برآورد هزینه های حاشیه ای از بهبود کیفیت: مورد شرکت های توزیع برق انگلستان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|5306||2012||9 صفحه PDF||سفارش دهید||8340 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy Economics, Volume 34, Issue 5, September 2012, Pages 1498–1506
The main aim of this paper is to develop an econometric approach to the estimation of marginal costs of improving quality of service. Estimating marginal costs of quality can help energy regulators to design more effective incentive mechanisms for network utilities to achieve optimal quality levels and reduce welfare losses due to sub-optimal quality. We implement this methodology by way of applying it to the case of the UK electricity distribution networks. The proposed method allows us to measure the welfare effect of the observed quality improvements in the UK between 1995 and 2003. Our results suggest that the regulatory incentives to reduce service interruptions have not been strong enough to achieve economically efficient levels of service quality. We, find that the incentives to encourage utilities to reduce network energy losses have led to to performance improvement. We estimate that the observed improvements in quality during the period of the study only represented about 20% of the potential customer welfare gains, hence leaving considerable scope for further economically efficient improvements in service quality.
Since the 1990s, many regulators of infrastructure industries around the world have implemented incentive-based regulation models that mimic market mechanisms and promote efficiency improvements in natural monopolies. Such schemes have in particular been adopted in the regulation of electricity transmission and distribution networks (Jamasb and Pollitt, 2001). Service quality is an important attribute of electricity distribution for residential, commercial and industrial customers as most functions of the modern economy depend on reliable electricity. The incentive schemes incentivize the network utilities to undertake cost savings. However, the striving for cost savings may result in lower quality of service as maintaining or improving upon a given level of quality is costly (see Ter-Martirosyan, 2003). Concerns regarding the side effects of simple incentive regulation models on service quality have, in recent years, led many electricity regulators to design incentive regulation mechanisms for quality of service in transmission and distribution networks (see Yu et al., 2009a). Sappington (2005) concludes that there are no simple policy solutions for effective regulation of quality of service but they depend on the information available to the regulator on consumer preferences and production technologies. While previous studies have attempted to quantify the value of service reliability (Allan and Kariuki, 1999, Kariuki and Allan, 1996 and Yu et al., 2009a) and have showed that utilities respond to quality of service incentives (Jamasb and Pollitt, 2007 and Tangeras, 2009), marginal cost of quality improvements were not explicitly estimated. Basing the incentives on marginal benefit of quality improvement may provide utilities with an overly generous incentive for socially efficient quality improvement. In some incentive models, as in Norway, quality incentives are integrated in cost benchmarking of the companies for determining their allowed revenues while the UK regulator Ofgem has used quality of service targets with associated penalty/reward schemes for distribution networks. The quality targets can vary across the companies taking into account the heterogeneities among them and their potential to improve during a given distribution price control regulatory period. Meeting the quality targets requires allowances justified in the utilities' periodic capital investment plans to upgrade assets and equipment that need to be approved by the regulator. In designing quality-incorporated regulatory mechanisms, regulators are faced with the task of identifying a demand curve for service quality (i.e. the price that customers are willing to pay for quality) and marginal cost of quality improvements. The latter can be viewed as a lower bound for setting incentive targets. Hence, knowledge of the marginal cost of quality improvement and how these compare to marginal benefits or customers' willingness to pay (WTP) for quality can help the regulators in setting better informed quality targets and rewards/penalties for the companies. The aim of this paper is to propose a methodology to estimate econometrically marginal costs of improving quality of services in the UK electricity distribution utilities, and assess the effectiveness of the current incentives to improve quality. We also measure the effect on economic welfare of quality improvements in the UK and the welfare losses due to sub-optimal quality. Section 2 introduces the empirical model and discusses several issues concerning the estimation of the marginal cost of quality of service. Section 3 describes the data and variables used in the empirical exercise. Section 4 presents the parameter estimates using different specifications and estimators. Section 5 summarizes the results, and presents the main conclusions.
نتیجه گیری انگلیسی
Quality of service in electricity distribution networks is important for residential, commercial, and industrial customers alike, as many functions of a modern society depend on electricity. However, improving upon a given level of quality of service has a cost. The likely effects of incentive regulation on service quality has in recent years attracted regulators' interest and a number of electricity regulators have made considerable effort to design appropriate regulation mechanisms of quality of service in electricity transmission and distribution networks. In designing quality-incorporated regulatory mechanisms, regulators are faced with the task of determining a market demand curve for service as well as the marginal cost of quality improvements. The main aim of this paper is to estimate econometrically marginal costs of improving quality services in the UK electricity distribution networks. The estimated marginal costs allow us to shed light on the effectiveness of the current UK incentives to improve quality, and to compute optimal quality levels and welfare losses due to sub-optimal quality levels. Our parameter estimates also allow us to measure the effect on welfare of the quality improvements observed in the UK. In order to achieve these objectives, we addressed several issues. First, while accurate information about operational and capital costs and quality services may be available, the marginal cost of quality improvements is not directly observed. For this reason, it is inferred from a previous estimation of the utilities' cost function that reflects both the underlying (physical) technology and the (consequences of the) regulatory environment that conditions utilities' performance. A second issue is that service quality is likely to be negatively correlated with corrective costs, but positively correlated with preventative costs. We attempted to isolate the pure marginal cost of quality improvements by replacing current levels with (a proxy of) expected levels of quality services as cost determinant. A third issue is to control for the effect of differences among utilities in environmental factors, such as weather, geography, etc. In order to estimate consistently a cost function for electricity networks, we included weather variables as cost determinants, and tested for potential endogeneity issues. The performed tests indicated that the OLS parameter estimates are consistent and can be used to analyze economies of scale or economies of density. Our tests also supported the view that the marginal cost of quality improvements can be estimated using expected customer minutes lost. The estimated marginal costs suggest that the incentives offered by the UK regulator to reduce their network energy losses are sufficient to yield an improvement in sector performance. However, this improvement is likely not homogeneously distributed among utilities as some of them seem to be insufficiently incentivized to reduce their energy losses. Our results also suggest the existence of different strategies in the UK electricity distribution networks to undertake reductions in network energy losses. We found that while higher service quality level is associated with higher marginal cost of quality improvement, the marginal cost of improving quality varies considerably across utilities due to their different configuration. Our results hence suggest tailoring the incentives for each utility. The high correlation between incentive rates and estimated marginal costs (76%) seems to indicate that the regulator did take differences in marginal costs into account in designing the incentive schemes in the UK. However, based on our results, we conclude that the UK incentive scheme, at least for the period of our study, was not sufficiently strong to incentivize reductions in customer minutes lost as the marginal costs estimated in this paper are much larger than the incentives offered by the UK regulator. We also found different strategies to tackle reductions in customer minutes lost. Indeed, for low quality utilities, reducing customer minutes lost mostly implies increasing operating cost. In contrast, when service quality is already high, reducing customer minutes lost mostly implies investing in capital inputs. Finally, based on a conservative estimate of the willingness to pay, we found that the optimal customer minutes lost is 45% less than the actual levels. The observed improvements in quality during the period of this study only represented 20% of the potential customer welfare gains, and hence there remains significant scope for quality improvements. However, achieving the optimal level of customer minutes lost would require a 19% increase in the total cost of the utilities.