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Conditional Yardstick Competition in Energy Regulation

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  • Timo Kuosmanen and Andrew L. Johnson

Abstract

Yardstick competition is a regulation regime that forces local monopolies to compete against a variable cost or total cost benchmark. The variable cost benchmark ignores the fixed capital, creating a strong incentive to over-invest, whereas the total cost benchmark assumes all costs to be variable, ignoring the investment risk. We propose theoretical, methodological, and operational advances to increase applicability of yardstick competition in energy regulation. In the proposed conditional yardstick regime capital is treated as a fixed input, and the local monopolies compete against the variable cost conditional on the fixed input. We develop a benchmarking method that can handle multiple outputs, heterogeneity, and shape constraints to ensure incentive compatibility. We discuss the real-world application of the proposed regime to the Finnish electricity distribution firms in 2016ý2023. We argue that smarter regulation of network industries can contribute to lower risk premiums and help to achieve win-win solutions both in terms of reliability and affordability.

Suggested Citation

  • Timo Kuosmanen and Andrew L. Johnson, 2020. "Conditional Yardstick Competition in Energy Regulation," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
  • Handle: RePEc:aen:journl:ej41-si1-kuosmanen
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    References listed on IDEAS

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    1. Jean-Jacques Laffont & Jean Tirole, 1993. "A Theory of Incentives in Procurement and Regulation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262121743, December.
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    3. Kuosmanen, Timo & Johnson, Andrew, 2017. "Modeling joint production of multiple outputs in StoNED: Directional distance function approach," European Journal of Operational Research, Elsevier, vol. 262(2), pages 792-801.
    4. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.
    5. Mark Armstrong & Simon Cowan & John Vickers, 1994. "Regulatory Reform: Economic Analysis and British Experience," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262510790, December.
    6. 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.
    7. Eskelinen, Juha & Kuosmanen, Timo, 2013. "Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5163-5175.
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    Cited by:

    1. Timo Kuosmanen & Sheng Dai, 2025. "Modeling economies of scope in joint production: Convex regression of input distance function," Journal of Productivity Analysis, Springer, vol. 63(1), pages 69-86, February.
    2. Liao, Zhiqiang & Dai, Sheng & Kuosmanen, Timo, 2024. "Convex support vector regression," European Journal of Operational Research, Elsevier, vol. 313(3), pages 858-870.
    3. Zhiqiang Liao, 2024. "Variable selection in convex nonparametric least squares via structured Lasso: An application to the Swedish electricity distribution networks," Papers 2409.01911, arXiv.org, revised Nov 2024.
    4. Asantewaa, Adwoa & Jamasb, Tooraj & Llorca, Manuel, 2022. "Reforming Small Electricity Systems: Market Design and Competition," Working Papers 12-2022, Copenhagen Business School, Department of Economics.
    5. Asantewaa, Adwoa & Jamasb, Tooraj & Llorca, Manuel, 2023. "Electricity sector reforms and cost efficiency: The case of small electricity systems in Sub-Sahara Africa," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 880-893.

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