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Public Voting and Prosocial Behavior

Published online by Cambridge University Press:  05 March 2019

Rebecca B. Morton  and
Kai Ou
Rebecca B. Morton*
Affiliation:
Department of Politics, NYU NYC and NYU Abu Dhabi, New York, NY 10012, USA
Kai Ou
Affiliation:
Department of Political Science, Florida State University, Tallahassee, FL 32306, USA, e-mail: kou@fsu.edu
*
*Corresponding author. Email: rebecca.morton@nyu.edu
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Abstract

One argument against secret ballots is that such procedures lead to more selfish voting behavior and that public voting can increase prosocial voting and the likelihood of prosocial outcomes when voters are not subject to intimidation and coercion from outside interests. We investigate this supposition as well as voter preferences over observability in voting in this context. We find that voters are significantly more likely to choose unselfishly when voting is public. These differences in behavior advantage prosocial choices in elections (by 27%) when voting is public. Moreover, voters appear to recognize these differences and a substantial minority of voters whose selfish preference is not the prosocial choice willingly choose public voting even though the likely outcome will be costly to themselves.

Keywords

Laboratory experimentprosocial votingobservability
Type
Research Article
Information
Journal of Experimental Political Science , Volume 6 , Issue 3 , Winter 2019 , pp. 141 - 158
Copyright
© The Experimental Research Section of the American Political Science Association 2019 

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Footnotes

Support for this research from New York University is gratefully acknowledged. We appreciate the comments of Bernd Beber, Eric Dickson, Jon Eguia, Ignacio Esponda, Timothy Feddersen, Guillaume Fréchette, Jens Großer, Sera Linardi, Reuben Kline, Dorothea Kübler, Salvatore Nunnari, and especially Ernesto Reuben whose suggestions greatly improved the paper. Earlier versions of this paper were presented at the WZB Berlin Social Sciences Center, the Center for Experimental Social Sciences, Columbia University, New York University, University of Rochester, University of Warwick, Shanghai Jiao Tong University, and the University of Pittsburgh Behavioral Models Conference. We thank the participants for their comments and suggestions. We also thank Han Il Chang, Dominik Duell, Jorge Gallego, Tianyang Xi, and Biling Zhang for their assistance in conducting the experiments. All errors remain the responsibility of the authors. 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: https://doi.org/10.7910/DVN/NCH88M (Morton and Ou 2018). The experiment was approved by the New York University Institutional Review Board. There are no conflicts of interest.

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