How to Measure Privacy-Related Consumer Harm in Merger Analysis? A Critical Reassessment of the EU Commission’s Merger Control in Data-Driven Markets

Abstract

This study contributes to the current debate on how privacy concerns can and should be integrated into merger analysis. First, I contend that while competition authorities increasingly account for the role of personal data as a source of market power and entry barriers, privacy-related consumer harm still remains a blind spot in merger analysis. Second, I discuss how this analytical gap can be filled by mapping out three potential theories of privacy-related consumer harm: namely, privacy as an element of product quality, privacy as a feature of consumer choice, and privacy as price.

Third, and this is my major claim and contribution, this study proposes willingness-to-pay studies in the form of conjoint analysis as a methodology that enables competition authorities to quantify privacy-related consumer harm in monetary terms. In a fourth section, this study discusses potential objections to this approach. In so doing, it shows that the widespread opposition against the incorporation of privacy into merger analysis is based on a ‘privacy fallacy’. This ‘privacy fallacy’ derives from the erroneous assumption that deteriorations in the level of privacy protection as a consequence of a merger automatically amount to a breach of data-protection rules which should be addressed by data protection authorities, but which do not constitute an antitrust concern.

Keywords: big data, privacy in merger analysis, data market, privacy harm, conjoint analysis, willingness to pay