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Prosociality in Majority Decisions: A Laboratory Experiment on the Robustness of the Uncovered Set

Published online by Cambridge University Press:  20 January 2021

Jan Sauermann Open the ORCID record for Jan Sauermann [Opens in a new window]
Jan Sauermann*
Affiliation:
Cologne Center for Comparative Politics, University of Cologne, Cologne, Germany; Department of Social Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
*
Corresponding author. Email: jan.sauermann@uni-koeln.de; Twitter: @jan_sauermann
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Abstract

Social choice theory demonstrates that majority rule is generically indeterminate. However, from an empirical perspective, large and arbitrary policy shifts are rare events in politics. The uncovered set (UCS) is the dominant preference-based explanation for the apparent empirical predictability of majority rule in multiple dimensions. Its underlying logic assumes that voters act strategically, considering the ultimate consequences of their actions. I argue that all empirical applications of the UCS rest on an incomplete behavioral model assuming purely egoistically motivated individuals. Beyond material self-interest, prosocial motivations offer an additional factor to explain the outcomes of majority rule. I test my claim in a series of committee decision-making experiments in which I systematically vary the fairness properties of the policy space while keeping the location of the UCS constant. The experimental results overwhelmingly support the prosociality explanation.

Keywords

Chaos theoremscommittee decision-makingprosocialitymajority ruleuncovered set
Type
Research Article
Information
Journal of Experimental Political Science , Volume 9 , Issue 1 , Spring 2022 , pp. 22 - 35
Copyright
© The Author(s) 2021. Published by Cambridge University Press on behalf of The Experimental Research Section of the American Political Science Association

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Footnotes

This work has received generous funding from the Center for Social and Economic Behavior (C-SEB) at the University of Cologne. Financial support from the German Research Foundation (DFG) for the Cologne Laboratory for Economic Research is also gratefully acknowledged. I am grateful to Paul Beckmann for helping me conducting the experiments and Anne Kailuweit for her research assistance. I would also like to thank seminar and presentation participants at Cologne, Vienna, Oldenburg, Konstanz, EPSA (Vienna), and DVPW (Frankfurt) as well as the Associate Editor, three anonymous reviewers, André Kaiser, Bernhard Kittel, Ingo Rohlfing, and the members of the Kölumni-network for many helpful comments on prior versions of this manuscript. The data, code, and any additional materials required to replicate all analyses in this article are available at the Journal of Experimental Political Science Dataverse within the Harvard Dataverse Network, at: doi:10.1017/XPS.2020.43 (Sauermann 2020c). The author declares that there is no conflict of interest.

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