Many of the incentive schemes proposed recently have aimed to encourage economic efficiency and to streamline regulator workloads: such incentive mechanisms have appeared in regulatory hearings and academic literature since the 1970s. Although significant results have been obtained in the way of designing and justifying alternative approaches, there still remains an important class of economic problems that are difficult to solve by those approaches and that arise frequently in several applications: regulation of interdependent economic agents under asymmetric information. Prime examples of the kind of regulatory situation are $\bullet$ enhancing market performance of those segments of the telecommunications and banking industries that are, or soon will be, oligopolistic competitive, $\bullet$ regulation of multiple polluters, and $\bullet$ control of interdependent divisions in a large organizations. The basic question is how to make an optimal incentive scheme which will induce firms to do what is best in the context of asymmetric information. This thesis is devoted to formalizing the question, giving an answer of the incentive scheme, and analyzing the answer. In the way of designing and analysing the incentive schemes, we also address some broad questions as follows: $\bullet$ How do regulatory schemes depend on market structure? $\bullet$ How do regulatory schemes vary with the nature of informational asymmetries? $\bullet$ How do regulatory schemes vary with the nature of competition? Major contributions of the study are in order. First, we provide a decentralized framework for regulating interdependent agents who behave in a non-Nash way. Specifically, we derive optimal incentive schemes for regulating oligopolistic firms (chapter 3) and for pollution-emitting firms (chapter 5) under asymmetric information. The key to deriving the scheme is to equate the first-order necessary conditions for maximization of the regulator and the equilibrium conditions of ...