An investigation into withdrawing from M&A deals : evidence from the United States

Abstract

Purpose: This study investigates whether managers withdraw from a M&A deal once they observe a negative cumulative abnormal return. Moreover, it assesses whether their decision changes with respect to factors such as the listing status of the firm, its macro industry, and target size. Design/methodology/approach: Using a sample of 767 M&A US deals over the period 2005-2014 and applying an Event Study methodology, Cumulative Abnormal Returns (CAR) are calculated and introduced in a Logit model to assess the above mentioned matter. Findings: Results show that managers do listen to the market when observing a negative CAR during the acquisition announcement period; hence, they withdraw from the takeover deal. Moreover, managers of firms who are acquiring a private target firm and/or a diversifying target firm ignore the market reaction, and the likelihood of deal cancellation does not change. However, whenever the target firm is a public firm and from the same industry, the likelihood of deal cancellation increases. Furthermore, there is simply no effect of CAR on the likelihood of deal cancellations in large acquisitions. Research limitations/Implications: A theoretical implication for this study lies in examining the implications of the Agency Theory on manager’s decisions. However, like any other research, this study faces some limitations, in particular, having more firm specific data, defining the characteristics of a private and public target, and defining the structure of acquirer firm. Practical implications: A practical implication for this study lies in informing decision makers of the different variables affecting the likelihood of withdrawal or success of M&A deals. Originality/value: Despite the academic attention paid to the subject of M&A, there is a research gap in studying whether managers listen to the market. Hence, this study attempts to fill this gap by constructing a comprehensive model that assesses the effect of identified variables on the decision to withdraw or stay.