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Using Grouped Data to Estimate Revenue Heterogeneity in Online Advertising Auctions

Author

Listed:
  • Nils A. Breitmar
  • Matthew Harding
  • Carlos Lamarche

Abstract

This paper estimates the heterogeneous impact of advertising networks from the perspective of a publisher who has access to limited information provided by the advertising platform in the form of grouped data over different auctions and users. The models account for the high-dimensional nature of the data and allow for time-varying interactive effects. We estimate models for different countries, and the measured heterogeneity may reflect factors such as local competition or cost effectiveness.

Suggested Citation

  • Nils A. Breitmar & Matthew Harding & Carlos Lamarche, 2023. "Using Grouped Data to Estimate Revenue Heterogeneity in Online Advertising Auctions," AEA Papers and Proceedings, American Economic Association, vol. 113, pages 161-165, May.
    • Handle: RePEc:aea:apandp:v:113:y:2023:p:161-65
    DOI: 10.1257/pandp.20231095
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    More about this item

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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