A Dynamic Approach to Estimate the Efficiency of U.S. Electric Utilities

The static production efficiency model and the dynamic duality model of intertemporal decision making using a parametric approach have been continuously developed but in separate direction. The parametric approach takes statistical noise into account, which consequently provides accurate measures in a stochastic environment. In this study the static shadow cost approach and the dynamic duality model of intertemporal decision making are integrated to formulate theoretical and econometric models of dynamic efficiency with intertemporal cost minimizing firm behavior. The dynamic efficiency model is a dynamic measure of firms’ inefficiency and it accounts for allocative and technical inefficiencies of net investment and of variable inputs. The dynamic efficiency model is implemented by using the Generalized Method of Moment (GMM) estimation and empirically applied into a panel data set of 72 U.S. major investor-owned electric utilities using fossil-fuel fired steam electric power generation during the time period of 1986 to 1999. The major results of this study are that most electric utilities in this study underutilized fuel relative to the aggregated labor and maintenance input and they overutilized capital in production. The estimates of the input price elasticities present the substitution possibilities among the inputs. Finally, the results suggest evidence of increasing returns to scale in the production of the electricity industry