Full surplus extraction and within-period ex post implementation in dynamic environments
研究了在动态环境中如何利用代理人类型的跨期相关性设计期内事后激励相容机制，以实现完全剩余提取和分配规则实施，为机制设计者提供了可操作的条件。
We study full surplus extraction and implementation in dynamic environments. We exploit intertemporal correlations of agents' types to construct within-period ex post incentive compatible mechanisms. First, we formulate one-shot environments, in which a single agent has a hidden type and the planner observes a public signal about the agent's type after a type-contingent allocation is chosen. We propose necessary and sufficient conditions for full surplus extraction (strong detectability) and for implementability of the targeted allocation rule (weak detectability) in this one-shot problem. We decompose the general dynamic problem into one-shot problems, and obtain sufficient conditions for surplus extraction and implementation.