DP14446 Data and Competition: a General Framework with Applications to Mergers, Market Structure, and Privacy Policy

Author(s): Alexandre de Cornière, Greg Taylor
Publication Date: February 2020
Date Revised: February 2020
Keyword(s): Big Data, Competition, data-driven mergers, privacy
JEL(s): L1, L4, L5
Programme Areas: Industrial Organization
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=14446

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 pro- or anti-competitive (UPC or UAC). The conditions are simple and often requires 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.