Data and Competition: A Simple Framework with Applications to Mergers and Market Structure

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 provide a simple framework for studying the competitive effects of data, encompassing a wide range of applications (product improvement, targeted advertising, price-discrimination) using a competition-in-utilities approach. We model data as a revenue-shifter, and identify conditions for data to be pro- or anti-competitive. The conditions are simple and often do not require knowledge of market demand or calculation of equilibrium. We use this framework to address policy-relevant questions related to market structure and data-driven mergers. We show that the effects of a data-driven merger between firms operating on adjacent markets depend both on whether data is pro- or anti-competitive and on firms' ability to trade data absent the merger.

Keywords: Big Data, Competition, data-driven mergers, privacy

JEL Classification: L1, L4, L5