Behavioral and network origins of wealth inequality: insights from a virtual world

10793 6 54758 2 153888 document 54758 Behavioral and Network Origins of Wealth Inequality.PDF application/pdf 56887479a42a4f9289993a72a5276edb MD5 1213789 2016-05-09 13:52:36 https://pure.iiasa.ac.at/id/eprint/10793/1/Behavioral%20and%20Network%20Origins%20of%20Wealth%20Inequality.PDF 10793 1 1 application/pdf text en public cc_by

Behavioral and Network Origins of Wealth Inequality.PDF

published 54759 2 153891 document 54759 lightbox.jpg image/png ac618414c643eefce778e38fcb05da0a MD5 65776 2016-05-09 13:52:50 https://pure.iiasa.ac.at/id/eprint/10793/2/lightbox.jpg 10793 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/54758 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/54758 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/54758 archive 351 disk0/00/01/07/93 2016-01-15 08:50:13 2021-08-27 17:39:37 2016-01-15 08:50:13 article show Fuchs B. Thurner S. 1918 Behavioral and network origins of wealth inequality: insights from a virtual world pub iis_sys iis_ecn prog_asa 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 g=65, 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. 2014-08 published Public Library of Science (PLoS) 10.1371/journal.pone.0103503 XJ-14-258 PLoS ONE; 9(8):103503 (August 2014) [doi:10.1371/journal.pone.0103503] 307 public PLoS ONE 9 8 103503 TRUE 1932-6203 FALSE info:eu-repo/semantics/article