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Some Simple Tests of Rational Voting and Agenda Setting

Published online by Cambridge University Press:  21 October 2014

Sean Corcoran ,
Thomas Romer  and
Howard Rosenthal
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Abstract

This article analyzes election data that permit simple tests of rational voting and agenda setting. The voting test pertains to aggregate election results. The prediction is that when voters have single-peaked preferences, there will be more opposition to the second of two budget proposals that are voted on simultaneously. Unlike the standard binary choice setting, not all voters have weakly undominated voting strategies, but the game among the voters can be solved simply by iterative application of weak dominance. The agenda-setting prediction tested is that agenda setters should make one proposal rather than two when given the option. The data come from Oregon school district financial elections from 1980–83, years in which the rules for these elections were abruptly changed.

Type
Original Articles
Information
Political Science Research and Methods , Volume 3 , Issue 2 , May 2015 , pp. 155 - 168
Copyright
Copyright © The European Political Science Association 2014 

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Footnotes

Sean Corcoran is Associate Professor of Education Economics, Steinhardt School of Culture, Education, and Human Development, New York University, New York, NY 10012, USA (sean.corcoran@nyu.edu). Thomas Romer is Professor of Politics and Public Affairs in the Woodrow Wilson School and the Department of Politics, Princeton University, Princeton, NJ 08544, USA (romer@princeton.edu). Howard Rosenthal is Professor of Politics, Wilf Family Department of Politics, New York University, New York, NY 10012, USA (hr31@nyu.edu). We thank Alexander Ruder for extensive and effective research assistance. We also thank seminar participants at Columbia University for comments on an earlier draft. Thanks are also in order to the referees and the editor. The data collection for this study was supported by the Russell Sage Foundation.

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Supplementary material: Link

Corcoran et al Dataset

Dataset

http://dx.doi.org/10.7910/DVN/25893
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