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Estimating Dynamic Ideal Points for State Supreme Courts

Published online by Cambridge University Press:  04 January 2017

Jason H. Windett ,
Jeffrey J. Harden  and
Matthew E. K. Hall
Jason H. Windett*
Affiliation:
Department of Political Science, Saint Louis University, 127 McGannon Hall, 3750 Lindell Blvd, St Louis, MO 63108, USA
Jeffrey J. Harden
Affiliation:
Department of Political Science, University of Colorado Boulder, 416 Fleming, UCB 333, Boulder, CO 80309, USA. e-mail: [email protected]
Matthew E. K. Hall
Affiliation:
Department of Political Science, University of Notre Dame, 217 O'Shaughnessy Hall, Notre Dame, IN 46556, USA. e-mail: [email protected]
*
e-mail: [email protected] (corresponding author)
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Abstract

Courts of last resort in the American states offer researchers considerable leverage to develop and test theories about how institutions influence judicial behavior. One measure critical to this research agenda is the individual judges' preferences, or ideal points, in policy space. Two main strategies for recovering this measure exist in the literature: Brace, Langer, and Hall's (2000, Measuring preferences of state supreme court judges, Journal of Politics 62(2):387–413) Party-Adjusted Judge Ideology and Bonica and Woodruff's (2014, A common-space measure of state supreme court ideology, Journal of Law, Economics, & Organization, doi: 10.1093/jleo/ewu016) judicial CFscores. Here, we introduce a third measurement strategy that combines CFscores with item response (IRT) estimates of judicial voting behavior in all fifty-two state courts of last resort from 1995 to 2010. We show that leveraging two distinct sources of information (votes and CFscores) yields a superior estimation strategy. Specifically, we highlight several key advantages of the combined measure: (1) it is estimated dynamically, allowing for the possibility that judges' ideological leanings change over time and (2) it maps judges into a common space. In a comparison against existing measurement strategies, we find that our measure offers superior performance in predicting judges' votes. We conclude that it is a valuable tool for advancing the study of judicial politics.

Type
Letters
Information
Political Analysis , Volume 23 , Issue 3 , Summer 2015 , pp. 461 - 469
Copyright
Copyright © The Author 2015. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Authors' note: The measures described here as well as complete replication materials are available at the Political Analysis Dataverse (Windett, Harden, and Hall 2015). This article is part of a larger research agenda by the authors on representation and state supreme courts. The ordering of names reflects a principle of rotation. We thank Mike Alvarez, Fred Boehmke, Jake Bowers, Paul Brace, David Nickerson, and Steve Rogers for helpful comments. We also thank Elizabeth Alberty, Eric Behna, Meaghan Gass, and Chad Williams for research assistance. Supplementary materials for this article are available on the Political Analysis Web site.

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