  This paper considers dynamic moral hazard settings, in which the consequences
of the agent's actions are not precisely understood. In a new continuous-time
moral hazard model with drift ambiguity, the agent's unobservable action
translates to drift set that describe the evolution of output. The agent and
the principal have imprecise information about the technology, and both seek
robust performance from a contract in relation to their respective worst-case
scenarios. We show that the optimal long-term contract aligns the parties'
pessimistic expectations and broadly features compressing of the high-powered
incentives. Methodologically, we provide a tractable way to formulate and
characterize optimal long-run contracts with drift ambiguity. Substantively,
our results provide some insights into the formal link between robustness and
simplicity of dynamic contracts, in particular high-powered incentives become
less effective in the presence of ambiguity.
