Robust Monopoly Regulation

Abstract

We study how to regulate a monopolistic firm using a robust-design, nonBayesian approach. We derive a policy that minimizes the regulator’s worst-case regret, where regret is the difference between the regulator’s complete-information payoff and his realized payoff. When the regulator’s payoff is consumers’ surplus, he caps the firm’s average revenue. When his payoff is the total surplus of both consumers and the firm, he offers a piece-rate subsidy to the firm while capping the total subsidy. For intermediate cases, the regulator combines these three policy instruments to balance three goals: protecting consumers’ surplus, mitigating underproduction, and limiting potential overproduction. (joint with Eran Shmaya)