How Do Digital Advertising Auctions Impact Product Prices?

S-Tier
Journal: Review of Economic Studies
Year: 2025
Volume: 92
Issue: 4
Pages: 2330-2358

Authors (3)

Dirk Bergemann (Yale University) Alessandro Bonatti (not in RePEc) Nicholas Wu (not in RePEc)

Score contribution per author:

2.681 = (α=2.01 / 3 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

We present a model of digital advertising with three key features: (1) advertisers can reach consumers on and off a platform, (2) additional data enhances the value of advertiser–consumer matches, and (3) the allocation of advertisements follows an auction-like mechanism. We contrast data-augmented auctions, which leverage the platform’s data advantage to improve match quality, with managed-campaign mechanisms that automate match formation and price-setting. The platform-optimal mechanism is a managed campaign that conditions the on-platform prices for sponsored products on the off-platform prices set by all advertisers. This mechanism yields the efficient on-platform allocation but inefficiently high off-platform product prices. It attains the vertical integration profit for the platform and the advertisers, and it increases off-platform product prices while decreasing consumer surplus, relative to data-augmented auctions.

Technical Details

RePEc Handle
repec:oup:restud:v:92:y:2025:i:4:p:2330-2358.
Journal Field
General
Author Count
3
Added to Database
2026-01-24