Using Persistence to Generate Incentives in a Dynamic Moral Hazard Problem

Abstract

This paper studies how persistence can be used to create incentives in a continuous-time stochastic game in which a long-run player interacts with a sequence of short-run players. Observation of the long-run player's actions are distorted by a Brownian motion and the actions of both players impact future payoffs through a state variable. For example, a firm or worker provides customers with a product, and the quality of this product depends on both current and past investment choices by the rm. I derive general conditions under which a Markov equilibrium emerges as the unique perfect public equilibrium, and characterize the equilibrium payoff and actions in this equilibrium, for any discount rate. I develop an application of persistent product quality to illustrate how persistence creates effective intertemporal incentives in a setting where traditional channels fail, and explore how the structure of persistence impacts equilibrium behavior. This demonstrates the power of the continuous-time setting to deliver sharp insights and a tractable equilibrium characterization for a rich class of dynamic games.