Make or Buy Decisions and Data Sharing

Antoine Dubus and Patrick Legros

No 21125, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: Firms may share data to discover potential synergies between their data sets and algorithms, eventually leading to more efficient mergers and acquisitions (M&A) decisions. However, data sharing also modifies the competitive balance when firms do not merge, and a company may be reluctant to share data with potential rivals. Under general conditions, we show that firms benefit from (partially) sharing data. By doing so, they can merge conditionally based on high synergies. Compared to a laissez-faire situation, the presence of a regulator allowing or refusing the M&A may increase or decrease data sharing, with a concomitant increase or decrease in consumer surplus. Hence, regulation can lower the surplus of consumers it is willing to protect. We revisit the Google/Fitbit acquisition through the lens of this interplay between strategic data sharing and antitrust policy.

Keywords: Artificial intelligence; Synergies; Mergers and acquisitions; Incomplete information; Antitrust (search for similar items in EconPapers)
JEL-codes: G34 K21 L1 L21 L24 L5 L86 (search for similar items in EconPapers)
Date: 2026-02
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