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Alliance Formation in a Side-Taking Experiment

Published online by Cambridge University Press:  03 August 2018

Peter DeScioli  and
Erik O. Kimbrough
Peter DeScioli
Affiliation:
Department of Political Science, Stony Brook University, Stony Brook, NY 11794-4392, USA e-mail: pdescioli@gmail.com
Erik O. Kimbrough
Affiliation:
Smith Institute for Political Economy and Philosophy, Chapman University, Orange, CA 92866, USA e-mail: ekimbrou@chapman.edu
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Abstract

We investigate in an economic experiment how people choose sides in disputes. In an eight-player side-taking game, two disputants at a time fight over an indivisible resource and other group members choose sides. The player with more supporters wins the resource, which is worth real money. Conflicts occur spontaneously between any two individuals in the group. Players choose sides by ranking their loyalties to everyone else in the group, and they automatically support the disputant they ranked higher. We manipulate participants’ information about other players’ loyalties and also their ability to communicate with public chat messages. We find that participants spontaneously and quickly formed alliances, and more information about loyalties caused more alliance-building. Without communication, we observe little evidence of bandwagon or egalitarian strategies, but with communication, some groups invented rank rotation schemes to equalize payoffs while choosing the same side to avoid fighting costs.

Keywords

Alliancesbandwagonegalitarianconflictexperimental economics
Type
Research Article
Information
Journal of Experimental Political Science , Volume 6 , Issue 1 , Spring 2019 , pp. 53 - 70
Copyright
Copyright © The Experimental Research Section of the American Political Science Association 2018 

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Footnotes

We thank Morimitsu Kurino, Rahmi Ilkilic, Bettina Klaus, Rob Kurzban, Ronald Peeters, Dotan Persitz, Dave Porter, and Bart Wilson for comments. We thank participants in seminars at the University of Arkansas, Simon Fraser University, the New York Area Political Psychology Meeting, the NYU CESS Experimental Political Science Conference, and the Yale Center for the Study of American Politics Conference. We thank Ian Mark for computer programming of the experiment software. We thank Bay Mcculloch for research assistance. This research was supported by a grant from the International Foundation for Research in Experimental Economics (IFREE). The authors declare no potential conflicts of interest. The data, code, and all analyses in this article are available at the JEPS Dataverse at doi: 10.7910/DVN/1KIEXG.

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