【12月10日】Human Capital and Knowledge Spillover in Mergers and Acquisitions发布日期：2019-09-12 21:09:35
Dr. Jin Wang is an associate professor of finance in the Lazaridis School of Business and Economics of Wilfrid Laurier University. His research interests are primarily in empirical corporate finance and investment. His work has been published in leading academic journals such as the Journal of Financial Economics, Management Science, the Journal of Financial and Quantitative Analysis, and the Journal of Corporate Finance. His recent research focuses on corporate innovation and investigates corporate policies and valuations in technology space. Dr. Wang teaches courses in corporate finance and investment at the undergraduate and MBA levels. He also teaches empirical corporate finance to PhD students in the Lazaridis School of Business and Economics.
“Human Capital and Knowledge Spillover in Mergers and Acquisitions”, by Kai Li (University of British Columbia) and Jin Wang (Wilfrid Laurier University)
In this paper, we examine what acquirers get from buying other innovative firms: best people, best ideas, or both. We first show that target inventors with a high level of target-specific capital, with a high level of target-specific team capital, as well as with a greater patent output are more likely to be retained by an acquirer, whereas target inventors with a large coinventing network, and having a different core technology class from the acquirer are less likely to be retained. Using a sample of withdrawn bids for identification and a difference-in-differences specification, we show that post-merger, retained target inventors experience no change in their patent output compared to their peers in withdrawn bids, whereas acquirer inventors experience a surge in their patent output compared to their peers in withdrawn bids. In terms of cross-sectional variation, we find that more specialized inventors, longer-tenured inventors, and inventor with less firm-specific team capital tend to be more productive post-merger. We further show evidence of knowledge spillover from acquirers to targets by the significant increase in the share of new patents by retained target inventors in the acquirer’s technology classes, but we do not find similar spillover from targets to acquirers as there is no significance increase in the share of new patents by acquirer inventors in the target’s technology classes post-merger. Moreover, we show that post-merger, retained target inventors produce significantly more patents in new classes (to the acquirer and the target) and more impactful patents than their peers in withdrawn bids. We conclude that the primary reason for innovation-driven M&As appears to be acquiring target talent rather than taking advantage of knowledge spillover.