Motivating Effort with Information about Future Rewards

TL;DR

This paper develops a framework for optimal dynamic information disclosure to motivate effort in a principal-agent setting without transfers, highlighting conditions under which dynamic disclosure enhances effort and how patience influences the policy.

Contribution

It provides a unified, closed-form solution for the optimal information policy in both stationary and nonstationary environments, identifying key conditions for the value of dynamic disclosure.

Findings

Dynamic disclosure is valuable if the principal is less patient than the agent.

In environments where the agent becomes pessimistic over time, disclosure can sustain effort.

Patience critically shapes the structure of the optimal information policy.

Abstract

This paper studies the optimal mechanism to motivate effort in a dynamic principal-agent model without transfers. An agent is engaged in a task with uncertain future rewards and can quit at any time. The principal knows the reward and provides information over time to motivate effort. We provide a unified framework and derive the optimal information policy in closed form across stationary and nonstationary environments. Within this framework, we identify two precise conditions, each of which guarantees that dynamic disclosure is strictly valuable. First, if the principal is impatient compared to the agent, she prefers the front-loaded effort schedule induced by dynamic disclosure; in a stationary environment, dynamic disclosure is beneficial if and only if the principal is less patient. Second, in an environment where the agent would become pessimistic over time absent any disclosure, dynamic information provision can counteract this downward trend and encourage longer effort. Notably, patience remains a crucial determinant of the structure of the optimal policy.