Contracting over persistent information

TL;DR

This paper studies a dynamic moral hazard setting where a principal incentivizes an agent through information disclosure, showing optimal strategies depend on the agent's learning and patience levels.

Contribution

It characterizes the structure of optimal disclosure contracts in a dynamic moral hazard model with persistent information and learning.

Findings

Optimal contracts involve early stopping of disclosure when the agent's best response is static.

If the agent learns the state, it occurs in finite time with probability one.

Greater patience of the agent delays the learning process.

Abstract

We consider a dynamic moral hazard problem between a principal and an agent, where the sole instrument the principal has to incentivize the agent is the disclosure of information. The principal aims at maximizing the (discounted) number of times the agent chooses a particular action, e.g., to work hard. We show that there exists an optimal contract, where the principal stops disclosing information as soon as its most preferred action is a static best reply for the agent or else continues disclosing information until the agent perfectly learns the principal's private information. If the agent perfectly learns the state, he learns it in finite time with probability one; the more patient the agent, the later he learns it.