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Benchmarking and regulation

Author

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  • AGRELL, Per

    (Université catholique de Louvain, CORE & Louvain School of Management, Belgium)

  • BOGETOFT, Peter

    (Copenhagen Business School, Denmark)

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.

Suggested Citation

  • AGRELL, Per & BOGETOFT, Peter, 2013. "Benchmarking and regulation," LIDAM Discussion Papers CORE 2013008, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:2013008
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    File URL: https://sites.uclouvain.be/core/publications/coredp/coredp2013.html
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. 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.
    3. Endre Bjoerndal & Mette Bjoerndal & Astrid Cullmann & Maria Nieswand, 2016. "Finding the Right Yardstick: Regulation under Heterogeneous Environments," Discussion Papers of DIW Berlin 1555, DIW Berlin, German Institute for Economic Research.
    4. Orea, Luis & Álvarez, Inmaculada C., 2019. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Journal of Econometrics, Elsevier, vol. 213(2), pages 556-577.
    5. Maria Nieswand & Stefan Seifert, 2016. "Operational Conditions in Regulatory Benchmarking Models: A Monte Carlo Analysis," Discussion Papers of DIW Berlin 1585, DIW Berlin, German Institute for Economic Research.
    6. Agrell, Per J. & Brea-Solís, Humberto, 2017. "Capturing heterogeneity in electricity distribution operations: A critical review of latent class modelling," Energy Policy, Elsevier, vol. 104(C), pages 361-372.
    7. Bruno, Clementina & Manello, Alessandro, 2015. "Benchmarking and effects of reforms in the fixed telecommunications industry: A DDF approach," Telecommunications Policy, Elsevier, vol. 39(2), pages 127-139.
    8. Nieswand, Maria & Seifert, Stefan, 2018. "Environmental factors in frontier estimation – A Monte Carlo analysis," European Journal of Operational Research, Elsevier, vol. 265(1), pages 133-148.
    9. Gert Brunekreeft, 2012. "On the Role of International Benchmarking of Electricity Transmission System Operators facing significant investment requirements," Bremen Energy Working Papers 0012, Bremen Energy Research.

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    More about this item

    Keywords

    agency theory; regulation; energy networks;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • L59 - Industrial Organization - - Regulation and Industrial Policy - - - Other
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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