ROBUSTNESS TEST: ADDITIONAL CONTROL VARIABLES

As a further robustness test, we added two additional control variables: cash holdings and female presence on corporate boards20. In short, we were interested in seeing whether our initial results of female CEOs of micro firms issuing more

19 Total debt represents only interest-bearing current- and non-current debt. Thus, total debt is defined as other long-term liabilities (item 98) plus short-term liabilities to financial institutions (item 101) plus other short-term liabilities (item 108). Meaning that elements such as provisions, trade credit and tax payable are excluded.

20 Cash Holdings is measured as cash and cash equivalent (item 76) divided by total assets (item 63 + item 78), while Female presence is measured as total female board members (item 605)

leverage compared to male CEOs of micro firms were robust to the inclusion of other control variables. Empirical research has emphasized that cash holdings are negatively related to leverage (Opler, Pinkowitz, Stulz & Williamson, 1999;

Ferreira & Viela, 2004). Following the pecking order theory, firms only issue debt when their internally generated funds are insufficient to finance new investments.

After Norway first introduced gender quotas in 2005, requiring at least 40% female presence on corporate boards for all listed companies, the topic on the effect of higher female presence on corporate boards have attracted much attention. Previous studies have emphasized that females in general are more risk averse than males.

Thus, some argue that higher female presence on corporate boards would lead firms to take more risk averse decisions, such as adopting a capital structure with less leverage (Yang, Riepe, Moser, Pull, & Terjesen, 2019). On the contrary, other authors such as Adams and Funk (2012) have emphasized that females´ risk aversion may disappear once they have broken through the glass ceiling. Thus, the presence of females in boardrooms may not necessarily result in more risk averse decision making.

From table 5, it is observed that when adding the two additional control variables, the effect of female CEOs changes from being statistically significant at the 0,01 level to being statistically significant at the 0,05 level. However, female CEO is still estimated to have a positive effect on firm leverage, but the coefficient decreases from 0,0087 to 0,0079. More interestingly, female CEOs of SMEs changes from being statistically insignificant to now being statistically significant at the 0,01 level. Thus, there is now sufficient evidence to argue that female CEOs of SMEs have a positive effect upon firm leverage. The estimated coefficient of 0,0078 implies that SMEs led by female CEOs issue 0,78% more leverage than SMEs led by male CEOs. In sum, our initial findings that female CEOs of smaller firms issue more leverage compared to male CEOs is robust to the inclusion of other control variables. Thus, our hypothesis is still not supported.

TABLE 5: Effect of female CEOs on leverage with additional control variables

Table 5 presents the result from the robustness test when adding Cash Holdings and Female Presence on boards as additional control variables. The results demonstrate the effect of female CEOs on firm’s leverage ratio. The results are obtained by running the estimated two-way random effects model with leverage as the dependent variable. Leverage is measured as total current liabilities plus total long-term liabilities, divided by total current liabilities plus total long-term liabilities plus total equity. Female CEO is defined as a dummy variable taking the value of 1 if the CEO is female, and 0 otherwise. Further, all models include firm-, industry- and CEO control variables as well as year fixed effects. Profitability is measured as return on assets, meaning operating income before depreciation divided by total assets. Tangibility is measured as total fixed assets (tangible) over total assets. Firm size is measured as the natural logarithm of sales. Growth is measured as the change in log of total assets. Risk is measured as the standard deviation of the growth in sales. Industry leverage is measured as the median of total liabilities-to-capital ratio per sector. CEO age indicates the age of the CEO in the current year t. CEO ownership is measured as the shares owned ultimately by the CEO. The additional control variable Cash Holdings is measured as cash and cash equivalent divided by total assets. Female Presence refers to the percentage of female board members and is measured as the total number of female board members divided by the total number of board members. Column (1), (2), (3) and (4) reports the estimated results for micro firms, SMEs, large firms and all firms respectively. All standard errors are clustered at firm level and presented in parentheses.

Only small differences are observed for the control variables, hence only the new additional variables are discussed. Cash holdings is observed to be negatively related to firm leverage with an estimated effect of -0,0940, -0,1244 and -0,1635

(1)

No. of observations 193 905 544 007 3 600 741 512

No. of firms 43 239 86 127 1 228 109 685

Significance at 10%, 5% and 1% are repoted as *, ** and *** respectively

for micro firms, SMEs and large firms respectively. The coefficients are statistically significant at the 0,01 level for all sub-samples, implying that as cash holdings increase by one per cent, the leverage ratio decreases by 9,40%, 12,44% and 16,35% for micro firms, SMEs and large firms respectively. On the contrary, female presence on corporate boards is only statistically significant at the 0,10 level for micro firms. In finance, the general accepted limit is at the 0,05 level. Thus, at the 0,10 level we would argue that there is not sufficient evidence to conclude on the influence of higher female presence on boards, for corporate leverage ratios. In addition, we observed that R-squared is higher for all sub-samples than in the original model.