Chain novel, or Markov chain? Estimating the authority of U.S. Supreme Court case law

Abstract

How does the authority of case law evolve over time? On the Dworkinian legal formalist view, cases increase in authority as they become more embedded in the “chain” of legal precedent, but on the Holmesian legal realist view, each case's authority is proportional to its ability to predict future legal outcomes. In this article, I show how modeling the citation network of U.S. Supreme Court case law not as a chain novel (à la Dworkin) but instead as a Markov chain (à la Holmes, or so I argue) unlocks an intuitive measure of case authority—called HolmesRank—that outperforms the existing approach in a variety of validation tasks. I then demonstrate how the authority scores produced using this Markov machinery empower the analysis of two important normative questions: (1) the ideological basis of lasting precedential authority and (2) the causal effect of the Supreme Court's citation choices on lower court compliance.