Co-écrit avec Bhaskar Dutta et Marcin Dziubinski

Abstract:

We consider a problem of mechanism design without money, where a planner selects a winner among a set of agents with binary types. We show that

the planner can leverage an outside signal (e.g. a report by an impartial referee) to elicit information about the agents' types. The optimal

Bayesian Incentive Compatible (BIC) mechanisms are lexicographic mechanisms, where the planner first shortlists agents who receive high reports from the referees and

then uses agents' reports to break ties among agents in the shortlist. We compare the ``self-evaluation'' mechanism with a ``peer evaluation'' mechanism where agents evaluate other agents, and show that for the same signal precision, the self- evaluation mechanism outperforms the peer evaluation mechanism.