CAREER:Foundational Questions in the Theory of Incentives

Stanford University, Stanford CA

Investigators

Abstract

This CAREER award funds research in mechanism design and contract theory, the economic theory of the effects of incentives. Current core mathematical models are well-understood for simple environments but difficult to extend to more complicated environments. This project will develop new basic modeling tools, with the aim of broadening the scope of the theory. The tools will allow researchers to better design incentive schemes for complex environments, including incentive schemes that guarantee performance despite uncertainties about the economic environment. The integrated education plan includes an interdisciplinary conference to connect theorists in mechanism design with experts in potential application areas; and outreach activities with high school students and educators interested in advanced mathematical problem solving to build awareness of this fruitful area of study. This research promotes the national interest because it will guide the design of better incentive mechanisms. Existing theory in this area has historically had many applications, including taxation, regulation, procurement, and corporate finance. New theory will allow further improvements and better efficiency in these and other areas. The overall project has three main components. (1) Multidimensional mechanism design. Major workhorse models typically assume agents' preferences are summarized by a one-dimensional parameter; extending these models to multiple dimensions is widely viewed as challenging, yet important. This research will adapt a new modeling approach, based on uncertainty about the correlation across dimensions of preference, to study several questions concerning when and why simple mechanisms can deliver good guarantees. (2) Mechanism design when agents' information is endogenous. In many situations, agents can take costly actions to either acquire relevant information or influence others' information before an economic interaction, and a planner designing the interaction may be concerned that this gaming is socially wasteful. This project characterizes mechanisms that give robust guarantees when such "information games" are considered. (3) Design of incentives in situations of moral hazard, when it is unknown exactly what actions agents can take. This project considers several theoretical questions on this theme, focusing on understanding when simple incentive structures can be optimally robust in complex situations. The research plan also includes some related directions of study, including approximation of complex environments by simple ones, and optimal experimentation by incentive designers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.