Financial Performance Benchmarking in the Electricity Distribution Indu

A Review of Research Literature Results on Financial Per getance Benchmarking in the Electricity Distribution Industry inletSince the late 1980s, there has been significant regulatory reform in the electrical energy infection and dispersion industries in many countries. Under traditional cost-of-service place regulation, companies recover their costs under a regulated rate of return, which may provide little incentive to minimize costs. Alternatively, incentive or capital punishment based regimes are designed to incent productive efficiency by compensating the accompany 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 allow for review the literature results on benchmarking methods for electricity distributo rs.Jamasb and Pollitt 3 published the results of an international spate 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 correct Ordinary Least Squares (COLS), Data Envelopment Analysis (DEA) and Stochastic edge Analysis (SFA) as methods commonly employed in electricity distribution benchmarking. After briefly describing several models of incentive regulation, we compare the literature results compriseed 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... ...- particular(prenominal) efficiency levels in parametric, semi-parametric and non-parametric settings. Sickles, R. 2005, ledger of Econometrics, Vol. 126, pp. 305-334.30. love of technical inefficiiency in panel data models with f irm and time specific effects. Kumbhakar, S.C. 1991, Economics Letters, Vol. 36, pp. 43-48.31. Panel estimates of a two tiered earnings boundary. 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 use of the StoNED method in the Finnish regulatory model. Aalto University School of Economics. s.l. complaisant Science Research Network, 2011.