Financial Performance Benchmarking in the Electricity Distribution Indu

A Review of Research Literature Results on Financial Performance Benchmarking in the Electricity Distribution Industry Introduction Since the late 1980s, there has been significant regulatory reform in the electricity transmission and distribution industries in many countries. Under traditional cost-of-service rate regulation, companies recover their costs under a regulated rate of return, which may provide little incentive to minimize costs. Alternatively, incentive or performance based regimes are designed to incent productive efficiency by compensating the company for achieving costs savings. Joskow [1] and Joskow and Schlalensee [2] discuss a number of economic regulatory models have been proposed in the literature. According to Jamasb and Pollitt [3], incentive regulation usually involves some form of benchmarking or comparison of actual versus some reference level of performance. We will review the literature results on benchmarking methods for electricity distributors. Jamasb and Pollitt [3] published the results of an international survey on the use of benchmarking in incentive regulation of electricity transmission and distribution utilities. Farsi et al. [4] provide a summary of benchmarking methods used in regulation in several countries. Both of these survey papers cite Corrected Ordinary Least Squares (COLS), Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) as methods commonly employed in electricity distribution benchmarking. After briefly describing several models of incentive regulation, we compare the literature results presented in each survey paper ( [3], [4] ) with respect to the techniques mentioned above (COLS, DEA, and SFA). We then present addition results from the literature on th... ...-specific efficiency levels in parametric, semi-parametric and non-parametric settings. Sickles, R. 2005, Journal of Econometrics, Vol. 126, pp. 305-334. 30. Estimation of technical inefficiiency in panel data models with firm and time specific effects. Kumbhakar, S.C. 1991, Economics Letters, Vol. 36, pp. 43-48. 31. Panel estimates of a two tiered earnings frontier. Polachek, S. and Yoon, B. 1996, Journal of Applied Econometrics, Vol. 11, pp. 169-178. 32. Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Greene, W.H. 2005, Journal of Econometrics, Vol. 126, pp. 269-303. 33. Kuosmanen, T. Stochastic semi-nonparametric efficiency analysis of electricity distribution networks: application of the StoNED method in the Finnish regulatory model. Aalto University School of Economics. s.l. : Social Science Research Network, 2011.