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Improved Methods for Detecting Acquirer Skills

Paper Number: 1419
Creation Date: 05/17/2016

Large merger and acquisition (M&A) samples feature the pervasive presence of repetitive acquirers. They offer an attractive empirical context for revealing the presence of acquirer skills (persistent superior performance). But panel data M&A are quite heterogeneous; just a few acquirers undertake many M&As.  Does this feature affect statistical inference? To investigate the issue, our study relies statistical support for the presence of acquirer skills appears compromised.  We introduce a new resampling method to detect acquirer skills with attractive statistical properties (size and power) for presence of acquirer skills but only for a marginal fraction of the acquirer population.  This result is robust to endogenous attrition and varying time periods between successive transactions. Claims according to which acquirer skills are a first order factor explaining acquirer cross-sectional cumulated abnormal returns appears overstated. 

Paper Length: 42
Paper: SSWP1419.pdf