A principal-agent model of sequential testing
研究了动态信息获取过程中的最优激励设计，代理人可获取对委托人决策有用的成本信息，但努力和信号结果均不可观测。分析了代理人无私人信息及有初始私人信息时的最优机制，发现代理人仅在消息与状态一致时获得奖励，且正确宣布好状态的支付随时间递增。
This paper analyzes the optimal provision of incentives in a dynamic information acquisition process. In every period, the agent can acquire costly information that is relevant to the principal's decision. Each signal may or may not provide definitive evidence in favor of the good state. Neither the agent's effort nor the realizations of his signals are observable. First, we assume that the agent has no private information at the time of contracting. Under the optimal mechanism, the agent is rewarded only when his messages are consistent with the state. The payments that the agent receives when he correctly announces the good state increase over time. We then characterize the optimal mechanisms when the agent has superior information about the state at the outset of the relationship. The principal prefers to offer different contracts if and only if the agent types are sufficiently diverse. Finally, all agent types benefit from their initial private information.