Improved Methods for Detecting Acquirer Skills
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.