IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0103503.html

Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World

Author

Listed:
  • Benedikt Fuchs
  • Stefan Thurner

Abstract

Almost universally, wealth is not distributed uniformly within societies or economies. Even though wealth data have been collected in various forms for centuries, the origins for the observed wealth-disparity and social inequality are not yet fully understood. Especially the impact and connections of human behavior on wealth could so far not be inferred from data. Here we study wealth data from the virtual economy of the massive multiplayer online game (MMOG) Pardus. This data not only contains every player's wealth at every point in time, but also all actions over a timespan of almost a decade. We find that wealth distributions in the virtual world are very similar to those in Western countries. In particular we find an approximate exponential distribution for low wealth levels and a power-law tail for high levels. The Gini index is found to be , which is close to the indices of many Western countries. We find that wealth-increase rates depend on the time when players entered the game. Players that entered the game early on tend to have remarkably higher wealth-increase rates than those who joined later. Studying the players' positions within their social networks, we find that the local position in the trade network is most relevant for wealth. Wealthy people have high in- and out-degrees in the trade network, relatively low nearest-neighbor degrees, and low clustering coefficients. Wealthy players have many mutual friendships and are socially well respected by others, but spend more time on business than on socializing. Wealthy players have few personal enemies, but show animosity towards players that behave as public enemies. We find that players that are not organized within social groups are significantly poorer on average. We observe that “political” status and wealth go hand in hand.

Suggested Citation

  • Benedikt Fuchs & Stefan Thurner, 2014. "Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-13, August.
  • Handle: RePEc:plo:pone00:0103503
    DOI: 10.1371/journal.pone.0103503
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0103503
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0103503&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0103503?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
    ---><---

    Other versions of this item:

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World
      by Alessandro Cerboni in Knowledge Team on 2014-04-01 01:17:27

    Citations

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


    Cited by:

    1. Young Bin Kim & Sang Hyeok Lee & Shin Jin Kang & Myung Jin Choi & Jung Lee & Chang Hun Kim, 2015. "Virtual World Currency Value Fluctuation Prediction System Based on User Sentiment Analysis," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-18, August.
    2. repec:plo:pone00:0112606 is not listed on IDEAS
    3. Andres M Belaza & Jan Ryckebusch & Koen Schoors & Luis E C Rocha & Benjamin Vandermarliere, 2020. "On the connection between real-world circumstances and online player behaviour: The case of EVE Online," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-15, October.
    4. Duong, Khanh, 2025. "If inequality is an economic choice, what is the relationship between inequality and growth?," Structural Change and Economic Dynamics, Elsevier, vol. 74(C), pages 116-128.
    5. 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.
    6. Young Bin Kim & Kyeongpil Kang & Jaegul Choo & Shin Jin Kang & TaeHyeong Kim & JaeHo Im & Jong-Hyun Kim & Chang Hun Kim, 2017. "Predicting the Currency Market in Online Gaming via Lexicon-Based Analysis on Its Online Forum," Complexity, Hindawi, vol. 2017, pages 1-10, December.

    More about this item

    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:plo:pone00:0103503. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.