This paper develops a “consensus voting” model for estimating preferences of judges on federal circuit courts. Rather than assuming sincere voting, as is typical in ideal point estimation, this model accounts for the norm of consensus in the courts of appeals by including a “cost of dissent” in the judicial utility function. A test of the consensus voting model using a data set of asylum appeals in the Ninth Circuit demonstrates that it provides a substantially better fit and generates more accurate predictions of voting probabilities than a comparable sincere voting model. The model generates credible estimates of the impact of panel composition on case outcomes, which is surprisingly large in the asylum cases. Even though 95% of these decisions were unanimous, roughly half could have been decided differently if assigned to a different panel.
Joshua Fischman, Estimating Preferences of Circuit Judges: A Model of Consensus Voting, 54 Journal of Law & Economics 781–809 (2011).