Using Grouped Data to Estimate Revenue Heterogeneity in Online Advertising Auctions

Nils A. Breitmar, Matthew Harding and Carlos Lamarche

AEA Papers and Proceedings, 2023, vol. 113, 161-65

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.

JEL-codes: D44 D83 L82 M37 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1257/pandp.20231095

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