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Bidding with budgets: Data-driven bid algorithms in digital advertising

Author

Listed:
  • Bergemann, Dirk
  • Bonatti, Alessandro
  • Wu, Nicholas

Abstract

In digital advertising, auctions determine the allocation of sponsored search, sponsored product, or display advertisements. The bids in these auctions for attention are largely generated by auto-bidding algorithms that are driven by platform-provided data.

Suggested Citation

  • Bergemann, Dirk & Bonatti, Alessandro & Wu, Nicholas, 2025. "Bidding with budgets: Data-driven bid algorithms in digital advertising," International Journal of Industrial Organization, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:indorg:v:102:y:2025:i:c:s0167718725000384
    DOI: 10.1016/j.ijindorg.2025.103172
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    References listed on IDEAS

    as
    1. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2020. "Artificial Intelligence, Algorithmic Pricing, and Collusion," American Economic Review, American Economic Association, vol. 110(10), pages 3267-3297, October.
    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. Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2025. "On the Alignment of Consumer Surplus and Total Surplus under Competitive Price Discrimination," American Economic Journal: Microeconomics, American Economic Association, vol. 17(4), pages 234-259, November.
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    5. Bergemann, Dirk & Bonatti, Alessandro & Smolin, Alex, 2025. "The Economics of Large Language Models: Token Allocation, Fine-Tuning, and Optimal Pricing," TSE Working Papers 25-1670, Toulouse School of Economics (TSE).
    6. Justin P. Johnson & Andrew Rhodes & Matthijs Wildenbeest, 2023. "Platform Design When Sellers Use Pricing Algorithms," Econometrica, Econometric Society, vol. 91(5), pages 1841-1879, September.
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    8. Dirk Bergemann & Tibor Heumann & Stephen Morris & Constantine Sorokin & Eyal Winter, 2022. "Optimal Information Disclosure in Classic Auctions," American Economic Review: Insights, American Economic Association, vol. 4(3), pages 371-388, September.
    9. Pai, Mallesh M. & Vohra, Rakesh, 2014. "Optimal auctions with financially constrained buyers," Journal of Economic Theory, Elsevier, vol. 150(C), pages 383-425.
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    11. Santiago R. Balseiro & Yonatan Gur, 2019. "Learning in Repeated Auctions with Budgets: Regret Minimization and Equilibrium," Management Science, INFORMS, vol. 65(9), pages 3952-3968, September.
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    Keywords

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    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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