Quality Externalities on Platforms∗

In order to screen out low-quality sellers or incentivize high quality, platforms need a good measure of seller quality. Having high-quality sellers is particularly important if buyers on a platform have limited information about the sellers; buyers’ learning means that the quality of a seller in any given transaction will affect whether or how frequently that buyer returns to the platform. The number of times that a seller’s buyers return to the platform is an externality that the seller exerts on other sellers on the platform; we propose using this externality to measure seller quality. Using data from Airbnb, a peer-to-peer accommodation platform, we calculate each listing’s guest return propensity (GRP), defined as the average number of subsequent bookings a listing’s guests complete, controlling for guest and trip characteristics. There is substantial variation in GRP across listings and its correlation with a listing’s average rating is only 0.05. Using an instrumental variable analysis to account for unobservable guest characteristics, we find that our measure of GRP has a causal effect on returns: a one standard deviation increase in GRP causes guests to take an additional 0.34 trips (a 17% increase). We discuss how platforms can increase overall seller surplus by directing buyers towards higher quality sellers, either by using Pigouvian subsidies for quality or by prioritizing high-quality sellers in their search algorithms. ∗The opinions and views expressed herein are those of the authors, not Airbnb. The authors thank Kevin Murphy for helpful comments and Ryan Parks and Anya Marchenko for research assistance. †University of Chicago. Corresponding author: [email protected] ‡Airbnb §University of Chicago ¶Airbnb