Greg Goelzhauser (Utah State University – Department of Political Science), Benjamin Kassow (University of North Dakota-Department of Political Science and Public Administration), and Douglas Rice (University of Massachusetts Amherst – Department of Political Science) have posted “Measuring Supreme Court Case Complexity” (Journal of Law, Economics, and Organization, Forthcoming) on SSRN. Here is the abstract:
Case complexity is central to the study of judicial politics. The dominant measures of Supreme Court case complexity use information on legal issues and provisions observed post-decision. As a result, scholars using these measures to study merits stage outcomes such as bargaining, voting, separate opinion production, and opinion content introduce post-treatment bias and exacerbate endogeneity concerns. Furthermore, existing issue measures are not valid proxies for complexity. Leveraging information on issues and provisions extracted from merits briefs, we develop a new latent measure of Supreme Court case complexity. This measure maps with the prevailing understanding of the underlying concept while mitigating inferential threats that hamper empirical evaluations. Our brief-based measurement strategy is generalizable to other contexts where it is important to generate exogenous and pre-treatment indicators for use in explaining merits decisions.