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Article

Women on Boards in Portuguese Listed Companies: Does Gender Diversity Influence Financial Performance?

1
GOVCOPP (Research Unit on Governance, Competitiveness and Public Policies), University of Aveiro, 3810-193 Aveiro, Portugal
2
ISCA-UA (Higher Institute of Accounting and Administration), University of Aveiro, 3810-193 Aveiro, Portugal
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(10), 6186; https://doi.org/10.3390/su14106186
Submission received: 1 April 2022 / Revised: 5 May 2022 / Accepted: 12 May 2022 / Published: 19 May 2022

Abstract

:
Corporate sustainability integrates financial performance with environmental, social, and governance (ESG) performance. Due to their personal characteristics, women can play an important role in promoting sustainable actions and strategic decision-making, creating positive effects on a company’s financial performance. The main objective of this paper is to analyze the effect of Board gender diversity on financial performance, in the context of Portuguese listed companies. Financial performance was measured through an accounting-based measure, the return on assets (ROA), and a market-based measure, the Tobin’s Q. Board gender diversity was proxied through several measures identified in the literature and the information needed to construct them was manually collected from the corporate governance reports. A regression analysis was conducted on panel data consisting of 29 companies from the period from 2010 to 2019. The results show that female presence is positively related with ROA when there are at least two women on the Board, or when the proportion of women is, at the least, 20%. A positive relationship was also found between the Tobin’s Q and the presence of at least 20% women on the Board. The results confirm the existence of the positive effects of Board gender diversity on financial performance, as predicted by resource dependence theory and agency theory, but only when a critical mass of women is reached. In general, we conclude that, although gender diversity promotion measures underlying Portuguese legislation are not yet fully consolidated, the imposed threshold of 20% women on Boards is a signal sent to the market and one that is valued by investors.

1. Introduction

Boards of directors have an important role in corporate governance, as they are responsible for monitoring management; supervising and advising on strategic decision-making; preparing and disseminating information to the various stakeholders; and also for providing valuable contact networks with entities outside the company [1]. For this reason, a large body of research has analyzed the extent to which certain characteristics or practices of the Board have positive economic effects for companies, particularly in terms of the company’s performance and market value [2]. More recently, particular attention has been given to Board diversity, which can be defined as the variety inherent in the Board’s composition [3]. Because women are generally under-represented in “old boys’ networks”, Board gender diversity refers to the presence of more female directors on the Board and in other top management positions as Chief Executive Officer (CEO) or Chief Financial Officer (CFO). Diversity in terms of gender, age, nationality, or ethnicity allows for different opinions, perspectives, and experiences, more connections with entities outside the company, and problem-solving skills which may contribute to a greater ability to monitor and resolve conflicts of interest between different stakeholders [4]. Due to their personal characteristics, women are more concerned with social causes, environmental protection, and ethical issues [5]. For this reason, gender diversity in companies is an important driver for sustainable actions [6] and contributes to enhancing their reputation [7,8].
In 2012, the European Union presented a proposal for a Directive “on improving the gender balance among non-executive directors of companies listed on stock exchanges and related measures” [9]. Although its approval has not yet occurred, the Directive has triggered several legislative actions by member states. In Portugal, Law 62/2017 [10] mandated a gender quota for the Boards of state-owned companies and listed companies. For state-owned companies, the proportion of people of each gender appointed to each management and supervisory body may not be less than 33.3% from 1 January 2018, and this proportion shall apply to both executive and non-executive directors. For listed companies, that proportion may not be less than 20% as from the first elective general meeting after 1 January 2018 and 33.3% as from the first elective general meeting after 1 January 2020. The law provides for sanctions in case of non-compliance with the minimum thresholds. At the same time, the transposition into national law of Directive 2014/95/EU [11], through the Decree Law 89/2017 [12], amended the Portuguese securities code requirements on the corporate governance content, requiring a description of the diversity policy applied by the company in relation to its management and supervisory bodies, namely in terms of age, gender, qualifications, and professional background.
This study analyzes the effect of Board gender diversity on financial performance, based on a sample of Portuguese listed companies from the period from 2010 to 2019. For this purpose, several measures of gender diversity are tested and both accounting-based and market-based measures of financial performance are applied. This investigation seeks to make several contributions to the existing literature. First, because previous evidence on the relationship between Board gender diversity and financial performance is mixed [13], the use of the alternative measures of gender diversity and accounting-based and market-based measures of financial performance will make it possible to identify the types of relationships that are applied to the Portuguese context. Second, we provide empirical evidence on the Portuguese context, which has been scarcely analyzed. To the best of our knowledge, in Portugal, the effects of Board gender diversity on financial performance are documented using a limited set of gender variables, both for family and non-family listed companies, by Vieira [14], and for family-owned companies, by Fėlix and David [15]. Finally, we provide evidence based on a long and recent period covering the publication of the proposal of Directive on Board gender balance and the entry into force of the gender quota law in Portugal.

2. The Relationship between Board Gender Diversity and Financial Performance

2.1. Theoretical Framework

Several organizational, economic, sociological, and psychological theoretical approaches predict that a female presence in management positions and more gender diverse Boards lead to positive economic effects for companies [16,17,18]. Kirsch [19] presents two causal paths that can explain why Board gender composition, in particular the presence of female directors, may positively affect organizational outcomes. Firstly, Board gender composition affects the Board as a group, and this causality draws upon agency theory [20] and resource dependence theory [21,22]. Agency theory predicts that the presence of female directors provides the Board with greater insight and closer monitoring of management, because women are more active and more inclined to ask questions that would not be asked by male directors [23], and they tend to be more independent than their male counterparts, as they tend to be more often outside directors and not part of “old boys’ networks” [19]. Resource dependence theory is used to argue that diverse Boards have superior resources because female directors provide resources that male directors are not able to provide. Gender differences in values and traits may also affect Board processes and organizational outcomes, because women adopt more ethical, risk-averse, and long-term oriented points of view [19]. Considering that the presence of women on Boards enhances its independence and improves its efficiency, a positive relationship between Board gender diversity and financial performance is expected [24]. Additionally, if female directors improve management control and enhance the independence of corporate Boards, Board gender diversity may improve the transparency and disclosure quality and reduce earnings management practices [23].
The second causal pathway linking Board gender composition with organizational outcomes relates to how that composition, more specifically the presence of women, affects stakeholders inside and outside the company, or both [19]. This causality is based on signaling theory [25] and considers that appointing women to Boards signals legitimacy and adherence to social values, thus enhancing the company’s reputation [26,27]. This signal, sent by the company to their stakeholders, leads them to take certain actions (such as buying the company’s shares or products, promoting female managers, initiating acquisitions, or working for the company) that, predictably, have a positive effect on financial performance [28]. There is evidence that the market reacts positively to the announcement of female Board appointments, suggesting that investors on average believe that female directors add value to the company [3]. The presence of women on Boards also has a positive effect on the quantity and quality of public disclosure and therefore companies with higher gender diversity on their Boards show lower levels of information asymmetry in the market [23,29]. If gender diversity leads to an improvement in information disclosure, and greater transparency and disclosure reduces information risk for market participants, a positive effect of Board gender diversity on stock prices and market value is expected.
The causal paths presented consider that Board diversity is beneficial because there is “value-in-diversity”, but a diversified composition of the Board can be viewed negatively, i.e., “diversity-as-process-loss” [19]. On the one hand, diverse groups can make better decisions because they consider many points of view, which generates more ideas and improves creativity, innovation, and adaptability, resulting in better decisions. On the other hand, diverse groups can be more conflictual, have trouble communicating, and have more divergence of opinions; therefore, decision-making will usually be more time-consuming and less effective [30].
Additionally, according to critical mass theory, minority gender (women) directors cannot fully play their role in a group (a Board) until a certain threshold or critical mass of women in the group is reached [31,32]. When only a marginal number of women directors are present, they are treated as female representatives (“tokens” or “symbols”), bringing about tokenism issues, such as stereotyping, suspicion, isolation, and exclusion, which discourage the women directors and the incumbent men directors to speak and perform in Board interaction processes. Critical mass theory posits that once a certain threshold or critical mass of women in the Board is reached, their presence becomes normalized. In this context, gender-unbalanced Boards are more problematic and even less efficient than more gender uniform ones [31,32]. The critical threshold often pointed to is of three women or around 30% of the group [33,34].
The negative effects of a diversified Board composition could also arise when the decision to appoint women to certain positions is motivated by societal pressure for greater equality between sexes, i.e., they are hired as “tokens” and not because of their competence. If men perceive women as “tokens”, it could be very possible that women will be marginalized and their opinions will not be considered [31,32]. This can lead to conflicts among Board members and a loss of effectiveness of decisions, with consequential negative economic effects. The presence of women is also associated with negative economic effects when they are appointed to Boards of companies experiencing periods of underperformance or other turmoil, a phenomenon known as the “glass cliff” [35,36].

2.2. Empirical Evidence

The literature on Board gender composition has expanded significantly in recent years, with the literature analyzing the effects of the female presence on corporate Boards in aspects such as decision-making, risk-taking, financial and non-financial performance, market value, corporate social responsibility, transparency, and disclosure (see [4,16,17,18,19,37,38]). Two factors may explain this growing trend. First, despite the rapid increase in female participation in the labor force during the 20th century, the “glass ceiling effect” still exists, with women remaining underrepresented in leading positions, including on corporate Boards [39]. Second, following the Directive proposal, several countries have introduced regulatory requirements to increase the number of women on corporate Boards [40]. In this context, research on Board gender diversity economic effects is needed to empirically test the theoretical reasons given for increasing female presence in corporate management positions and to assist regulators in gender policy-making.
In this study, we focus on the Board gender diversity. However, the effects of gender diversity on financial performance have also been studied, considering the presence of a woman in the chair position and in other top management positions, such as CEO and CFO (e.g., [41,42,43,44]). More recently, along with gender diversity, other characteristics of women have been analyzed, such as independence, multiple directorships, nationality, tenure, age, education level, and business education (e.g., [45]).
The United States of America has often been pointed out as the context where the effects of Board gender diversity have been most studied, as it is there that research on the role of the Board of directors in corporate governance has flourished [13,46,47,48]. However, research on the effects of Board gender diversity on financial performance has spread out to other settings such as Europe (see Appendix A), Asia (e.g., [49,50]), Africa (e.g., [44]), Latin America (e.g., [51]), and Russia (e.g., [52]). Considering the scope of our study, we focus on the empirical evidence from European countries, which is summarized in the Appendix A. The studies reveal mixed results concerning the effect of Board gender diversity on financial performance, showing positive, negative, or no effect. We consider that this may be explained by two reasons. The first reason concerns the differences in the time periods, countries, and/or companies studied that represent the institutional contexts with different agency problems, information asymmetries, or resource needs. The period “before” or “after” the introduction of a recommendation on Board gender diversity or a law on women’s quota may also influence the relationship between female presence on the Board and financial performance, with studies finding a positive relationship “before” and a negative relationship “after” [53], in Italy) or no effect “before” and a positive effect “after” but only for highly performing companies, suggesting that the costs of appointing more women could be high for low performing companies [54], in France). In Romania, Ionascu et al. [55] also found differences in Board gender diversity effects according to a company’s profitability, observing a positive effect only for profitable, small, and less well governed companies. In Portugal, Vieira [14] found a positive effect of female presence on Board on financial performance for family firms and a negative relationship for non-family firms. In specific contexts, the market reacts negatively to higher proportions of women on Boards, stating that more female presence means more expensive and less experienced Boards [56,57] in Norway; [54] in France). For a similar period and in the same country, the United Kingdom (UK), a positive relationship between Board gender diversity and financial performance was found for listed companies by Brahma et al. [45] and a negative relationship was found for small and medium sized companies (SME) by Shehata et al. [58]. Finally, recent evidence has shown that the economic effects of female presence are evident only when women have an active involvement in corporate governance, occupying decision-making positions such as CEO [59,60].
The second reason why empirical evidence on the effects of Board gender diversity is mixed may be related to the use of different measures of financial performance and gender diversity [13]. Regarding financial performance, the most popular measurements are accounting-based measures and market-based measures for the categories of the return on assets (ROA) and the Tobin’s Q, respectively. Tobin’s Q is defined as the market value of the company’s assets divided by their replacement cost. However, researchers commonly calculate Tobin’s Q as the sum of the market value of equity and the book value of debt divided by the book value of total assets. A value of Tobin’s Q which is greater than one reflects investors’ confidence in the company and its growth opportunities. Market-based measures capture the market expectations about the ability of the company to generate future cash flows and its associated risk. Accounting-based measures reflect past events and only those reflected in accounting. For this reason, diverse results can be found depending on whether an accounting-based or a market-based measure of financial performance is used (e.g., [42] in France; [14] in Portugal). Because it is unclear when the effects of the appointment of women to Boards become apparent [19], these measures should be combined and carefully analyzed, considering that changes in Board composition tend to be captured by accounting with some delay, while market-based measures may anticipate a future performance different from what will occur.
In relation to gender diversity measures, some studies use only one measure (e.g., [41] in France; [14,15] in Portugal), while others use several (e.g., [54] in France; [58] in the UK). The “total number” and the “proportion” of women on Boards consider a linear relationship between gender diversity and the economic effect. The “presence of at least X women on the Board” (gender “dummies”) forms a proxy of the critical mass that is needed to achieve the desired economic outcome. The Blau index and the Shannon index capture the balance between the two genders, being both qualitatively similar, but the Shannon index is a logarithmic measure of diversity, and thus is more sensitive to minor differences in Boards’ gender diversity. The use of more than one proxy may shed light on the most efficient level of gender diversity, as the relationships established may not be linear. For example, in the UK, Brahma et al. [45] only found a positive effect of financial performance for the presence of three or more women on the Board. More recent studies test the presence of a possible quadratic relationship between financial performance and gender diversity, using the square of the proportion of women, the Blau index, and the Shannon index ([61] in Spain; [59] in Turkey).
Considering the theoretical arguments that underlie the “value-in-diversity” perspective and the empirical evidence presented above, we formulate the following hypotheses:
Hypothesis 1 (H1).
The proportion of women on the Boards of Portuguese listed companies is positively related with financial performance.
Hypothesis 2 (H2).
The presence of women on the Boards of Portuguese listed companies is positively related with financial performance only when a critical mass of female presence is reached.

3. Research Methodology

3.1. Sample Selection and Data Collection

The empirical analysis is based on data from three sources: SABI database (Iberian Balance Sheet Analysis System), for economic and financial information; corporate governance reports, from which data about Board characteristics were hand-collected; and companies’ market data, available online. The initial sample consisted of 55 listed Portuguese companies included in the SABI database, with non-consolidated accounts for the period 2010 to 2019. The financial sector, football clubs, and companies with a fiscal year not ending on 31 December were excluded, due to the lack of comparability of accounting information. Companies with negative equity were also removed because extreme financial constrains might compromise the relationships tested. After this process, only 29 companies had corporate governance reports available, making a total of 290 observations. The regressions with Tobin’s Q as the dependent variable were carried out for only 250 observations, corresponding to 25 companies, due to lack of stock market data for some of the company–year observations.
Table 1 presents an overview of gender diversity in the Boardrooms over the years of the sample. The Board size ranges from 3 members to 24 members and the number of women on Boards from 0 (zero) to a maximum of 5. Only one company in the sample has a woman as a chair, from 2016. We can see a positive evolution of Board gender diversity over the years, but in 2019, the most recent year of the sample, there are still companies with no female directors in their Boards. The size of the Boards has remained stable over the years, which is a similar scenario to that documented in Spain by Martínez and Rambaud [61]. After the enactment of the gender law in 2017, the number of women on Boards increased, on average, from one to two. In 2019, the 20% threshold of the gender quota law is exceeded only by 24 companies (from the 29 analyzed), which may be explained by the fact that the law only applies to appointments from 2018 onwards.

3.2. Model and Variables

The effects of Board gender diversity on financial performance are tested through a multivariate regression model, with the following specification:
Financial Performancei,t = β0 + β1 × Genderi,t + β2 × Controlsi,t + β3 × Yeari,t + εi,t
We chose two measures of financial performance for our dependent variable: ROA, as accounting-based measure; and Tobin’s Q as market-based. The independent variables include the Board gender diversity proxies (Gender) and an array of control variables (Controls) identified in previous studies (e.g., [14,45,62]). The gender proxies are included in the models one at a time and consider a set of “continuous” gender variables that capture the proportion of women on Boards, for testing Hypothesis 1; and “gender dummies” for testing Hypothesis 2. The models also include year dummy variables (Year) and the error term (εi,t) of the equation to be estimated. The definitions of all variables are presented in Table 2.
Considering that our data consist of a balanced panel, it is recommended to control for company-specific and time-invariant unobserved heterogeneity through fixed effects model (FEM) or random effects model (REM). Thus, for each regression, adequate tests are carried out to decide which estimation method produces the most efficient estimators: pooled ordinary least squares (OLS), fixed effects model (FEM), or random effects model (REM).

4. Empirical Findings and Discussion

4.1. Descriptive and Correlations Analysis

The descriptive statistics of the continuous variables to be included in the regressions are presented in Table 3. ROA is, on average, close to zero because some companies have a high negative net income. The statistics for Tobin’s Q corroborate that most of the companies have a market value above their book value. As for the continuous gender diversity variables, the minimum values for the proportion of women (PMUL), Blau index (BLAU), and Shannon Index (SHANNON) corroborate the existence of companies without female directors, at least in one of the years of the period analyzed. Concerning the control variables, the only noteworthy fact is that, on average, the leverage ratio is around 42%, with some observations where this ratio reaches a maximum of 87% revealing the existence of highly leveraged firms.
After ensuring that the normality assumptions hold for the continuous variables, an independent samples t-test was conducted to compare the differences between the financial performance of companies, according to the gender diversity of their Boards. The results are presented in Table 4. For the continuous gender variables, the sample was divided according to the median of the gender variable (companies whose proportion of women, Blau index, or Shannon index is above or below the respective median for the year). For gender dummies, the sample was divided according to their definition. The results show statistically significant differences for ROA in all the groups analyzed (except for 1WOM), suggesting that more gender diverse companies have a higher ROA. The Tobin’s Q exhibits statistically significant differences only when comparing companies with at least 20% women (20%W) and the rest, with a higher Tobin’s Q for more gender diverse companies.
The correlations among the variables to be included in the regressions are presented in Table 5. The coefficients confirm a statistically significant and positive association between ROA and all gender variables, except for the Shannon index and the presence of at least 33% women (33%W); and between Tobin’s Q and the presence of at least 20% women (20%W). The correlations between the independent variables reveal low correlation coefficients with the highest being 0.486, suggesting that multicollinearity does not pose an issue in this study.

4.2. Regression Analysis

Table 6 reports the results of the regression analysis, considering ROA and Tobin’s Q as dependent variables in Panel A and Panel B, respectively. The regression results presented correspond to the estimation method identified as the most efficient, based on the F statistic and the Hausman test: Fixed Effects Model (FEM) for ROA and the Random Effects Model (REM) for Tobin’s Q. The adjusted R2 is higher in the models with Tobin’s Q than in the models with ROA as dependent variables, suggesting that gender diversity collectively with control variables have greater explanatory power for market-based performance compared to accounting-based performance.
Regarding the effect of gender diversity on ROA (Table 6—Panel A), only the presence of at least two women (2WOM) and the presence of at least 20% women (20%W) on Boards show statistically significant coefficients, with positive signs, as expected. This result leads us to conclude that the effect of gender diversity on financial performance is not linear, because the proportion of women (PWOM) and the Blau and Shannon indexes (BLAU, SHAN) do not present statistically significant coefficients. In Portugal, for listed companies from the period from 2002–2013, Vieira [14] concluded that the proportion of women was positively related to ROA in family firms, and negatively related to ROA in non-family firms. This may be justified by the fact that in family firms, women are family members, with a long-term business outlook and the aim of maximizing the firm’s wealth in the long term [14], and in non-family firms, they may be merely seen as “tokens”. However, when considering the whole sample, no statistically significant relationship was found, which is consistent with our results.
Concerning the gender dummies variables, our findings are consistent with critical mass theory [31,32], confirming that gender diversity only influences financial performance when a critical mass of female presence is reached, or more precisely, two women or 20% women. The absence of statistically significant coefficients for the presence of at least one woman (1WOM) confirms that, unless there are two or more women on the Boardroom, a female presence is unlikely to motivate significant improvement in financial performance [33,34]. The lack of significant results for the presence of 33% of women (33%W) confirms that, in our context, the optimal number of women on Boards is of two or 20%, contrasting, for example, with Brahma et al. [45] in the UK, whose results concluded that the critical mass needed was of three women.
For the effect of gender diversity on Tobin’s Q (Table 6—Panel B), only the variable concerning the presence of at least 20% women (20%W) reports statistically significant coefficients, which are also positive. Considering that Tobin’s Q captures market expectations about companies’ future cash flows and risk, our results indicate that investors assign higher value to companies that have already reached the target of 20% imposed by the quota law, for two reasons. First, the presence of women improves economic performance and consequently contributes to higher future cash flows. Second, these companies pose less risk as they will not incur penalties for non-compliance with the law or reputational losses for being considered discriminatory or non-compliant. The 20% threshold for the proportion of women on the Board signals an adherence to social values and compliance with legal provisions, which in turn enhances the firm’s reputation [26,27].
Regarding the control variables, SIZE presents positive and statistically significant coefficients in most estimations, corroborating that financial performance is positively influenced by the company size in the Portuguese context [14]. The remaining control variables do not show statistically significant coefficients.
Thus, the results obtained lead to the rejection of hypothesis 1, which predicted a linear relationship between Board gender diversity and financial performance, and to the confirmation of hypothesis 2, for a critical mass of 20% for both measures of financial performance.
In line with previous studies conducted in contexts with a low presence of women on Boards, as in Portugal, we have not found statistically significant relationships between financial performance and the proportion of women on Boards, the Blau index, and the Shannon index [54,59,65,66]. Moreover, the presence of at least one woman on the Board does not seem to influence the financial performance of Portuguese companies, similarly to other studies [45,62,66,67,68]. In fact, few studies, and most of them carried out in specific contexts, have documented a positive effect on financial performance for the presence of at least one woman on the Board ([69] in banks; [15] for family firms; [70] only for ROE; [71] for SMEs). The proportion of women, the Blau index, the Shannon index, and the presence of at least one woman on the Board are measures frequently used in previous studies, some of which have concluded for the non-existence of a relationship between gender diversity and financial performance, on the basis of these measures alone [59,65,66]. Our results demonstrate the importance of using alternative measures of gender diversity as a means of identifying the optimal level of gender diversity for the context analyzed.

4.3. Robustness Tests

To assess the robustness of the results, the model was estimated with two modifications. The first consisted in introducing as independent variables lagged financial performance variables (1 year lag for ROA and Tobin’s Q), because managers and investors may adopt strategies based on past performance that may affect future performance [72]. In the second modification, an alternative accounting measure of financial performance was used—return on equity (ROE)—computed as the ratio of net income to equity [41,42,53,68,70]. The results, presented in Appendix B, in Table A2 and Table A3, respectively, do not change the previous conclusions regarding the effect of gender diversity on financial performance. For the models with accounting-based measures of financial performance as dependent variables (ROA in Table A2—Panel A; ROE in Table A3), only the presence of at least two women (2WOM) and the presence of at least 20% women (20%W) on Boards show statistically significant coefficients, with positive signs. For the model with Tobin’s Q as the dependent variable (Table A2—Panel B), only the presence of at least 20% women (20%W) on Boards shows a positive and statistically significant coefficient.
The appointment of women to the Boards is not random and financial performance may causally affect female representation on Boards, as either female directors would prefer to join Boards of better performing companies or better performing companies may appoint a greater number of women to their Boards [73]. Because financial performance may affect the incentive for women to join corporate Boards and the motivation of Boards to appoint female directors, an endogeneity problem may arise from simultaneity/reverse causality between gender diversity and financial performance [47,73]. To address the reverse causality, a procedure similar to that of Ararat and Yurtoglu [59] was employed, consisting of testing whether ROA and Tobin’s Q of year t predicts female representation on Boards in years t + 1 and t + 2. For this purpose, a logit model was applied with 2WOM and 20%W (for years t + 1 and t + 2) as dependent variables and with ROA, Tobin’s Q, and the remaining variables of the model as independent variables (as per Table 6). The estimation results are presented in Table A4 and show no statistically significant coefficients for ROA and Tobin’s Q, indicating no evidence for reverse causality between gender diversity and financial performance.

5. Conclusions

Based on a sample of 29 Portuguese listed companies from the period from 2010 to 2019, this paper studied the effects of Board gender diversity on financial performance. Portuguese listed companies are subject to gender quota law, which imposes a minimum proportion of women on Boards of 20% from the first elective general meeting after 1 January 2018 and 33.3% from the first elective general meeting after 1 January 2020. Our results support that the presence of women exerts a positive effect on financial performance, corroborating the economic premises for more gender diverse Boards, based on resource dependence theory and agency theory. However, this effect is not observed linearly with the proportion of women on Boards or for the presence of only one woman, rendering support for critical mass theory. In fact, a positive effect on ROA and ROE was only observed when the Board has at least two women or when the minimum threshold of 20% of female directors is reached. Concerning the Tobin’s Q, a positive effect of Board gender diversity was found only for the presence of at least 20% of women. Consistently with signaling theory, this result leads to the conclusion that by complying with the gender quota law, companies send a positive signal to the market about their future risk and cash flows. The gender diversity underlying the 20% threshold not only ensures better economic performance and higher future cash flows, but also reduces the perceived risk for investors, as these companies will not incur penalties for non-compliance with the law or reputational losses for being considered discriminatory or non-compliant. Meeting the 20% threshold signals adherence to social values and compliance with legal provisions, which in turn enhances the firm’s reputation.
This research makes three primary contributions to the literature. First, it adds to the scarce literature [14,15] on the effects of Board gender diversity on financial performance, in the Portuguese context. Second, it presents empirical evidence on the levels at which female representation affects the financial performance of Portuguese listed companies, in a period in which two important moments occurred: in 2012, the European Union presented a proposal for a Directive on Board gender balance; and, in 2017, a law came into force in Portugal, imposing gender quota for the Boards of state-owned and listed companies. Third, it provides an economic justification for the gender diversity regulation imposed on companies, legitimizing the thresholds imposed and encouraging companies to meet them as soon as possible, which makes the evidence found particularly important for managers, investors, and policymakers.
Despite its contributions, this paper has some limitations, the first of which is the reduced sample size due to the small number of companies on the Portuguese stock market. A second limitation regards the period analyzed, which ends in the year 2019, not allowing the effects of reaching the 33.33% threshold to be fully understood. Finally, it should be noted that other personal characteristics of women which may affect the relationship between financial performance and gender diversity, such as education and experience, have not been studied due to the lack of information on these aspects, which has only more recently started to be disclosed in governance reports. Certainly, future studies will contemplate periods that will make it possible to remedy these limitations. Concurrently, future research may consider not only the female presence on Boards but also in specific committees and other top management positions as CFO and CEO (e.g., [41,43]). Additionally, other effects of female presence should be studied, such as on earnings management (e.g., [74]) and sustainability performance and disclosures (e.g., [75,76,77]).

Author Contributions

Conceptualization, C.C.; methodology, C.C. and S.A.; validation, C.C. and S.A.; formal analysis, C.C., S.A. and B.Q.; investigation, C.C., S.A. and B.Q.; resources, C.C. and S.A.; writing—original draft preparation, C.C. and S.A.; writing—review and editing, C.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the research unit on Governance, Competitiveness and Public Policy (UIDB/04058/2020) + (UIDP/04058/2020), funded by national funds through FCT—Fundação para a Ciência e a Tecnologia.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Empirical evidence from European countries on the effects of Board gender diversity on financial performance.
Table A1. Empirical evidence from European countries on the effects of Board gender diversity on financial performance.
CountryAuthorsSampleFinancial Performance MeasuresGender Diversity MeasuresResults
11 western European countriesGreen and Homroy [60]Eurotop 100 companies
2004–2015
177 companies
16.647 obs.
ROA.Proportion of women on the Board.
Presence of women in specific committees.
Positive relationship for both measures of gender diversity.
16 European countriesIsidro and Sobral [78]Financial Times 500 largest companies
2010–2012
922 obs.
ROA, Return on Sales, Tobin’s Q.Proportion of women on the Board.
Presence of at least 30% women on the Board.
Positive relationship with ROA and ROS. No significant relationship with Tobin’s Q.
DenmarkRose [66]Copenhagen stock exchange (excluding financial sector and football clubs)
1998–2001
443 obs.
Tobin’s Q.Proportion of women on the Board.
Presence of at least 1 woman on the Board.
No significant relationship was found.
DenmarkSmith et al. [79]Largest Danish companies
1993–2001
2500 companies
12,085 obs.
Gross profit/net sales; contribution margin/net sales; operating income/net assets; net income after tax/net assets.Proportion of women on the Board.
Presence of a woman in other positions: CEO and vice-directors.
Positive relationship, depending on education of women.
FranceAhmadi et al. [41]Euronext Paris CAC 40
2011–2013
108 observations
ROA, ROE.Proportion of women on the Board.Positive correlation.
FranceBennouri et al. [42]Euronext Paris CAC All-shares
2001–2010
3403 observations
ROA, ROE, Tobin’s Q.Proportion of women on the Board.
Proportion of non-executive women directors to total women directors.
Presence of a woman in other positions: chair, CEO (among others).
Positive relationship between all gender diversity variables and ROA and ROE. Negative relationship between all gender diversity variables and Tobin’s Q. When other characteristics of women are considered, the relationship with ROA and ROE remains and the relationship with Tobin’s Q disappears.
FranceDang et al. [67]Euronext Paris Compartment B and Alternext (listed SMEs excluding financial and utilities sectors)
2010–2014
466 observations
ROA.Total number of women on the Board.
Proportion of women on the Board.
Presence of at least 1 woman on the Board.
Blau index of diversity.
Positive relationship between proportion of women and financial performance. The results for other measures of gender diversity were not significant.
FranceSlama et al. [54]Euronext Paris CAC All-shares (excluding financial sector)
2008–2011
356 observations
ROA, Tobin’s Q.Proportion of women on the Board.
Presence of at least X women on the Board.
(X = 1, 3)
The relation is analyzed before and after the introduction of a “comply or explain” recommendation concerning Board gender diversity. In the period “before”, the Board gender diversity does not influence financial performance. In the period “after”, Board gender diversity only increases ROA in highly performing companies. For low performing companies, Board diversity decreases ROA, suggesting that costs of appointing more women could be high for low performing companies. For higher proportions of women on Boards (around 40%), Tobin’s Q decreases, suggesting that investors react negatively to such proportions.
ItalyDel Prete and Stefani [69]Italian banks
1995–2010
≅10,000 obs.
ROA and other bank-specific indicators.Presence of at least 1 woman on the Board.Positive relationship between Board gender diversity and ROA. The relationship with other measures of performance was not significant.
ItalyIacoviello et al. [53]Italian stock exchange
2008–2014
799 observations
ROA, ROE, EBITDA.Proportion of women on the Board.The relation is analyzed “before” and “after” the introduction of a law on women’s quotas. The relation between Board gender diversity and ROE is positive for the period “before” and negative for the period “after” the law. The results for the other financial performance measures are inconclusive.
NetherlandsLückerath–Rovers [70]Euronext Amsterdam stock exchange
2005–2007
297 observations
ROE, Return on Sales, Return on Invested Capital.Proportion of women on the Board.
Presence of at least 1 woman on the Board.
Positive relationship between all Board gender diversity variables and ROE. The relationship with other measures of performance was not significant.
NorwayAhern and Dittmar [56]Oslo Stock Exchange
2001–2009
248 companies
1230 obs.
Tobin’s Q.Proportion of women on the Board.Negative relationship.
NorwayBøhren and Strøm [57]Oslo Stock Exchange (excluding financial sector)
1989–2002
229 companies
1290 obs.
ROA, Tobin’s Q, Market Return on Stock.Proportion of women on the Board.Negative relationship.
NorwayDale–Olsen et al. [65]Oslo stock exchange (excluding financial sector)
2003–2007
128 companies
ROA.Proportion of women on the Board.No significant relationship was found.
PortugalVieira [14]Euronext Lisbon stock exchange
2002–2013
381 observations
ROA, MTB.Proportion of women on the Board.Positive relationship between Board gender diversity and ROA in family firms and negative relationship in non-family firms.
No significant relationship was found for MTB.
PortugalFélix and David [15]Family firms
2006–2014
1683 observations
Variation of sales, business volume over total assets, variation of business volume.Presence of at least 1 woman on the Board.Positive relationship between Board gender diversity and all variables of financial performance.
RomaniaIonascu et al. [55]Bucharest stock exchange
2012–2016
343 observations
ROA, Tobin’s Q, MTB.Proportion of women on the Board.
Presence of a woman in chair position.
Positive relationship between all Board gender diversity variables and all measures of financial performance only for profitable companies and those listed on the Standard tier (smallest and presumably less well governed than those listed on the Premium tier).
SpainCampbell and Mínguez–Vera [62]Listed companies (excluding financial sector)
1995–2000
68 companies
408 obs.
Tobin’s Q.Proportion of women on the Board.
Presence of at least 1 woman on the Board.
Blau Index of diversity.
Shannon Index of diversity.
Positive relationship between all gender diversity variables and financial performance, except for the presence of at least 1 woman on the Board.
SpainMartín–Ugedo and Minguez–Vera [71]Non-financial SMEs
2003–2008
42,979 observations
ROA.Proportion of women on the Board.
Presence of at least 1 woman on the Board.
Blau Index of diversity.
Shannon Index of diversity.
Positive relationship between all Board gender diversity variables and financial performance.
SpainMartínez and Rambaud [61]Companies listed in IBEX35
2003–2017
302 observations
Tobin’s Q.Proportion of women on the Board.
Blau Index of diversity.
Shannon Index of diversity.
Positive relationship between all Board gender diversity variables and financial performance.
SpainReguera–Alvarado et al. [72]Madrid stock exchange general index (excluding financial sector)
2005–2009
497 observations
Tobin’s Q.Proportion of women on the Board.
Blau Index of diversity.
Shannon Index of diversity.
Positive relationship between all Board gender diversity variables and financial performance.
SpainRodríguez–Fernández et al. [80]Companies listed in IBEX35 (excluding financial sector)
2016
28 companies
Net sales, EBITDA.Presence of at least 1 woman in top management teams.Positive relationship between gender diversity and all variables of financial performance.
TurkeyArarat and Yurtoglu [59]Borsa Istanbul (excluding financial sector)
2011–2018
268 companies
1882 obs.
Tobin’s Q, EBIT/Assets.Total number of women on the Board.
Proportion of women on the Board.
Presence of at least X women on the Board
(X = 1, 2, 3, 4, 5).
No significant relationship.
A positive relationship was found between Tobin’s Q and the proportion of women on Board for women that are members of key Board committees (in relatively large numbers) and for women that are members of controlling families. The relationship is economically more significant in companies with higher inside ownership and less effective in companies with a high degree of Board independence.
TurkeyYıldız et al. [68]Borsa Istambul
2016
389 companies
ROA, ROE, MTB.Proportion of women on the Board.
Presence of at least 1 woman on the Board.
Presence of at least 25% women on the Board.
ROA in companies with at least 25% female members is lower than the companies with less than 25% female members.
United KingdomBrahma et al. [45]Companies listed in FTSE 100
2005–2016
12,608
ROA, Tobin’s Q.Presence of at least X women on the Board (X = 1, 2, 3)Positive relationship between Board gender diversity and financial performance only for the presence of at least 3 women on the Board.
United KingdomShehata et al. [58]SMEs
2005–2013
34,798
ROA.Proportion of women on the Board.
Presence of at least 1 woman on the Board.
Blau index of diversity.
Shannon index of diversity.
Negative relationship between all Board gender diversity variables and financial performance.
The studies are presented in alphabetical order, country first, then authors.

Appendix B

Table A2. Models with one year lagged financial performance as independent variable.
Table A2. Models with one year lagged financial performance as independent variable.
Panel A—Financial Performance Measured by ROA
PWOMBLAUSHAN1WOM2WOM3WOM20%W33%W
FEMFEMFEMFEMFEMFEMFEMFEM
Intercept−3.845 *
(0.540)
−3.854 *
(0.544)
−3.842 *
(0.546)
−3.771 *
(0.543)
−3.864 *
(0.535)
−3.824 *
(0.540)
−4.009 *
(0.536)
−3.777 *
(0.535)
Gender0.181
(0.192)
0.125
(0.149)
0.156
(0.238)
−0.001
(0.054)
0.078 ***
(0.045)
−0.039
(0.056)
0.109 **
(0.042)
0.058
(0.066)
Previous Performance−0.362 *
(0.066)
−0.361 *
(0.067)
−0.361 *
(0.067)
−0.361 *
(0.067)
−0.358 *
(0.067)
−0.363 *
(0.067)
−0.368 *
(0.066)
−0.364 *
(0.067)
BOARD0.007
(0.142)
−0.005
(0.142)
−0.010
(0.142)
−0.001
(0.150)
−0.044
(0.144)
0.018
(0.144)
0.051
(0.141)
0.048
(0.152)
SIZE0.665 *
(0.100)
0.668 *
(0.101)
0.668 *
(0.100)
0.661 *
(0.101)
0.067 *
(0.100)
0.671 *
(0.101)
0.067 *
(0.099)
0.653 *
(0.101)
LEV0.101
(0.140)
0.100
(0.140)
0.097
(0.141)
0.097
(0.141)
0.100
(0.140)
0.078
(0.143)
0.131
(0.139)
0.101
(0.141)
N261261261261261261261261
Adj. R212.93%12.86%12.75%12.57%13.72%12.77%15.18%12.88%
F-Test5.811 *5.797 *5.802 *5.878 *5.935 *5.879 *6.147 *5.938 *
Haussman test41.022 *39.010 *42.631 *68.821 *75.006 *38.626 *84.558 *67.416 *
Panel B—Financial performance measured by Tobin’s Q
PWOMBLAUSHAN1WOM2WOM3WOM20%W33%W
FEMFEMFEMFEMFEMFEMFEMFEM
Intercept4.220 *
(1.364)
4.192 *
(1.369)
4.196 *
(1.372)
4.256 *
(1.368)
4.254 *
(1.364)
4.153 *
(1.388)
3.993 *
(1.325)
4.323 *
(1.360)
Gender0.381
(0.583)
0.253
(0.439)
0.325
(0.696)
0.022
(0.154)
0.041
(0.129)
−0.076
(0.169)
0.423 *
(0.124)
0.214
(0.209)
Previous Performance0.371 *
(0.070)
0.372 *
(0.070)
0.373 *
(0.070)
0.371 *
(0.070)
0.371 *
(0.070)
0.367 *
(0.071)
0.348 *
(0.068)
0.365 *
(0.070)
BOARD0.314
(0.458)
0.294
(0.459)
0.284
(0.462)
0.289
(0.485)
0.281
(0.469)
0.335
(0.462)
0.559
(0.451)
0.450
(0.477)
SIZE−0.695 *
(0.263)
−0.687 **
(0.264)
−0.685 **
(0.265)
−0.692 *
(0.266)
−0.690 *
(0.264)
−0.677 **
(0.267)
−0.706 *
(0.256)
−0.730 *
(0.265)
LEV1.118 *
(0.393)
1.112 *
(0.393)
1.105 *
(0.392)
1.094 *
(0.393)
1.101 *
(0.392)
1.055 *
(0.404)
1.271 *
(0.384)
1.118 *
(0.392)
N225225225225225225225225
Adj. R226.74%26.70%26.66%26.58%26.61%26.65%30.88%26.98%
F-Test3.307 *3.294 *3.287 *3.285 *3.288 *3.321 *3.821 *3.375 *
Haussman test85.143 *84.871 *84.684 *84.571 *84.736 *85.130 *101.97 *86.575 *
Variables definitions as per Table 2. Previous performance corresponds to lagged financial performance variables (1 year lag for ROA in Panel A; 1 year lag for Tobin’s Q in Panel B). Each column presents estimation results for the respective gender proxy and for the most efficient model, based on the F statistic and the Hausman test. *, **, and *** represent statistical significance at 1%, 5%, and 10%, respectively. Robust standard errors in parenthesis.
Table A3. Alternative accounting-based measure of financial performance.
Table A3. Alternative accounting-based measure of financial performance.
Financial Performance Measured by ROE
PWOMBLAUSHAN1WOM2WOM3WOM20%W33%W
FEMFEMFEMFEMFEMFEMFEMFEM
Intercept−4.295 *
(0.573)
−4.311 *
(0.574)
−4.309 *
(0.575)
−4.267 *
(0.574)
−4.285 *
(0.568)
−4.384 *
(0.582)
−4.302 *
(0.568)
−4.259 *
(0.573)
Gender0.223
(0.237)
0.165
(0.183)
0.217
(0.291)
0.002
(0.065)
0.121 **
(0.056)
−0.077
(0.072)
0.110 **
(0.050)
0.038
(0.083)
BOARD0.004
(0.177)
−0.011
(0.177)
−0.017
(0.177)
−0.005
(0.185)
−0.077
(0.178)
−0.032
(0.179)
−0.035
(0.176)
−0.026
(0.189)
SIZE0.770 *
(0.108)
0.775 *
(0.108)
0.775 *
(0.108)
0.770 *
(0.108)
0.782 *
(0.107)
0.787 *
(0.109)
0.763 *
(0.107)
0.763 *
(0.109)
LEV−0.108
(0.168)
−0.109
(0.168)
−0.113
(0.168)
−0.119
(0.168)
−0.102
(0.167)
−0.157
(0.171)
−0.064
(0.168)
−0.116
(0.168)
N290290290290290290290290
Adj. R211.70%11.68%11.59%23.96%13.00%11.82%13.03%11.47%
F-Test5.228 *5.194 *5.207 *5.379 *5.586 *5.699 *5.512 *5.674 *
Haussman test50.325 *51.072 *50.970 *48.388 *60.390 *59.881 *63.195 *45.08 *
ROE is return on equity, measured as the ratio of net income to equity during a financial year. Variables definitions as per Table 2. Each column presents estimation results for the respective gender proxy and for the most efficient model, based on the F statistic and the Hausman test. *, and **, represent statistical significance at 1%, and 5%, respectively. Robust standard errors in parenthesis.
Table A4. Test for reverse causality.
Table A4. Test for reverse causality.
Panel A—ROA as Predictor of Gender Diversity
2WOMt+12WOMt+220%Wt+120%Wt+2
ROA0.158
(0.533)
0.047
(0.548)
0.353
(0.541)
0.368
(0.583)
N261232261223
Log—likelihood−122.60−113.34−133.61−124.02
Panel B—Tobin’s Q as Predictor of Gender Diversity
2WOMt+12WOMt+220%Wt+120%Wt+2
Tobin’s Q0.248
(0.157)
0.217
(0.161)
0.230
(0.143)
0.073
(0.152)
N225200225200
Log—likelihood−89.73−83.66−105.71−99.41
Variables definitions as per Table 2. Each column presents estimation results for logit models with gender diversity as dependent variable and financial performance as independent variable. The regressions include intercept, year dummies, and the independent variables of the models of Table 6. The analysis performed aims to test whether ROA and Tobin’s Q of year t predicts the presence of at least two women (2WOM) or at least 20% women (20%WOM) on Boards for the following year (t + 1) and two years ahead (t + 2). Standard errors in parenthesis.

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Table 1. Board gender diversity over the years of the sample.
Table 1. Board gender diversity over the years of the sample.
Total Number Members of the BoardTotal Number Women on the BoardProportion of Women on BoardChair Is WomanBoards with at Least 1 WomanBoards with at Least 2 WomenBoards with at Least 3 WomenBoards with at Least 20% WomenBoards with at Least 33% Women
YearsMin.MedianMax.Min.MedianMax.Min.MeanMax.Number of Companies
201039200040%7%27%0142130
201139240140%7%31%0153130
201239240140%9%40%0185141
201339210150%10%40%0195262
201438200150%11%44%0187353
201538190150%13%43%0189484
201638190140%15%43%119107105
201738190140%15%43%119117105
201838210250%19%43%124178184
201939210250%22%33%1272111241
Table 2. Variables definitions.
Table 2. Variables definitions.
Dependent Variable (Financial Performance)
ROAROA is measured as the ratio of net income to average total assets during a financial year.
TOBINTobin’s Q is defined as the sum of the market value of equity (share price multiplied by the number of ordinary shares in issue at fiscal year-end) and the book value of debt divided by book value of total assets.
Gender Variables
PWOMProportion of women on the Board, calculated by the ratio between the number of women and the total of members on the Board.
BLAUBlau [63] Index, defined as:
B l a u   I n d e x = 1 i = 1 K P i 2
where K is the number of gender categories, i.e., 2 (women and men) and Pi is the percentage of each category. This variable ranges between 0 (the Board has only men or women) and 0.5 (there are the same number of men and women on the Board).
SHANShannon [64] Index, defined as:
S h a n n o n   I n d e x = i = 1 K P i × ln ( P i )
where K is the number of gender categories, in this case two (women and men), and Pi is the percentage of each category. For companies with only women or only men on the Boards, the value of ln(Pi) is forced to be zero, because ln(0) equals infinity. This variable ranges between 0 (the Board has only men or women) and 0.69 (there are the same number of men and women on the Board).
1WOMDummy variable coded 1 if the company has at least 1 woman on the Board and 0 otherwise.
2WOMDummy variable coded 1 if the company has at least 2 women on the Board and 0 otherwise.
3WOMDummy variable coded 1 if the company has at least 3 women on the Board and 0 otherwise.
20%WDummy variable coded 1 if the company has at least a percentage of 20% of women on the Board and coded 0 otherwise.
33%WDummy variable coded 1 if the company has at least a percentage of 33% of women on the Board and coded 0 otherwise.
Control Variables
BOARDBoard size measured by the natural logarithm of total members.
SIZECompany size measured by the natural logarithm of total assets.
LEVLeverage ratio of total liabilities to total assets.
Table 3. Descriptive statistics.
Table 3. Descriptive statistics.
Min.MeanMax.Standard Deviation
ROA−2.9120.0170.5540.245
TOBIN0.0031.1547.0011.119
PWOM0.0000.1280.4440.121
BLAU0.0000.1950.4940.165
SHAN0.0000.1330.2980.106
BOARD0.4770.9271.3800.198
SIZE4.6485.7647.3830.641
LEV0.0010.4190.8710.224
Table 4. Differences in financial performance based on gender diversity measures.
Table 4. Differences in financial performance based on gender diversity measures.
ROATOBIN
NMeanTSigmaNMeanTSigma
PWOM
BLAU
SHAN
Above
median
1450.0469−2.0840.038 **1251.13690.0160.986
Below
median
145−0.01451251.1392
1WOMYes1910.0236−0.7670.4431611.1913−1.0980.273
No990.0049891.0361
2WOMYes900.0549 −2.4160.016 **711.2541−1.1970.232
No2000.00031791.0858
3WOMYes450.0566−2.3490.019 **351.1486−0.0930.925
No2450.01012151.1361
20%WYes910.0604−2.6910.007 *731.3174−1.9030.058 ***
No199−0.00241771.0589
33%WYes250.0475−1.7140.088 ***191.3299−0.8490.404
No2650.01442311.1225
Variables definitions as per Table 2. *, **, and *** represent statistical significance at 1%, 5%, and 10%, respectively.
Table 5. Correlation matrix (Pearson Correlations).
Table 5. Correlation matrix (Pearson Correlations).
ROATOBINBOARDSIZELEV
ROA1
TOBIN0.195 *1
BOARD0.0200.0871
SIZE0.106 ***0.129 **0.486 *1
LEV0.074−0.0190.348 *0.342 *1
PWOM0.102 ***0.0740.010−0.058−0.112 **
BLAU0.099 ***0.0720.053−0.064−0.105 ***
SHAN0.0890.0710.091−0.064−0.108 ***
Variables definitions as per Table 2. *, **, and *** represent statistical significance at 1%, 5%, and 10%, respectively.
Table 6. Estimation results.
Table 6. Estimation results.
Panel A—Financial Performance Measured by ROA
PWOMBLAUSHAN1WOM2WOM3WOM20%W33%W
FEMFEMFEMFEMFEMFEMFEMFEM
Intercept−2.740 *
(0.438)
−2.751 *
(0.440)
−2.748 *
(0.441)
−2.718 *
(0.439)
−2.732 *
(0.436)
−2.761 *
(0.447)
−2.749 *
(0.434)
−2.714 *
(0.439)
Gender0.157
(0.182)
0.114
(0.140)
0.142
(0.222)
−0.004
(0.050)
0.077 ***
(0.043)
−0.028
(0.055)
0.094 **
(0.039)
0.034
(0.063)
BOARD0.485
(0.136)
−0.061
(0.136)
−0.065
(0.136)
−0.053
(0.142)
−0.103
(0.137)
−0.044
(0.137)
−0.023
(0.135)
−0.029
(0.144)
SIZE0.485 *
(0.082)
0.488 *
(0.082)
0.488 *
(0.082)
0.483 *
(0.083)
0.492
(0.082)
0.491 *
(0.084)
0.479 *
(0.082)
0.479 *
(0.083)
LEV0.099
(0.129)
0.099
(0.128)
0.096
(0.128)
0.092
(0.128)
0.103
(0.127)
0.078
(0.131)
0.139
(0.129)
0.094
(0.128)
N290290290290290290290290
Adj. R28.24%8.21%8.12%7.97%9.12%8.06%10.09%8.07%
F-Test5.087 *5.085 *5.096 *5.194 *5.272 *5.185 *5.370 *5.233 *
Haussman test44.264 *44.635 *44.380 *42.788 *51.193 *51.585 *46.064 *42.652 *
Panel B—Financial performance measured by Tobin’s Q
PWOMBLAUSHAN1WOM2WOM3WOM20%W33%W
REMREMREMREMREMREMREMREM
Intercept−0.571
(1.099)
−0.594
(1.101)
−0.595
(1.102)
−0.545
(1.101)
−0.509
(1.093)
−0.772
(1.118)
−0.629
(1.079)
−0.491
(1.096)
Gender0.520
(0.616)
0.360
(0.457)
0.512
(0.717)
0.061
(0.155)
0.127
(0.140)
−0.212
(0.184)
0.468 *
(0.130)
0.232
(0.225)
BOARD0.391
(0.463)
0.366
(0.463)
0.351
(0.465)
0.333
(0.482)
0.288
(0.474)
0.470
(0.468)
0.574
(0.455)
0.525
(0.481)
SIZE0.081
(0.209)
0.088
(0.209)
0.092
(0.209)
0.089
(0.209)
0.093
(0.208)
0.119
(0.211)
0.047 ***
(0.205)
0.052
(0.211)
LEV0.219
(0.367)
0.215
(0.367)
0.208
(0.367)
0.185
(0.365)
0.201
(0.365)
0.088
(0.373)
0.408
(0.361)
0.209
(0.365)
N250250250250250250250250
Adj. R227.00%26.97%26.94%26.84%26.98%27.21%30.65%27.09%
F-Test18.702 *18.674 *18.684 *18.755 *18.563 *18.824 *19.687 *18.947 *
Haussman test0.9580.9600.9390.9111.4020.7631.5271.462
Variables definitions as per Table 2. Each column presents estimation results for the respective gender proxy and for the most efficient model, based on the F statistic and the Hausman test. *, **, and *** represent statistical significance at 1%, 5%, and 10%, respectively. Robust standard errors in parenthesis.
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Carmo, C.; Alves, S.; Quaresma, B. Women on Boards in Portuguese Listed Companies: Does Gender Diversity Influence Financial Performance? Sustainability 2022, 14, 6186. https://doi.org/10.3390/su14106186

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Carmo C, Alves S, Quaresma B. Women on Boards in Portuguese Listed Companies: Does Gender Diversity Influence Financial Performance? Sustainability. 2022; 14(10):6186. https://doi.org/10.3390/su14106186

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Carmo, Cecília, Sandra Alves, and Bruna Quaresma. 2022. "Women on Boards in Portuguese Listed Companies: Does Gender Diversity Influence Financial Performance?" Sustainability 14, no. 10: 6186. https://doi.org/10.3390/su14106186

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