Statistical Evidence and the Problem of Robust Litigation

We develop a model of statistical evidence with a sophisticated Bayesian fact-i¬ nder. The context is litigation, where a litigant (defendant or plaintiff) may disclose hard evidence and a jury (the fact-finder) interprets it. In addition to hard evidence, the litigant has private unverii¬ able information. We study the robustness of the parties' reasoning regarding the legal fundamentals and the litigant's strategic behavior. The litigant's choice of whether to disclose hard evidence entails two channels of information: the face-value signal of the hard evidence disclosure (relating to the probabilities that the hard evidence exists in different states of the world) and as a possible signal of the litigant's private information. Our results suggest that in some situations, a desire for robust reasoning about evidence would lead the court to restrict the admissibility of some relevant evidence. The modeling exercise provides support for the Federal Rules of Evidence Rules 403 and 404, along with general conclusions about evidence policy.