The effect of gender diversity on the financial performance of firms
in EU-19 countries
Abstract
This paper investigates the link between the percentage of female board directors and the financial performance of firms in the Eurozone (EU-19) countries. Tobin’s Q is applied to estimate the financial performance of firms. Using the unbalanced panel data of 974 listed firms during the period from 2005 to 2015 in EU-19 countries, this study confirms the positive role of board gender diversity on Tobin’s Q. Additionally, this paper shows that board gender diversity has no squared impact on Tobin’s Q, but a cubic association with Tobin’s Q. Furthermore, this study does not provide significant evidence that gender diversity has linear or curvilinear relations with return on investments (ROI) and return on assets (ROA).
Key words: Gender diversity, Financial performance, Board of directors
1. Introduction
In recent years, many scholars have devoted increasing attention to board gender diversity with the objective of enhancing equality in corporate governance. Veen and Marsman (2008) noted that commercial entities have intensified calls for diversity of boards. Although there has been an increasing trend of female directors appointed to boards recently, men still occupy a significant amount of the workforce (Torchia et al. 2008). In order to combat this imbalance, many developed nations, including some European countries, Australia and the United States, have focused governmental efforts on enhancing board diversity (Adams and Kirchmaier, 2016). One prime element of such efforts is through legislation. For example, the government of Australia conducted an affirmative action plan in 19861 in order to provide equal employment opportunities in corporations (Ali et al 2011). The equal employment opportunity regulations have promoted further hiring of females to manager companies, thereby improving gender diversity. Moreover, some European governments have implemented gender quota laws, which require a minimum proportion of women to be appointed to the boards of publicly listed firms or state-owned companies (Adams 2016; Terjesen al et 2008, Stary, K.2014). The government of Norway, for instance, implemented a gender quota in 2013 that necessitates at least 40% women to be appointed to the board of publicly listed companies (Stary, K. 2014).
As women gradually occupy an increasing percentage of boards, corporations face prominent changes in pools of potential candidates for high-ranking officer positions (Conyon & Mallin, 1997). Most researchers have focused considerable attention to gender diversity on boards. Harrison and Klein (2007) mentioned that the findings in terms of the relations between board gender diversity and organizations are still ambiguous in many empirical studies. A great majority of studies (such as Nekhili and Gatfaoui 2013; Carter 2003; Cartera 2007; Erhardt et al. 2003 and Francoeur and Labelle 2008) summarized that board gender diversity positively impacts the financial performance of firms. On the other hand, several other analysts (Bøhren et al 2007; Shrader, Blackburn, and Iles 1997; Smith and Verner 2006 and Adams and Ferreira 2004) have argued that a high ratio of women on a board has a negative relationship with the firm’s financial performance. Meanwhile, there also exist some studies that found a non-linear relationship between board gender diversity and firm performance. For example, according to critical mass theory, Joecks (2013) provided evidence of a U-shaped effect of board gender composition on the financial performance of firms; conversely, Frink et al. (2003) found an inverted U-shaped
relationship between these variables. Moreover, Gallego-Álvarez et al. (2010) indicated that gender diversity on boards has a cubic impact on return on equity (ROE) and net return on assets (ROAN) of a firm.
Due to the elusive nature of this relationship, this paper is based on the study by Ali al et. (2011), which indicated a positive linear and inverted U-shaped curvilinear relationship between organizational gender diversity and organizational performance, as well as a moderating effect of industry type. This paper aims to advance the line of research that investigates the impact of female boardroom representation on firms’ financial performance using various basic functional forms (such as the linear, quadratic and cubic function). This study particularly focuses on the EU-19 region during the period of 2005 to 2015. To accomplish the purpose of this study, three main research questions are presented:
1. What is the linear relationship between gender diversity and the financial performance of firms in EU-19?
2. What is the quadratic relationship between gender diversity and the financial performance of firms in EU-19?
3. What is the cubic relationship between gender diversity and the financial performance of firms in EU-19?
In order to answer these research questions, 974 publicly traded firms during the period of 2005 to 2015 are examined with an OLS (Ordinary Least Squares) in this study. In the market-based measurement (Tobin’s Q), we confirmed that the gender diversity has a positive-linear and cubic curvilinear relation with firm performance. Additionally, there is no evidence indicates that the square link exists between the gender diversity and firm performance. With accounting-based measurements (ROA and ROI), we found no relation between gender and performance.
which investigate and compare the influence of gender diversity in boardrooms on firm performance, as measured with various indicators.
The remainder of this paper is organized as follows. Prior theoretical and empirical research that is relevant to this paper is presented in Chapter 2. In Chapter 3, the specifications of the methodology, sample data, model and analysis are discussed. Next, in Chapter 4, the results of the research on the connection between gender diversity and financial performance of firms are presented. Chapter 5 summaries the main content and recommendations of this study, as well as implications and limitations.
2. Literature review and hypotheses proposed
This section further discusses the most relevant and widely accepted theories and empirical research by considering the relationship between board gender diversity and financial performance of firms. There are many empirical studies that have analyzed the relationship between the presence of women on the board and firm performance, and the results are mixed.
2.1 Linear relation of gender diversity with financial performance
With progress in social and economic development, more women are now appointed to higher positions in the workforce. Erhardt et al. (2003) found that gender diversity on executive boards in recent years has attracted widespread attention to the public policy and governance of business firms. In order to understand the theoretical foundations of the causal link between gender diversity in the boardroom and firm performance, the pluralistic approach is used in this study (Balasubramanian et. al, 2013). In addition, the resource dependence theory, agency theory, human capital theory and stakeholder theory are applied as they offer arguments to support the findings of positive effects of board gender diversity on firm performance.
have an influence on the firm’s performance and survival since they play an important role in the development of the corporate strategy (Chapple al et. 2014). Litz and Folker (2002) indicated that a board’s increased female human capital may add complementary capabilities and improve the balance and stability of the board. In this way, board diversity boosts the network of board members and helps the company to establish networks and links with other companies (Hermalin et al. 1991. Diversity also improves the company’s relationships with customers, suppliers, and competitors, and it may additionally extend the firm’s industry knowledge and improve its opportunity to obtain external financing (Julizaerma, and Sori 2012). Campbell and Minguez-Vera (2007) believed that the appointment of women to boards offers integrity and legitimacy to organizations such that they can improve their understanding of the markets; the authors also suggested that it helps to match the board directors’ diversity with their collaborators’ diversity. That is, gender diversity on the boardroom is able to promote further market penetration (Ingley and Van der Walt 2003, Carter et al., 2003). More broadly, board diversity enhances key resources that give rise to the stronger performance of an organization. Besides, the responsibilities of resource dependence are critical to gaining external capital for companies that do not enter capital markets (Voordeckers et al. 2007). For example, using the OLS regression method to test data from the Bursa Malaysia’s listed companies during the period from 2008 to 2009, Julizaerma (2012) examined the effect of gender diversity on firm performance; the results suggested that firm performance is affected by female directorship. De Cabo et al. (2012) investigated the characteristics of board gender diversity in 612 European banks from 20 European countries. They found that banks with larger boards and lower risk tend to have high percentages of females on their boards; the authors also suggested that banks show a growth orientation trend to increased gender difference on the board. Post and McQuillen (2015) used OLS regression to examine the lagged data that assert the firms' corporate social responsibility ratings mediate the relationship between the number of females on the board and the firm’s corporate reputation. Carter (2003) observed the diversity of boards has a positive relation with the firm’s value in the list of Fortune 1000 companies.
important role in optimizing corporate governance structures, thus the board can reduce the firm’s agency costs and advance its performance. The main role of the board is to monitor and manage suppliers, employees, customers and other shareholders; these responsibilities act as a key governance approach to help to coordinate the relationships between different interests in the organization (Fama and Jensen 1983). The board members not only have responsibilities to set executive compensation and oversee the CEOs of firms, but they also have an incentive to establish the organization’s reputation, which means the outside directors on the board will not conflict with insider board members to overthrow the interests of shareholders. Fama and Jensen (1983) also expressed the belief that board independence plays a significant role in the best interests of the shareowners. Consequently, it is important to analyze whether board diversity has an effect on board independence. One of the elements indicates that more diversity in the board improves board independence and renders it less likely to operate counter to the shareholders’ interests. In other words, a more heterogeneous board has better internal control since board diversity provides a wider range of views that help to monitor and protect the interest of shareholders. Moreover, various gender, cultural, ethnic and educational backgrounds among directors would result in different questions and new ideas and thus provide a better corporate structure. Since outside board members with non-traditional features are always considered outsiders by those with traditional backgrounds, a more diversified board could be more effective. Female leadership has shown attitudes of more openness to other shareholders, which provide potentially beneficial influences on both internal and external relationships of firms (Bruni et al. 2004.; Dobbin and Jung 2010). Consequently, gender diversity can be an important mechanism to decrease agency costs and thus raise the firm’s value (Hillman and Dalziel 2003). Studies on the appointment of women within Fortune 500 firms during the period of 2009 and 2013 found out that, on average, women held only one out of every seven executive positions in the workforce (Catalyst, 2014). Based on the agency theory, Francoeur and Sinclair (2008) found that a high ratio of females on a board adds a positive and significant influence to the abnormal return in the complex working environment in the listed Canadian firms. Chen et al. (2016) provided evidence that the gender diversity plays an important role in decreasing internal control weaknesses (ICWs) on corporate boards because women directors are better at monitoring and making risk aversion investments.
impact on the performance of the board because of the unique human capital of the diverse members. This theory supplements the conceptions of sex diversity on the board that stem from the theory of resource dependence, which indicates that board members should comprise people who provide more tangible resources in uncertain environments (Salancik and Pfeffer 1978). The human capital of females provides evidence that female capabilities are comparable to those of men in several key aspects such as education, knowledge and experiences (Terjesen et al., 2008). That is to say, due to uniqueness and diversity among humans, the theory of human capital suggests that board gender diversity effects firm performance. For instance, corporate board diversity not only leads to solving problems more effectively, but it also enhances the creativity and innovation of the firm (Robinson and Dechant 1997). Carter al et. (2003) indicated that board diversity of firms could create a broader perspective than firms with board homogeneity because boards, as a group, can be better acquainted with the complexity of their environment and make more accurate decisions.
the company’s financial performance. They examined the panel sample data of the Fortune 500 listed firms from 1998 to 2002, and they agreed that board composition differences contributed to increasing the shareholders’ value. Figure 1 provides an illustration of the positive effect between gender diversity and firm performance.
Figure1: The positive effect between gender diversity and firm performance Whereas prior theories seem to support a positive relationship between gender diversity and performance, there are also other theories that provide evidence of the aforementioned mixed results. Following social psychology theory, introducing greater board gender diversity may result in negative effects on firm performance. From the perspective of social psychology, people have strong personalities with varying manners of thinking, which may create equally variable impacts on group cooperation. As a result, individuals with independent personalities and manners of thinking or expressing emotion may create an unbalanced effect on team decisions. Considering this perspective, diversity can decrease team cohesion in the firm. Consequently, firms with greater board gender diversity may experience more conflicts and less cooperation or communication within their boards of directors; this possibility can give rise to poorer firm performance (Westphal and Milton 2000). Finally, Lau and Murninghan (1998) also pointed out the negative influences of greater board gender diversity on the decision-making of an organization since the diversity may consume more time and thus conclude in less effective group work. A previous paper by Shrader, Blackburn and Iles (1997) found a significantly negative consequence on the ROE and ROA of Fortune 500 firms when they appointed a large number of women to the board. Adams and Ferreira (2004) asserted that a greater percentage of female board members has a negative effect on both ROA and Tobin's Q of large companies in US between 1996 and 2003.
In addition, social identity and self-categorization theories imply that board diversity can produce disadvantages to firms. Following these theories, people are more likely to feel accepting toward others who occupy the same social categories, and gender is an important part of self-categorization (Reed 2002.; Ashforth and Mael 1989; Mannix; Neale 2005). Bøhren et al. (2007) investigated the idea that board composition leads to poorer performance, and this research used a sample that included all non-financial Thailand listed firms during the period of 1989 to 2002. Smith and Verner (2006) used panel data of firms in Denmark. They concluded that there exists a negative relationship between the ratio of females among directors in the board and firm performance.
In brief, females have higher levels of organizational commitment and more difficulties in exercising their responsibility. Women occupy an important place on boards through their tendency to pay more attention to implementing the enterprises' development strategies and plan further improvement to the value of companies. That is to say that gender heterogeneity can enhance creativity and decision-making, which can lead to advanced firm performance. On the other hand, theories based on social psychology, social identity and self-categorization suggest that sex differences on the board may have a negative impact on firm performance. All in all, although some of the above theories suggest a negative relationship between gender diversity and firm performance, we suggest that the empirical literature that supports a positive effect is stronger. For this reason, this study proposes the first hypothesis:
!": The percentage of female board directors of firms is positively related to the financial performance of firms in the EU-19 countries.
2.2 Non-linear relationship
From the above discussion, it can be seen that there are positive effects to be expected in the relation between increased gender diversity and firm performance. Additionally, several theories are presented to illustrate the possible non-linear gender-performance relationships. The integration of the different theories supplies the basic principle for the existence of the non-linear connection between gender diversity and firm performance.
2.2.1 Quadratic relationship
Figure2: The inverted U-shaped effect between gender diversity and firm performance In establishing the theory of critical mass, Kanter (1977a, 1977b) constructed four different categories of group composition: uniform groups, skewed groups, tilted groups and balanced groups. Uniform groups are those in which all members have the same gender, such as a situation in which all board directors are either men or women (male or all-female group). Skewed groups, in Kanter’s research, are male-dominated groups, which is when the majority of men influences the lower number of women (around 20%) in an organization. Compared to the extreme distribution of the former group, tilted groups represent a subgroup in which members have individual skills and expertise; they are a minority group that impacts the majority in the organization. Kanter (1977a) defined that a male-dominated titled group is composed of about 20% to 40% females. Finally, the balanced groups (around 40 to 60% female) do not focus on gender diversity; rather, they are concerned with the different skills and abilities of the females and males in the organization. From the resource-based view, the skewed groups (20% gender diversity) produce positive effects to firm performance. The low level of women on the board offers the benefits of problem-solving or enlarged market insight. The firm performance continues to increase from the low ranges of gender diversity to mid-range gender diversity. For instance, when the ratios of age or racial diversity in the group are around 11% to 30%, an optimal relationship between group diversity and group effectiveness is achieved (Knouse and Dansby 1999). Additionally, from the psychological view, the tilted groups (40% gender diversity) may result in bad performance for the company. Blau (1977a, b) found that higher percentages of women appointed to the company decreases communication in the group (Kravitz et al. 2003) and increases conflict with employees (Pelled 1996). As a result, mid-level gender diversity may lead to negative outcomes. For example, if the age or racial diversity is higher than 30% of the members, group
effectiveness is perceived as weak (Knouse and Dansby 1999). For this reason, gender diversity has a negative effect on performance when the number of the women is over the optimal ratio because of the weakness in the self-categorization and social identity theories beyond the resource-based theory. When there are balanced proportions of gender (balanced groups) in the boardroom, gender may exacerbate the weakness influence on the firm’s performance. For instance, Blalock (1967) observed that the majority (men) may feel threatened by an increasing number of the minority (women) and then create unhealthy competition among employees. The increased cutthroat competition leads to lower value of the firms. Consequently, Nakagawa (2015) argued that, with managerial gender diversity at a low to medium level, resource dependency theory can better predict firm performance than the social identity and self-categorization theories. In this way, the levels of gender diversity on the board from low to medium have a positive impact on firm performance, whereas the social identity and self-categorization theories are better at making this prediction than the theory of resource dependency when gender diversity is at a medium to high level. Therefore, at the medium to high level, gender diversity has a negative effect on firm performance (Richard and Shelor 2002).
Additionally, there is empirical literature to support the inverted U-shaped relationship between the ratio of women on the board and the financial performance of firm. For instance, Ali et al. (2001) predicted variables of gender diversity 2002 and gender diversity 2005 in Australia companies and found an inverted U-shaped connection between gender diversity management and firm performance. Litz and Folker (2002) cited that more than a 40% share of females in a management group has a positive effect on the marginal profits of corporate. Richard and Shelor (2002) uncovered an inverted U-shaped relationship between managerial gender diversity and employee productivity in high leverage companies. Similarly, Frink et al. (2003) provided evidence that gender composition has an inverted U-shaped relationship with an equal proportion of men and women and the organizational performance of a firm.
Based on these empirical studies, the second hypothesis of this paper can be established as follows:
2.2.2 Cubic relationship
In recent years, some economic and business research has explored the cubic relationship between variables. In addition to the cubic relationship, the polynomial relationship also exists. In other words, the polynomial relationship includes more than one type of relationship (linear, quadratic and cubic) in the functional form (Delsing et al. 2001). Suggesting the functional equation is $ % = '%(+ *%#+ +% + , (' ≠ 0) , and the
slope of the x function is $′ % = 3'%# + 2*% + +. The cubic relationship exists when
' ≠ 0, * = + = 0. The polynomial relationship exists when the coefficient A, B and C at least two are not equal to zero.
Figure 3 reflects several trends in the cubic relationship (part A of figure 3), which are briefly explained. The left interval U-shape can be interpreted by the integration of the theories of resources dependence and self-categorization. In this part of Figure 3, performance increases from a low percentage of women (skewed groups) to the middle range of the proportion of females (tilted groups). After the ratio of the women appointed to the board reaches a certain point, there is a downward trend of firm performance as the proportion of women on the board continues to grow. In other words, the groups with balanced gender representation perform badly, likely because the balanced ratio may lead to poor communication and increased conflict among the group members in the organizations (Kravitz 2003). However, in the remaining part of Figure 3 (part b), firm performance shows a steady increase when the gender representation of the balanced group changes to either a tilted or skewed group. The reason for this trend is that as the proportion of women becomes the majority (skewed group become the female-dominated group), higher company performance may result.
A< 0
For instance, Fenwick et al. (2001) observed that more effective performance occurs when the number of females exceeds the number of males because women are better at dealing with for the information management and processing, and they show more aptitude for planning in complex management environments in the long term. Based on the theory of social psychology by Brewer (1991), Gallego-Álvarez et al. (2010) found that there is a cubic relationship between gender diversity and firm performance, such that when individuals are a part of a group, then they need to differentiate themselves from others in a group. If individuals feel the environment is balanced, they feel more satisfaction and work with more motivation. A balanced ratio of gender diversity is related to positive performance, while an imbalanced ratio, such as a very high or very low percentage of managerial gender diversity, more likely results in negative performance. The authors asserted that females contribute more to performance compared to men with similar academic backgrounds and working environments in male-dominated sectors. In addition, the authors provided evidence that a balanced proportion or moderately higher representation of women on boards are associated with more positive performance of the firms. They also offered evidence that sex diversity has a cubic impact on the return on sales (ROS) and net return on assets (ROAN), but there is no significant link between sex difference and the variables of ROA, ROE and gross margin (GM). Finally, the third hypothesis can be established as follows:
H(: The percentage of female board directors of firm has a polynomial relationship to the financial performance of firms in the EU-19 countries.
3. Data and Methodology 3.1 Research context
Rather than comparative research that only investigates a single country, this research focuses on multiple countries for a broader scope. The selected sample is firms from the EU-19 countries, which are as follows: Austria, Belgium, Cyprus, Lithuania, Luxembourg, France, Germany, Italy, Spain, Latvia, Slovakia, the Netherlands, Slovenia, Estonia, Finland, Greece, Malta, Portugal and Ireland. The chosen period of investigation is between 2005 and 2015.
Strid 2012). Some EU countries have set quotas for a minimum proportion of women appointed to the boards of publicly listed firms or state-owned companies (The Global Gender Gap Report 2013). For example, according to Coyer (2017), the average percentage of women’s representation on boards increased by 11.9% in 2010, and female board representation is about 23.3% on the boards of the largest European public traded firms in 2016. However, companies in EU countries still have not achieved a gender balance. As can be seen in Appendix A, some European countries already had a quota for gender diversity targets in firms. For example, countries such as France and Spain have adopted the Norway model, which is a policy that requires at least 40% of board directors in publicly traded or state-owned firms are female, and these two countries reached 37.1% and 20.2% female boardroom representation in 2016, respectively. Italy set a quota that requires reaching 33% gender diversity on the board of listed firms and state-owned firms in 2015. Italy reported that 30% of board positions were held by females in 2016, and the country had the largest ratio appointed female board members of the EU-19 countries in 2016. Conversely, Malta has the lowest percentage of the women board directors in the EU-19 countries, which equaled around 5% in 2016, and the country does not have a gender quota (European Commission).
This research is concerned with the EU-19 countries due to their similar economic conditions and use of the same currency. This consistency ensures that the comparison of their financial performance is not influenced by an exchange rate. In addition, the sample data from 2005 to 2015 was selected for the purpose of controlling for the market changes that may affect the diversity of boards.
3.2 Data and sample
603 companies were removed because of a lack of ISIN codes2. After adjustment, there were 974 available firms in the sample.
Table 1 Summary of sample selection Panel A: Firms’ selection
1. Total number of firms in Board Ex 1585 2. Less: firms without complete board
information and ISIN number
603 3. Total number of available companies 974 4. Less: without complete financial data 113
5. Total number of firms 861
6. Total number of firm-year observations 9,468 Panel B: Category industry types
1. Manufacturing industry firms 379
2. Service industry firm 482
3. Total number of firms 861
In order to test the effect of industry on the relationship between gender diversity and firm performance, the sample was classified to the manufacturing and service industries. For this reason, the industry type data were also collected from the Board EX database, which uses Standard Industrial Classification (SIC) codes for categorization. Firms in the manufacturing industry have SIC codes less than 4000, and the service industry is assigned SIC codes from 4000 to 8999. There was a total of 379 firms in the manufacturing operations and 482 firms in the services operations (see Panel B in Table 3). In sum, after screening, there were around 7,468 total observations in this study.
Table 2 Country sample distribution
Country Number of companies Percentage of total number of companies Austria 55 5.59% Belgium 81 8.23% Cyprus 17 1.73% France 249 25.30% Finland 53 5.39% Germany 207 21.04% Greece 11 1.12% Italy 100 10.16% Lithuania 1 0.10% Luxembourg 9 0.91% Malta 1 0.10% Netherlands 82 8.33%
Slovenia 1 0.10%
Portugal 30 3.05%
Spain 87 8.84%
Total 974 100%
Table 2 shows the detailed distribution of the sample country selection. France and Germany have the largest and second largest percentages of firms included in the sample, which are 25.3% and 21.04%, respectively. On the contrary, Malta, Slovenia and Lithuania have the lowest ratio and all three make up 0.1% of the sample data.
3.3 Variables estimation
Dependent variable
In the previous research by Shah and Nageswara (2014), financial performance was measured by added economic value and added market value, while Siantar (2011) used return on assets as a measure for financial performance of companies. In addition, some prior studies used Tobin’s Q to measure a firm’s financial performance (Campbell and Minguez-Vera, 2007; Reguera- Alvarado et al. 2017 and Gordini and Elisa 2017). Wernerfelt and Montgomery (1988) suggested that Tobin’s Q represents a forecast of future earnings in the market and that it is a suitable proxy for competitive advantage of the companies. It is for this reason that this research also adopted Tobin’s Q to measure the financial performance of firms.Tobin’s Q is used to measure the financial performance of companies that is defined as the sum of the stock’s market value and the debt’s book value scaled by the total assets (Campbell and Minguez-Vera, 2007). In this paper, firm performance is measured by a simple Tobin’s Q, which was calculated by Chung and Pruitt (1994). The ratio is measured by the market value of its outstanding stock and debt scaled by the total assets of firms. Equity market value on DataStream is calculated as the issue of ordinary shares multiplied by the stock price. The formula is as follows:
5obin′s ; = Market BCDEF FGEHIJ
5otal assets
gender in investment strategy (Dobbin, 2011), this study uses the ROI as a proxy to research the association between financial performance and sex difference. The formula for ROI is as follows:
LMN = OFI HPQRSF +apital investment
Furthermore, this study also uses ROA as another indicator to measure the financial performance of a firm (robustness test), which is consistent with prior researchers such as Farrell and Hersch (2005), Erhardt et al. (2003) and Shrader et al. (1997). The ROA is measured as the net operating income divided by the total assets (Delen, 2013). Past studies have given evidence that ROA is linked to firm performance; for example, Farrell and Hersch (2005) found that firms with more females appointed to top jobs are more likely to have stronger ROAs. Erhardt et al. (2003) investigated 117 companies in the Fortune 1000 and found that sex diversity had positive and significant relations with the ROE and ROA in 1998. The formula for ROA is as follows:
LM' =OFI RWFXCIHPY HPQSF 5oICD CZZFIZ
Independent variables
The main independent variable in this paper is the ratio of women directors present in the boardroom of firms. Based on the paper by Liu et al. (2014), the first proxy (Pfemale) is applied, which is the ratio of females in the boardroom, and it is determined by dividing the total number of female directors on the board by the total number of board directors.
Control variables
decision-making and poor communication (Guest, P. M. 2009). In this study, the board size measure is the nature logarithm of the total number of directors sitting on the board. In addition, multiple studies provided evidence that firm size has a causal relationship with firm performance. Firm size is approximated by the nature logarithm of the total number of firm employees. Pfeffer and Salancik (1978) found that larger-scale firms with more centralized market power can more easily obtain outside resources than smaller-sized firms. Terjesen and Singh (2008) assumed that larger firms have are visible to the public, which is likely to affect the performance of the firm; for this reason, this study controls for firm size. Moreover, Barnett and Salomon (2012) found that a company’s debt effects the value of the firm. Cohen and Wang (2013) indicated that high leverage companies have an impact on the boards. Loderer and Waelchli (2010) thought that the leverage of the firm is connected with firm performance because it enhances the costs of financial distress and decreases the agency costs of an organization. As a result, there are many studies that use leverage as a control variable to measure financial risk (e.g., Nollet et al. 2016). Chen et al. (2014) indicated that leverage can be calculated as the nature logarithm of total debt scaled by the total assets. To control for market risk, the market-to-book ratio was applied in this study, which is estimated as the market value divided by the book value. Finally, following prior literature (Richard 2013; Bonn 2004), market capitalization and sales growth were used as proxy variables to control for market performance, which tests the causality between the percentage of women board members and firm performance. Market capitalization is estimated as a natural logarithm of the market value of the outstanding shares of a firm, and sale growth is measured as the average sales growth over the prior five fiscal years (Bonn 2004).
industry (SIC codes less than 4000) and 0 if it is the service industry (SIC code 4000 to 8999).
3.4 Model
To test the linear relationship between women on the board of directors and firm financial performance (!"), the following two statistical regression models were used:
Model 1: [HXS WFX$RXSCPQF\] = ^\]+ _"W$FSCDF + _#`\]+ a\]
In the regression model, financial performance is the dependent variable that is measured by Tobin’s Q, ROI and ROA. The independent variables in this study are Pfemale, Sfemale and Cfemale. The percentage of women appointed to the board is represented by Pwomen, whereas Sfemale is the square of Pfemale, which is calculated as the square of the difference between Pfemale and the mean of Pfemale. Cfemale represents the cube of Pfemale that is measured as the cube of different value.
Here, β1 in both models is the parameter of interest. The vector of control variables is
denoted by Xit, and this may affect the financial value of firms including firm size, board size, market-to-book ratio, leverage, market capitalization and sales growth. Finally, in the model, ε is relative to the error term for indexes of firm i and indexes of time t.
To test the second hypothesis, we used model 2,
Model 2: [HXS WFX$RXSCPQF\] = ^\] + _"W[FSCDF + _#(W[FSCDF)\]#+ _(`\]+ a\] To test the third hypothesis, we used model 3,
Model 3: [HXS WFX$RXSCPQF\] = ^\]+ _"W[FSCDF + _#(W[FSCDF)#+ _((W[FSCDF)(+
_b`\]+ a\]
In accordance with the paper of Gallego-Álvarez et al. (2010), the inflection points, in relation to Model 3, can be estimated as c" CPd c#, which indicates the change of influence
of the different gender diversity ratios; the calculation used the following equations: c" = ef
c# =h#βg± bβg
gh"#β fβj
kβj (2)
3.5 Analysis method
Firstly, in order to test the non-linear relations between gender diversity and firm performance, the variables of the ratio of women on the board (Pfemale), square of gender diversity (Sfemale) and cube of gender diversity (Cfemale) were added to the regression model. However, introduction of the square of Pfemale and the cube of Pfemale in the same regression model would result in a multicollinearity problem. Based on the methods of Kwak et al. (2010), we implemented a process that is known as centering to reduce the problem of multicollinearity. Dalal and Zickar (2012) also found that mean-centering could reduce nonessential collinearity and ill-conditioning of the data without changing the fit of the regression models.
On the other hand, for the purpose of further testing for potential multicollinearity, the variance inflation factors (VIF) test is examined in this study. In addition, the process of centering can be used to reduce the multicollinearity problem. First, we calculated the centered values of Pfemale by subtracting the mean values of Pfemale from the observes valued of Pfemale. In order to calculate the squared values of Pfemale, we squared the centered values. Moreover, for purpose of calculating the cubic values, we cubic of centered values of Pfemale.
Moreover, the study used unbalanced panel data in the regression to test the hypotheses. Based on the methodology of Gallego-Álvarez et al. (2010), this research included the Hausman test to distinguish between random effects and fixed effects, and it also served to help determine which effects model is suitable for this study. The null hypothesis of the Hausman test was that random effect is more suitable due to its higher efficiency, while the alternative hypothesis was that the fixed effect is at least as effective as random effects, thus the fixed effect is suitable.
4.Results
4.1 Data statistics
Table 3 shows the number of observations, mean, median, maximum, minimum and standard deviations for the independent variables, dependence variables and control variables. Table 3 shows that the mean of Pfemale (percentage of women on the board) is 0.12. In addition, the mean of Tobin’s Q is 0.78, which means that the worth of companies is less than the cost of the firm’s assets. On the other hand, regarding the control variables, the mean of LNBOARD is 2.34, the maximum is 3.53 and minimum is 0. The LNBOARD is the natural logarithm of the total number of a board, which means the average size of the sample boards is around 11 people, the maximum is 34 and the minimum size is 1. These results are in line with the work of Reguera-Alvarado (2017).
Table 3: Summary of sample statistics in this research
N Mean Median Maximum Minimum Std. Dev.
PFEMALE 7968 0.12 0.10 0.50 0.00 0.12 SQUARE 7968 0.01 0.01 0.15 0.00 0.02 CUBIC 7968 0.00 (0.00) 0.06 (0.00) 0.01 TOBIN_SQ 8665 0.78 0.53 19.96 0.00 1.00 ROA 8665 4.17 4.35 142.47 (160.68) 10.44 ROI 8665 6.48 6.86 1389.30 (3367.32) 49.94 LEVERAGE 8658 26.39 24.48 927.78 0.00 22.03 LNMC 8629 13.74 13.68 19.70 6.90 1.88 MTB 8556 2.34 1.49 1683.87 (181.25) 20.26 LNBOARD 7968 2.34 2.30 3.53 0.00 0.45 LNFIRM 8389 8.22 8.29 13.32 0.00 2.15 SALEGROWT 8414 7.79 5.30 985.85 (100.00) 25.52 D_INDUSTRY 8656 0.33 0.00 1.00 0.00 0.47
Note: Pfemale is the percentage of females centered in the boardroom, so this variable measures gender
Based on the research by Liu et al. (2014), the multicollinearity problem could be relevant in a regression when the correlation value (absolute value) between the variables is above 0.7 (see Table 4). However, all of the variables used in the regression model have absolute correlation values less than 0.7. In addition, the results of the VIF test (see Appendix D) show that all of the VIF values were less than 10, thus it can be concluded that the multicollinearity does not exist in this research.
4.2 Fixed effect vs random effect
From Appendix F, it can be determined that the result of the Hausman test, which showed the p-value is equal to 0, is significant. As a result, the null hypothesis of the Hausman test is that the fixed and random effect models do not differ significantly from each other. The significant result reflects that the null hypothesis is rejected, which means the fixed effects model is more suitable for this study. Carter et al. (2010) pointed out the importance of using fixed effects in research because they not only contribute to deal with the change of time that has not as yet been observed, but they also decrease omitted variable bias. Adams and Ferreira (2009) found significant results through using the fixed effect in their research.
4.3 The relation between the board gender diversity and Tobin's Q.
Table 5 indicates the OLS regression results with fixed effects from the three different models. From Table 5, we cannot reject the hypothesis of the positive impact of percentage of female board directors on financial performance of firms (H1). Since we found a weak
Table 4: Correlation matrix
Probability Pfemale D_industry Tobins’q ROA ROI Leverage Lnboard Lnfirm Lnmc MTB Salegrowth
Pfemale 1 --- D_industry 0.109394 1 0 --- TOBIN_SQ -0.00656 0.071328 1 0.57 (0) --- ROA 0.012657 0.016257 0.223263 1 0.27 (0) (0) --- ROI 0.005511 0.002412 0.024951 0.4661 1 0.63 (0.835) (0.0311) (0) --- Leverage -0.01763 -0.037098 -0.157304 -0.264 -0.186 1 0.12 (0.0014) (0) (0) (0) --- LNBOARD 0.003483 -0.004926 -0.165818 0.0139 0.0341 0.039224 1 0.76 (0.6706) (0) (0.227) (0.003) (0.0007) --- LNfirm 0.110892 0.082288 -0.135767 0.0945 0.0576 -0.049955 0.436214 1 0 0 0 0 0 0 0 --- LNMC 0.129407 0.060458 0.010083 0.2383 0.0909 -0.018668 0.512907 0.657135 1 0 0 0.38 0 0 0.106 0 0 --- MTB -0.00261 0.014532 0.209562 -0.021 -0.005 0.003177 -0.01922 -0.01706 0.0063 1 (0.8215) (0.2095) (0) (0.066) (0.644) (0.7838) (0.0968) (0.14) (0.586) --- Salegrowth -0.10329 -0.042801 0.104851 0.1045 0.0348 -0.010812 -0.01893 -0.04074 0.0358 0.185 1 (0) (0.0002) (0) (0) (0.002) (0.3504) (0.102) (0.0004) (0.002) (0) ---
Total observation number is 7468. Notes: This table shows the correlation relationship among each variables. P Pfemale is the percentage of females centered in
Table5: OLS - the relation between the board gender diversity and Tobin’s Q.
Model 1 Model 2 Model 3
Variables β β β Constant -0.05511 -0.04571 -0.115493 Pfemale 0.167988* 0.208086* 0.392799*** Sfemale -0.376755 2.540834*** Cfemale -11.59391*** LNboard -0.266046 -0.269667 -0.261769 LNfirm -0.147061 -0.147157 -0.147854 LNMC 0.189515 0.189545 0.19042 MTB 0.001539 0.001533 0.001532 Leverage 0.000424 0.00042 0.000416 Salegrowth 0.000783 0.000797 0.000774
D-industry yes yes yes
D-Country yes yes yes
R-squared 0.75216 0.752179 0.752559
Adjusted "# 0.717203 0.717181 0.717572
F-statistic 21.51693*** 21.4925*** 21.50981***
Observations 7468 7468 7468
Note: This table shows the linear relationship between Tobin’s Q and Pfemale, Sfemale and Cfemale. Pfemale is the percentage of females in the boardroom, so this variable measures gender diversity; square is the squared centered value of Pfemale. (centered value measures by subtracting the mean values of Pfemale from the observed values of Pfemale). Cubic refers to the cubic centered value of Pfemale. D-industry is the dummy of the industry, which equals zero for the services operations and equals 1 for the manufacturing industry. The control variable of LNMC is the market capitalization; MTB is market-to-book value; leverage is total debt to total asset that is used to measure the risk of a firm; LNFirm is the natural logarithm of the total number of staff members of firms; LNBoard is the natural logarithm of the total number of board directors; Salegrowth is the average of the growth sales of firms in the past five years; ROA is the return on assets of a company; D-Country is the dummy of the EU-19 country that, when equal to yes, means that there is effect in each country, or otherwise it is no and *, **, *** show that the statistical significance level is at p < 0.1, p < 0.05 and p < 0.01, respectively. Hypothesis 2 proposed that rate of female directors in the boardroom has an inverted U-shaped curvilinear relation with Tobin’s Q in the EU-19 countries. The result of Model 2 in Table 5 shows the weak negative impacts of the percentage of women on Tobin’s Q, which has a significant influence at 10%. On the other hand, regarding the quadratic equation, the results show that the sign of the coefficient is negative (β2 =
quadratic equation (p > 0.1), thus hypothesis 2 is rejected. This rejection means that the ratio of women present on the board has no quadratic relation with Tobin’s Q.
Cubic analyses of the relationship between gender diversity and Tobin’s Q are shown in Table 7 (model 3). The results indicate that the β coefficient for the cubic term was negative and significant (β3 = -11.59391, p < 0.01), which means the relationship
between gender diversity and financial performance of a firm is polynomial curvilinear. Based on the results, hypothesis 3, which states that the ratio of female directors in the boardroom of a firm has a polynomial impact on the firm’s performance, can be verified; the trend first increases, then decreases and finally increases again. Moreover, it can be found that the β weight for the linear term and quadratic term of gender diversity are both positive and significant (β2 = 2.540834, p < 0.01; β1 = 0.392799, p < 0.01).
According to the calculated equations (1) and (2), the cut-off points in the figure are 8% and 17%. That is to say, the value of Tobin’s Q increases as the percentage of female board member increases, and this relationship reaches its peak at 8% female representation. Then, the figure maintains a decreasing trend of financial performance and reaches the lowest point when gender diversity is around 17% of the firm. Finally, the remaining part of this trend trends upwardly with the continually increasing percentage of women present on the board. Consequently, hypothesis 3 is supported in this research.
4.4 Robustness checks
In order to check the robustness of the results, this research used alternative variables (ROI and ROA) to measure financial performance of the firms. Furthermore, this study applied a model without control variables to determine whether endogeneity exists among variables.
Table 6: OLS regression analyses- the relation between the board gender diversity and ROA and ROI
Model 1 Model 2 Model 3
Variables ROA ROI ROA ROI ROA ROI
Salegrowth 0.038715 0.07929 0.038628 0.077373 0.038608 0.076429
D-industry yes yes yes yes yes yes
D-Country yes yes yes yes yes yes
R-squared 0.560983 0.229217 0.560991 0.229367 0.560994 0.229617
Adjusted "# 0.499062 0.120502 0.498994 0.120538 0.498921 0.120689
F-statistic 9.0596*** 2.108*** 9.0487*** 2.107*** 9.03766*** 2.1079***
Observations 7968 7468 7468 7468 7468 7468
Note: This table shows the relationship between ROA and Pfemale, Sfemale and Cfemale. Pfemale is the percentage of females centered in the boardroom, so this variable measures gender diversity; square is the squared centered value of Pfemale. (centered value measures by subtracting the mean values of Pfemale from the observed values of Pfemale). Cubic refers to the cubic centered value of Pfemale. D-industry is the dummy of the D-industry, which is equal to zero when the firm is in services operations and equal to one when the firm is in the manufacturing industry. Market Capitalization is LNMC; MTB is market-to-book value; leverage is total debt to total asset, which is used to measure the risk of firm; LNfirm is the natural logarithmic function of the total number of staff members in the firms; LNBOARD is the natural logarithm of the total number of board directors, Salegrowth is the average growth of sales of firms in the prior five years and *, **, *** show that the statistical significant level is at p < 0.1, p < 0.05 and p < 0.01, respectively.
Table 6 indicates the relationship between the ratio of female directors on the boardroom and ROA. Gender diversity has a positive impact on firm performance (ROA), but the result is not significant (β = 0.807917, p > 0.1%). This result is line with some prior analyses (Haslam et al. 2010; Miller and Triana 2009). At the same, with linear relations, a significant result of the square and cubic relations between gender diversity and ROA was also not found.
To further check the robustness, we used ROI as another measurement of financial performance. The results also do not provide significant evidence of a negative connection between sex differences and ROI (β = -1.412912, p > 0.1%). Similar to the findings of ROA, from Model 2 in Table 7, the result of ROI indicates a positive and not significant result, which reveals that there does not exist a square association between the proportion of women present on the board and ROI (β2 = 53.21929, p >
0.1). Furthermore, no significant results were found in the cubic relationship between gender diversity and ROI. This finding is consistent with our own (previous) results of financial performance measured by Tobin’s Q. However, the paper of Gallego-Alvarez et al. (2010) did not find significant result in ROI.
hypotheses 1 and hypotheses 3 are supported by Tobin’s Q, while hypotheses 1 and hypotheses 3 are not verified by ROA and ROI. Hypothesis 2 is thus rejected in this study.
Moreover, Bhagat and Black (2001) pointed out that board composition may influence firm performance. However, firm performance may also affect the composition of the board. Based on Hermalin and Weisbach (2003), the gender-performance relationship may be triggered by endogeneity. To check whether for the existence of endogeneity, this study used the model in which all of the control variables are excluded from the regression. Table 8 shows the same relationship outcomes as Table 5 (including all of the control variables), which means Tobin’s Q is not caused by endogeneity in this study. Table 8- OLS regression analyses without control variables –Gender-Tobin’s Q relationships
Model 1 Model 2 Model 3
Variables β β β Constant 0.727951 0.728171 0.683174 Pfemale 0.361937*** 0.377157*** 0.562475*** Sfemale -0.144193 2.718792** Cfemale -11.37915*** R-squared 0.719384 0.719387 0.719745 Adjusted "# 0.681982 0.68194 0.6823 F-statistic 19.2338*** 19.21077*** 19.22166*** Observations 7468 7468 7468
Note: This table shows the connection between Tobin’s Q and Pfemale, Sfemale and Cfemale without control variables.Pfemale is the percentage of females centered in the boardroom, so this variable measures gender diversity; square is the squared centered value of Pfemale. (centered value measures by subtracting the mean values of Pfemale from the observed values of Pfemale). Cubic refers to the cubic centered value of Pfemale. and *, **, *** show that the statistical significance level is at p < 0.1, p < 0.05 and p < 0.01, respectively.
5.Conclusion implications and limitations
This research relates to previous analyses by Ali al et. (2011), who offered the hypothesis that gender diversity in organizations has a linear (positive and negative) and curvilinear interval U-shaped relation with firm performance. Based on these hypotheses, the present study improves the field of research that investigates the cubic effect of women’s representation on firm performance. The sample of public companies in 19 Eurozone countries from 2005 to 2015 was used to estimate the OLS regression. In addition, the control variables used in this research were board size, return on assets, firm size, leverage, market-to-book ratio, market capitalization and sales growth. In order to address potential endogeneity issues, the fixed effects model was also used in this research.
Firstly, the findings of the fixed effect of OLS regression indicates that the ratio of women in the boardroom has a positive and significant impact on Tobin’s Q. On the other hand, however, this research did not find any significant results of a linear effect of sex diversity on either ROA and ROI. This finding can be explained by the theory of resources dependence (Gabrielsson and Huse 2004; Campbell & Minguez-Vera 2007). A higher proportion of females on the board enhances the market penetration rate since it improves the firm’s knowledge of the markets (Campbell, 2008). Meanwhile, the agency theory (Core et al. 2006) and stakeholder theory (Berman et al 1999) also suggest that the greater numbers of female directors could provide unique ideas and experiences, thus increasing the firm value when they are present at the board meetings. These results are consistent with the prior analysis by De Cabo et al. (2012), Erhardt et al (2003), Carter (2003), Chen et al. (2016), Francoeur and Labelle (2008) and Cartera (2007). Female directors increase firm value because they contribute novel and unique ideas and experiences during their tenures on boards. Moreover, firms with greater board gender diversity may experience increased market penetrability because the diversity of leadership matches the diversity of the firms’ shareholders. Consequently, according to the results of this research, companies can clearly increase the proportion of females on their boards in order to create more value for the firms. Secondly, the result of the quadratic relationship between the percentage of women appointed to the board and firm performance are not significant. These findings are line with the research by Ali et al. (2011), which also found no interaction effect on the inverted U-shaped connection between board gender diversity in 2005 and employee productivity in 2007. This outcome is line with the results of the robustness test, which measure firm performance using ROA and ROI.
Huse (2004) and the self-categorization theory by (Westphal and Milton 2000), the results for the cubic relationship between gender differences and Tobin’s Q are significant. On the contrary, the other two indicators of ROA and ROI did not offer a significant result, which means gender difference does not have a cubic relation with ROA and ROI. Consequently, hypothesis 3 is not entirely supported. This finding was outlined in a previous study, which offered the argument for a cubic connection between the proportion of female directors and ROAN and ROS (Gallego-Álvarez et al.2010). As suggested by the findings of this study, companies with low levels of gender diversity may experience increased firm performance because the few number of female directors added to the boardroom provides the new perspectives and knowledge on problem-solving, according to the resource-based theory. In addition, as the ratio of the women on the board increases, the firm performance decreases. Different styles, arguments, behaviors and attitudes in a team may create conflicts among the directors on the board and also decrease coordination and communication, whereas when the percentage of females reaches a tilted group or balanced group, the comparatively higher gender diversity may enhance work efficiency through better time management habits and cautious attitudes in long-term investments.
Firstly, this study expands the existing theoretical framework by investigating curvilinear relationship between gender diversity and firm performance. Many scholars have focused on a linear (positive or negative) diversity-performance relationship and squared relations, which have already been tested by Joecks (2013), Roberson (2006) and Richard al et (2004). However, there is still a lack of empirical analyses of theories in the curvilinear relationship. This is the first investigation in which the cubic relation between gender diversity and firm performance in different industries has been examined. This research emphasizes the complexity of the relationship between diversity and financial performance and the inflection points at which female directors present on the board may cause positive or negative effects on the performance of firms. The findings suggest that firms with gender diversity among directors might be required to the differently manage their operations in order to fully experience the advantages of gender diversity. In other word, this study indicates that an effective board composition should have the optimal diversity percentage on the board for the particular environment. Compared to requiring increased representation of women in the boardroom, selecting and matching a reasonable percentage of female directors for the board can bring better performance of firms.
This recommendation is advised for those countries without this awareness of the important of recruiting a diverse workforce so that they may establish quotas to ensure a minimum percentage of women on the board of firms.
This study is subjected to several limitations. Firstly, the sample selection could be biased by including financial firms and utility firms because these firms might be subjected to special regulatory supervision. Simultaneously, the sample range start from 2005 to 2015, which means the results might be potentially influenced by the global financial crisis. Therefore, future researches should pay an attention to the impact of financial crisis. Secondly, the construction of Tobin’s Q is learned from Chung and Pruitt (1994). An advanced measure of Tobin’s Q could be achieved by incorporating both firm-specific factors and country-specific factors into construction. This could be the potential reason for the inconsistent results of the robustness test by using alternative measures of firm performance (ROA and ROI). Thirdly, this study applied OLS regression to test the diversity-performance relationships. Hermalin and Weisbach (1991) argued that there exists endogeneity between board composition and firm performance. Gujarati (2009) suggested that instrumental variables methods or Two-Stage least squares are better approaches than OLS to check the endogeneity problem in a study. Consequently, the future research should find a better methodology to improve the accuracy of this test.
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