Incentives for Boundedly Rational Agents

Suren Basov, Melbourne University

Abstract

This paper develops a theoretical framework for analyzing incentive schemes under bounded rationality. It starts from a standard principal-agent model and then superimposes an assumption of boundedly rational behavior on the part of the agent. Boundedly rational behavior is modeled as an explicit optimization procedure, which combines gradient dynamics with imitation and experimentation. The results predict the underprovision of optimal incentives and deviation from a standard sufficient statistics result from the agency literature. It also allows us to address the question of creating the optimal incentives in a multicultural environment.