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 514-524.
    • Handle: RePEc:eee:phsmap:v:415:y:2014:i:c:p:514-524
    DOI: 10.1016/j.physa.2014.08.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437114006967
    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.2014.08.018?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Chakrabarti,Bikas K. & Chakraborti,Anirban & Chakravarty,Satya R. & Chatterjee,Arnab, 2013. "Econophysics of Income and Wealth Distributions," Cambridge Books, Cambridge University Press, number 9781107013445.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    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. Rashkovskiy, Sergey A., 2019. "‘Bosons’ and ‘fermions’ in social and economic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 90-104.
    2. Kiran Sharma & Subhradeep Das & Anirban Chakraborti, 2017. "Global Income Inequality and Savings: A Data Science Perspective," Papers 1801.00253, arXiv.org, revised Aug 2018.
    3. David Santiago Quevedo & Carlos José Quimbay, 2020. "Non-conservative kinetic model of wealth exchange with saving of production," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 93(10), pages 1-12, October.
    4. Costas Efthimiou & Adam Wearne, 2016. "Household Income Distribution in the USA," Papers 1602.06234, arXiv.org.
    5. Hutzler, S. & Sommer, C. & Richmond, P., 2016. "On the relationship between income, fertility rates and the state of democracy in society," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 9-18.
    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. Campolieti, Michele, 2018. "Heavy-tailed distributions and the distribution of wealth: Evidence from rich lists in Canada, 1999–2017," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 263-272.
    8. Ivan D Chase & W Brent Lindquist, 2016. "The Fragility of Individual-Based Explanations of Social Hierarchies: A Test Using Animal Pecking Orders," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-16, July.
    9. Jean-Philippe Bouchaud, 2020. "How Much Income Inequality Is Too Much?," Papers 2004.09835, arXiv.org.
    10. Thitithep Sitthiyot & Kanyarat Holasut, 2024. "Income distribution in Thailand is scale-invariant," Papers 2402.01141, arXiv.org.
    11. Thitithep Sitthiyot & Kanyarat Holasut, 2020. "A simple method for measuring inequality," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 6(1), pages 1-9, December.
    12. Rashkovskiy, S.A., 2021. "Thermodynamics of markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    13. Menale, M. & Toscani, G., 2025. "Measuring inequality in society-oriented Lotka–Volterra-type kinetic equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 680(C).
    14. Kohlrausch, Gustavo L. & Gonçalves, Sebastian, 2024. "Wealth distribution on a dynamic complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 652(C).
    15. Kerim Eser Afc{s}ar & Mehmet Ozyi~git & Yusuf Yuksel & Umit Ak{i}nc{i}, 2021. "Testing the Goodwin Growth Cycles with Econophysics Approach in 2002-2019 Period in Turkey," Papers 2106.02546, arXiv.org.
    16. 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).
    17. Maia, Adriano & Matsushita, Raul & Demarcus, Antonio & Da Silva, Sergio, 2023. "Scalability in a two-class interoccupational earnings distribution model," SocArXiv 23brg, Center for Open Science.
    18. Marcelo B. Ribeiro, 2025. "Modeling Income Distribution with the Gause-Witt Population Ecology System," Papers 2506.20881, arXiv.org.
    19. Pokrovskii, Vladimir N. & Schinckus, Christophe, 2016. "An elementary model of money circulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 111-122.
    20. Thitithep Sitthiyot, 2023. "Income distribution in Thailand is scale-invariant," PLOS ONE, Public Library of Science, vol. 18(7), pages 1-9, July.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:415:y:2014:i:c:p:514-524. 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.