A New and Interesting Take on Measuring Case Complexity
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Most judicial decisionmaking papers can be criticized for inadequately controlling for variation in “case complexity.” Lingering disputes over what “complexity” even means in terms of litigated cases only increase the degree of difficulty in constructing such a control. And even if a consensus on what “case complexity” means existed, constructing a reliable, consistent, and stable measure introduces additional challenges.
Difficulties, conceptual and mechanical, aside, a recent paper, Measuring Supreme Court Case Complexity, makes a helpful contribution. In it, Greg Goelzhauser (Utah State–Poli Sci) et al., both critique an array of earlier efforts and advance their own Bayesian measurement model to construct a latent (Supreme Court) case complexity measure that exploits issue and provision counts from the cases’ merits briefs. By measuring case complexity from pre-decision data (merits briefs) the paper argues that its ex poste approach “diminishes endogeneity and post-treatment bias concerns when studying merits stage outcomes.” To develop its measure, the authors draw from issue and provision (hand-coded) counts extracted from merits briefs filed in the 1954 through 2017 Court Terms, incident to Supreme Court Rules 24(1)(a) and 24(1)(f).
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