Application of Panel Data Models in Benchmarking Analysis of the Electrivity Distribution Sector

This paper explores the application of several panel data models in measuring productive efficiency of the electricity distribution sector. Stochastic Frontier Analysis has been used to estimate the cost-efficiency of 59 distribution utilities operating over a nine-year period in Switzerland. The estimated coefficients and inefficiency scores are compared across three different panel data models. The results indicate that individual efficiency estimates are sensitive to the econometric specification of unobserved firm-specific heterogeneity. When these factors are considered as a separate stochastic term, the efficiency estimates are substantially higher indicating that conventional models could confound efficiency differences with other unobserved variations among companies. The results suggest that alternative panel models such as the “true” random effects model proposed by Greene (2005) could be used to evaluate the possible impacts of unobserved factors such as network effects on efficiency estimates.