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International Benchmarking in Electricity Distribution: A Comparison of French and German Utilities

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  • Astrid Cullmann
  • Hélène Crespo
  • Marie-Anne Plagnet

Abstract

In this paper we present an international cross-country benchmarking analysis for utility regulation of France and Germany, the two largest electricity distribution countries in Europe. We examine the relative performance of 99 French and 77 German distribution companies operating within two different market structures. This paper applies several parametric benchmarking approaches to assess the relative technical efficiency of the utilities, such as deterministic Corrected Ordinary Least Squares (COLS) and Stochastic Frontier Analysis (SFA). Our base model uses the number of employees as a proxy for labor and network length as a proxy for capital as inputs. Units sold and the numbers of customers are considered as outputs. Our model variations and extensions analyze the effect of different characteristics of distribution areas (e.g. population density and the choice of investment in underground cable network). We find that utilities operating in urban areas feature higher efficiency scores and that investment in underground cables increase the technical efficiency of the distribution utilities.

Suggested Citation

  • 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.
    • Handle: RePEc:diw:diwwpp:dp830
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    References listed on IDEAS

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    1. Christian Growitsch & Tooraj Jamasb & Michael Pollitt, 2009. "Quality of service, efficiency and scale in network industries: an analysis of European electricity distribution," Applied Economics, Taylor & Francis Journals, vol. 41(20), pages 2555-2570.
    2. Christian von Hirschhausen & Astrid Cullmann & Andreas Kappeler, 2006. "Efficiency analysis of German electricity distribution utilities - non-parametric and parametric tests," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2553-2566.
    3. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    4. Mehdi Farsi & Massimo Filippini, 2004. "Regulation and Measuring Cost-Efficiency with Panel Data Models: Application to Electricity Distribution Utilities," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 25(1), pages 1-19, August.
    5. Antonio Estache & MartÌn A. Rossi & Christian A. Ruzzier, 2004. "The Case for International Coordination of Electricity Regulation: Evidence from the Measurement of Efficiency in South America," Journal of Regulatory Economics, Springer, vol. 25(3), pages 271-295, May.
    6. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    7. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, November.
    8. 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.
    9. Astrid Cullmann & Christian Hirschhausen, 2008. "Efficiency analysis of East European electricity distribution in transition: legacy of the past?," Journal of Productivity Analysis, Springer, vol. 29(2), pages 155-167, April.
    10. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    11. Jamasb, T. & Pollitt, M., 2001. "International Benchmarking and Yardstick Regulation: An Application to European Electricity Utilities," Cambridge Working Papers in Economics 0115, Faculty of Economics, University of Cambridge.
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    Cited by:

    1. H. Örkcü & Mehmet Ünsal & Hasan Bal, 2015. "A modification of a mixed integer linear programming (MILP) model to avoid the computational complexity," Annals of Operations Research, Springer, vol. 235(1), pages 599-623, December.
    2. Luis Alberto Andrés & José Luis Guasch & Sebastián López Azumendi, 2011. "Regulation and Corporate Governance of State-owned Enterprises: Issues for Improved Efficiency and Competitiveness and Lessons for China," Chapters, in: Michael Faure & Xinzhu Zhang (ed.), Competition Policy and Regulation, chapter 7, Edward Elgar Publishing.

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    More about this item

    Keywords

    International benchmarking; electricity distribution; parametric efficiency analysis;
    All these keywords.

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

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