Full Surplus Extraction and within-period Ex Post Implementation in Dynamic Environments

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