Estimating Dynamic Ideal Points for State Supreme Courts

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 Politics62(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.