DP17404 The Sale of Data: Learning Synergies Before M&As

Author(s): Antoine Dubus, Patrick Legros
Publication Date: June 2022
Keyword(s): Antitrust, incomplete information, mergers, privacy, sale of data, synergies
JEL(s): K21, L1, L21, L24, L41, L5
Programme Areas: Industrial Organization
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=17404

Firms may share information to discover potential synergies between their data sets and algorithms, which eventually may lead to more e�cient mergers and acquisitions (M&A) decisions. However, as pointed out by Arrow, information sharing also modi�es the competitive balance when companies do not merge, and a �rm may be reluctant to share information with potential rivals. Under general conditions, we show that �rms bene�t from (partially) sharing information. Because more sharing of information may increase industry expected pro�ts both when there is head-to-head competition and when there is an M&A, the presence of a regulator who can prevent or allow the M&A can decrease or increase the level of information sharing, as well as consumer surplus, with respect to the no-regulator case. A regulator who can also control the level of information sharing will allow �rms to share information.