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Benchmarking and Regulation in the Electricity Distribution Sector

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  • Mehdi Farsi

    (Center for Energy Policy and Economics CEPE, Department of Management, Technology and Economics, ETH Zurich, Switzerland)

  • Aurelio Fetz

    (Center for Energy Policy and Economics CEPE, Department of Management, Technology and Economics, ETH Zurich, Switzerland)

  • Massimo Filippini

    (Center for Energy Policy and Economics CEPE, Department of Management, Technology and Economics, ETH Zurich, Switzerland)

Abstract

In the last two decades electricity distribution sector have witnessed a wave of regulatory reforms aimed at improving efficiency through incentive regulation. Most of these regulation schemes use benchmarking namely measuring a company’s efficiency and rewarding them accordingly. The reliability of efficiency estimates is crucial for an effective implementation of those incentive mechanisms. A main problem faced by the regulators is the choice among several legitimate benchmarking models that usually produce different results. After a brief overview of the benchmarking methodologies, this paper summarizes the methods used in the regulation practice in several OECD countries, in which the benchmarking practice is relatively widespread. Repeated observation of similar companies over time namely panel data, allows a better understanding of unobserved firm-specific factors and disentangling them from efficiency estimates. Focusing on parametric cost frontier models, this paper presents two alternative approaches that could be used to improve the reliability of benchmarking methods, and based on recent empirical evidence, draws some recommendations for regulatory practice in power distribution networks.

Suggested Citation

  • Mehdi Farsi & Aurelio Fetz & Massimo Filippini, 2007. "Benchmarking and Regulation in the Electricity Distribution Sector," CEPE Working paper series 07-54, CEPE Center for Energy Policy and Economics, ETH Zurich.
  • Handle: RePEc:cee:wpcepe:07-54
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    2. Neumann, Anne & Nieswand, Maria & Schubert, Torben, 2016. "Estimating Alternative Technology Sets in Nonparametric Efficiency Analysis: Restriction Tests for Panel and Clustered Data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 45(1), pages 35-51.
    3. Astrid Cullmann, 2012. "Benchmarking and firm heterogeneity: a latent class analysis for German electricity distribution companies," Empirical Economics, Springer, vol. 42(1), pages 147-169, February.
    4. Tim Coelli & Axel Gautier & Sergio Perelman & Roxana Saplacan-Pop, 2012. "Estimating the cost of improving quality in electric distribution: a parametruc distance function approach," CREPP Working Papers 1202, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
    5. Ferro, Gustavo & Lentini, Emilio & Mercadier, Augusto & Romero, Carlos A., 2010. "Retornos a escala en agua y saneamiento: estimaciones para América Latina [Returns to scale in water and sanitation: estimates for Latin Amercia]," MPRA Paper 20324, University Library of Munich, Germany, revised Jan 2010.
    6. Astrid Cullmann & Hélène Crespo & Marie-Anne Plagnet, 2008. "International Benchmarking in Electricity Distribution: A Comparison of French and German Utilities," Discussion Papers of DIW Berlin 830, DIW Berlin, German Institute for Economic Research.
    7. Coelli, Tim J. & Gautier, Axel & Perelman, Sergio & Saplacan-Pop, Roxana, 2013. "Estimating the cost of improving quality in electricity distribution: A parametric distance function approach," Energy Policy, Elsevier, vol. 53(C), pages 287-297.
    8. Darío Ezequiel Díaz, 2013. "La Distribución Eléctrica en Argentina y su Eficiencia Técnica:Una Aplicación del Análisis de Fronteras Estocásticas (SFA) Utilizando Funciones Distancia," Revista de Economía y Estadística, Universidad Nacional de Córdoba, Facultad de Ciencias Económicas, Instituto de Economía y Finanzas, vol. 51(1), pages 85-118, Diciembre.
    9. Marques, Vítor & Bento, Nuno & Costa, Paulo Moisés, 2014. "The “Smart Paradox”: Stimulate the deployment of smart grids with effective regulatory instruments," Energy, Elsevier, vol. 69(C), pages 96-103.
    10. Müller, Christine & Growitsch, Christian & Wissner, Matthias, 2010. "Regulierung und Investitionsanreize in der ökonomischen Theorie. IRIN Working Paper im Rahmen des Arbeitspakets: Smart Grid-gerechte Weiterentwicklung der Anreizregulierung," WIK Discussion Papers 349, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH.
    11. Haney, Aoife Brophy & Pollitt, Michael G., 2011. "Exploring the determinants of “best practice” benchmarking in electricity network regulation," Energy Policy, Elsevier, vol. 39(12), pages 7739-7746.
    12. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.

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