Publication Date: September 2019
Revision Date: March 2020
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 Classification Codes: D44, D82, D83.