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Information Provision, Voter Coordination, and Electoral Accountability: Evidence from Mexican Social Networks

Published online by Cambridge University Press:  19 March 2019

ERIC ARIAS*
Affiliation:
College of William and Mary
PABLO BALÁN*
Affiliation:
Harvard University
HORACIO LARREGUY*
Affiliation:
Harvard University
JOHN MARSHALL*
Affiliation:
Columbia University
PABLO QUERUBÍN*
Affiliation:
New York University
*
*Eric Arias, Assistant Professor, Department of Government, College of William and Mary, [email protected].
Pablo Balán, Graduate Student, Department of Government, Harvard University, [email protected].
Horacio Larreguy, Associate Professor, Department of Government, Harvard University, [email protected].
**John Marshall, Assistant Professor, Department of Political Science, Columbia University, [email protected].
††Pablo Querubín, Associate Professor, Department of Politics, New York University, [email protected].

Abstract

How do social networks moderate the way political information influences electoral accountability? We propose a simple model in which incumbent malfeasance revelations can facilitate coordination around less malfeasant challenger parties in highly connected voter networks, even when voters update favorably about incumbent party malfeasance. We provide evidence from Mexico of this mechanism by leveraging a field experiment in a context where the provision of incumbent malfeasance information increased support for incumbent parties, despite voters continuing to believe that challengers were less malfeasant than incumbents. Combining this experiment with detailed family network data, we show that—consistent with the model—the increase in incumbent party vote share due to information provision was counteracted by coordination around less malfeasant challengers in precincts with greater network connectedness. Individual-level data further demonstrate that networks facilitated explicit and tacit coordination among voters. These findings suggest that networks can help voters coordinate around information to help remove poorly performing politicians.

Type
Research Article
Copyright
Copyright © American Political Science Association 2019 

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Footnotes

We thank Francisco Cantú, Donghyun Danny Choi, Anirvan Chowdhury, Juan Dodyk, Thad Dunning, Ryan Enos, Fran Hagopian, Bhumi Purohit, Shanker Satyanath, Alastair Smith, Daniel Smith, David Stasavage, Yuhua Wang, and Xiang Zhou, and seminar participants at APSA, Berkeley, Harvard, MIT, and MPSA for valuable feedback. The experimental component of this study was financed by the EGAP Metaketa initiative, and was approved by the Harvard Committee on the Use of Human Subjects (15-1068) and the New York University Committee on Activities Involving Human Subjects (15-10587). Replication files are available at the American Political Science Review Dataverse: https://doi.org/10.7910/DVN/8IWRBI.

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