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Regulatory benchmarking: Models, analyses and applications

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  • Per J. Agrell
  • Peter Bogetoft

Abstract

Benchmarking methods, and in particular Data Envelopment Analysis (DEA), have become well-established and informative tools for economic regulation. DEA is now routinely used by European regulators to set reasonable revenue caps for energy transmission and distribution system operators. The application of benchmarking in regulation, however, requires specific steps in terms of data validation, model specification and outlier detection that are not systematically documented in open publications, leading to discussions about regulatory stability and economic feasibility of these techniques. In this paper, we review the modern foundations for frontier-based regulation and we discuss its actual use in several jurisdictions.
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Suggested Citation

  • Per J. Agrell & Peter Bogetoft, 2017. "Regulatory benchmarking: Models, analyses and applications," LIDAM Reprints CORE 2912, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:2912
    Note: In : Data Envelopment Analysis Journal, 3, 49-91, 2017
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    Cited by:

    1. Kerstens, Kristiaan & Sadeghi, Jafar & Toloo, Mehdi & Van de Woestyne, Ignace, 2022. "Procedures for ranking technical and cost efficient units: With a focus on nonconvexity," European Journal of Operational Research, Elsevier, vol. 300(1), pages 269-281.
    2. Afsharian, Mohsen & Ahn, Heinz & Lopes, Ana & Vilela, Bruno, 2019. "Pitfalls in estimating the X-factor: The case of energy transmission regulation in Brazil," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 1-9.
    3. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.
    4. Binlei Gong & Robin C. Sickles, 2020. "Non-structural and structural models in productivity analysis: study of the British Isles during the 2007–2009 financial crisis," Journal of Productivity Analysis, Springer, vol. 53(2), pages 243-263, April.
    5. Mahlberg, Bernhard & Frank-Stocker, Andrea & Koller, Wolfgang & Ramerstorfer, Christian, 2023. "Cost efficiency of renewable district heating systems: the case of Austria," MPRA Paper 118595, University Library of Munich, Germany.
    6. Waidelich, Paul & Haug, Tomas & Wieshammer, Lorenz, 2022. "German efficiency gone wrong: Unintended incentives arising from the gas TSOs’ benchmarking," Energy Policy, Elsevier, vol. 160(C).
    7. Emil Heesche & Mette Asmild, 2020. "Controlling for environmental conditions in regulatory benchmarking," IFRO Working Paper 2020/03, University of Copenhagen, Department of Food and Resource Economics.
    8. An, Qingxian & Tao, Xiangyang & Xiong, Beibei, 2021. "Benchmarking with data envelopment analysis: An agency perspective," Omega, Elsevier, vol. 101(C).
    9. Bogetoft, Peter & Eskesen, Anita, 2022. "Balancing information rents and service differentiation in utility regulation," Energy Economics, Elsevier, vol. 106(C).
    10. Costa, Marcelo Azevedo & Lopes-Ahn, Ana Lúcia & Kilger, Alexander de Carvalho & Micas, Artur Fontenelle, 2023. "Limitations of weight restrictions in data envelopment analysis for benchmarking Brazilian electricity distribution system operators," Utilities Policy, Elsevier, vol. 82(C).
    11. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2021. "A review of DEA approaches applying a common set of weights: The perspective of centralized management," European Journal of Operational Research, Elsevier, vol. 294(1), pages 3-15.
    12. Stronzik, Marcus & Wissner, Matthias, 2019. "Entwicklung des Effizienzvergleichs in Richtung Smart Grids," WIK Discussion Papers 447, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH.
    13. Afsharian, Mohsen & Bogetoft, Peter, 2020. "Identifying production units with outstanding performance," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1191-1194.
    14. An, Qingxian & Tao, Xiangyang & Chen, Xiaohong, 2023. "Nested frontier-based best practice regulation under asymmetric information in a principal–agent framework," European Journal of Operational Research, Elsevier, vol. 306(1), pages 269-285.
    15. Emil Heesche & Peter Bogetoft, 2021. "Incentives in regulatory DEA models with discretionary outputs: The case of Danish water regulation," IFRO Working Paper 2021/04, University of Copenhagen, Department of Food and Resource Economics.
    16. Benítez-Peña, Sandra & Bogetoft, Peter & Romero Morales, Dolores, 2020. "Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach," Omega, Elsevier, vol. 96(C).
    17. Robin C. Sickles & Wonho Song & Valentin Zelenyuk, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," CEPA Working Papers Series WP082018, School of Economics, University of Queensland, Australia.
    18. Julio Cesar Mosquera Gutierres & Rafael Coradi Leme & Rodrigo Luiz Mendes Mota & Paulo E. Steele Santos, 2021. "Regulatory efficiency decomposition for utilities’ parallel subsystems," Operational Research, Springer, vol. 21(1), pages 331-347, March.
    19. Tobias Rösch & Peter Treffinger, 2019. "Cluster Analysis of Distribution Grids in Baden-Württemberg," Energies, MDPI, vol. 12(20), pages 1-25, October.
    20. Edens, Marga G. & Lavrijssen, Saskia A.C.M., 2019. "Balancing public values during the energy transition – How can German and Dutch DSOs safeguard sustainability?," Energy Policy, Elsevier, vol. 128(C), pages 57-65.
    21. Heesche, Emil & Asmild, Mette, 2022. "Controlling for environmental conditions in regulatory benchmarking," Utilities Policy, Elsevier, vol. 77(C).
    22. Stead, Alexander D. & Wheat, Phill & Greene, William H., 2023. "Robust maximum likelihood estimation of stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 309(1), pages 188-201.
    23. Emil Heesche & Mette Asmild, 2022. "Implications of Aggregation Uncertainty in DEA," IFRO Working Paper 2022/02, University of Copenhagen, Department of Food and Resource Economics.
    24. de Souza Pereira, Mariana & Magalhães Filho, Fernando Jorge Corrêa & de Morais Lima, Priscila & Tabak, Benjamin Miranda & Constantino, Michel, 2022. "Sanitation and water services: Who is the most efficient provider public or private? Evidences for Brazil," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    25. Duras, Toni & Javed, Farrukh & Månsson, Kristofer & Sjölander, Pär & Söderberg, Magnus, 2023. "Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution data," Energy Economics, Elsevier, vol. 120(C).

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