Vague by Design: Performance Evaluation and Learning From Wages

We study a dynamic principal-agent setting in which both sides learn about the importance of effort. The quality of the agent’s output is not observed directly. Instead, the principal jointly designs an evaluation technology and a wage schedule. More precise performance evaluation reduces current agency costs but promotes learning, which is shown to increase future agency costs. As a result, the optimal evaluation technology is both imprecise and tough: a bad performance is always sanctioned, but a good one is not always recognized. We also study the case in which principal and agent have different priors, for instance because the agent is overconfident. Then, the principal uses a tough evaluation structure to preserve the agent’s profitable misperception. For an underconfident agent, by contrast, she either uses a fully informative evaluation in order to promote learning and eliminate costly underconfidence, or is lenient if learning is too costly.