Abstract: The advent of online advertising has simultaneously created unprecedented opportunities for advertisers to target consumers and prompted privacy concerns among consumers and regulators. This paper estimates the financial impact of privacy policies on the online display ad industry by applying an empirical model to a proprietary auction dataset. Two challenges complicate the analysis. First, while the advertisers are assumed to publicly observe tracking profiles, the econometrician does not see this data. My model overcomes this challenge by disentangling the unobserved premium paid for certain users from the observed bids. In order to simulate a market in which advertisers can no longer track users, I set the unobserved bid premium's variance to zero. Second, the data provider uses a novel auction mechanism in which first-price bidders and second-price bidders operate concurrently. I develop new techniques to analyze these hybrid auctions. I consider three privacy policies that vary by the degree of user choice. My results suggest that online publisher revenues drop by 3.9% under an opt-out policy, 34.6% under an opt-in policy, and 38.5% under a tracking ban. Total advertiser surplus drops by 4.6%, 40.9%, and 45.5% respectively.

Abstract: Yahoo! Yahoo! Research partnered with a nationwide retailer to study the effectiveness of display advertising on online and in-store sales for more than three million shared customers. We measure the impact of higher ad impression frequency using a simple experimental design on Yahoo!: users in the `Full' treatment group see the retailer's ads, users in the `Control' group see unrelated control ads, and users in the `Half' treatment group see an equal probability mixture of the retailer and control ads. We find statistically significant evidence that the retailer ads increase sales 3.6% in the Full group relative to the control group. Doubling the average number of impressions per person, from 17 to 34 in a two-week period, nearly doubled the treatment effect. Leveraging our experimental design, we find that the returns to ad frequency are approximately linear among those who were eligible to see up to 50 ads and the marginal return to an additional ad exposure is $0.04. We also find evidence that the ads had a stronger effect on customers who live closest to the retailer's brick-and-mortar locations, customers who purchased recently, loyal customers, and wealthy customers.