Bargaining over Treatment Choice under Disagreement
一群持有不同先验信念的专家必须选择一种治疗方案。公开数据集导致信念更新，专家通过纳什讨价还价解决分歧，但可能导致信息利用低效，表现为所有状态下收益更低。
A group of experts with different prior beliefs must choose a treatment. A dataset is made public and leads to revisions of beliefs. We propose a model where the experts’ disagreements are resolved through bargaining, using the Nash bargaining solution. Experts bargain after disclosure of the dataset. Bargaining may lead to an inefficient use of information in a strong sense: experts receive a lower payoff in every state and for any prior belief (i.e., inadmissibility). Bargaining exhibits underreaction to information as compared to the normative solution in which experts bargain ex ante on the procedure used to exploit the data.