Incentives for Learning
We analyze a dynamic principal-agent problem with moral hazard and private learning. Each period the agent faces a choice between two actions: a safe action with known returns (exploitation) and a costly risky action with unknown returns (experimentation). We explicitly characterize the cheapest time-dependent wage contracts implementing an action sequence by the agent consisting of a mix of risky and safe actions. We show that the wages for experimentation must be increasing to compensate for the agent’s pessimistic beliefs whereas the wages for exploitation are driven by distinct upper bounds. The model’s predictions have some empirical support.