Efficiency and regulation of the Slovenian electricity distribution companies

Filippini, Massimo; Hrovatin, Nevenka; Zorić, Jelena

doi:10.1016/s0301-4215(02)00295-1

Cited by 57 publications

(35 citation statements)

References 21 publications

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“…1 To note that in Slovenia a price-cap incentive regulation scheme combined with benchmarking analysis has been already applied to the electricity distribution utilities (AERS, 2004). Use of stochastic frontier benchmarking in estimating cost inefficiency of Slovenian electricity distribution companies is considered in Filippini, Hrovatin and Zorić (2004).…”

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Cost efficiency of Slovenian water distribution utilities: an application of stochastic frontier methods

2007

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This study estimates cost inefficiency and economies of scale of Slovenian water distribution utilities over the 1997-2003 period by employing several different stochastic frontier methods. The results indicate that significant cost inefficiencies are present in the utilities. An introduction of incentive-based price regulation scheme might help resolve this problem. However, the inefficiency scores obtained from different cost frontier models are not found to be robust. The levels of inefficiency estimates as well as the rankings depend on the econometric specification of the model. The established lack of robustness can be at least partly explained by different ability of the models to separate unobserved heterogeneity from inefficiency. Newly proposed true fixed effects model (Greene, 2005a, b) appears to perform better than the conventional panel data models with respect to distinguishing between unobserved heterogeneity and inefficiency. On the other hand, different models produce fairly robust results with respect to estimates of economies of output density, customer density and economies of scale. The optimal size of a company is found to closely corresponds to the sample median. Economies of scale are found in small-sized utilities, while large companies exhibit diseconomies of scale.

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Cost efficiency of Slovenian water distribution utilities: an application of stochastic frontier methods

2007

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“…This variable is to capture the heterogeneity dimension of the distribution business [43,44]. Further, the consumer density also can be accommodated in the model by using the consumers per unit network length, that is, number of consumers per kilometer of line length.…”

Section: Implementation Of Benchmarking Techniques Using Colsmentioning

confidence: 99%

Benchmarking of Electricity Distribution Licensees Operating in Sri Lanka

Neelawala

2016

Journal of Energy

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Electricity sector regulators are practicing benchmarking of distribution companies to regulate the allowed revenue. Mainly this is carried out based on the relative efficiency scores produced by frontier benchmarking techniques. Some of these techniques, for example, Corrected Ordinary Least Squares method and Stochastic Frontier Analysis, use econometric approach to estimate efficiency scores, while a method like Data Envelopment Analysis uses linear programming. Those relative efficiency scores are later used to calculate the efficiency factor (X-factor) which is a component of the revenue control formula. In electricity distribution industry in Sri Lanka, the allowed revenue for a particular distribution licensee is calculated according to the allowed revenue control formula as specified in the tariff methodology of Public Utilities Commission of Sri Lanka. This control formula contains the X-factor as well, but its effect has not been considered yet; it just kept it zero, since there were no relative benchmarking studies carried out by the utility regulators to decide the actual value of X-factor. This paper focuses on producing a suitable benchmarking methodology by studying prominent benchmarking techniques used in international regulatory regime and by analyzing the applicability of them to Sri Lankan context, where only five Distribution Licensees are operating at present.

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“…As in Sing (1987), Kwoka (2002), Filippini, Hrovatin et al (2004) and Fraquelli, Piacenza et al (2005) customer density is introduced as a service area characteristic.…”

Section: Model Specificationmentioning

confidence: 99%

“…8 See also studies by Gilsdorf (1995), Filippini (1996) and (1998), Yatchew (2000) and Filippini, Hrovatin et al (2004) which included the load factor of the network and studies by Maloney (2001), Kwoka (2002), Ida and Kuwahara (2004) and Jara-Diaz, Martinez-Budria et al (2004) where the generation capacity utilization factor was included.…”

Section: Model Specificationmentioning

confidence: 99%

Economies of vertical integration in the Swiss electricity sector

Fetz

Filippini

2010

Energy Economics

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Over the last two decades, several European nations have introduced reforms to their electricity sector. Generally, these reforms require a legal and functional unbundling of vertically integrated companies. These unbundling processes may reduce the possibilities that exist to fruitfully exploit the advantages of vertical integration.The goal of this paper is to empirically analyze the presence of economies of scale and vertical integration in the Swiss electricity sector. Economies of vertical integration between electricity production and distribution result from reduced transaction costs, better coordination of highly specific and interdependent investments and less financial risk. Different econometric specifications for panel data, including a random effects and a random-coefficients model, have been used to estimate a quadratic multi-stage cost function for a sample of electricity companies.The empirical results reflect the presence of considerable economies of vertical integration and economies of scale for most of the companies considered in the analysis. Moreover, the results suggest a variation in economies of vertical integration across companies due to unobserved heterogeneity.JEL Classification: C33, D24, L11, L25, L94, L95 1 We gratefully acknowledge the insightful comments and help from Mehdi Farsi. All remaining errors and omissions are ours.The views expressed in this paper do not necessarily reflect the position of any sponsoring agency.2

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Efficiency and regulation of the Slovenian electricity distribution companies

Cited by 57 publications

References 21 publications

Cost efficiency of Slovenian water distribution utilities: an application of stochastic frontier methods

Cost efficiency of Slovenian water distribution utilities: an application of stochastic frontier methods

Benchmarking of Electricity Distribution Licensees Operating in Sri Lanka

Economies of vertical integration in the Swiss electricity sector

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