Bayesian comparative statics
研究贝叶斯博弈中信号信息量变化如何影响均衡行动分布，聚焦超模环境，给出私人信号精度导致均衡行动均值扩散的条件，并应用于发送者与多个接收者的信息披露博弈。
We study how changes to the informativeness of signals in Bayesian games and single‐agent decision problems affect the distribution of equilibrium actions. Focusing on supermodular environments, we provide conditions under which a more precise private signal for one agent leads to an increasing‐mean spread or a decreasing‐mean spread of equilibrium actions for all agents. We apply our comparative statics to information disclosure games between a sender and many receivers and derive sufficient conditions on the primitive payoffs that lead to extremal disclosure of information.