Mars-Venus Marriages: Culture and Cross-Border M&A

For computing abnormal returns, we use the market-adjusted returns approach – i.e.
the simple excess of stock returns over market returns 14 . Table 3 presents the summary
statistics for the BHARs of the acquiring company over different windows. Since data is not
available for all acquiring companies for the entire 36-month post-merger period, the number
of observations decline as the length of the window increases. One trend evident in Table 3 is
the negative performance of the median acquirer vis-à-vis its country index, though the
average BHARs are positive owing to large gains by the “winners”.
In Panel A of Table 4, we present the summary statistics for the key explanatory
variables in our study, the Hofstede measure of cultural distance. Table 4 (Panel B) shows the
five country pairs with maximum similarity in culture and the five pairs with most dissimilar
cultures. We provide the Hofstede cultural distance measure for these ten country pairs. In
our sample, Australia and United States have the most similar cultures, while Sweden and
Japan have the most dissimilar cultures.
In Table 5 Panel A, we present the results of our regression of long-term performance
on various independent variables. The dependent variable is the BHARs of acquiring
companies over 36 months. The explanatory variables are the various deal-specific, economic
and cultural country-level variables. The variables used in the regression analysis have been
discussed previously and are also presented in summary form in Appendix I. We use effective
year fixed-effects to control for all time-related factors (e.g. macroeconomic conditions,
merger waves etc.) One major challenge in studying the determinants of cross-border M&A
performance is to satisfactorily control for country-specific effects which are not related to
our variables of interest. In our OLS regressions, we have a common problem arising in
regressions involving cross country regressions. While we include several country-level
variables, there may be many unknown country specific variables that are difficult to control
for. In order to minimize this problem, we use clustered multivariate regressions with robust
standard errors and target country and year fixed effects. Our specifications account for
14
In our robustness checks, we also use the Fama-French factors to adjust for risk for the US
acquirers.
14