Department of Economics. University of Melbourne. Melbourne Victoria 3010 Australia

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 a specific form of social learning called imitation of scope. 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.