Why Do Merger Premiums Vary Across Industries and Through Time? Explaining merger premiums by time-varying industry factors

Abstract

To understand how merger premia vary across industries and over time, we analyze 1184 deals involving US public targets and acquirers between 2010 and 2020. The variables and methodology are inspired by Madura, Ngo & Viale (2012) who examined merger premiums on US public targets and acquirers between 1986 and 2007. We use random effects regressions to study cross-sectional variation in average merger premiums per industry per quarter, and time-series variation among quarters per industry. Therefore, our unit of analysis is industries, rather than individual deals. We also create separate sub-samples and analyze differences between the medium of payment. Overall, we are unable to replicate the results of Madura et al. (2012). Specifically, in our total sample and in our sub sample on cash, we identify a positive relationship between premiums and Tobin's Q. We also observe a negative relationship between GDP growth and premiums in our total sample. In contrast and regardless of the medium of payment, Madura et al. (2012) found that premiums were positively related to industries experiencing strong growth, industries with high levels of R&D expenditures, and highly concentrated industries. However, similar to Madura et al. (2012), we find that there is variation in quarterly average premiums among industries for a given quarter, indicating that the cost of a merger is segmented by industries. This means that acquirers may need to pay higher premiums for targets in certain industries and at certain times. To test the robustness of the methodology presented by Madura et al. (2012), we conduct disaggregated OLS regressions. As measuring at the industry level yields small variations among the variables, we run regressions on individual takeover premiums. Instead of regressing industry averages, we conduct OLS regressions on individual target-specific factors. We also assign each target with their corresponding industry values for variables that cannot be measured at the individual level. Our robustness test suggests that not all papers on this subject are replicable, and that the methodology presented by Madura et al. (2012) may have certain challenges in explaining premiums.