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Budget-Management Strategies in Repeated Auctions

Author

Listed:
  • Santiago Balseiro

    (Columbia University, New York, New York 10027)

  • Anthony Kim

    (Amazon, New York, New York, 10001)

  • Mohammad Mahdian

    (Google Research, New York, New York 10011)

  • Vahab Mirrokni

    (Google Research, New York, New York 10011)

Abstract

In online advertising, advertisers purchase ad placements by participating in a long sequence of repeated auctions. One of the most important features that advertising platforms often provide and advertisers often use is budget management, which allows advertisers to control their cumulative expenditures. Advertisers typically declare the maximum daily amount they are willing to pay, and the platform adjusts allocations and payments to guarantee that cumulative expenditures do not exceed budgets. There are multiple ways to achieve this goal, and each one, when applied to all budget-constrained advertisers simultaneously, drives the system toward a different equilibrium. Our goal is to compare the “system equilibria” of a range of budget-management strategies. In particular, we consider six different budget-management strategies, including probabilistic throttling, thresholding, bid shading, reserve pricing, and two versions of multiplicative boosting. We show that these methods admit a system equilibrium, study their incentive properties, prove dominance relations among them in a simplified setting, and confirm our theoretical findings using real ad auction data from a sponsored search. Our study sheds light on the impact of budget-management strategies on the trade-off between the seller’s profit and buyers’ utility and may be of practical relevance for advertising platforms.

Suggested Citation

  • Santiago Balseiro & Anthony Kim & Mohammad Mahdian & Vahab Mirrokni, 2021. "Budget-Management Strategies in Repeated Auctions," Operations Research, INFORMS, vol. 69(3), pages 859-876, May.
  • Handle: RePEc:inm:oropre:v:69:y:2021:i:3:p:859-876
    DOI: 10.1287/opre.2020.2073
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    References listed on IDEAS

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    Cited by:

    1. Luofeng Liao & Christian Kroer, 2024. "Statistical Inference and A/B Testing in Fisher Markets and Paced Auctions," Papers 2406.15522, arXiv.org, revised Aug 2024.
    2. Benedikt Bünz & Benjamin Lubin & Sven Seuken, 2022. "Designing Core-Selecting Payment Rules: A Computational Search Approach," Information Systems Research, INFORMS, vol. 33(4), pages 1157-1173, December.
    3. Vincent Conitzer & Christian Kroer & Debmalya Panigrahi & Okke Schrijvers & Nicolas E. Stier-Moses & Eric Sodomka & Christopher A. Wilkens, 2022. "Pacing Equilibrium in First Price Auction Markets," Management Science, INFORMS, vol. 68(12), pages 8515-8535, December.
    4. Luofeng Liao & Christian Kroer & Sergei Leonenkov & Okke Schrijvers & Liang Shi & Nicolas Stier-Moses & Congshan Zhang, 2024. "Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis," Papers 2402.07322, arXiv.org.

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