56 Pages Posted: 29 Jan 2020 Last revised: 17 Aug 2020

There are 2 versions of this paper

Date Written: January 29, 2020

Abstract

This paper studies the effects of the EU’s General Data Protection Regulation (GDPR) on the ability of firms to collect consumer data, identify consumers over time, accrue revenue via online advertising, and predict their behavior. Utilizing a novel dataset by an intermediary that spans much of the online travel industry, we perform a difference-in-differences analysis that exploits the geographic reach of GDPR. We find a 12.5% drop in the intermediary-observed consumers as a result of the new opt-in requirement of GDPR. At the same time, the remaining consumers are observable for a longer period of time. We provide evidence that this pattern is consistent with the hypothesis that privacy-conscious consumers substitute away from less efficient privacy protection (e.g, cookie deletion) to explicit opt out, a process that would reduce the number of artificially short consumer histories. Further in keeping with this hypothesis, we observe that the average value of the remaining consumers to advertisers has increased, offsetting most of the losses from consumers that opt out. Finally, we find that the ability to predict consumer behavior by the intermediary’s proprietary machine learning algorithm does not significantly worsen as a result of the changes induced by GDPR. Our results highlight the externalities that consumer privacy decisions have both on other consumers and for firms.

