This article develops a framework that delivers tractable (i.e., closed-form) optimal contracts, with few restrictions on the utility function, cost of effort, or noise distribution. By modeling the noise before the action in each period, we force the contract to provide correct incentives state-by-state, rather than merely on average. This tightly constrains the set of admissible contracts and allows for a simple solution to the contracting problem. Our results continue to hold in continuous time, where noise and actions are simultaneous. We illustrate the potential usefulness of our setup by a series of examples related to CEO incentives. In particular, the model derives predictions for the optimal measure of incentives and whether the contract should be convex, concave, or linear.
Stored only when both papers are in the corpus — 120 citations exist upstream.
Imported from OpenAlex (CC0) — nothing here is generated.