The Sale of Data: Learning Synergies Before M&As

Antoine Dubus (antoine1dubus@gmail.com) and Patrick Legros
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Antoine Dubus: D-MTEC - Department of Management, Technology, and Economics [ETH Zürich] - ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]

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Abstract: Firms may share information to discover potential synergies between their data sets and algorithms, eventually leading to more efficient mergers and acquisitions (M&A) decisions. However, information sharing also modifies the competitive balance when companies do not merge, and a firm may be reluctant to share information with potential rivals. Under general conditions, we show that firms benefit from (partially) sharing information. 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 information sharing, with a concomitant increase or decrease in consumer surplus. Hence, regulation can lower the surplus of consumers it is willing to protect. An optimal merger policy combines merger control with mandated data-sharing rules.

Date: 2024-10-30
New Economics Papers: this item is included in nep-bec, nep-com, nep-ind, nep-mic and nep-reg
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Working Paper: The Sale of Data: Learning Synergies Before M&As (2022)
Working Paper: The Sale of Data:Learning Synergies Before M&As (2022)
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