Nested frontier-based best practice regulation under asymmetric information in a principal–agent framework

This study focuses on public or private organisations with a large set of operation units. Central managers in these organisations face asymmetric information on the operating costs of sub-units and wish to incentivise them to reveal their minimal costs. In this paper, best practice regulation is implemented to deal with the asymmetric information via a regulation game. In the regulation game, the operating costs of sub-units are divided into several cost levels. To describe the unknown cost levels, a nested frontier-based approach, called context-dependent data envelopment analysis (CD-DEA), is introduced. By using CD-DEA, the efficient feasible incentive contract to the regulation game is proposed, and the condition that guarantees optimality of the proposed contract is also presented. Moreover, the efficient feasible incentive contract shows that the best responses of sub-units in the regulation game are to announce their actual cost levels, which constitute the Nash equilibrium. Several discussions are further provided to ensure the applicability of the proposed approach in realistic environments. Lastly, the proposed approach is illustrated by data from electricity generation and distribution sectors.