Stochastic programming perspective on the agency problems under uncertainty

We study the application of the stochastic programming framework to the analysis of complex agency problems under exogenous and endogenous uncertainty, presenting several models that deal with different types of such uncertainty. We demonstrate that the utilization of this framework extends the possibilities for the definition of parameters of incentive schedules. In this paper, we often refer to a model in a telecommunication environment consisting of a regulator (principal) and a service provider (agent) and study different aspects of regulation and licensing. However, the results can easily be generalized to other principal agent relationships.

VIEW CONTENT