Optimal Contract Design with Moral Hazard: A Detail-Free Guidance

In this article, we explore how much a principal (person or entity that hires an agent) can learn about an agent’s performance through rich monitoring data. We focus on moral hazard problems, where the agent has an incentive to exert less effort as they are paid based on their performance.
To understand this concept, imagine you hire a gardener to take care of your lawn. You want them to work hard and make sure your lawn looks great, but they might have an incentive to slack off if they know they’ll only be paid based on how well the lawn does. In this case, monitoring their progress closely could help you identify any issues and adjust their pay accordingly.
Our main result shows that simple contracts, such as those with a binary wage scheme (e.g., high wage for good performance, low wage for poor performance), can achieve the optimal convergence rate when the amount of monitoring data grows large. In other words, these contracts do a better job than more complex contracts that vary wages more finely based on observed data.
To explain why this is the case, consider a cutoff point where the agent receives a high or low wage based on their performance. If the principal sets this cutoff point too low, they may not be able to accurately assess the agent’s performance, leading to suboptimal contracts. On the other hand, setting the cutoff point too high can result in lost opportunities for the agent to improve their performance and receive a higher wage.
Overall, our findings demonstrate that rich monitoring data can significantly impact the rate at which a principal’s payoffs converge to the optimal outcome. By using simple contracts with a lenient cutoff point, principals can achieve a high convergence rate without relying on complex contracts that may be less effective in practice.
In summary, this article explores how monitoring data can help principals learn about their agents’ performance and create optimal contracts to encourage good behavior. By using simple contracts with a lenient cutoff point, principals can achieve a high convergence rate without relying on more complex contracts that may not be as effective in practice.