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Screening for Collusion in Wholesale Electricity Markets: A Review of the Literature

Author

Listed:
  • David P. Brown

    (University of Alberta, Department of Economics)

  • Andrew Eckert

    (University of Alberta, Department of Economics)

  • Douglas Silveira

    (University of Alberta, Department of Economics)

Abstract

Wholesale electricity markets have several features that increase the likelihood of collusion, including frequent interaction, multimarket contact, and a high degree of information transparency. As a result, screening techniques for detecting collusive agreements are desired. In this paper, we survey the existing literature on collusive screens and collusion in electricity markets. We discuss key features of non-competitive behaviour to be reflected in screens and suggest directions for improved screening in this industry. In particular, there is considerable potential to include machine learning and data mining techniques in screens in the electricity sector due to recent improvements in these methods.

Suggested Citation

  • David P. Brown & Andrew Eckert & Douglas Silveira, 2023. "Screening for Collusion in Wholesale Electricity Markets: A Review of the Literature," Working Papers 2023-07, University of Alberta, Department of Economics.
  • Handle: RePEc:ris:albaec:2023_007
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    File URL: https://sites.ualberta.ca/~econwps/2023/wp2023-07.pdf
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    References listed on IDEAS

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    Cited by:

    1. Antweiler, Werner & Muesgens, Felix, 2025. "The new merit order: The viability of energy-only electricity markets with only intermittent renewable energy sources and grid-scale storage," Energy Economics, Elsevier, vol. 145(C).
    2. Jeremy Proz & Martin Huber, 2025. "Machine Learning for Detecting Collusion and Capacity Withholding in Wholesale Electricity Markets," Papers 2508.09885, arXiv.org, revised Dec 2025.
    3. Chiara Fusar Bassini & Jacqueline Adelowo & Priya L. Donti & Lynn H. Kaack, 2025. "Strategic bid response under automated market power mitigation in electricity markets," Papers 2511.20812, arXiv.org.
    4. Till Fladung & Anna Saile, 2024. "Electricity Prices during the Energy Crisis in Germany: The Role of Market Power," ifo Working Paper Series 414, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    5. Frédéric Marty, 2023. "Deciphering Algorithmic Collusion: Insights from Bandit Algorithms and Implications for Antitrust Enforcement," Working Papers halshs-04363106, HAL.
    6. De Blauwe, Jilles & Zhang, Xiaobing & Keles, Dogan, 2025. "Investigating empirical bidding curves in the electricity spot market: Expected patterns vs anomalies?," Energy Economics, Elsevier, vol. 152(C).

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    JEL classification:

    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L40 - Industrial Organization - - Antitrust Issues and Policies - - - General
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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