scholarly journals Performance Effects of Network Structure and Ownership: The Norwegian Electricity Distribution Sector

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7160
Author(s):  
Wenche Tobiasson ◽  
Manuel Llorca ◽  
Tooraj Jamasb
Keyword(s):  
Vertical Integration ◽  
Stochastic Frontier Analysis ◽  
Low Voltage ◽  
Distribution Networks ◽  
Electricity Sector ◽  
Economies Of Scope ◽  
Economic Regulation ◽  
Electricity Distribution ◽  
Frontier Analysis ◽  
Electricity Networks

Transmission and distribution networks are capital intensive segments of the electricity sector and are generally considered natural monopolies. Due to their non-competitive nature, these are subject to independent regulation to prevent the abuse of monopolistic power and to induce competitive behaviour. Effective economic regulation of the electricity networks has become a key target in most developed economies after the 1980s. In Norway, incentive regulation and efficiency benchmarking were introduced in 1997. In Norway, the electricity grid is divided into three levels, namely, central, regional and distribution networks. In this paper, we study two overlooked aspects when analysing the performance of electricity networks: vertical integration and ownership structure. We use a stochastic frontier analysis approach to analyse the performance of Norwegian electricity distribution utilities for the period 2007–2014. We observe that vertical integration between distribution and regional transmission implies higher cost inefficiencies. This indicates that the efficiency gains due to separate management of the networks exceed the economies of coordination from vertical economies of scope. In addition, we find that council ownership entails higher efficiencies. This could be explained by the state having an interest in high-voltage electricity networks, rather than low-voltage ones, and the decentralised model from which the now centralised system was once developed.

Performance of Portuguese water utilities: how do ownership, size, diversification and vertical integration relate to efficiency?

Water Policy ◽  
2010 ◽  
Vol 13 (3) ◽  
pp. 343-361 ◽  
Author(s):  
Tânia Correia ◽  
Rui Cunha Marques
Keyword(s):  
Vertical Integration ◽  
Economies Of Scale ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Water Utilities ◽  
Economies Of Scope ◽  
Translog Cost Function ◽  
Water Sector ◽  
Frontier Analysis ◽  
Portuguese Water

This research applies the stochastic frontier analysis benchmarking method to measure the performance of the water sector in Portugal. It estimates a multiproduct translog cost function in order to study the efficiency of the water and sewerage services, using an unbalanced panel comprising 68 Portuguese water utilities for the biennium 2004–2005. The sample is formed by concessionaire companies, municipal companies and semi-autonomous utilities which represent approximately 61% of the Portuguese population, around 6.4 million inhabitants. The water utilities studied have a satisfactory level of efficiency (89% on average). The study points to the assumption that private utilities are, on average, more efficient than public utilities and that there are benefits if the companies specialize in providing a single activity. It also leads to the conclusion that there are increasing economies of scale and decreasing economies of scope associated with the Portuguese water sector.

scholarly journals Benchmarking of Electricity Distribution Licensees Operating in Sri Lanka

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
K. T. M. U. Hemapala ◽  
Lilantha Neelawala
Keyword(s):  
Sri Lanka ◽  
Relative Efficiency ◽  
Stochastic Frontier Analysis ◽  
Least Squares Method ◽  
Ordinary Least Squares ◽  
Electricity Sector ◽  
Regulatory Regime ◽  
Electricity Distribution ◽  
Factor X ◽  
Frontier Analysis

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.

Theory, Techniques, and Applications of Regulatory Benchmarking and Productivity Analysis

2018 ◽  
pp. 522-554 ◽  
Author(s):  
Per J. Agrell ◽  
Peter Bogetoft
Keyword(s):  
Stochastic Frontier Analysis ◽  
Model Development ◽  
Stochastic Frontier ◽  
Distribution Networks ◽  
Analysis Data ◽  
Economic Regulation ◽  
Data Envelopment ◽  
Productivity Analysis ◽  
Frontier Analysis ◽  
Energy Network

State-of-the-art benchmarking methods, and in particular data envelopment analysis (DEA) and stochastic frontier analysis (SFA), are well-established and informative tools in economic regulation to set reasonable revenue caps for energy network operators. However, regulatory benchmarking is not just another application of productivity analysis. This chapter reviews the economic theory upon which these applications are based and the additional stages in activity analysis, data analysis, and model development that are necessary. The chapter also provides detailed analyses of the applications in international electricity transmission and for the Norwegian electricity distribution networks.

DEA window analysis and Malmquist index to assess efficiency and productivity in the Spanish electricity sector

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jaime Sánchez-Ortiz ◽  
Teresa Garcia-Valderrama ◽  
Vanesa Rodríguez-Cornejo ◽  
Francisca Cabrera-Monroy
Keyword(s):  
Malmquist Index ◽  
Electricity Sector ◽  
Theory Of Constraints ◽  
Economic Regulation ◽  
Data Envelopment ◽  
Electricity Distribution ◽  
Content Type ◽  
External Constraints ◽  
Efficiency And Productivity ◽  
Dea Window Analysis

Purpose The purpose of this paper is to demonstrate that overcapacity and tariff deficit (external constraints) negatively affect the efficiency of distribution firms in the Spanish electricity sector. To do this, the paper is based on the theory of constraints and theory of economic regulation. Design/methodology/approach Data envelopment analysis (DEA) window methodology is carried out on the constant scales (I-C) with a sample consisting of five main distribution firms during the period from 2006 to 2015. In turn, an analysis of the Malmquist index is carried out to assess whether it has had a displacement with respect to the efficiency frontier. Findings The results show that the overcapacity and the tariff deficit negatively affect the efficiency of the distribution firms of the Spanish electricity sector. In addition, there is an existence of external constraints that affect the activities of regulated organisations and the importance of adequate legislation in regulated sectors. Originality/value This study defines a model that shows how the efficiency problems associated with electricity distribution companies such as productive overcapacity or tariff deficit can be measured based on the theory of constraints and theory of economic regulation.

Performance analysis of electricity distribution sector post the implementation of electricity act 2003: empirical evidence from India

2020 ◽  
Vol 17 (5) ◽  
pp. 669-696
Author(s):  
Pavan Khetrapal
Keyword(s):  
Stochastic Frontier Analysis ◽  
Corporate Strategy ◽  
Unobserved Heterogeneity ◽  
Stochastic Frontier ◽  
Operational Efficiency ◽  
Electricity Distribution ◽  
Content Type ◽  
Frontier Analysis ◽  
Explanatory Variables ◽  
Utility Managers

PurposeThe objective of the present study is to evaluate and analyse the performance of Indian electricity distribution utilities post the implementation of landmark Electricity Act 2003.Design/methodology/approachStochastic frontier analysis (SFA) that incorporates exogenous influences on operational efficiency is adopted in the present study. Specifically, a stochastic frontier production function model with a technical inefficiency effects model (Battese and Coelli, 1995) is chosen as a preferred model. In this model, the function that explains the inefficiency scores is estimated in a single stage with the production technology. This avoids the problem of inconsistency which is possible in the two-stage approach.FindingsThe sample involved 52 Indian electricity distribution utilities for seven-year period from 2006 to 2013. Major findings of SFA show that Indian electricity distribution utilities post the implementation of Electricity Act (2003) had, on average, experienced efficiency improvement during the observed period. The overall mean technical effciency score is estimated as 78.5% which indicates that there exist wide scope for effciency improvement in the sector. Further, the empirical findings also indicate that publicly owned distribution utilities obtain average technical efficiencies of 71.3%, which is lower than privately owned distribution utilities, which achieve average technical efficiencies of 85.7%.Research limitations/implicationsPower supply quality indicators such as SAIFI, SAIDI, CAIFI, etc. and unobserved heterogeneity also influence the efficiency analysis of electricity distribution utilities. Hence, these parameters as explanatory variables can be incorporated in the future work.Practical implicationsThe results obtained from this empirical study would likely be helpful for utility managers and policymakers to know how well they are performing, and how a better corporate strategy a particular utility can formulate to improve its operational efficiency and also its position in the marketplace.Originality/valueThis paper is amongst the first significant attempts that implement SFA approach to the panel dataset over a longer period of time – 2006 to 2013, so, as to evaluate and analyse the operational efficiency of Indian electricity distribution utilities in a single framework after the enactment of Electricity Act (2003). Unlike previous studies, this study investigates the degree to which various exogenous (or environmental) factors influence efficiency levels in these utilities.

scholarly journals The Cost Efficiency of the Brazilian Electricity Distribution Utilities: A Comparison of Bayesian SFA and DEA Models

2010 ◽  
Vol 2010 ◽  
pp. 1-20 ◽  
Author(s):  
Marcus Vinicius Pereira de Souza ◽  
Madiagne Diallo ◽  
Reinaldo Castro Souza ◽  
Tara Keshar Nanda Baidya
Keyword(s):  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Fundamental Aspect ◽  
Data Envelopment ◽  
Electricity Distribution ◽  
Frontier Analysis ◽  
Dea Models ◽  
The Cost ◽  
Analysis Models

The purpose of this study is to evaluate the efficiency indices for 60 Brazilian electricity distribution utilities. These scores are obtained by DEA (Data Envelopment Analysis) and Bayesian Stochastic Frontier Analysis models, two techniques that can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental aspect in incentive regulation schemes. In addition, this paper also addresses the problem of identifying outliers and influential observations in deterministic nonparametric DEA models.

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