Conveying value via categories
研究卖方通过单调分类传递商品质量信息的最优策略，发现完全混合优于完全分离，并应用于教育机构设计评分方案以平衡信号传递与学习激励。
A sender sells an object of unknown quality to a receiver who pays his expected value for it. Sender and receiver might hold different priors over quality. The sender commits to a monotone categorization of quality. We characterize the sender's optimal monotone categorization, the optimality of full pooling or full separation, and make precise a sense in which pooling is dominant relative to separation. As an application, we study the design of a grading scheme by an educational institution that seeks to signal student qualities and simultaneously incentivize students to learn. We show how these incentive constraints are embedded as a distortion of the school's prior over student qualities, generating a monotone categorization problem with distinct sender and receiver priors.