IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp830.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.89723.de/dp830.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    9. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    10. 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, October.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Astrid Cullmann & Christian von Hirschhausen, 2007. "From Transition to Competition: Dynamic Efficiency Analysis of Polish Electricity Distribution Companies," Discussion Papers of DIW Berlin 716, DIW Berlin, German Institute for Economic Research.
    3. Deng, Yaguo, 2024. "A Bayesian semi-parametric approach to stochastic frontier models with inefficiency heterogeneity," DES - Working Papers. Statistics and Econometrics. WS 43837, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Hess, Borge & Cullmann, Astrid, 2007. "Efficiency analysis of East and West German electricity distribution companies - Do the "Ossis" really beat the "Wessis"?," Utilities Policy, Elsevier, vol. 15(3), pages 206-214, September.
    5. Frauke G. Braun & Astrid Cullmann, 2008. "Key Parameters and Efficiency of Mexican Manufacturing: Are There Still Differences between the North and the South? An Application of Nested and Stochastic Frontier Panel Data Models," Discussion Papers of DIW Berlin 816, DIW Berlin, German Institute for Economic Research.
    6. Cambini, Carlo & Croce, Annalisa & Fumagalli, Elena, 2014. "Output-based incentive regulation in electricity distribution: Evidence from Italy," Energy Economics, Elsevier, vol. 45(C), pages 205-216.
    7. 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.
    8. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Department of Economics - Working Papers Series 1092, The University of Melbourne.
    9. Karim L. Anaya & Michael G. Pollitt, 2014. "Does Weather Have an Impact on Electricity Distribution Efficiency? Evidence from South America," Working Papers EPRG 1404, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    10. Rita, Rui & Marques, Vitor & Bárbara, Diogo & Chaves, Inês & Macedo, Pedro & Moutinho, Victor & Pereira, Mariana, 2023. "Crossing non-parametric and parametric techniques for measuring the efficiency: Evidence from 65 European electricity Distribution System Operators," Energy, Elsevier, vol. 283(C).
    11. Mulwa, Richard & Kabubo-Mariara, Jane, 2017. "Productive Efficiency and Its Determinants in a Changing Climate: A Monotonic Translog Stochastic Frontier Analysis," EfD Discussion Paper 17-6, Environment for Development, University of Gothenburg.
    12. Adwoa Asantewaa & Tooraj Jamasb & Manuel Llorca, 2022. "Electricity Sector Reform Performance in Sub-Saharan Africa: A Parametric Distance Function Approach," Energies, MDPI, vol. 15(6), pages 1-29, March.
    13. Rendao Ye & Yue Qi & Wenyan Zhu, 2023. "Impact of Agricultural Industrial Agglomeration on Agricultural Environmental Efficiency in China: A Spatial Econometric Analysis," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    14. 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.
    15. Anne-Kathrin Last & Heike Wetzel, 2009. "Effizienzmessverfahren – eine Einführung," Working Paper Series in Economics 145, University of Lüneburg, Institute of Economics.
    16. Papadopoulos, Alecos & Parmeter, Christopher F., 2021. "Type II failure and specification testing in the Stochastic Frontier Model," European Journal of Operational Research, Elsevier, vol. 293(3), pages 990-1001.
    17. Xu Guo & Gao-Rong Li & Michael McAleer & Wing-Keung Wong, 2018. "Specification Testing of Production in a Stochastic Frontier Model," Sustainability, MDPI, vol. 10(9), pages 1-10, August.
    18. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    19. Mehdi Farsi & Massimo Filippini & William Greene, 2006. "Application Of Panel Data Models In Benchmarking Analysis Of The Electricity Distribution Sector," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 77(3), pages 271-290, September.
    20. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C., 2016. "A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers," Journal of Econometrics, Elsevier, vol. 190(2), pages 289-300.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:diw:diwwpp:dp830. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.