Uncertainty in Mechanism Design

We consider mechanism design problems with Knightian uncertainty formalized using incomplete preferences, as in Bewley (1986). Without completeness, decision making depends on a set of beliefs, and an action is preferred to another if and only if it has larger expected utility for all beliefs in this set. We consider two natural notions of incentive compatibility in this setting: maximal incentive compatibility requires that no strategy has larger expected utility than reporting truthfully for all beliefs, while optimal incentive compatibility requires that reporting truthfully has larger expected utility than all other strategies for all beliefs. In a model with a continuum of types, we show that optimal incentive compatibility is equivalent to ex-post incentive compatibility under fairly general conditions on beliefs. In a model with a discrete type space, we characterize full extraction of rents generated from private information. We show that full extraction is generically possible with maximal incentive compatible mechanisms, but requires su ¢ cient disagreement across types, which neither holds nor fails generically, with optimal incentive compatible mechanisms