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Bidders' Responses to Auction Format Change in Internet Display Advertising Auctions

Author

Listed:
  • Shumpei Goke
  • Gabriel Y. Weintraub
  • Ralph Mastromonaco
  • Sam Seljan

Abstract

We study actual bidding behavior when a new auction format gets introduced into the marketplace. More specifically, we investigate this question using a novel dataset on internet display advertising auctions that exploits a staggered adoption by different publishers (sellers) of first-price auctions (FPAs), instead of the traditional second-price auctions (SPAs). Event study regression estimates indicate that, immediately after the auction format change, the revenue per sold impression (price) jumped considerably for the treated publishers relative to the control publishers, ranging from 35% to 75% of the pre-treatment price level of the treatment group. Further, we observe that in later auction format changes the increase in the price levels under FPAs relative to price levels under SPAs dissipates over time, reminiscent of the celebrated revenue equivalence theorem. We take this as evidence of initially insufficient bid shading after the format change rather than an immediate shift to a new Bayesian Nash equilibrium. Prices then went down as bidders learned to shade their bids. We also show that bidders' sophistication impacted their response to the auction format change. Our work constitutes one of the first field studies on bidders' responses to auction format changes, providing an important complement to theoretical model predictions. As such, it provides valuable information to auction designers when considering the implementation of different formats.

Suggested Citation

  • Shumpei Goke & Gabriel Y. Weintraub & Ralph Mastromonaco & Sam Seljan, 2021. "Bidders' Responses to Auction Format Change in Internet Display Advertising Auctions," Papers 2110.13814, arXiv.org, revised Jan 2022.
  • Handle: RePEc:arx:papers:2110.13814
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    References listed on IDEAS

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    1. Ulrich Doraszelski & Gregory Lewis & Ariel Pakes, 2018. "Just Starting Out: Learning and Equilibrium in a New Market," American Economic Review, American Economic Association, vol. 108(3), pages 565-615, March.
    2. Robert Zeithammer, 2019. "Soft Floors in Auctions," Management Science, INFORMS, vol. 65(9), pages 4204-4221, September.
    3. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    4. Jun Li & Serguei Netessine, 2020. "Higher Market Thickness Reduces Matching Rate in Online Platforms: Evidence from a Quasiexperiment," Management Science, INFORMS, vol. 66(1), pages 271-289, January.
    5. Santiago Gallino & Antonio Moreno, 2014. "Integration of Online and Offline Channels in Retail: The Impact of Sharing Reliable Inventory Availability Information," Management Science, INFORMS, vol. 60(6), pages 1434-1451, June.
    6. Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007. "Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords," American Economic Review, American Economic Association, vol. 97(1), pages 242-259, March.
    7. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    8. L. Elisa Celis & Gregory Lewis & Markus Mobius & Hamid Nazerzadeh, 2014. "Buy-It-Now or Take-a-Chance: Price Discrimination Through Randomized Auctions," Management Science, INFORMS, vol. 60(12), pages 2927-2948, December.
    9. William Vickrey, 1961. "Counterspeculation, Auctions, And Competitive Sealed Tenders," Journal of Finance, American Finance Association, vol. 16(1), pages 8-37, March.
    10. Hendricks, Ken & Porter, Robert H., 2007. "An Empirical Perspective on Auctions," Handbook of Industrial Organization, in: Mark Armstrong & Robert Porter (ed.), Handbook of Industrial Organization, edition 1, volume 3, chapter 32, pages 2073-2143, Elsevier.
    11. Athey, Susan & Haile, Philip A., 2007. "Nonparametric Approaches to Auctions," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 60, Elsevier.
    12. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    13. Mark Armstrong & Robert Porter (ed.), 2007. "Handbook of Industrial Organization," Handbook of Industrial Organization, Elsevier, edition 1, volume 3, number 1.
    14. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2015. "Repeated Auctions with Budgets in Ad Exchanges: Approximations and Design," Management Science, INFORMS, vol. 61(4), pages 864-884, April.
    15. Chiara Farronato & Jessica Fong & Andrey Fradkin, 2020. "Dog Eat Dog: Measuring Network Effects Using a Digital Platform Merger," NBER Working Papers 28047, National Bureau of Economic Research, Inc.
    16. Roger B. Myerson, 1981. "Optimal Auction Design," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 58-73, February.
    17. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
    18. David H. Autor, 2003. "Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growth of Employment Outsourcing," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 1-42, January.
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