Tractability in Incentive Contracting: Table 1

Abstract

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. (JEL D86, G34) The principal-agent problem is central to many settings in economics and finance, such as compensation, insurance, taxation, and regulation. A vast literature analyzing this problem has found that it is typically difficult to solve, even in simple settings. The first-order approach is often invalid, requiring the use of more intricate techniques. Even if an optimal contract can be derived, it is often not attainable in closed form, which reduces tractability—a particularly important feature in applied theory models. This article develops a broad framework that delivers tractable, closed-form contracts, with few restrictions on the utility function, cost of effort, or noise distribution. The framework requires two conditions: the analysis of a given path of effort levels, and either continuous time or a discrete-time model with a modified timing assumption. Grossman and Hart (1983) show that the Funding: This work was supported by National Science Foundation grants [numbers DMS-0938185 and SES