Abstract
What role does data play in competition? This question has been at the center of a fierce debate around competition policy in the digital economy. We use a competition-in-utilities approach to provide a general framework for studying the competitive effects of data, encompassing a wide range of markets where data has many different uses. We identify conditions for data to be unilaterally proor anti-competitive (UPC or UAC). The conditions are simple and often require no information about market demand. We apply our framework to study various applications of data, including training algorithms, targeting advertisements, and personalizing prices. We also show that whether data is UPC or UAC has important implications for policy issues such as data-driven mergers, market structure, and privacy policy.
JEL codes
- L1: Market Structure, Firm Strategy, and Market Performance
- L4: Antitrust Issues and Policies
- L5: Regulation and Industrial Policy
Replaced by
Alexandre de Cornière, and Greg Taylor, “Data and Competition: A Simple Framework”, TSE Working Paper, n. 23-1404, January 2023.
Reference
Alexandre de Cornière, and Greg Taylor, “Data and Competition: a General Framework with Applications to Mergers, Market Structure, and Privacy Policy”, TSE Working Paper, n. 20-1076, February 2020, revised December 2021.
See also
Published in
TSE Working Paper, n. 20-1076, February 2020, revised December 2021