Optimal Platform Design

Search and matching increasingly takes place on online platforms. These platforms have elements of centralized and decentralized matching; platforms can alter the search process for its users, but are unable to eliminate search frictions entirely. I study a model where platforms can change the distribution of potential partners that an agent searches over and characterize search equilibria on platforms. When agents possess private information about their match characteristics and the platform designer acts as a profit maximizing monopolist, I characterize the optimal platform. If match characteristics are complementary and utility is transferable, I show that the only possible source of inefficiency in the optimal platform is exclusion, unlike standard non-linear pricing problems. That is, the optimal platform is efficient conditional on inclusion. Matching on the optimal platform is perfectly assortative -- there is no equilibrium mismatch.