100 Fuqua Drive
Durham, NC 27708
Institutional Affiliation: Duke University
NBER Working Papers and Publications
|September 2019||Too Much Data: Prices and Inefficiencies in Data Markets|
with Daron Acemoglu, Azarakhsh Malekian, Asuman Ozdaglar: w26296
When a user shares her data with an online platform, she typically reveals relevant information about other users. We model a data market in the presence of this type of externality in a setup where one or multiple platforms estimate a user’s type with data they acquire from all users and (some) users value their privacy. We demonstrate that the data externalities depress the price of data because once a user’s information is leaked by others, she has less reason to protect her data and privacy. These depressed prices lead to excessive data sharing. We characterize conditions under which shutting down data markets improves (utilitarian) welfare. Competition between platforms does not redress the problem of excessively low price for data and too much data sharing, and may further reduce wel...
|November 2017||Fast and Slow Learning From Reviews|
with Daron Acemoglu, Azarakhsh Malekian, Asuman Ozdaglar: w24046
This paper develops a model of Bayesian learning from online reviews, and investigates the conditions for asymptotic learning of the quality of a product and the speed of learning under different rating systems. A rating system provides information about reviews left by previous customers. A sequence of potential customers decide whether to join the platform. After joining and observing the ratings of the product, and conditional on her ex ante valuation, a customer decides whether to purchase or not. If she purchases, the true quality of the product, her ex ante valuation, an ex post idiosyncratic preference term and the price of the product determine her overall satisfaction. Given the rating system of the platform, she decides to leave a review as a function of her overall satisfaction....