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How Partisan Is Local Law Enforcement? Evidence from Sheriff Cooperation with Immigration Authorities

Published online by Cambridge University Press:  11 November 2019

DANIEL M. THOMPSON*
Affiliation:
Stanford University
*
*Daniel M. Thompson, PhD candidate, Department of Political Science, Stanford University, danmckinleythompson@gmail.com.

Abstract

Is local law enforcement conducted differently based on the party in power? I offer an answer to this question by focusing on a case in which law enforcement is elected and has meaningful independent discretion: sheriff compliance with federal requests to detain unauthorized immigrants. Using a regression discontinuity design in a new dataset of over 3,200 partisan sheriff elections and administrative data on sheriff behavior, I find that Democrats and Republicans comply at nearly the same rate. These results contribute to ongoing research into the role that partisanship plays in local policy making, indicating that law enforcement officers make similar choices across party lines even when they have broad authority. I also present evidence that sheriffs hold more similar immigration enforcement views across party than the general public, highlighting the role of candidate entry and selection in determining the level of partisan polarization.

Type
Research Article
Copyright
Copyright © American Political Science Association 2019 

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Footnotes

For helpful discussion, the author thanks Justin de Benedictis-Kessner, Justin Grimmer, Andy Hall, Jens Hainmueller, Mirya Holman, Nathan Lee, Hans Lueders, Clayton Nall, Sarah Thompson, Matt Tyler, Chris Warshaw, and Jesse Yoder as well as the members of the Stanford Immigration Policy Lab and the Stanford Working Group on Empirical Research in American Politics. Data on immigration enforcement were provided by the Transactional Records Access Clearinghouse (TRAC) at Syracuse University. I received support for this project from the Stanford Immigration Policy Lab. Replication files are available at the American Political Science Review Dataverse: https://doi.org/10.7910/DVN/CFASH6.

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