Motivated by markets for ''expertise,'' we study a bandit model where a principal chooses between a safe and risky arm. A strategic agent controls the risky arm and privately knows whether its type is high or low. Irrespective of type, the agent wants to maximize duration of experimentation with...

We study a repeated principal-agent model with transferable utility, where the principal's evaluation of the agent's performance is subjective. Our focus is on equilibria which are robust to the addition of small privately observed shocks to the payoffs. Existing constructions of positive-effort...

In the context of a canonical agency model, we study the payoff implications of introducing optimally structured incentives. We do so from the perspective of an analyst who does not know the agent's preferences for responding to incentives, but does know that the principal knows them. We...

I show that stochastic contracts generate powerful incentives when agents suffer from probability distortion. When implementing these contracts, the principal can target probability distortions in order to inflate the agent's perceived benefits of exerting high levels of effort. This novel...