(Bad) Reputation in Relational Contracting

Abstract:

Motivated by reputation management in a variety of different markets for “expertise” (such as online content providers and experts in organizations), we develop a novel repeated-game framework in which a principal screens a strategic agent whose type determines the rate at which he privately receives payoff relevant information. The stage game is a bandit setting, where the principal chooses whether or not to experiment with a risky arm which is controlled by an agent who privately knows its type. Irrespective of type, the agent strategically chooses output from the arm to maximize the duration of experimentation. Experimentation is only potentially valuable to the principal if the arm is of the high type. Our main insight is that reputational incentives can be exceedingly strong: the agent makes inefficient output choices in all equilibria (subject to a mild refinement) and that this can result in market breakdown even when the uncertainty about the agent’s type is arbitrarily small. We show that (one-sided) transfers do not prevent this inefficiency and we suggest alternate ways to improve the functioning of these markets.