Finding the right yardstick: Regulation of electricity networks under heterogeneous environments

Abstract

Revenue cap regulation is often combined with systematic benchmarking to reveal the managerial inefficiencies when regulating natural monopolies. One example is the European energy sector, where benchmarking is based on actual cost data, which are influenced by managerial inefficiency as well as operational heterogeneity. This paper demonstrates how a conditional nonparametric method, which allows comparison of firms operating under heterogeneous technologies, can be used to estimate managerial inefficiency. A dataset of 123 distribution firms in Norway is used to show aggregate and firm-specific effects of conditioning. We compare the models presently used by the Norwegian regulator to a suggested conditional model, thus providing a viable alternative to distinguish between managerial inefficiency and operational heterogeneity. The use of the conditional model in this regulatory context leads, first, to a decrease in aggregate efficient costs and, second, to a reallocation effect that affects the relative profitability of firms and relative customer prices, thus providing a fairer basis for setting revenue caps.

An analysis of distribution planning under a regulatory regime: An integrated framework

“…Revenue sharing is implemented in (Colorado, Connecticut, Florida, Georgia, Kentucky, Tennessee and Texas) [53], in Norway [55] and the Netherlands [56].…”

“…Modeling the profit sharing scheme as the dynamic game between a franchise holder and owner, the drawback of revenue regulation was stated as profit sharing prescriptions would require audited cost information to calculate allowable profit levels, which are usually difficult for a regulator to collect [54]. A DEA model was used to evaluate the Revenue cap for 123 distribution firms in Norway [55]. The study of quality regulation of electricity distribution in the Netherlands inferred that a revenue cap has the advantage of allowing network operators to set individual tariffs [56].…”

The Effect of Restructuring Electricity Distribution Systems on Firms’ Persistent and Transient Efficiency: The Case of Germany

“…In developing countries where only a small share of the population is supplied with electric power and other public infrastructures, the implementation of efficient networks could help increasing the benefits from urban concentration. 1 There are ample empirical works estimating the extent of inefficiency of DSOs for multiple regions; e.g., Kumbhakar et al (2015a) and Bjørndal et al (2018) analyze DSOs in Norway, Kumbhakar and Hjalmarsson (1998) in Sweden, Filippini et al (2004) in Slovenia, Cullmann (2012) and Hirschhausen et al (2006) in Germany, Filippini and Wetzel (2014) in New Zealand, Giannakis et al (2005) in the UK, Filippini (2004) in Switzerland, andBağdadioğlu et al (1996) in Turkey. A shortcoming of these studies is that they rely on the assumption that inefficiency is either time-variant (transient) or time-invariant (persistent).…”

“…electricity delivered (y E ) in MWh and the number of connected customers (y C ). Since the technology of electricity distribution is subject to the characteristics of its operational environment (Bjørndal et al, 2018;Nieswand and Seifert, 2018), we incorporate population density (z D ), defined as the number of connection points per squared km in the operational area, to capture exogenously induced neutral technology shift. Neglecting such shift variables from the production process is likely to bias estimates of inefficiency.…”