Unique bidder-target relatedness and synergies creation in mergers and acquisitions

Tingting Liu, Lu, Zhongjin (Gene), Tao Shu and Fengrong Wei

Journal of Corporate Finance, 2022, vol. 73, issue C

Abstract: Despite the theoretical appeal of the importance of the uniqueness of firm relation in merger synergy creation, empirical evidence supporting this synergy source is limited. We examine the effect of the uniqueness of the bidder-target relationship, i.e., the number of firms that share the bidder-target relationship, on merger synergies. We use machine learning tools to measure unique bidder-target relatedness and find that unique relatedness is associated with a much larger increase in merger synergies than non-unique relatedness. The measure of unique relatedness mostly captures product relatedness, and this measure dominates alternative product relatedness measures in predicting merger synergies. Analysis of the acquirer's post-merger operating performance shows that the unique relatedness creates synergies through enhanced operating efficiency rather than increased investment or revenue.

Keywords: Mergers and acquisitions; Uniqueness of bidder-target relation; Synergy; Machine learning; Conditional dependence (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:corfin:v:73:y:2022:i:c:s0929119922000396

DOI: 10.1016/j.jcorpfin.2022.102196

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