Unique Bidder-Target Relatedness and Synergies Creation in Mergers and Acquisitions

Abstract

We examine the effect of the uniqueness of bidder-target relation, i.e., the number of firms that share the bidder-target relation, 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 the 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 an increase in investment or revenue.

Keywords: Distinct Relatedness, Synergies, Mergers and Acquisitions, Conditional Dependence, Lasso, Stock return comovement

JEL Classification: G34, G30