IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v283y2023ics0360544223019059.html
   My bibliography  Save this article

Crossing non-parametric and parametric techniques for measuring the efficiency: Evidence from 65 European electricity Distribution System Operators

Author

Listed:
  • Rita, Rui
  • Marques, Vitor
  • Bárbara, Diogo
  • Chaves, Inês
  • Macedo, Pedro
  • Moutinho, Victor
  • Pereira, Mariana

Abstract

Benchmarking techniques have been one of the main tools used by National Regulatory Authorities (NRA) to provide reliable information to define the efficiency targets for regulated undertakings. This paper aims to define the operational efficiency of the Portuguese mainland electricity Distribution System Operator (DSO), a monopoly incumbent with more than six million customers. Given the monopolistic nature of the electricity distribution activity in Portugal, the analysis was supported on a wide sample of 65 European DSO that operate in 16 European countries. This geographic spread required the use of different data harmonization procedures for an adequate use of different methodologies, namely Stochastic Frontier Analysis (SFA), Data Envelopment Analysis (DEA) and Total Productivity Indices (Malmquist), in order to guarantee robust results for the efficiency assessment. The study combines two outputs (number of supply points and network extension) and two inputs (operating costs and total costs) in different models. The results obtained are relatively positive for Portuguese DSO, placing the mainland DSO at efficiency levels between the 1st quartile and the efficiency frontier. There is a high correlation between DEA and SFA predicted efficiency scores, which supports the robustness of the analysis.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223019059
    DOI: 10.1016/j.energy.2023.128511
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223019059
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128511?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Agrell, Per J. & Bogetoft, Peter, 2017. "Regulatory Benchmarking: Models, Analyses and Applications," Data Envelopment Analysis Journal, now publishers, vol. 3(1-2), pages 49-91, November.
    2. Cardoso de Mendonça, Mário Jorge & Pereira, Amaro Olimpio & Medrano, Luis Alberto & Pessanha, José Francisco M., 2021. "Analysis of electric distribution utilities efficiency levels by stochastic frontier in Brazilian power sector," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    3. 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.
    4. P. Nillesen & M. Pollitt, 2010. "Using Regulatory Benchmarking Techniques to Set Company Performance Targets: The Case of Us Electricity," Competition and Regulation in Network Industries, Intersentia, vol. 11(1), pages 50-85, March.
    5. Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & de Pinho Matos, Giordano Bruno Braz, 2015. "Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 47-60.
    6. Henningsen, Arne & Bělín, Matěj & Henningsen, Géraldine, 2017. "New insights into the stochastic ray production frontier," Economics Letters, Elsevier, vol. 156(C), pages 18-21.
    7. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528, Decembrie.
    8. 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.
    9. Capece, Guendalina & Costa, Roberta & Di Pillo, Francesca, 2021. "Benchmarking the efficiency of natural gas distribution utilities in Italy considering size, ownership, and maturity," Utilities Policy, Elsevier, vol. 72(C).
    10. Andor, Mark A. & Parmeter, Christopher & Sommer, Stephan, 2019. "Combining uncertainty with uncertainty to get certainty? Efficiency analysis for regulation purposes," European Journal of Operational Research, Elsevier, vol. 274(1), pages 240-252.
    11. Ioannis E. Tsolas, 2022. "Assessing Regional Entrepreneurship: A Bootstrapping Approach in Data Envelopment Analysis," Stats, MDPI, vol. 5(4), pages 1-10, November.
    12. Tsionas, Mike G., 2021. "Optimal combinations of stochastic frontier and data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 294(2), pages 790-800.
    13. Richard Schmalensee, 1989. "Good Regulatory Regimes," RAND Journal of Economics, The RAND Corporation, vol. 20(3), pages 417-436, Autumn.
    14. Bryon J. Parman & Allen M. Featherstone, 2019. "A comparison of parametric and nonparametric estimation methods for cost frontiers and economic measures," Journal of Applied Economics, Taylor & Francis Journals, vol. 22(1), pages 60-85, January.
    15. 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.
    16. Altoé, Andrey Vinícius & da Costa Jr., Newton & Lopes, Ana Lúcia Miranda & Veloso, Thiago Roberto Magalhães & Saurin, Valter, 2017. "Technical efficiency and financial performance in the Brazilian distribution service operators," Socio-Economic Planning Sciences, Elsevier, vol. 59(C), pages 79-92.
    17. Kuosmanen, Timo, 2012. "Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model," Energy Economics, Elsevier, vol. 34(6), pages 2189-2199.
    18. Ikram, Majid & Rafique, Muhammad Zahid & Mohammed, Kamel Si & Waheed, Rida & Ferraz, Diogo, 2023. "Efficient resource utilization of the electricity distribution sector using nonparametric data envelopment analysis and influential factors," Utilities Policy, Elsevier, vol. 82(C).
    19. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    20. Janda, Karel & Krska, Stepan, 2014. "Benchmarking Methods in the Regulation of Electricity Distribution System Operators," MPRA Paper 59442, University Library of Munich, Germany.
    21. Tu Van Binh & Abay Mulatu & Boying Xu, 2022. "Corporate social responsibility & firm efficiency: evidence from endogenous cost inefficiency stochastic frontier analysis," Applied Economics, Taylor & Francis Journals, vol. 54(55), pages 6380-6392, November.
    22. Musau, Andrew & Kumbhakar, Subal C. & Mydland, Ørjan & Lien, Gudbrand, 2021. "Determinants of allocative and technical inefficiency in stochastic frontier models: An analysis of Norwegian electricity distribution firms," European Journal of Operational Research, Elsevier, vol. 288(3), pages 983-991.
    23. Haikel Khalfallah, 2013. "An assessment of Incentive Regulation in electricity networks: The story so far," Working Papers halshs-00931301, HAL.
    24. Alexandros M. Theodoridis & Md. Mazharul Anwar, 2011. "A comparison of DEA and SFA methods: a case study of farm households in Bangladesh," Journal of Developing Areas, Tennessee State University, College of Business, vol. 45(1), pages 95-110, July-Dece.
    25. Quang Nguyen & Sean Pascoe & Louisa Coglan & Son Nghiem, 2021. "The sensitivity of efficiency scores to input and other choices in stochastic frontier analysis: an empirical investigation," Journal of Productivity Analysis, Springer, vol. 55(1), pages 31-40, February.
    26. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    27. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    28. J. Barrera-Santana, G.A. Marrero, and F.J. Ramos-Real, 2022. "Energy Efficiency and Energy Governance: A Stochastic Frontier Analysis Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    29. 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, January.
    30. Ali Homayoni & Reza Fallahnejad & Farhad Hosseinzadeh Lotfi, 2022. "Cross Malmquist Productivity Index in Data Envelopment Analysis," 4OR, Springer, vol. 20(4), pages 567-602, December.
    31. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107029514, November.
    32. 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.
    33. Chung, William, 2011. "Review of building energy-use performance benchmarking methodologies," Applied Energy, Elsevier, vol. 88(5), pages 1470-1479, May.
    34. A. M. Theodoridis & A. Psychoudakis, 2008. "Efficiency Measurement in Greek Dairy Farms: Stochastic Frontier vs. Data Envelopment Analysis," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 1(2), pages 53-67, December.
    35. Matheus Koengkan & José Alberto Fuinhas & Emad Kazemzadeh & Fariba Osmani & Nooshin Karimi Alavijeh, 2022. "Measuring the economic efficiency performance in Latin American and Caribbean countries: An empirical evidence from stochastic production frontier and data envelopment analysis," International Economics, CEPII research center, issue 169, pages 43-54.
    36. Farsi, Mehdi & Filippini, Massimo & Kuenzle, Michael, 2007. "Cost efficiency in the Swiss gas distribution sector," Energy Economics, Elsevier, vol. 29(1), pages 64-78, January.
    37. Tsionas, Mike G., 2023. "Combining data envelopment analysis and stochastic frontiers via a LASSO prior," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1158-1166.
    38. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 1-11, December.
    39. Murillo-Zamorano, Luis R. & Vega-Cervera, Juan A., 2001. "The use of parametric and non-parametric frontier methods to measure the productive efficiency in the industrial sector: A comparative study," International Journal of Production Economics, Elsevier, vol. 69(3), pages 265-275, February.
    40. Jamasb, Tooraj & Pollitt, Michael, 2003. "International benchmarking and regulation: an application to European electricity distribution utilities," Energy Policy, Elsevier, vol. 31(15), pages 1609-1622, December.
    41. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    42. Parmeter, Christopher F. & Kumbhakar, Subal C., 2014. "Efficiency Analysis: A Primer on Recent Advances," Foundations and Trends(R) in Econometrics, now publishers, vol. 7(3-4), pages 191-385, December.
    Full references (including those not matched with items on IDEAS)

    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. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    3. Janda, Karel & Krska, Stepan, 2014. "Benchmarking Methods in the Regulation of Electricity Distribution System Operators," MPRA Paper 59442, University Library of Munich, Germany.
    4. Ahn, Heinz & Clermont, Marcel & Langner, Julia, 2023. "Comparative performance analysis of frontier-based efficiency measurement methods – A Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 307(1), pages 294-312.
    5. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    6. Lukáš Čechura & Zdeňka Žáková Kroupová, 2021. "Technical Efficiency in the European Dairy Industry: Can We Observe Systematic Failures in the Efficiency of Input Use?," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    7. Lazović-Pita Lejla & Šćeta Lamija, 2021. "A Stochastic Frontier Approach to Measuring Inefficiency of Local Communities in Bosnia and Herzegovina," South East European Journal of Economics and Business, Sciendo, vol. 16(1), pages 18-29, June.
    8. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    9. Massimo Filippini & Thomas Geissmann & William H. Greene, 2018. "Persistent and transient cost efficiency—an application to the Swiss hydropower sector," Journal of Productivity Analysis, Springer, vol. 49(1), pages 65-77, February.
    10. Zangin Zeebari & Kristofer Månsson & Pär Sjölander & Magnus Söderberg, 2023. "Regularized conditional estimators of unit inefficiency in stochastic frontier analysis, with application to electricity distribution market," Journal of Productivity Analysis, Springer, vol. 59(1), pages 79-97, February.
    11. Andor, Mark A. & Parmeter, Christopher & Sommer, Stephan, 2019. "Combining uncertainty with uncertainty to get certainty? Efficiency analysis for regulation purposes," European Journal of Operational Research, Elsevier, vol. 274(1), pages 240-252.
    12. Tovar, Beatriz & Javier Ramos-Real, Francisco & de Almeida, Edmar Fagundes, 2011. "Firm size and productivity. Evidence from the electricity distribution industry in Brazil," Energy Policy, Elsevier, vol. 39(2), pages 826-833, February.
    13. Robin C. Sickles & Jiaqi Hao & Chenjun Shang, 2014. "Panel data and productivity measurement: an analysis of Asian productivity trends," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 12(3), pages 211-231, August.
    14. Sabrina Auci & Laura Castellucci & Manuela Coromaldi, 2021. "How does public spending affect technical efficiency? Some evidence from 15 European countries," Bulletin of Economic Research, Wiley Blackwell, vol. 73(1), pages 108-130, January.
    15. Vittadini, Giorgio & Sturaro, Caterina & Folloni, Giuseppe, 2022. "Non-Cognitive Skills and Cognitive Skills to measure school efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    16. Martin, Sheila Ann, 1992. "The effectiveness of state technology incentives: evidence from the machine tool industry," ISU General Staff Papers 1992010108000011381, Iowa State University, Department of Economics.
    17. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    18. Sebastian Lakner & Thelma Brenes‐Muñoz & Bernhard Brümmer, 2017. "Technical Efficiency in Chilean Agribusiness Industry: A Metafrontier Approach," Agribusiness, John Wiley & Sons, Ltd., vol. 33(3), pages 302-323, June.
    19. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    20. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.

    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:eee:energy:v:283:y:2023:i:c:s0360544223019059. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.