Experimentation and Approval Mechanisms
研究了当代理人可以结束实验且与委托人偏好不一致时，如何设计最优审批规则。发现最优规则具有历史依赖性，审批阈值随时间下降，且私人信息可能导致代理人选择快速通道选项。
We study the design of approval rules when costly experimentation must be delegated to an agent with misaligned preferences. When the agent has the option to end experimentation, we show that in contrast to standard stopping problems, the optimal approval rule must be history‐dependent. We characterize the optimal rule and show the approval threshold moves downward over the course of experimentation. We find that private information may qualitatively change the optimal mechanism: an agent can choose a fast‐track option in the form of an initially depressed approval threshold. On expiry of the fast track, the threshold jumps up, introducing more stringent standards. Our results provide a theoretical foundation for both the loosening of approval standards on longer experimentation paths and fast‐track mechanisms.