Governmental Ownership, Board Gender Diversity, and ESG Performance: Evidence from an Emerging Market

Abstract

Consistent with Sustainable Development Goal 5 (SGG 5) concerned with gender equality, this study examines the relationship between Board Gender Diversity (BGD) and environmental, social, and corporate governance (ESG) performance. In addition, it investigates the moderating role of governmental ownership concerning this relation by focusing on an emerging market. A sample of 71 Egyptian-listed companies on EGX100 during 2014–2019 has been examined. Both univariate and multivariate analyses are conducted to examine the relationship between BGD and ESG performance and the effect of governmental ownership on this relationship using OLS, 2SLS, and Logistic regressions. The results revealed a positive relation between BGD and ESG performance. In addition, we found that governmental ownership has a moderating effect on the relationship between BGD and ESG performance. This finding indicates that the effect of BGD on ESG performance in emerging markets is conditional on the governmental ownership, which provides a fertile environment for BGD to support ESG issues. The results add to the growing interest regarding the implications of BGD and governmental ownership for ESG performance in emerging economies. This study has significant implications for regulatory bodies, firms, and investors in emerging markets such as Egypt. It ensures that board gender diversity can enhance ESG performance in the case of governmental ownership. In addition, it highlighted the value of enforceable regulations on overseeing private firms’ ESG performance.

1. Introduction

Following the issuance of SDG 5 by the United Nations in 2015, gender equality and the representation of females in corporate boards (i.e., board gender diversity (BGD)) have become of growing importance in the business world [1]. Recognizing the value of gender diversity is crucial to building a future that is more resilient and sustainable, especially in emerging economies [2,3,4]. Thus, today’s firms in emerging markets strive to establish a more equitable and an inclusive environment [5]. The inclusion of female directors is vital to enhancing board effectiveness in managing stakeholders and to giving women equal opportunities to participate in sustainability initiatives at all levels. It also promotes corporate social equality and female empowerment, as required by SDG 5 [1,6]. As a result, examining the implications of board diversity for firm performance and practices has recently attracted researchers’ attention [1]. Bernile et al. noted that board diversity leads to lower volatility [7]. Bin Khidmat et al. showed that BGD positively and significantly affects firm performance [8]. Consequently, diverse boards with a good representation of females can outperform boards that lack such a representation [9,10,11].

The existence of women in companies’ boards results in distinct viewpoints and multiple experiences and abilities which can increase creativity and decision-making, e.g., [7,9,12,13]. Women also have different human capital and backgrounds, which can improve employee engagement and create a more welcoming work environment. This context can foster organizational success and enhance corporate social and environmental performance [8,10]. In this regard, the recent literature has highlighted that a firm’s overall performance, including ESG performance, can benefit from board diversity, and that women’s representation on boards is essential for advancing sustainable practices [13,14,15,16].

However, private firms are limited in their ability to fulfill social responsibilities, as they focus mainly on accumulating capital [17]. Hence, the undertaking of ESG responsibilities by private firms is likely to involve an egoistic behavior [18,19,20] to achieve utilitarian objectives, such as meeting shareholders’ needs or enhancing firms’ reputations [21]. According to the legitimacy and stakeholder theories, governments pressure firms to improve their social performance [22]. Thus, it is recognized that governments of different countries are investing in firms to ensure that social objectives, including gender equality, are achieved and that sustainable developments are promoted. In other words, governmental owners can bring an effective monitoring system in private firms, which allows all stakeholders to engage in corporate governance, including female directors [23]. Hence, increasing governmental ownership may enhance a firm’s ESG performance [24,25,26,27]. State-owned firms have two goals: economic and social performance. Despite this potential value of governmental ownership, none of the previous studies examined the possible role of governmental owners concerning BGD and ESG performance, especially in emerging markets. Therefore, this paper extends the literature on BGD and ESG performance by examining the moderating role of governmental ownership of the relation between BGD and ESG performance.

In doing so, this research focuses on the Egyptian market using data during the period 2014 to 2019, i.e., following the second revolution that broke out in 2013. Following the recent revolutions in Egypt, the government started to empower female representation in all life aspects [28,29]. These revolutions are expected to enhance women’s role in politics and economics [30]. Article 214 of the 2014 Constitution resulted in the development of a number of institutions like the National Council for Women, National Council for Human Rights, National Council for Persons with Disability, and National Council for Childhood and Motherhood. Hence, gender equality and human rights in general clearly appeared to be vital objectives on Egypt’s political agenda [31].

Recently, the Egyptian government has issued new laws and regulations to encourage sustainable development and motivate companies to commit to ethical business procedures [32]. The corporate governance code was issued in 2005 by the Egyptian Institute of Directors and the Ministry of Investment to be applied by businesses listed on EGX. Further, detailed governance standards have been issued by the Egyptian Financial Supervisory Authority in 2016 to replace the previous code, and to be applied to both public and unlisted enterprises. In order to take into account the interests of all stakeholders, the new regulations emphasized the importance of reporting nonfinancial information, including ESG [33]. Moreover, the use of the S&P/EGX ESG index in 2010 was a significant milestone in improving sustainability performance in the context of Egypt. This index identifies the top-performing EGX 100 firms in terms of ESG initiatives [19]. Moreover, Law No. 12 was released by the Ministries of Manpower and Environmental in 2019 to advance sustainable development via the defense of labor rights and the improvement of working conditions [32]. Finally, the Egyptian Financial Supervisory Authority has issued the Board of Directors’ Resolution No. 123 in September 2019, amending the rules of firms’ registration and delisting of securities on the EGX. These amendments required listed firms to include at least one female in the firms’ boards.

The result of this research enhances the literature in some respects. It enhances the limited literature on BGD and ESG performance in emerging economies by focusing on the Egyptian market as one of the most important emerging markets in the Middle East and North Africa. Our results support the findings of prior research regarding the positive role of BGD in enhancing ESG performance. Besides, this research extends the literature on the relationship between BGD and ESG performance in emerging economies by examining the moderating role of governmental ownership [15,16,34,35]. The results indicated that governmental ownership moderates the positive relationship between BGD and ESG performance. This finding implies that the positive impacts of BGD diversity in emerging markets are conditional on governmental ownership that provides a fertile environment for ESG performance in this context.

The remainder of the study is organized as follows. Section 2 presents the literature review and hypotheses development. Section 3 summarizes the research methods. Section 4 displays the research results. Finally, Section 5 and Section 6 discuss the findings and conclude the paper, respectively.

2. Literature Review and Hypotheses Development

Recent literature has identified the main topics and trends related to the SDGs [36]. A noticeable trend among these was the focus on SDG 5 concerned with gender equality. According to the gender social role theory, women are more sensitive to sustainability challenges [16,37]. They have a stronger sense of morality and exhibit more social welfare concerns and humility. Further, they are more concerned about the quality of the business life and, so, they are more likely to give ethical business practices a top priority by putting them into action [38]. Female directors’ concerns about stakeholders are reflected in their leadership style [16]. Accordingly, it is suggested that women are more concerned about environmental and sustainability challenges than their male counterparts [39]. Ben-Amar et al. indicated that increasing the number of women on boards would enhance climate change disclosure [6]. Liu noted that more diverse boards of directors face fewer lawsuits for violating environmental regulations, as female directors tend to act morally [37]. In the same context, Nadeem et al. showed a positive relationship between environmental innovation and BGD [40]. Kahtri reported a positive relationship between BGD and ESG performance [16].

In addition, some previous studies used the upper echelons theory to address the association between BGD and corporate performance. According to this theory, corporate leaders can influence firms’ performance through their personal beliefs, experiences, and personality traits [41]. Psychological processes and traits are different between women and men, which substantially affects their actions and decisions [42]. Thus, this theory suggests that boards with gender diversity will consider environmental concerns and moral behavior. In this regard, Li et al. found that female directors’ greater sense of social responsibility and personal qualities contribute to stronger environmental policies [42]. Nadeem et al. demonstrated how environmental concerns raised by female directors could play a significant role in fostering environmental innovation in contemporary businesses [40].

2.1. BGD and ESG Performance

Over the past ten years, the literature has focused on the relationship between BGD and ESG performance. However, most of the literature concentrates on developed markets, i.e., contexts with higher gender parity and stronger shareholder protection, where this relationship is found to be positive. For instance, using UK data, Al-Shaer and Zaman reported a positive relation between BGD and ESG reporting quality [15]. Using European data, Kyaw et al. found that BGD enhances ESG performance across all industries [34]. Focusing on Canadian firms, Ben-Amar et al. showed that BGD increases the probability of voluntary climate change disclosure [6]. Focusing on Australia, Islam et al. conducted interviews with 19 Australian board directors using a qualitative methodology [35]. The results imply that BGD improves ESG investment and enhances ESG performance. Focusing on Nordic countries, Khatri indicated that BGD significantly and positively affects ESG performance [16]. Focusing on Italy, Provasi and Harasheh observed a positive effect of BGD on ESG performance [43]. Using a meta-analysis, Di Vaio et al. noted that green technology adoption could enhance sustainable practices and gender equality [44]. Using European data, Paolone et al. found that BGD could contribute to knowledge sharing in the financial sector, which improves ESG performance [13].

However, a few studies reported different findings to those mentioned above. Focusing on Italy, Cucari et al. revealed a negative relationship between BGD and ESG disclosure [45]. By examining USA firms, Manita et al. found an insignificant relationship between BGD and ESG disclosure [46].

Considering the above, we noticed that there is a dearth of studies on the link between BGD and ESG performance in developing countries such as Egypt. This context is linked with lower levels of environmental consciousness and weak investors’ protection [16,34,35,40,46,47], which can yield different consequences regarding the relationship between BGD and ESG performance. As discussed above, the unique characteristics of female directors in terms of having a stronger sense of morality and exhibiting more social welfare concerns and humility motivate then to prioritize ethical business practices, including ESG performance [38]. Thus, we believe that their inclusion on boards of emerging markets such as Egypt can make a difference concerning the adoption of social practices such as ESG. Consequently, H1 is formulated as follows:

H1. 

There is a significant positive relationship between BGD and ESG performance.

2.2. The Moderating Role of Governmental Ownership

ESG can have positive implications, such as enhancing a firm’s reputation and performance (e.g., [15]). However, firms’ operating costs can increase because of adopting ESG initiatives. ESG activities provided by private firms are typically utilitarian [18], whereby ESG can be employed as a tool to accomplish particular economic objectives, such as satisfying shareholders’ requirements [21]. In other words, in most cases, controlling shareholders in a private firm have a substantial influence over the firm’s resources and, consequently, over its ESG initiatives. They almost focus on profit maximization and ignore the interests of other stakeholders [48].

Hence, private firms are unlikely to proactively adopt ESG without a regulatory inducement [32]. Especially in emerging markets with ineffective enforcement systems, to encourage firms to engage with ESG performance, it is imperative to mandate them through regulations and other relevant systems [49] and to enhance the enforcement of corporate governance procedures [50]. As a result, governmental ownership of private firms may enhance the government–business connection and offer a reputational guarantee. This opens the door to more financial subsidies, tax incentives, credit resources, and other policy-related resources [17].

Governmental shareholders can directly choose directors, senior managers, and supervisors in a private firm if their ownership percentage reaches five percent or more [17,26]. This will eliminate the restrictions imposed by private-controlling shareholders in private firms. Because of the effective checks and balances governmental ownership can provide, private firms may create a framework that allows all stakeholders to engage in corporate governance, including female directors, which enhances the governance structure. Governmental shareholders also ensure the fulfillment of corporate social duties as required by government laws and processes [17]. Corporate management promotion and pay in state-owned firms are not only tied to firms’ commercial success but also to political and social performances, including the preservation of the environment. Therefore, public firms with higher governmental ownership can actively fulfill their ESG performance and satisfy the governance objectives [23]. Consequently, we expect that governmental ownership can moderate the association between BGD and ESG performance, as governmental shareholders may increase the ability of female directors to promote ESG performance. Consequently, H2 is formulated as follows:

H2. 

There is a significant positive influence of governmental ownership on the relation between BGD and ESG performance.

3. Research Design

3.1. Sample and Data Sources

The study sample comprises all listed Egyptian companies on EGX100 during the period 2014–2019. We depend on this period as it more stable to avoid the negative effect of COVID-19 on the investigated hypotheses. ESG performance data are collected from the Egyptian Stock Exchange (EGX) to calculate the ESG score assigned for each firm in our sample. BGD data are manually extracted from governance reports, and financial information is collected from the firms’ annual reports published by the EGID Corporation.

Table 1. The sample of the study.

	No. of Firms	Observations
Panel A: Sample selection methodology
Firms listed on EGX100 (2014–2019)	100 firms	600
(−) Firms belonging to Financial and Banking	(22)	(132)
(−) Firms with missing data	(7)	(42)
Final sample	71	426
Panel B: Sample distribution by sector
Trade and distributors	2	12
Food, drinks, and tobacco	11	72
Real estate	11	66
Engineering contracting and construction	5	30
Building materials	5	30
Basic resources	12	72
Industrial services, products, and cars	3	18
Energy and support services	2	12
Transportation and shipping services	3	18
Tourism and entertainment	4	24
Educational services	1	6
Textiles and durable goods	4	24
Paper and packaging materials	1	6
Communications, media, and information technology	4	24
Health care and medicines	2	6
Utilities	1	6
Total	71	426

displays the sample selection process in Panel A and sample distribution by sector in Panel B.

3.2. Research Models

To test the first research hypothesis (H1), which examines the association between BGD and ESG performance, Model 1 is formulated based on previous literature (e.g., [6,15,16]). This model is extended to examine the second hypothesis (H2) by adding governmental ownership as a moderator in Model (2):

$$\begin{gathered} {\mathrm{ESG}}_{\mathrm{it}}=\mathsf{\alpha }+{\mathrm{B}}_1\left({\mathrm{BGD}}_{\mathrm{it}}\right)+{\mathrm{B}}_2\left({\mathrm{Size}}_{\mathrm{it}}\right)+{\mathrm{B}}_3\left({\mathrm{Lev}}_{\mathrm{it}}\right)+{\mathrm{B}}_4\left({\mathrm{Age}}_{\mathrm{it}}\right)+{\mathrm{B}}_5\left({\mathrm{Prof}}_{\mathrm{it}}\right)+{\mathrm{B}}_6\left({\mathrm{MtB}}_{\mathrm{it}}\right)+{\mathrm{B}}_7\left({\mathrm{Bsize}}_{\mathrm{it}}\right) \\ +{\mathrm{B}}_8\left({\mathrm{Duality}}_{\mathrm{it}}\right)+{\mathrm{B}}_9\left({\mathrm{BIND}}_{\mathrm{it}}\right)+{\mathrm{B}}_{10}\left(\mathrm{Industries}\right) \\ +{\mathrm{B}}_{11}\left(\mathrm{Years}\right)\hspace{1em}\hspace{1em} \mathrm{Model} \left(1\right) \end{gathered}$$

To test H2, which examines the effect of governmental ownership on the relationship between BGD and ESG performance, Model (1) is extended by adding governmental ownership as a moderator in Model (2), as follows:

$$\begin{gathered} {\mathrm{ESG}}_{\mathrm{it}}=\mathsf{\alpha }+{\mathrm{B}}_1\left({\mathrm{BGD}}_{\mathrm{it}}\right)+{\mathrm{B}}_2\left({\mathrm{GO}}_{\mathrm{it}}\right)+{\mathrm{B}}_3\left({\mathrm{BGD}}_{\mathrm{it}}{*\mathrm{GO}}_{\mathrm{it}}\right)+{\mathrm{B}}_4\left({\mathrm{Size}}_{\mathrm{it}}\right)+{\mathrm{B}}_5\left({\mathrm{Lev}}_{\mathrm{it}}\right)+{\mathrm{B}}_6\left({\mathrm{Age}}_{\mathrm{it}}\right) \\ +{\mathrm{B}}_7\left({\mathrm{Prof}}_{\mathrm{it}}\right)+{\mathrm{B}}_8\left({\mathrm{MtB}}_{\mathrm{it}}\right)+{\mathrm{B}}_9\left({\mathrm{Bsize}}_{\mathrm{it}}\right)+{\mathrm{B}}_{10}\left({\mathrm{Duality}}_{\mathrm{it}}\right)+{\mathrm{B}}_{11}\left({\mathrm{BIND}}_{\mathrm{it}}\right) \\ +{\mathrm{B}}_{12}\left(\mathrm{Industries}\right)+{\mathrm{B}}_{13}\left(\mathrm{Years}\right)\hspace{1em}\hspace{1em} \mathrm{Model} \left(2\right) \end{gathered}$$

where ESG is Environmental, Social, and Governance performance measured as a dummy variable based on S&P/EGX/ESG data and the ESG index score assigned to the firm. The Egyptian Institute of Directors, Standard & Poor’s, and Crisil collaborated to create the Environment, Social, and Governance Index for the Egyptian market (i.e., (S&P/EGX ESG Index)). The goal of that index is to discern those firms performing well along the three categories of environmental, social, and corporate governance responsibilities as compared to their market peers. There are two steps involved in developing this index. Establishing a multi-layered strategy to obtain an ‘ESG’ score for every organization is the first stage. This method is based on quantitative information rather than subjective considerations. Ranking businesses with the best ESG scores to develop the index is the second stage. Each company’s weight in the index is determined by its relative score: those with higher scores are better in ESG performance. Additionally, firm size and liquidity are taken into consideration while developing such an index (see [28,29] for more details regarding ESG calculation). BGD is board gender diversity calculated as the percentage of female directors on the board. GO is governmental ownership.

Along with previous research, e.g., [6,16,40], we used some control variables in the regression as they can affect the independent variable, such as firm size (size), firm leverage (Lev), financial performance (Prof), market-to-book ratio (MtB), board size (Bsize), board duality (Duality), and board independence (Duality).

Table 2. Variable measurements.

Abbreviation	Variable	Measurement
ESG	ESG Score	The natural logarithm for 1 + ESG score assigned for companies registered in S&P/EGX/ESG index in year t.
BGD	Board gender diversity	The total number of female directors to total number of directors on the board.
GO	Governmental ownership	The proportion of ordinary shares owned by the government (not less than 5% of the company’s total outstanding shares).
Size	Firm size	The natural logarithm of total assets in year t.
Lev	Firm leverage	The total debt scaled by total assets in year t.
Age	Firm age	The natural logarithm of the company’s age since listing to year t.
Prof	Firm profitability	Return on assets in year t.
MtB	Market-to-book ratio	The ratio of the equity’s market value to its the book value.
Bsize	Board size	Number of directors on the board.
Duality	Board duality	A binary variable that equals to 1 if the CEO is a chairman of the firm and 0 otherwise.
BIND	Board independence	Total non-executive directors scaled by the total number of directors on the board in year t.

presents further information about variables’ measurement.

4. Research Results and Discussion

4.1. Descriptive Results

Descriptive results are displayed in

Table 3. Descriptive results.

Panel A: Descriptive results for the sample (Full Sample = 426)
Variables	Mean		SD	Median	Minimum	Maximum
ESG	4.474		0.763	4.605	0.000	4.615
BGD	0.075		0.107	0.000	0.000	0.444
GO	0.258		0.230	0.000	0.000	1.000
Size	20.925		1.665	20.979	16.959	25.499
Lev	0.429		0.261	0.399	0.001	0.986
Age	2.735		0.696	2.944	0.000	3.970
Prof	0.057		0.110	0.040	−0.167	0.292
MtB	1.525		1.423	0.988	0.000	4.325
Bsize	8.113		2.885	8.000	3.000	17.000
Duality	0.704		0.457	1.000	0.000	1.000
BIND	0.696		0.209	0.750	0.143	1.000
Panel B: Univariate statistics (Full Sample = 426)
Variables	Firms with at least one female on the board (178 observations)		Firms without females on the board (248 observations)		t-test	Sig.
	$\mathrm{Mean}$	$\mathrm{SD}$	$\mathrm{Mean}$	$\mathrm{SD}$
ESG	0.326	0.470	0.161	0.369	4.047	0.000 ***
GO	0.285	0.336	0.237	0.325	2.613	0.107
Size	20.827	1.736	20.996	1.613	−1.037	0.300
Lev	0.355	0.239	0.481	0.264	−5.012	0.000 ***
Age	2.643	0.725	2.800	0.667	−2.318	0.021 **
Prof	0.079	0.116	0.041	0.103	3.624	0.000 ***
MtB	1.706	1.464	1.395	1.381	2.234	0.026 **
Bsize	8.983	3.168	7.488	2.487	5.452	0.000 ***
Duality	0.770	0.422	0.657	0.476	2.520	0.012 **
BIND	0.754	0.174	0.655	0.223	4.934	0.000 ***

See Table 2 for variables’ definitions. *** denotes that results are significant at <1%. ** denotes that findings are significant at <5%, and * means that findings are significant at <10%.

, where Panel A presents descriptive statistics for the whole sample. ESG varies between 0.000 and 4.615 with a mean value of ESG 4.474 and a standard deviation (SD) of 0.763. BGD varies between 0.000 and 0.444 with a mean value of 0.075 and a SD of 0.107. GO varies between 0.000 and 1.00 with a mean value of 0.258 and a SD of 0.230.

Panel B presents univariate statistics, where the findings show that 178 observations (41.78% of the sample) have at least one female on the board. This finding indicates that companies with at least one female on the board are more likely to have higher ESG scores. This reflects the initial results regarding female directors’ contribution to ESG performance consistent with some previous studies (e.g., [6]). Companies with at least 1 female on the board have higher GO than other companies. However, this result is insignificant.

The Pearson’s correlation matrix for the study variables is shown in

Table 4. Pearson’s correlation matrix.

Variables	1	2	3	4	5	6	7	8	9	10	11
ESG	1
BGD	0.120 **	1
GO	0.168 ***	−0.017	1
Size	0.169 ***	−0.132 ***	0.059	1
Lev	−0.137 ***	−0.269 ***	−0.157 ***	−0.006	1
Age	−0.051	−0.080 *	0.132 ***	−0.026	0.210 ***	1
Prof	0.145 **	0.163 ***	0.165 ***	0.257 ***	−0.294 ***	−0.073	1
MtB	0.104 ***	0.090 *	−0.031	0.283 ***	−0.045	−0.062	0.228 ***	1
Bsize	0.111 **	0.202 ***	0.239 ***	0.388 ***	−0.119 **	0.015	0.230 ***	0.161 ***	1
Duality	0.045	0.152 ***	0.125 ***	−0.077	−0.110 **	−0.042	0.021	0.022	0.006	1
BIND	0.059	0.201 ***	0.131 ***	0.033	−0.194 ***	−0.110 **	0.102 **	0.109 **	0.401 ***	−0.275 ***	1

See Table 2 for variables’ definitions. *** denotes that results are significant at <1%. ** denotes that findings are significant at <5%, and * means that findings are significant at <10%.

. The results show that BGD has a positive relationship with ESG at the 5% level. GO has a positive relationship with ESG at the 1% level. Size, Prof, and Bsize have positive relationships with ESG at the 1%, 5%, and 5% levels, respectively. In contrast, Lev has a negative relationship with ESG at the 1% level. The correlation matrix indicates that the correlations between independent variables are below 0.5. Also, the VIF test confirms that all VIF scores in all regressions are less than 4, indicating no multicollinearity issues between the independent variables in the study. These findings ensure that the dataset does not appear to have a multicollinearity issue [51].

4.2. Regression Results

The data are analyzed depending on OLS regression, where we have checked some assumptions to ensure that the OLS method is appropriate for our data, as follows. Firstly, we checked the normality of the residuals, and the analysis indicated a normal distribution of the residuals. We depended on the normal predicted probability (P–P) plot as a diagnostic mechanism, and we found that a normal distribution of residuals aligns closely with the plot’s diagonal line. Secondly, we have checked homoscedasticity assumptions, which concerns the distribution of residuals. A scatterplot of predicted values against residuals revealed that the variance of errors is constant. Consequently, the assumption of linearity is achieved as the residuals are normally distributed and exhibit homoscedasticity. Finally, the absence of multicollinearity ensures that OLS regressions are appropriate. Additionally, the correlation matrix reveals that the correlations between independent variables are below 0.5, and the VIF scores in all regressions are less than 4, which indicates the nonexistence of a multicollinearity problem in the dataset.

Table 5. Regressing BGD on ESG.

Variables	Model (1)	Model (2)
Constant	5.575 *** (9.654)	5.627 *** (9.809)
BGD	0.750 ** (1.995)	−0.054 (−0.122)
GO		0.553 *** (3.422)
GO × BGD		4.144 *** (3.117)
Size	−0.016 (−0.625)	−0.014 (−0.529)
Lev	0.170 (1.093)	0.211 (1.360)
Age	−0.294 *** (−5.269)	−0.275 *** (−4.727)
Prof	0.703 ** (1.983)	0.664 * (1.866)
MtB	0.066 ** (2.357)	0.078 *** (2.792)
Bsize	0.067 *** (4.222)	0.071 *** (4.572)
Duality	−0.173 * (−1.885)	−0.140 (−1.542)
BIND	0.716 *** (3.500)	0.909 *** (4.336)
Years Effect	Included	Included
Industries Effect	Included	Included
N	426	426
Adj. R2	0.182	0.207
F test	4.610 ***	4.934 ***
VIF	<4	<4

See Table 2 for variables’ definitions. *** denotes that results are significant at <1%. ** denotes that findings are significant at <5%, and * means that findings are significant at <10%.

, Model 1, reveals that BGD significantly and positively affects ESG performance (β = 0.750, p > 0.05). The Adj. R² of 0.182 indicates that BGD can interpret the variance in ESG performance. This result echoes the upper echelons theory and gender social role theory, supporting H1. When we considered the moderating influence of GO, Model 2 showed that BGD has an insignificant positive effect on ESG performance. However, GO significantly and positively affect ESG performance (β = 0.553, p > 0.01), and the interaction between GO and BGD (GO × BGD) significantly and positively affect ESG performance (β = 4.144, p > 0.01).

4.3. Robustness Tests

To check the robustness of the primary findings, other tests were performed, as follows. Firstly, it is important to recognize that the potential issue for the OLS regression is that BGD might not be exogenous. The unobserved determinants of ESG performance may also explain BGD, leading to biased and inconsistent OLS estimates. We considered this issue by using the 2SLS method [52]. According to the 2SLS method, variables that are related to the independent variable (BGD) but unrelated to the dependent variables (ESG) are necessary to run the IV OLS regression model. Two instrumental variables and the independent variables are regressed in the first stage of the 2SLS method to estimate BGD. These variables are family ownership and the industrial average of BGD [16,53,54].

Table 6. The 2SLS regression models.

Variables	Model (1)	Model (2)
Constant	5.484 *** (9.285)	5.511 *** (9.400)
PBGD	0.901 * (1.913)	0.192 (0.371)
GO		0.486 *** (3.079)
GO × PBGD		4.656 *** (2.776)
Size	−0.013 (−0.495)	−0.008 (−0.301)
Lev	0.179 (1.142)	0.196 (1.252)
Age	−0.286 *** (−5.092)	−0.265 *** (−4.533)
Prof	0.709 ** (1.998)	0.732 ** (2.035)
MtB	0.065 ** (2.319)	0.075 *** (2.690)
Bsize	0.064 *** (4.047)	0.068 *** (4.324)
Duality	−0.173 * (−1.889)	−0.155 * (−1.706)
BIND	0.690 *** (3.391)	0.905 *** (4.284)
Years Effect	Included	Included
Industries Effect	Included	Included
N	426	426
Adj. R2	0.181	0.201
F test	4.594 ***	4.805 ***
VIF	<4	<4

See Table 2 for variables’ definitions. *** denotes that results are significant at <1%. ** denotes that findings are significant at <5%, and * means that findings are significant at <10%.

shows the second-stage OLS regression, and the findings align with the results presented in Table 5. The findings confirm the first hypothesis, i.e., BGD has a significant relationship with ESG performance. In addition, the findings confirm the moderating role of governmental ownership on the association between BGD and ESG performance, i.e., the impact of BGD on ESG performance is conditional on governmental ownership.

Secondly, we rerun Models 1 and 2 with a one-year lag for independent and control variables to address any potential simultaneity issues [32,54]. This method allows the effect of time on BGD to be discerned in ESG performance. The results presented in

Table 7. Regressing Lagged BGD on ESG performance.

Variables	Model (1)	Model (2)
Constant	5.531 *** (8.502)	5.568 *** (8.603)
BGDt−1	0.761 * (1.835)	0.154 (0.338)
GO		0.520 *** (2.997)
GO × BGDt−1		4.118 *** (2.903)
Size	−0.016 (−0.565)	−0.013 (−0.459)
Lev	0.125 (0.707)	0.172 (0.977)
Age	−0.295 *** (−4.768)	−0.276 *** (−4.257)
Prof	0.649 (1.615)	0.605 (1.494)
MtB	0.070 ** (2.201)	0.074 ** (2.389)
Bsize	0.062 *** (3.592)	0.068 *** (3.951)
Duality	−0.104 (−1.005)	−0.070 (−0.685)
BIND	0.664 *** (2.883)	0.857 *** (3.645)
Years Effect	Included	Included
Industries Effect	Included	Included
N	355	355
Adj. R2	0.166	0.191
F test	3.806 ***	4.087 ***
VIF	<4	<4

See Table 2 for variables’ definitions. *** denotes that results are significant at <1%. ** denotes that findings are significant at <5%, and * means that findings are significant at <10%.

show a significant association between BGD and ESG (β = 0.761, p > 0.10). In Model 2, BGD has an insignificant positive effect on ESG performance. GO significantly and positively affects ESG performance (β = 0.520, p > 0.01), and the interaction between GO and BGD (GO × BGD) has a positive influence on ESG performance (β = 4.118, p > 0.01). These results ensure the moderating role of governmental ownership on the relation between BGD and ESG performance along with the results shown in Table 5 and Table 6.

Finally, considering the reverse causality issues [55], the regressions of Models 1 and 2 are re-estimated by adding lagged ESG as an independent variable. The results presented in

Table 8. Re-estimating regressions after controlling for lagged ESG.

Variables	Model (1)	Model (2)
Constant	5.772 *** (9.392)	5.849 *** (9.595)
BGD	0.713 * (1.793)	−0.141 (−0.301)
GO		0.547 *** (3.232)
GO × BGD		4.531 *** (3.121)
Size	−0.038 (−1.378)	−0.036 (−1.328)
Lev	0.118 (0.701)	0.151 (0.895)
Age	−0.252 *** (−4.233)	−0.237 *** (−3.821)
Prof	0.568 (1.481)	0.519 (1.345)
MtB	0.066 ** (2.176)	0.073 ** (2.469)
Bsize	0.060 *** (3.604)	0.066 *** (4.014)
Duality	−0.130 (−1.319)	−0.096 (−0.980)
BIND	0.662 *** (3.013)	0.849 *** (3.798)
ESGt−1	0.120 *** (5.793)	0.121 *** (5.931)
Years Effect	Included	Included
Industries Effect	Included	Included
N	355	355
Adj. R2	0.242	0.268
F test	5.316 ***	5.606 ***
VIF	<4	<4

See Table 2 for variables’ definitions. *** denotes that results are significant at <1%. ** denotes that findings are significant at <5%, and * means that findings are significant at <10%.

show a significant relationship between BGD and ESG (β = 0.713, p > 0.10). In Model 2, BGD has an insignificant positive effect on ESG performance. GO has a significant positive influence on ESG performance (β = 0.547, p > 0.01), and the interaction between GO and BGD (GO × BGD) has a positive influence on ESG performance (β = 4.531, p > 0.01). These results confirm the moderating role of governmental ownership on the relationship between BGD and ESG performance along with the results displayed in Table 5, Table 6 and Table 7.

4.4. Additional Tests

Along with previous studies, Models 1 and 2 are re-estimated to examine the effect of BGD on the Environmental score (E_Score), the Social score (S_Score), and the Governance score (G_Score) rather than the ESG overall score (e.g., [34,40]).

Table 9. Regressing BGD on E, S, and G performances.

Variables	Model (1)			Model (2)
	E_Score	S_Score	G_Score	E_Score	S_Score	G_Score
Constant	−1.514 (−1.374)	−3.215 *** (−2.941)	4.364 *** (9.814)	−1.358 (−1.225)	−3.508 *** (−3.228)	4.398 *** (9.955)
BGD	1.785 ** (2.489)	3.250 *** (4.564)	0.587 ** (2.027)	0.777 (0.903)	1.888 (0.750)	−0.020 (−0.060)
GO				0.475 (1.523)	1.089 *** (3.560)	0.430 *** (3.459)
GO × BGD				5.329 ** (2.076)	2.791 *** (3.307)	3.121 *** (3.049)
Size	0.184 *** (3.689)	0.265 *** (5.368)	−0.016 (−0.786)	0.183 *** (3.666)	0.281 *** (5.746)	−0.014 (−0.681)
Lev	0.556 * (1.870)	0.554 * (1.878)	0.134 (1.114)	0.570 * (1.902)	0.709 ** (2.411)	0.167 (1.393)
Age	−0.294 *** (−2.763)	−0.359 *** (−3.398)	−0.226 *** (−5.270)	−0.299 *** (−2.666)	−0.244 ** (−2.219)	−0.210 *** (−4.697)
Prof	1.134 * (1.676)	0.487 (0.725)	0.536 * (1.961)	1.085 (1.580)	0.861 (1.278)	0.500 * (1.825)
MtB	0.035 (0.650)	0.037 (0.688)	0.052 ** (2.386)	0.046 (0.859)	0.054 (1.027)	0.060 *** (2.821)
Bsize	0.022 (0.737)	0.020 (0.685)	0.054 *** (4.441)	0.029 (0.947)	0.022 (0.739)	0.057 *** (4.785)
Duality	−0.416 ** (−2.382)	−0.597 *** (−3.444)	−0.131 * (−1.856)	−0.390 ** (−2.226)	−0.525 *** (−3.057)	−0.105 (−1.507)
BIND	0.885 ** (2.266)	0.515 (1.330)	0.566 *** (3.593)	1.046 ** (2.584)	0.120 (0.302)	0.716 *** (4.438)
Years Effect	Included	Included	Included	Included	Included	Included
Industries Effect	Included	Included	Included	Included	Included	Included
N	426	426	426	426	426	426
Adj. R2	0.262	0.327	0.189	0.267	0.347	0.213
F test	6.766 ***	8.906 ***	4.784 ***	6.492 ***	9.014 ***	5.097 ***
VIF	<4	<4	<4	<4	<4	<4

See Table 2 for variables’ definitions. *** denotes that results are significant at <1%. ** denotes that findings are significant at <5%, and * means that findings are significant at <10%.

, Model 1, shows a significant positive association between BGD and both E_Score, S_Score, and G_Score (β = 1.785, 3.250, 0.587 p > 0.05, 0.01, and 0.05, respectively). Model 2 reveals that the interaction between GO and BGD (GO × BGD) positively affects E_Score, S_Score, and G_Score (β = 5.329, 2.791, 3.121 p > 0.05, 0.01, and 0.01, respectively). These findings ensure the moderating role of governmental ownership on the relationship between BGD and different types of ESG performance, confirming the previous results of the main analysis and robustness tests.

Additionally, we measured ESG as a dummy variable that takes the value of one for companies listed in the S&P/EGX ESG index year t, and 0 otherwise [32]. We estimated logistic regressions for Models 1 and 2, as presented in

Table 10. Logistic regression.

Variables	Model (1): Dep, ESGD	Model (2) Dep, ESGD
Constant	−11.199 *** (−3.55)	−10.841 *** (−3.37)
BGD	5.312 *** (3.26)	2.263 (1.25)
GO		1.416 ** (2.01)
GO × BGD		14.103 *** (3.71)
Size	0.568 *** (4.58)	0.533 *** (4.18)
Lev	−0.631 * (−0.89)	−0.972 * (−1.27)
Age	−1.055 *** (−4.28)	−0.851 (−2.87)
Prof	1.314 (0.84)	1.469 (0.87)
MtB	0.001 (0.01)	0.036 (0.27)
Bsize	0.263 *** (3.83)	0.315 *** (4.26)
Duality	−1.073 ** (−2.40)	−0.986 ** (−2.12)
BIND	1.514 (1.53)	2.051 * (1.92)
Years Effect	Included	Included
Industries Effect	Included	Included
N	426	426
Pseudo R2	0.329	0.367

See Table 2 for variables’ definitions. *** denotes that results are significant at <1%. ** denotes that findings are significant at <5%, and * means that findings are significant at <10%.

. The findings indicate that BGD significantly and positively affects ESG (β = 5.312 p > 0.01), ensuring that BGD increases the likelihood of companies being indexed in the S&P/EGX ESG index. Model 2 reveals that the interaction between GO and BGD (GO × BGD) significantly and positively affects ESG performance (β = 14.103 > 0.01). These results confirm the moderating role of governmental ownership on the relationship between BGD and ESG performance.

5. Discussion

By analyzing the study data, we found that BGD significantly and positively affects ESG performance. This finding is consistent with previous studies such as [16,40,43,56]. However, it is different from previous studies such as [45,46]. The current finding supports the role of female directors in enhancing the adoption of ethical and social business practices [38]. It suggests that women are more concerned about environmental and sustainability challenges than their male counterparts [39]. They have a higher sense of social responsibility and sustainability issues, which is vital for enhancing corporate environmental and governance performance [40].

Additionally, when we considered the moderating influence of GO, our main analysis revealed that, although BGD has an insignificant influence on ESG performance, GO significantly and positively affects ESG performance, and the interaction between GO and BGD positively affects ESG performance. These findings ensure the moderating role of governmental ownership on the relationship between BGD and ESG performance. This result aligns with previous studies indicating that governmental owners, rather than regular investors, can pressure firms to promote sustainability issues, which enhances their monitoring over ESG performance (e.g., [24,26]). This finding echoes the postulation about the ineffective enforcement mechanisms in emerging markets, and, hence, the existence of GO can provide the necessary checks and balances required to eventually enhance corporate ESG performance.

Our findings align with Qian and Yang, who showed that governmental ownership can improve ESG performance, suggesting that more sustainable firms should consider introducing the government as a shareholder [26]. This finding ensures the crucial value that GO can bring to business organizations, in terms of enhancing monitoring and engagement with social activities [17]. In other words, the existence of GO allows the engagement of all stakeholders, including female directors, in corporate governance, which enhances corporate governance structures and induces listed firms to vigorously improve their ESG performance [23]. This is because managerial incentives in state-owned firms are mainly linked to political and social—rather than economic—performances, including the preservation of the environment.

6. Conclusions

Consistent with SGG 5 (Gender equality) and the recent calls to empower women in all fields, including corporate boards [36], this research examined the link between board gender diversity and ESG performance in Egypt, a prominent emerging market in the MENA region. In addition, it investigated the moderating role of governmental ownership concerning this relationship. A sample of nonfinancial companies listed on EGX100 during the period 2014–2019 has been investigated depending on univariate and multivariate analyses. Consistent with the gender social role theory [16,37] and the upper echelons theory [41], our findings revealed a positive link between board gender diversity and ESG performance. Moreover, the results indicate that governmental ownership moderates the relationship between board gender diversity and ESG performance. These results are robust in all analyses. In addition, the results are confirmed when we used the ESG overall score and ESG score for all components (i.e., social, environmental, and governance scores).

Consequently, the influence of board gender diversity on ESG performance is conditional on the existence of governmental ownership. In other words, increasing governmental ownership contributes a fertile environment that supports the ability of BGD to behave ethically towards ESG issues. Hence, this study provides robust evidence that board BGD can enhance ESG performance in state-owned firms. Along with the findings of this study, investors should be aware that attaining the value of BGD might be conditional on corporate ownership structure. The results also highlight the value of regulations in emerging markets to oversee private firms’ ESG performance.

The current results support the notion that governments’ investment in firms helps them achieve social objectives and promote sustainable development. Economic and ESG performance are the two goals of state-owned firms, while private firms tend to pay less attention to their ESG responsibilities due to their pure capital traits [17]. Our findings support the notion that, especially in emerging markets such as Egypt, undertaking social responsibilities by private firms is likely to be undermined by their egoistic and utilitarian behavior [21] unless being rationalized by governmental ownership. Hence, governmental intervention in emerging markets’ business sectors is considered an effective governance mechanism to encourage more firms to adopt ESG initiatives by boosting state equity participation.

The finding of this study has implications for both regulatory bodies, firms, investors, and academic researchers in emerging markets such as Egypt. It directs the attention of regulatory bodies and corporate management to the crucial value of board gender diversity in enhancing ESG performance in the case of governmental ownership. In addition, it enlightens them with the importance of enforceable regulations on overseeing private firms’ ESG performance. Besides, regular investors should consider that the ability of board gender diversity to enhance ESG performance is conditional on the governmental ownership proportion. In other words, they should consider the value of BGD and GO when making investment decisions.

However, these results are not without limitations. Ownership structures, other than governmental ownership, have not been examined in this research. Future research can examine the effect of family ownership, institutional ownership, and block-holder ownership on the link between BGD and ESG performance. Further, the focus of this study on the period 2014–2019 was beneficial in avoiding the possible impact of COVID-19 on our findings. Hence, future research can use more recent data to address the consequences of the COVID-19 pandemic on the relationships examined in the current study, i.e., on the relationship between BGD and ESG performance.