Using Grouped Data to Estimate Revenue Heterogeneity in Online Advertising Auctions
AbstractThis 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.
CitationBreitmar, Nils A., Matthew Harding, and Carlos Lamarche. 2023. "Using Grouped Data to Estimate Revenue Heterogeneity in Online Advertising Auctions." AEA Papers and Proceedings, 113: 161-65. DOI: 10.1257/pandp.20231095
- D44 Auctions
- D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- L82 Entertainment; Media
- M37 Advertising