PNAS 2026 Article
Title: Can Privacy Technologies Replace Cookies? Ad Revenue in a Field Experiment
Authors: Zhengrong Gu (Boston University), Garrett A. Johnson (Boston University), Shunto Kobayashi (Boston University)
Abstract/Summary: Digital advertising finances much of the open web, yet relies on tracking technologies that regulators increasingly seek to restrict. In response, industry has developed privacy-enhancing technologies intended to preserve advertising performance while limiting data collection, but their economic effects remain largely untested. We study this question using an open, industry-wide field experiment jointly overseen by Google and the UK Competition and Markets Authority, in which Chrome users were randomly assigned to browse with third-party cookies enabled, with cookies disabled, or with Google’s Privacy Sandbox replacing cookies. Combining this experimental variation with proprietary data from a major ad management firm, we analyze more than 200 million ad impressions across over 5,000 publishers worldwide. Removing third-party cookies reduces publisher advertising revenue by 29.1%. Privacy Sandbox recovers only 4.2% of this lost revenue; this estimate reflects observed adoption and performance during the study period and may reflect modest industry adoption. Privacy-preserving auctions also increase ad latency, reducing impression delivery and further limiting revenue performance. Together, these findings provide a large-scale experimental benchmark for evaluating privacy-preserving reforms and demonstrate the difficulty of reconciling privacy protection with the economics of online content provision.