Working Paper: CEPR ID: DP14466
Authors: Dirk Bergemann; Alessandro Bonatti; Tan Gan
Abstract: A data intermediary pays consumers for information about their preferences and sells the information so acquired to firms that use it to tailor their products and prices. The social dimension of the individual data---whereby an individual's data are predictive of the behavior of others---generates a data externality that reduces the intermediary's cost of acquiring information. We derive the intermediary's optimal data policy and show that it preserves the privacy of the consumers' identities while providing precise information about market demand to the firms. This enables the intermediary to capture the entire value of information as the number of consumers grows large.
Keywords: social data; personal information; consumer privacy; privacy paradox; data intermediaries; data externality; data flow; data policy; data rights
JEL Codes: D44; D82; D83
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Collection of individual data (C81) | Alters the terms of trade among consumers, advertisers, and platforms (D16) |
| Social dimension of individual data (C81) | Creates a data externality that lowers the intermediary's cost of acquiring information (D83) |
| Data intermediaries (L81) | Affect the aggregation and precision of information provided to producers (C43) |