Abstract
Gender diversity on the board of directors can influence companies’ voluntary disclosure such as their environmental, social and governance disclosure (ESG). A growing body of literature suggests that most of the work of the board occurs in committees, which are smaller working groups within the board. In a smaller working group, even a small number of women can represent a higher proportion of the group. Therefore, the influence of gender diversity on a board’s decisions can be more prevalent in committees, since women’s ideas and opinions can have more of an impact in smaller working groups. By being on committees, women have the chance to actively contribute to board tasks and decisions. This study investigates the relationship between the gender diversity of the board and its main committees and the ESG disclosure of Canadian-listed companies. The results indicate a positive and significant relationship between female representation on the board and committees and ESG disclosure. Using a structural equation model, the results suggest that there is a joint influence on ESG disclosure of gender diversity at the board level and at the committee. level. In addition, the study demonstrates that for ESG disclosure, the influence of female representation on committees is higher than the influence of female representation on the board. This study shows that by being on committees, women can better contribute to board decisions and that the influence of board gender diversity is not limited to female representation on the board but also comes from female representation on committees.
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Notes
Endrikat et al. (2021), following a meta-analysis of empirical studies, find that a specific country context can influence the effect of female board representation on, for example, corporate social responsibility. We expect the Canadian legal and institutional context to influence the findings of this research, which may limit the generalizability of the results.
We also had to add two instrumental variables, following the steps of previous studies such as Katmon et al. (2019). In fact, prior research suggests that board size and board independence are exogenous instruments to predict the percentage of women directors (Ben-Amar et al., 2017). Moreover, the presence of women in top management can also predict the presence of women on the board (Grosvold et al., 2016; Guldiken et al., 2019). We performed several post-estimation tests on our instrumental variables to ensure they are strong, valid and reliable. In order to deal with heteroscedasticity, we considered robust standard errors (White, 1980) in Stata.
The Bloomberg ESG disclosure score captures only the extent of the ESG disclosure. This score does not capture the quality of the ESG disclosure, which might induce some limitations in our study.
As in Baldini et al. (2018), the ESG scores of the companies included in our sample exposed high kurtosis (presence of outliers) and skewness (lack of symmetry).
The Blau index measures the diversity within a population. Blau’s (1960) heterogeneity index: \({\text{Blau - index}} = (1 - \sum\nolimits_{{\text{i}} = 1}^{\text{n}} {{\text{p}}_{\text{i}}^2} )\), where \({p}_{i}\) is the proportion of team members in the ith category (e.g., Wiersema & Bantel 1992).
The committees included in this study are all related to board functioning and decision-making. These committees are also the most represented among Canadian-listed companies.
The audit committee is the only mandatory committee, according to the Canadian regulation on corporate governance (National Instrument 52–110).
A study from De Villiers et al. (2022) shows that the risk committee is an important addition to the board of directors structure and that the characteristics of members of this committee (such as tenure as board member and work experience) can positively influence the environmental performance of companies.
Medsem is a post-estimation command that allows us to not only assess whether the mediator carries the influence of the independent variable to the dependent variable (Sobel, 1982) but also to calculate the indirect effects of the mediating variable using Baron and Kenny’s (1986) and Zhao et al.’s (2010) approaches.
Table 7 presents the standardized results of the overall model in terms of path coefficients, Z-statistics and proportion of variance (R2). Goodness-of-fit indices are presented in the footnote following the table.
Total effect calculation: Direct effect: 0.131. Indirect effect: \(0.36 \times 0.76 = 0.273\). Total effect = 0.131 + 0.273 = 0.404.
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Khemakhem, H., Arroyo, P. & Montecinos, J. Gender diversity on board committees and ESG disclosure: evidence from Canada. J Manag Gov 27, 1397–1422 (2023). https://doi.org/10.1007/s10997-022-09658-1
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DOI: https://doi.org/10.1007/s10997-022-09658-1