|Abstract as per original application
In the knowledge-based economy, high-skilled labor has become increasingly influential in firm value creation. Yet the motivations for and consequences of strategically integrating skilled labor remain empirically unexplored in the M&A literature. In this project, we take a step towards understanding the role of skilled labor in M&A decision-making and ask whether changes to the skilled labor supply help explain M&A decisions of publicly traded firms.
Large Silicon Valley technology companies such as Google and Facebook have faced significant talent shortages in recent years. This has resulted in the continued expansion of these large technology companies into other cities and states beyond Silicon Valley to access new populations of skilled labor. Anecdotal evidence suggests that in addition to direct hiring, "acquihiring", which is the practice of buying companies to acquire their talented employees rather than their projects and assets, has become a popular strategy to satisfy skilled labor demand. When the amount of highly talented individuals is in short supply, buying talent through M&A may be a more effective recruiting strategy for acquirers who are interested in teams rather than individuals. However, accurately identifying "acquihiring" is difficult, as acquirers rarely acknowledge their real intentions publicly.
In this project, we seek first to answer the fundamental question: do firms pursue M&A in response to skilled labor shortages? Employing two natural experiments, one based on random lotteries that the United States Citizenship and Immigration Services uses to allocate H-1B visas and the other based on a policy shock to the overall supply of skilled foreign labor through the H-1B program, we test whether shortages of skilled foreign workers can cause firms to pursue acquisitions. Our goal is to establish empirically a labor market channel in M&A.
Bias in estimating labor synergies by comparing firm performance between those engaging in M&A and those that do not is problematic due to the inability to control for unobservable confounding factors. We plan to address this issue with another natural experiment that compares the performance of acquirers of completed labor-driven M&A deals to acquirers of labor-driven M&A deals that are withdrawn due to reasons unrelated to skilled labor and beyond the control of those involved in the deals. We predict that exogenously completed M&A deals with high levels of labor complementarity between acquirers and targets, which we will measure using job classification data from our H-1B visa micro-dataset, will improve acquirer performance in the long-term.