Overcoming Incentive Constraints

Abstract

Consider an arbitrary Bayesian decision problem in which the preferences of each agent are private information. We prove that the utility costs associated with incentive constraints typically decrease when the decision problem is linked with independent copies of itself. This is established by first defining a mechanism in which agents must budget their representations of preferences so that the frequency of preferences across problems mirrors the underlying distribution of preferences, and then arguing that agents will satisfy their budget by being as truthful as possible. Examples illustrate the disappearance of incentive costs when problems are linked in a rich variety of problems, including public goods allocation, voting, and bargaining