This paper proposes a new semi‐parametric identification and estimation approach to multinomial choice models in a panel data setting with individual fixed effects. Our approach is based on cyclic monotonicity, which is a defining convex‐analytic feature of the random utility framework underlying multinomial choice models. From the cyclic monotonicity property, we derive identifying inequalities without requiring any shape restrictions for the distribution of the random utility shocks. These inequalities point identify model parameters under straightforward assumptions on the covariates. We propose a consistent estimator based on these inequalities.

We quantify the effect of deliberation on the decisions of US appellate courts. We estimate a model in which strategic judges communicate before casting their votes and then compare the probability of mistakes in the court with deliberation with a counterfactual of no communication. The model has multiple equilibria, and preferences and information parameters are only partially identified. We find that there is a range of parameters in the identified set—when judges tend to disagree ex ante or their private information is imprecise—in which deliberation can be beneficial; otherwise, deliberation reduces the effectiveness of the court.