Information design in competitive insurance markets
研究了竞争性保险市场中监管者如何设计最优评级系统，以最小化事前风险并满足参与约束，发现最优系统下所有个体都交易且评级将低成本与高成本类型负向匹配。
This paper characterizes the optimal information structure in competitive insurance markets with adverse selection. We consider a regulator that assigns ratings to individuals according to their expected costs. Insurers observe these ratings and compete as in Akerlof (1970). The optimal rating system minimizes ex-ante risk subject to participation constraints. We prove that in any such market there exists a unique optimal system under which all individuals trade and the ratings match low-cost types with high-cost types negative assortatively. We provide a simple algorithm that yields the optimal system and examine implications for government regulations of insurance markets.