Selling Data

55 Pages Posted: 10 May 2019 Last revised: 25 Aug 2022

Date Written: August 23, 2022

Abstract

A profit-maximizing monopolist (seller) sells multi-attribute consumer data to a firm (buyer). The seller is uncertain about which unknown consumer characteristic the buyer is interested in forecasting and how much the buyer values information. In order to screen among potential buyers along both margins, the seller chooses a menu of statistics of the data to offer and the price of each statistic. Assuming that the data and unknown characteristics follow an elliptical distribution, I obtain two results. First, I show that the seller optimally offers statistics that are linear combinations of the data. Second, I show that the seller might need to offer a continuum of statistics, and that they are less correlated than they would be if the seller could perfectly discriminate. Every optimal statistic contains information about every variable in the data, and does not include uncorrelated noise.

Keywords: Information Design, Mechanism Design, Multidimensional Screening, Product Design

JEL Classification: D42, D82, D83, D86

Suggested Citation

Segura-Rodriguez, Carlos, Selling Data (August 23, 2022). PIER Working Paper No. 19-006 , Available at SSRN: https://ssrn.com/abstract=3385500 or http://dx.doi.org/10.2139/ssrn.3385500

Carlos Segura-Rodriguez (Contact Author)

Central Bank of Costa Rica ( email )

Apartado Postal 10058
1000 San Jose
United States

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