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Innis Lecture: Algorithmic pricing and competition

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  • Robert Clark

Abstract

This article examines how advances in AI‐driven algorithmic pricing are reshaping the nature of cartel formation and coordination. Traditionally, cartels relied on explicit communication, extensive organization, and sustained human effort to reach and maintain agreement while avoiding detection. Recent technological developments now raise concerns that coordination may arise with far less human involvement. In particular, three main risks are identified: the deliberate use of algorithms to implement collusive strategies, the role of algorithms as third‐party facilitators of collusion, and the possibility that algorithms may autonomously learn to collude. While algorithmic pricing can enhance efficiency and competition, the article assesses these risks and considers associated legal implications.

Suggested Citation

  • Robert Clark, 2025. "Innis Lecture: Algorithmic pricing and competition," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 58(4), pages 1236-1253, November.
    • Handle: RePEc:wly:canjec:v:58:y:2025:i:4:p:1236-1253
    DOI: 10.1111/caje.70035
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    References listed on IDEAS

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    1. Robert Clark & Jean-Fran?ois Houde, 2013. "Collusion with Asymmetric Retailers: Evidence from a Gasoline Price-Fixing Case," American Economic Journal: Microeconomics, American Economic Association, vol. 5(3), pages 97-123, August.
    2. John Asker & Chaim Fershtman & Ariel Pakes, 2024. "The impact of artificial intelligence design on pricing," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 276-304, March.
    3. Marhsall, Robert C. & Marx, Leslie M., 2014. "The Economics of Collusion: Cartels and Bidding Rings," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262525941, December.
    4. Jorge Lemus & Fernando Luco, 2021. "Price Leadership and Uncertainty About Future Costs," Journal of Industrial Economics, Wiley Blackwell, vol. 69(2), pages 305-337, June.
    5. Juan Esteban Carranza & Robert Clark & Jean-François Houde, 2015. "Price Controls and Market Structure: Evidence from Gasoline Retail Markets," Journal of Industrial Economics, Wiley Blackwell, vol. 63(1), pages 152-198, March.
    6. Stephanie Assad & Robert Clark & Daniel Ershov & Lei Xu, 2024. "Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market," Journal of Political Economy, University of Chicago Press, vol. 132(3), pages 723-771.
    7. John Asker, 2010. "A Study of the Internal Organization of a Bidding Cartel," American Economic Review, American Economic Association, vol. 100(3), pages 724-762, June.
    8. Ulrich Schwalbe, 2018. "Algorithms, Machine Learning, And Collusion," Journal of Competition Law and Economics, Oxford University Press, vol. 14(4), pages 568-607.
    9. Robert Clark & Decio Coviello & Adriano De Leverano, 2025. "Complementary Bidding and the Collusive Arrangement: Evidence from an Antitrust Investigation," American Economic Journal: Microeconomics, American Economic Association, vol. 17(2), pages 66-93, May.
    10. Jean-Pierre Dubé & Sanjog Misra, 2023. "Personalized Pricing and Consumer Welfare," Journal of Political Economy, University of Chicago Press, vol. 131(1), pages 131-189.
    11. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2019. "Algorithmic Pricing What Implications for Competition Policy?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 55(1), pages 155-171, August.
    12. Douglas Rivers & Quang Vuong, 2002. "Model selection tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 1-39, June.
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