Board Gender Diversity and Firm Performance: The Effect of National Culture

Written by

A.A.J. Scheppink S2354306 (UoG)

T-271 (UU)

January 12th, 2018

Supervisor: prof. dr. C.L.M. Hermes Co-Assessor: dr. V. Purice

MSc International Financial

Management MSc Business and Economics

Faculty of Economics and Business Department of Business studies University of Groningen Uppsala University

Abstract This paper examines the moderating effect of national culture on the relationship between board gender diversity and corporate financial performance. To test the hypotheses, Fixed Effects regression is used in combination with a sample of 1,499 firms from 23 countries and 7,125 firm-year observations over a time frame of seven years. This paper provides evidence for a significant positive effect of board gender diversity on firm performance if there are at least three females seated on the board. Furthermore, a significant moderating effect of national culture on the relationship between board gender diversity and firm performance has been found. Keywords: Board gender diversity, firm performance, national culture, corporate governance, board of directors JEL Classification: C23, G30, G34, M14

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1. Introduction About two months ago, November 2017, the European Commission advocated for a

new series of legislations to improve gender equality in the senior positions of public companies

(The Guardian, 2017). Following countries such as Norway, Iceland, France, and Spain, this is

the latest and one of the most far-reaching attempts to increase gender diversity in corporate

boards. The purpose to provide everyone with the same opportunities is based on the principle

of equality of treatment and should be pursued by everyone. But, is there also an economic

explanation why increased gender diversity should be pursued? Or is it a merely social goal?

In other words, are these gender quotas scientifically justified based on economic reasons rather

than intuition or social desires? Over the last two decades, the interest of researchers in the link

between Board Gender Diversity (BGD) and Corporate Financial Performance (CFP) has

grown considerably. With mixed results and relatively small country sets and time frames, there

is no consensus yet in the debate whether women in the board of directors truly enhance firm

performance.

The argumentation for the effect of BGD on firm performance will be developed

through the lenses of the Resource Dependence Theory and the Agency Theory. Until now,

empirical evidence for the relationship between BGD and CFP has been mixed. In addition,

research suggests that the influence of diversity on firm performance may be moderated by

contextual factors (e.g. Schneid et al., 2015). Since the impact of contextual factors on the

BGD–CFP relationship has not yet been explored on a wider scale, the examination of the

moderating effect of national culture on the relationship between board gender diversity and

firm performance is vital to this research. Culture can create gender stereotypes and influences

the process of assigning different roles to men and women. This might influence the eventual

perception and acceptance of people towards women in the top of the business environment.

Furthermore, Brodbeck et al. (2004) found that societal culture has the strongest effect on

organizational culture, which is perceived to be one of the successors in a firm’s financial

performance. Therefore, the objective of this research is to provide empirical evidence on the

moderating effect of national culture on the BGD-CFP link as well as assessing the sole effect

of gender diversity in the board on firm financial performance.

In order to test the hypotheses, a fixed effects regression has been conducted on a multi-

country panel dataset over a time frame of seven years. The effect of gender diversity in the

board on firm performance will be examined trough two measures: the percentage of females

present in the board of directors and a dummy variable indicating the presence of a critical mass

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of females. Firm performance is measured using an approximation of Tobin’s Q. Furthermore,

the moderating effect of national culture is studied through three dimensions of the GLOBE

study by House et al. (2004): Gender Egalitarianism, Humane Orientation, and Institutional

Collectivism. These dimensions will be described in detail in the next section.

This paper expects a positive effect of gender diversity in the board on financial

performance. Furthermore, this study believes the relationship between BGD and CFP to be

positively moderated by national culture since the characteristics belonging to a high score on

Gender Egalitarianism, Humane Orientation and Institutional Collectivism will likely mitigate

the negative effects of social categorization while firms might still benefit from the positive

effects of board gender diversity drawn in the Agency and Resource Dependence theory.

The remainder of this paper is organized as follows. In the next section, applicable

theory around the effect of board gender diversity on firm performance and the moderating

effect of culture will be presented, followed by the hypotheses and a conceptual model. The

sample, data, variables and theoretical model will be discussed in Section 3. The results of the

statistical analysis will be presented in section four and conclusions will be drawn in the last

section after which the theoretical contribution, its limitations and suggestions for further

research will be discussed.

2. Literature Review

2.1 Board Gender Diversity and Corporate Financial Performance

Research on gender diversity often falls under the larger scope of diversity work and it

is believed that the general diversity arguments can also be applied for the specific case of

gender diversity. This method of argumentation has been applied extensively in previous

research (e.g. Carter et al., 2003; Carter et al., 2010; Francoeur, Labelle, & Sinclair-Desgagné,

2008; Marinova, Plantenga, & Remery, 2015; and Schneid et al., 2015). Gender diversity in the

workplace can be classified as the acceptance of both men and women and is accomplished

when there is a greater balance between the number of men and women on the work floor. The widely used Agency Theory (Jensen & Meckling, 1976) and Resource Dependence

Theory (Pfeffer & Salancik, 1978), together with the diversity arguments developed by

Robinson & Dechant (1997), are the building blocks on which almost all gender diversity work

is established. Therefore, an integration of these perspectives will follow in the following

section to build the business case for a positive relationship between gender diversity in the

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board and corporate financial performance. The diversity arguments and both theories will be

discussed first, before the first hypothesis will be developed. Then, the focus shifts to a more

specific aspect of board gender diversity: the critical mass theory. After discussing this theory

and its arguments, the second hypothesis will be presented. Please refer to Figure 1 for a visual

representation of the conceptual model, which can be found at the end of this section.

Agency theory

The Agency theory describes the role of a corporate board in aligning the interest of

management and shareholders through monitoring and controlling managers (Jensen &

Meckling, 1976; Marinova et al., 2015). This theoretical framework is also often used to

describe the link between board characteristics and firm performance (Carter et al., 2003). Since

boards are perceived to be crucial in the view of agency theory, recent literature puts more

emphasis upon the different characteristics that portray a ‘successful board’. It is believed that

gender diversity is, amongst others, one of these characteristics (Hillman & Dalziel, 2003).

Central to the argumentation for a gender-diverse board is the statement that “board

independence is critical for boards to function in the best interests of shareholders” (Carter et

al., 2003: p. 37). They argue that outside board members are less likely to collude with inside

directors at the expense of the respective shareholders, since they have the incentive to build a

reputation as experts in monitoring. One line of argumentation states that gender diversity can

increase board independence by increasing the variety of perspectives. People with a different

gender might ask other questions than their male counterparts with a more traditional

background, thereby creating a more activist board (Carter et al., 2003). In a similar vein,

Adams & Ferreira (2009) and Low, Roberts & Whiting (2015) found that female board

members tend to use tougher monitoring on management because they are not one of the “old

boys club”, and greater gender diversity on boards might also improve monitoring due to better

managerial accountability. Also, there is evidence that women tend to take their role in the

boardroom more seriously which might lead to better governance of an organization (Singh &

Vinnicombe, 2004).

Overall, this study believes that gender diversity can have a positive impact on the

board’s monitoring quality through growing board independence, which will lead to a decrease

in agency cost (Carter et al., 2010). This will ultimately enhance corporate financial

performance (Fama & Jensen, 1983; Jensen & Meckling, 1976).

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Resource dependence theory

Resource dependence theory suggests that boards provide the linkage to an

organization’s vital resources and its external environment (Pfeffer & Salancik, 1978). Even

more important, these linkages can be improved by an increase in size and diversity of the board

of directors through several factors (Goodstein, Gautam, & Boeker, 1994; Liu, Wei, & Xie,

2014; Pfeffer, 1973). First, Carter et al. (2010) argue that female board directors may broaden

the human capital by providing unique information due to their different perspective, which is

in line with the arguments proposed by Robinson & Dechant (1997). They state that diversity

promotes a better understanding of the market. Since approximately half of the total human

population are women, it makes sense to match an organization to the diverse consumer- and

supplier base in order to provide the organization with a better ability to penetrate a certain

market. Furthermore, they argue that incorporating a broader perspective into the process

stimulates creativity and innovation that ultimately enhances the quality of leadership, leading

to enhanced performance. Since “attitudes, cognitive functioning, and beliefs are not randomly

distributed in the population, but tend to vary systematically with demographic variables such

as age, race and gender”, a wider set of perspectives and resources are exploited that might lead

to a better understanding and ability to evaluate the complexities in the external environment

and take actions accordingly (Robinson & Dechant, 1997: p. 27). This view is supported by

Carter et al. (2003), Yi (2011), and Francoeur et al. (2008) who state that more diverse boards

lead to a variety of perspectives who are more likely to raise questions or challenge the current

strategy, solve complex issues and correct informational biases, thereby benefitting the ultimate

solution-making. This could imply that diverse teams might be better in producing solutions of

higher quality than homogenous groups. Although diversity can also create difficulties in

communication and a higher chance of conflicts, they will ultimately outperform less diverse

teams in their solutions.

Furthermore, Pfeffer & Salancik (1978) argue that increased diversity creates legitimacy

and provides commitment or support for an organization in its external environment, which is

supported by Hillman & Dalziel (2003) and Pfeffer & Salancik (2003). Moreover, Hillman,

Cannella & Harris (2002) argue that an increase of female board representation enhances an

organization’s legitimacy since gender equality is becoming one of the widely accepted social

norms.

In a similar vein, the importance of a firm’s stakeholders and their role on firm

performance has become more apparent in recent literature (Finegold, Benson, & Hecht, 2007;

Francoeur et al., 2008; Huse & Rindova, 2001). Whereas the classical approach towards

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corporate governance was about the relationship between management and shareholders,

nowadays firms are increasingly pressured by various stakeholders including politicians, the

media and NGOs to increase its female representation in senior management. Williams (2003),

for example, has shown that female directors are generally more sensitive to social and

environmental issues compared to their male counterparts, which might positively affect a

firm’s reputation among a wider group of stakeholders (Bear et al., 2010; Branco & Rodrigues,

2008). In this line, Robinson & Dechant (1997) argue that a more diverse board helps to reach

a greater and more diverse group of people through a better representation of the different

groups present in a society. This might lead to a feeling of affirmation with the relevant board

members that would not exist in the case of a homogenous board of directors. The increased

affirmation with gender-diverse organizations will create a differentiating advantage compared

to their competitors not characterized by a gender-diverse board. Similarly, Cox & Blake (1991)

state that the improved reputation of a gender-diverse organization will outperform their

competitors by attracting the best female talents. Since the composition of the labour force has

been changed and the competition increased, this might be a vital advantage for an organization

to win the battle of talent. Additionally, the number of female managers in senior management

might also have a positive influence on the lower-positioned women’s visions towards their

career development and future chances, leading to a boost in productivity and firm performance

(Bell, 2005; Burke & McKeen, 1996; Ely, 1990; Smith, Smith, & Verner, 2006).

Based on the Resource dependence theory it could be argued that gender diversity in the

boardroom provides different resources to the firm that can lead to improved information

processing, higher quality decisions, more valuable resources, better stakeholder management,

and additional strategic insights that may ultimately lead to better financial performance (Carter

et al., 2010; Dezsö & Ross, 2012; Hillman, Cannella, & Peatzold, 2000; and Rose, 2007).

Based on the argumentation developed in light of the Agency- and Resource dependence

theory, BGD is expected to positively influence the financial performance of a firm. Therefore,

I hypothesize the following:

Hypothesis 1: Board gender diversity has a positive effect on corporate financial

performance.

The critical mass

Based on the previous sections it becomes clear that BGD might have a positive impact

on firm performance, but does it make a difference how many women serve on a board?

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Previous research suggests it does (Joecks, Pull, & Vetter, 2013; Kramer et al., 2006). The

general consensus is that the threshold for a critical mass occurs when there are at least three

women seated on a board together. Kramer et al. (2006) found that a critical mass leads to a

different perception by the other board members where women are treated as an equal and better

able to influence the process and content of board discussions. They are no longer seen as

outsiders. In addition, they found several advantages of having a critical mass that might

constitute the enhanced financial performance. Delicate or tough issues will less likely be

ignored in discussions, which might enhance the decision-making. Due to a more open and

collaborative attitude, concerns are better heard and taken care of. And having more women on

the board leads to the inclusion of a broader perspective where other stakeholders are also

included. The financial performance of a firm might be damaged, if they are not heard.

In addition to hypothesis 1 in which a positive relation between BGD and CFP is

expected, it is believed that after a threshold value of three females on the board is reached, the

performance of the firm increases. Therefore, the following hypothesis is developed:

Hypothesis 2: If at least three females are present on the board of directors, firm

performance will significantly increase

2.2 The Effect of a Country’s National Culture

Since empirical evidence for the relationship between BGD and CFP has been mixed,

research suggests that the influence of diversity on firm performance may be moderated by

contextual factors (e.g. Schneid et al., 2015). Therefore, the moderating effect of national

culture on the relationship between board gender diversity and firm performance will also be

examined. A nation’s culture embodies general social norms and how certain things are done

(Hofstede, 1983; House et al., 2004). Culture can have an effect on the number of women on

the work floor as well as the equal treatment of people of different sexes (Schneid et al., 2015).

Previous research addressed the importance of culture already by stating that the BGD–CFP

relationship depends on contextual factors, of which culture is most prevalent (Stahl et al., 2010;

Van Knippenberg, De Dreu, & Homan, 2004). Culture can create gender stereotypes and

influences the process of assigning different roles to men and women. This might influence the

eventual perception and acceptance of people towards women in the top of the business

environment. Furthermore, Brodbeck et al. (2004) found that societal culture has the strongest

effect on organizational culture, which is perceived to be one of the successors in a firm’s

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financial performance. This effect will be examined through three cultural dimensions proposed

in the Global Leadership and Organizational Behaviour (GLOBE) study by House et al. (2004).

The three cultural dimensions are: Gender Egalitarianism, Humane Orientation, and

Institutional Collectivism. They will be discussed separately after which a hypothesis will be

presented for every individual dimension.

The underlying concept among the cultural dimensions is social categorization, which

makes a short explanation of the concept of social categorization vital. This study uses the terms

social categorization and gender categorization interchangeably since they have the same

meaning in the context of this specific research. Social categorization is based on social

perception and refers to the process by which people are placed into groups based on

characteristics like race, gender or ethnicity. An individual mentally groups people that share

important characteristics (e.g. demographic features, interests, occupation). This means that

people tend to make assumptions about certain characteristics of an individual based on the

group they belong to. Social categorization has the risk of stereotyping complete groups, which

might change the perception and attitude towards people from specific groups. This is also a

fundamental aspect of the traditional debate about female participation in society, which is why

it is important for this research. In short, this study believes the relationship between BGD and

CFP to be positively moderated by national culture since the characteristics belonging to a high

score on Gender Egalitarianism, Humane Orientation and Institutional Collectivism will likely

mitigate the negative effects of social categorization while firms might still benefit from the

positive effects of board gender diversity such as the arguments developed in the Resource

dependence theory.

Gender Egalitarianism

Gender Egalitarianism refers to “the degree to which a collective minimizes (and should

minimize) gender inequality” (House et al., 2004). They state that more gender egalitarian

societies seek to minimize gender role differences while non-gender egalitarian societies seek

to maximize these differences. In countries where equal treatment of men and women is highly

valued, there are typically more women in high positions, less occupational sex segregation,

and similar levels of income and education (Emrich, Denmark & den Hartog, 2004; Hausmann

et al., 2013). On the other hand, cultures that score high on gender inequality are characterized

by gender role differences that manifest in division of labour, differences in education, and

traditional activities such as taking care of the family and household (Eagly, 1987; Hausmann

et al., 2013; and Schneid et al., 2015).

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An important aspect of gender roles in society is an individual’s work-life balance and

the stereotypical beliefs about men and women. Gender Egalitarianism can play a pivotal role

in improving the individual work-life balance and simultaneously decreasing the stereotypical

beliefs of the different roles men and women have in society (Lyness & Judiesch, 2014). Low

gender egalitarian countries are generally more traditional in their gender roles while high

gender egalitarian countries have less differences in roles and expected priorities by gender

(McDaniel, 2008). Taking into account the aspects of low gender egalitarian countries, it might

be much more difficult for women to achieve a work-life balance due to a different perception

of gender-specific roles. However, if a culture promotes more gender equality, it could increase

women’s educational level and involvement in paid work while some of the caretaking

responsibilities are shifted towards men. If the gap in the levels of work-life balance between

men and women can be diminished, women will be better able to focus on their personal as

well as their corporate development. Furthermore, women will be better accepted due to their

equal role in society. These characteristics, belonging to high gender egalitarian countries, will

therefore not only lead to more females in senior management positions, but they are also better

equipped with improved firm performance as a result (Lyness & Judiesch, 2014).

Based on the arguments presented above, it could be inferred that there is less social

categorization in high gender egalitarian countries, which mitigates the possibly negative

effects on firm performance coming from intra-organizational frictions between genders. Also,

typical male and female occupations in organizations will be blurred and gender stereotypes

will be diminished (Schneid et al., 2015). Rather than be regarded as a threat, women in

boardroom positions will now be valued as an equal and might be better equipped to boost

financial performance of the firm. Based on the above discussion, the following hypothesis is

developed:

Hypothesis 3a: Gender Egalitarianism positively moderates the relationship between

board gender diversity and corporate financial performance.

Humane Orientation

Organizations tend to reinforce the values of the dominant gender in its culture (Klenke,

2004) and since most organizational cultures are predominantly shaped by men (Marshall,

1993), the focus lies in hierarchy, independence, and top-down communication (Bajdo &

Dickson, 2001). Contrarily, female-dominated cultures are characterized by interpersonal

relationships and the sharing of power. Several authors suggested a positive link between

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humane-oriented cultures and the role of women in corporations (Bajdo & Dickson, 2001;

Conelly & Rhoton, 1998; Grant, 1998). Not only will women’s advancement in organizations

be encouraged, but their perspectives and input are also better heard. This might strengthen the

relation between board gender diversity and firm performance.

Humane Orientation refers to “the degree to which an organization or society

encourages and rewards individuals for being fair, altruistic, friendly, generous, caring and kind

to others” (House et al., 2004: p. 569). While low humane oriented societies are characterized

by self-interest and motivated by power and material possessions, countries with a high score

on Humane Orientation are motivated by an urge of affiliation and belonging and sensitivity

for discrimination (Brodbeck & Frese, 2007; Kabasakal & Bodur, 2004).

This study believes that Humane Orientation diminishes the negative influence of the

traditional gender categorization, which might strengthen the effect of board gender diversity

on firm performance. First, individuals in low humane oriented countries mainly care about

their self-interest and are more likely to develop sub-groups which could hamper the overall

group-process. On the other hand, people in countries with a high score on Humane Orientation

tend to be more altruistic and caring, are more likely to form one group regardless of gender,

and focus on cooperation which boosts the overall performance (Kabasakal & Bodur, 2004).

Second, humane oriented societies are characterized by less discrimination which means there

will be less friction and negativities within a group of individuals belonging to different social

categories (House et al., 2004; Schneid et al., 2015). Lastly, Lundberg (2007) showed that

individual behaviours in countries with a high score on Humane Orientation are similar to

behaviours that characterize good teamwork, which could enhance interactions within a team.

By providing a safe, respectful and open place to discuss important issues, companies provide

women the opportunity to flourish and add value to the discussion by bringing in different

perspectives, with increased financial performance as a subsequent result.

Overall, countries with a high score on humane orientation are more open to others and

will likely benefit more from diversity and its different pool of resources while the negative

effects of diversity – the social categorization – will be minimized. Therefore, the following

hypothesis is developed:

Hypothesis 3b: Humane Orientation positively moderates the relationship between

board gender diversity and corporate financial performance

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Institutional Collectivism

Collectivism consists of two separate dimensions: Institutional Collectivism and In-

group Collectivism. Institutional Collectivism is “the degree to which organizational and

societal institutional practices encourage and reward collective distribution of resources and

collective action” (House et al., 2004: p. 12). In-group collectivism refers to “the degree to

which individuals express pride, loyalty, and cohesiveness in their organizations or families”

(House et al., 2004: p. 12).

At first sight, the In-group Collectivism seems the most relevant dimension for this

study. Closer investigation by Brewer & Venaik (2011), however, shows differently; more than

half of the questions used to investigate the In-group Collectivism construct are highly family-

related rather than group oriented. Although the definition used by House et al. (2004)

incorporates ‘organizations and families’, none of the items asks about organizations but rather

about families. Moreover, the dimension of Institutional Collectivism incorporates – next to the

elements of organizations, societies, businesses, economies and institutions – also the element

of groups in their measurement (Brewer & Venaik, 2011). Therefore, this study focuses on the

dimension of Institutional Collectivism only.

Collectivist countries are characterized by individuals who feel affiliated with their

employer and its respective organization with loyalty to the group being more important than

pursuing your own goal. Individualistic countries on the other hand, consist of independent

individuals that strive for their self-interest rather than pursuing the collective’s interest

(Gelfand et al., 2004; Schneid et al., 2015). As is also the case for Gender Egalitarianism and

Humane Orientation, it is believed that Institutional Collectivism can diminish the negative

effects of social categorization through higher group loyalty and commitment to pursue team

goals (Gelfand et al., 2004; Oyserman, Kemmelmeier, & Coon, 2002). In other words, the

strong commitment towards a group and the overall goal that characterizes collectivistic

societies enhances team cohesion and hence its performance (House et al., 2004).

However, these arguments could also be applied in the opposite direction. Stangor et al.

(1992) found gender is one of the most important bases of social categorization, which might

imply that a ‘group’ means ‘people within the same gender’ whereas people from the other

gender are seen as out-group. This might hamper the effectiveness of the group since

collectivistic societies are characterized by high group loyalty while they show a negative bias

towards individuals who do not belong to the same group (Gelfand et al., 2004).

Even though the arguments can be developed for both directions, this study argues the

positive association of Institutional Collectivism to be stronger than the negative one. In sum,

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this study believes that by creating cohesion and a focus on the overall group interest,

Institutional Collectivism eliminates the negative effects of gender categorization while it may

benefit from the additional knowledge, skills and perspectives brought to the table by a gender-

diverse group (van Knippenberg et al., 2004). Therefore, the following hypothesis is developed:

Hypothesis 3c: Institutional Collectivism positively moderates the relationship between

board gender diversity and corporate financial performance.

Figure 1 - Conceptual model including proposed hypotheses

3. Methodology

3.1 Sample and Data

In order to investigate the relationship between BGD and CFP and the subsequent

moderating effect of national culture on this relationship, this analysis is focused on a broad

range of publicly traded companies across the globe.1 In line with previous research, this

research focuses on public firms due to its extensive data availability (e.g. Marinova et al.,

2015). Companies in the financial and utilities sector are neglected in this sample because of

their specific accounting method and high correlation amongst each other. Data on the board of

1 The respective countries included are: Australia, Brazil, Canada, Switzerland, China, Germany, Denmark, Spain, Finland, France, Great Britain, Indonesia, Ireland, India, Italy, Japan, Mexico, Malaysia, The Netherlands, Sweden, Singapore, United States, and South-Africa.

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directors as well as financial performance and relevant controls are obtained through

DataStream from the Thomson Reuters’ Asset4 ESG database and converted to US$ where

applicable. The data for the cultural dimensions are obtained from the database of the GLOBE

study developed by House et al. (2004). Table 1 provides a short definition of each of the

variables. Data is collected for 1,499 firms from 2010 until 2016. In the end, the sample consists

of a balanced panel of 7,125 complete observations. While most studies are predominantly US

based with a few others focusing on a small set of specific countries, this study takes a broader

perspective by incorporating a relatively large set of countries coming from all regions.

Moreover, there are only very few studies using a seven-year timeframe after the start of the

most recent financial crisis.

3.2 Description of Variables

Corporate financial performance

In the area of corporate governance research, there are several ways of measuring

financial performance with the most predominant indicators being Tobin’s Q, ROE and ROA.

While the first indicator is a market-based measure the latter two are based on accounting data.

Although these measures are commonly used next to each other, they are not identical because

they measure significantly different aspects of CFP. Whereas accounting-based profitability

measures such as ROA or ROE are based on historical performance, Tobin’s Q also

incorporates market expectations and thus focusses on future performance expectations

(Campbell & Minguez-Vera, 2007).

In line with previous literature (e.g. Campbell & Minguez-Vera, 2007; Carter et al.,

2010), this research uses Chung & Pruitt’s (1994) approximation of Tobin’s Q, which equals

(market value of firm’s common stock + liquidating value of preferred stock + book value of

debt) divided by its book value of total assets. Although this approximation is slightly different

from the original version of Lindenberg & Ross (1981), it explains 96.6 per cent of its variability

(Carter et al., 2010). Tobin’s Q is associated with the wealth position of a firm’s shareholders

and creditors. Firms with a Tobin’s Q ratio higher than one are expected to be able to create

more value due to intangible assets associated with future growth opportunities and efficient

utilisation of resources (Campbell & Minguez-Vera, 2007; Rose, 2007; Sudarsanam, 2003). In

other words, if the value of Tobin’s Q is higher than one, the market value of the shareholders

and creditors’ investment is higher than the amortized historical costs (Carter et al., 2010). Due

to its characteristics of being a market measure, Tobin’s Q incorporates forecasts of future cash

flows. This might help reflecting the degree to which a firm would be able to seize the

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opportunity to strengthen its competitive advantages, which will in turn impact long-term

performance (Wernerfelt & Montgomery, 1988). Furthermore, women in the board are

generally characterized by a focus on long-term goals (Marinova et al., 2015). Whereas ROA

and ROE focus on past operational performance, Tobin’s Q measures long-term performance

leading this paper to believe that Tobin’s Q would be a better indicator for firm performance in

the context of this research. Furthermore, Tobin’s Q is not prone to reporting biases due to tax

laws and accounting conventions, which makes it easier to compare between firms from

different countries (Lindenberg & Ross, 1981; Campbell & Minguez-Vera, 2007). In line with

previous research, Tobin’s Q is transformed into its natural logarithmic form to mitigate the

effect of potential outliers (e.g. Nguyen, Locke, & Reddy, 2014).

Board gender diversity

The independent variable of interest is gender diversity on the board. Following the

previous strands of literature, this research makes use of two proxies for BGD (Campbell &

Minguez-Vera, 2007; Carter et al., 2003; Carter et al., 2010; Nguyen et al., 2014). First, I use

%FEMALE, which is the percentage of women on the board in relation to total board size. This

measure helps to understand whether the number of women relative to the total size of the board

have an impact. In other words, whether a higher presence of women on the board strengthens

the positive impact on CFP. The second measure, CRITICAL, links to the critical mass theory

described earlier. Both Joecks et al. (2013) and Kramer et al. (2006) found that the threshold

value of women on the board should be at least three. Therefore, a dummy variable is created

with a value of one if there are three or more female board members present and zero otherwise.

National culture

This study uses the three aforementioned cultural dimensions from the GLOBE study

by House et al. (2004): Gender Egalitarianism, Humane Orientation, and Institutional

Collectivism. Although Hofstede’s national culture work has been widely used in management

literature, this study uses the GLOBE research for several reasons. There is a possibility that

the data gathered by Hofstede has become outdated since the dimensions were measured in the

1960’s. In addition, the US, or even more specifically, IBM-centric nature of Hofstede’s data

might bias the results (Schwartz & Bilsky, 1990; Javidan et al., 2006; Venaik & Brewer, 2008).

The GLOBE study, on the other hand, was conducted more recently and involved more

organizations. Also, they developed more specific and new cultural dimensions compared to

Hofstede.

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Although there are nine dimensions in total this study only uses the dimensions that are

expected to be most relevant for the specific subject. Moreover, by using only three of the

dimensions, the critique proposed by Hofstede (2006) and Peterson & Castro (2006) that the

nine dimensions of the GLOBE study “may be too highly correlated to be considered distinct

at the nation level” can be directly countered (Peterson & Castro, 2006: p. 513).

The GLOBE study is also the only study that does not only measure values, but also

actual practices (Venaik & Brewer, 2008). While values represent the score that an individual

would like to see in the ideal situation, the practice score is based on the perception of the actual

situation. So, whereas the values score represents a score that countries wish to have, the

practice score shows the actual situation as it is. In line with previous literature, this study wants

to examine the real influence of culture rather than cultural ideals (Brock et al., 2008; Estrin,

Baghdasaryan, & Meyer, 2009; Schneid et al., 2015). Therefore, I only use the practice scores

to analyse the moderating effect of national culture. All three cultural indicators were measured

on a seven-point scale ranging from 1 to 7. A low score on the respective dimension indicates

poor performance on this dimension while a high score indicates good performance (House et

al., 2004). Meaning that if a country shows a low score on Gender Egalitarianism, Humane

Orientation, and Institutional Collectivism, it would be typified as a society with high gender

inequality, a strong hierarchy and power structure that promotes self-interest rather than the

common good.

Control variables

In order to investigate the real effect of BGD on CFP and the moderating effect of

national culture, several controls are incorporated. Next to several corporate governance

controls, some firm-level control variables are included as well. Furthermore, to control for

other unobserved factors, firm- and year effects are included in the model.

As a first corporate governance control I incorporated board size, measured by the total

number of directors on the board. There is no consensus yet about the exact effect of board size

on financial performance. In recent literature, a negative association between board size and

firm performance was found by Hermalin & Weisbach (2003) while Yermack (1996) and Carter

et al. (2003) found an inverse relationship, whereas others found a non-linear relationship. Also,

recent literature has shown that group size influences group dynamics and performance.

Second, board independence is included as a corporate governance control. The discussion

regarding independent directors relates to the Agency theory that studies conflicts of interest

between managers and owners. It is measured by the share of independent directors relative to

16

the total board size. The effect of board independence on firm performance has been thoroughly

investigated in the area of corporate governance but with mixed results (Carter et al., 2010).

Furthermore, this study accounts for a dual function of CEO/Chairman of the Board. The

Agency theory literature argues that, due to conflicts of interest, a dual function might reduce

the board’s ability to function properly in terms of its governance since its prime function is to

monitor the performance of its top management (Rechner & Dalton, 1991).

Next, some firm-level control variables are included. Firm size is expected to positively

influence a firm’s performance since larger firms generally create advantages through

economies of scale and possess more market power (Bain, 1951; Richard et al., 2004). On the

other hand, argumentation that advocates for a negative relationship evolves around the theory

that large firms come under control of self-interested managers who might pursue utility

maximization before profit maximization (Pervan & Višić, 2012). Also, the corporate

bureaucracy in large firms might reduce a firm’s competence to react fast on changes in the

business environment. In line with other research, firm size is measured by the natural logarithm

of total assets (e.g. Campbell & Minguez-Vera, 2007). Second, firm age is included as a control

even though there is no consensus on its impact yet. Older firms have more experience and are

expected to have larger earnings than younger ones who are in the starting phase. However,

older firms can be more prone to bureaucracy, become lax or are at the end of their product life

cycle (Smith et al., 2006). I also included leverage as a control measure, calculated as the share

of debt relative to a firm’s equity. Based on the free cash flow perspective developed by Jensen

(1986), leverage is positively related to firm performance due to increasing pressure on

managers to invest in positive NPV projects since they have promised future payments for the

issued debt. Also, the monitoring hypothesis states that higher leverage can act as a monitoring

mechanism in order to reduce the possible agency conflict that might arise between

shareholders and managers (Hutten, 2014). As a last control, a lagged performance variable is

included since the BGD–CFP relationship can be regarded as a dynamic rather than static

relationship (Wintoki, Linck, & Netter, 2012). Several studies support this argument by

reporting that past performance may significantly explain the variation in a firm’s current

performance (e.g. Nguyen et al., 2014).

17

3.3 Theoretical Model

To test the effect of BGD on CFP and the moderating effect of national culture on this

relationship, Fixed Effects regression is used.

A major concern in the diversity–performance research area is the possibility of

endogeneity. There are two sources of endogeneity: unobserved heterogeneity and reverse

causality. Although the focus in this research is on a unidirectional relation between BGD and

CFP, several authors express their concern about the reverse causality issue in this relationship

(e.g. Campbell & Minguez-Vera, 2007; Carter et al., 2010; Hermalin & Weisbach, 2003). They

argue that board characteristics are often not random exogenous variables. An often-heard

TABLE 1 Variable Definitions

Independent variable (BGD) %FEMALE Percentage of females in the board CRITICAL Dummy variable with value 1 if at least three women

in the board; 0 otherwise Dependent variable (CFP) TOBINQ (Market Value of Equity + Preferred Stock + Debt) /

Total Assets Moderating variable (National Culture) GE Cultural index score for Gender Egalitarianism

reflecting the degree to which a collective minimizes gender inequality ranging on a scale from 1 to 7

HO Cultural index score for Humane Orientation reflecting the degree to which an organization or society encourages and rewards individuals for being fair, altruistic, friendly, generous, caring and kind to others ranging on a scale from 1 to 7

IC Cultural index score for Institutional Collectivism reflecting the degree to which organizational and societal institutional practices encourage and reward collective distribution of resources and collective action ranging on a scale from 1 to 7

Control variables

BOARDSIZE Natural logarithm of number of people on the board INDEPENDENT % of independent board members DUALCEO Dummy variable with value 1 if the chairman is also

CEO or has been the CEO; 0 otherwise FIRMSIZE Natural logarithm of total assets AGE Years of existence since its incorporation LEV Debt-to-equity ratio TOBINQ-1 One-year lagged value of Tobin’s Q

18

argument is that firms might attract more diversified board members due to its sound operations

and performance (e.g. Smith et al., 2006). To mitigate the reverse causality issue, the

independent variables are lagged by one year. Furthermore, the use of the fixed-effects method

automatically diminishes the unobserved heterogeneity issue. To further reduce the unobserved

heterogeneity, this study follows Wintoki et al. (2012) by including a lagged performance

variable as a control. The fixed effects estimates are important since they help mitigating

omitted variables and address unobserved changes over time (Carter et al., 2010). Subsequently,

a Hausman specification test is performed. The null hypothesis states a random effects

regression is preferred while the alternative hypotheses states the fixed effects model is most

consistent. Returning a p-value of 0.000, we fail to accept the null hypothesis, which means the

fixed effects model is most consistent.

One of the drawbacks of the fixed effects model is the fact that time-invariant variables

are dropped in the regression. Therefore, this study is, in line with the research of Elkhuizen et

al. (2017), primarily interested in the coefficients of the interaction terms.

Tests for heteroskedasticity and autocorrelation have been conducted. To test for

heteroskedasticity, a White test is used which fails to accept the null hypothesis (p=0.000). In

addition, a Woolridge test is conducted to check for autocorrelation in panel data. This test also

fails to accept the null hypothesis (p=0.000), which means that the standard errors have to be

corrected for both heteroskedasticity and serial correlation. Therefore, standard errors that are

robust to heteroskedasticity and serial correlation need to be included.

All models (1, 2, 3, 4) show the Fixed Effects regression model including the lagged

variables as well as firm and year effects. While model (1) and (2) are used to test the first and

second hypotheses, model (3) and (4) are used to test hypotheses 3a, 3b, and 3c.

1 #$%&'(),+ = - + /0%234563),+70 + /8%$59:;&<3),+70 + /=&':3>3':3'#),+70

+ /?:@56A3$),+70 + /B2&94;&<3),+70 + /C5D3),+70 + /E63F),+70

+ /G#$%&'( − 1),+ + I),+ + J) + J+

2 #$%&'(),+ = - + /0A9&#&A56),+70 + /8%$59:;&<3),+70 + /=&':3>3':3'#),+70

+ /?:@56A3$),+70 + /B2&94;&<3),+70 + /C5D3),+70 + /E63F),+70

+ /G#$%&'( − 1),+ + I),+ + J) + J+

3 #$%&'(),+ = - + /0%234563),+70 + /8 %234563),+70 ∗ D3)

+ /= %234563),+70 ∗ N$) + /? %234563),+70 ∗ &A) + /B%$59:;&<3),+70

+ /C&':3>3':3'#),+70 + /E:@56A3$),+70 + /G2&94;&<3),+70 + /O5D3),+70

+ /0P63F),+70 + /00#$%&'( − 1),+ + I),+ + J) + J+

19

4 #$%&'(),+ = - + /0A9&#&A56),+70 + /8 A9&#&A56),+70 ∗ D3)

+ /= A9&#&A56),+70 ∗ N$) + /? A9&#&A56),+70 ∗ &A) + /B%$59:;&<3),+70

+ /C&':3>3':3'#),+70 + /E:@56A3$),+70 + /G2&94;&<3),+70 + /O5D3),+70

+ /0P63F),+70 + /00#$%&'( − 1),+ + I),+ + J) + J+

In these models, TOBINQ represents the financial performance of a firm, %FEMALE

indicates the degree of gender diversity on the board of directors measured by the percentage

of females, CRITICAL is a dummy variable that has a value of 1 if a critical mass of females

is present on the board, GE, HO, and IC capture either one of the three relevant cultural

dimensions; Gender Egalitarianism, Humane Orientation and Institutional Collectivism. Also,

I),+ is included as the error term and J) and J+ are incorporated to capture the entity- and time-

fixed effects.

4. Empirical Results

4.1 Descriptive Statistics

Table 2 provides descriptive statistics for this sample. The value of Tobin’s Q indicates

that the sample firms were relatively successful over the time period, but there was also wide

variation in the performance measure. The mean value of Tobin’s Q is 1.26, which is greater

than one. This indicates that the market value of the firm is greater than the book value of the

assets. With a standard deviation of 1.052, a minimum value of .0478 and a maximum value of

6.003 the variation is significant.

Furthermore, approximately twelve per cent of the firm’s board of directors were female

with a maximum of 58.33 per cent. From all sample firms, only 14.79 per cent of them had

three or more females seated on the board of directors. On average, people tend to assign lower

values to Gender Egalitarianism compared to the other two cultural dimensions.

In approximately 42 per cent of the firm years, the CEO and Chairman of the board were

the same person. On average, 55 per cent of a firm’s directors is classified as independent. And

the average debt-to-equity ratio is 79 per cent. Note that the leverage variable is winsorized at

the 1st and 99th percentile to avoid the effect of the extreme outliers on the results.

20

TABLE 2 Descriptive statistics

Variable N Mean SD Median Min Max Dependent

TOBINQ 10,173 1.256 1.052 .9444 .0478 6.003 Independent

%FEMALE 8,994 .1194 .1125 .1111 0 .5833 CRITICAL 8,994 .1479 .3550 0 0 1 GE 8,994 3.383 .2131 3.340 2.900 3.930 HO 8,994 4.110 .3357 4.170 3.290 4.960 IC 8,994 4.436 .4257 4.270 3.680 5.220 Moderators %FEMALE * GE 8,994 .4103 .3927 .3711 0 2.240 %FEMALE * HO 8,994 .4821 .4540 .4633 0 2.392 %FEMALE * IC 8,994 .5131 .4888 .4666 0 3.045 CRITICAL * GE 8,994 .5089 1.225 0 0 3.390 CRITICAL * HO 8,994 .5826 1.406 0 0 4.960 CRITICAL * IC 8,994 .6271 1.512 0 0 5.220 Controls

BOARDSIZE 8,994 2.249 .3315 2.303 .6931 3.497 INDEPENDENT 8,970 .5500 .2963 .6000 0 1 DUALCEO 8,994 .4168 .4931 0 0 1 FIRMSIZE 8,994 15.40 1.494 15.38 7.975 19.83 AGE 7,474 3.881 .7037 4.007 -.105 5.236 LEV 8,988 .7935 1.457 .4792 -3.99 9.641 TOBINQ-1 8,691 1.247 1.039 .9405 .0478 6.003 Note: Table 2 presents the number of observations, mean, standard deviation, median, minimum value and maximum value for each variable. The definition of each variable is presented in Table 1. LEV is winsorized at the 1st and 99th percentile.

TABLE 3 Descriptive statistics %FEMALE per country

Country N Mean SD Median Min Max Australia 917 .1205 .1220 .1250 .0000 .5000 Brazil 133 .0753 .0793 .0769 .0000 .2857 Canada 721 .1173 .1098 .1111 .0000 .5455 China 105 .0299 .0590 .0000 .0000 .3750 Denmark 105 .1810 .1009 .1818 .0000 .4167 Finland 119 .2504 .0969 .2500 .1111 .5000 France 175 .2923 .1024 .3000 .0000 .5455 Germany 350 .1712 .1079 .1667 .0000 .4167 Great Britain 1,190 .1605 .1098 .1429 .0000 .5000 India 196 .0775 .0684 .0833 .0000 .3000 Indonesia 112 .0497 .0803 .0000 .0000 .3333 Ireland 98 .1650 .0832 .1667 .0000 .3846 Italy 84 .1918 .0943 .2143 .0000 .4375 Japan 1,890 .0189 .0481 .0000 .0000 .5000 Malaysia 112 .1197 .0800 .1111 .0000 .2308 Mexico 98 .0532 .0953 .0000 .0000 .4545 Singapore 140 .0724 .0782 .0801 .0000 .3333 South-Africa 182 .1966 .0935 .2000 .0000 .4286 Spain 140 .1321 .0893 .1111 .0000 .4000 Sweden 175 .2995 .1172 .2727 .0667 .5833 Switzerland 224 .1081 .1034 .1111 .0000 .4000 The Netherlands 161 .1980 .1319 .2222 .0000 .5000 United States 3,066 .1593 .0980 .1538 .0000 .5455 Note: Table 3 presents the number of observations, mean, standard deviation, median, minimum value and maximum value per country for the percentage of females in the board. The definition of the variable is presented in Table 1.

21

TABLE 4 Descriptive statistics DCRITICAL per country

Country N Mean SD Median Min Max Australia 917 .0567 .2314 .0000 .0000 1.000 Brazil 133 .0150 .1222 .0000 .0000 1.000 Canada 721 .1345 .3415 .0000 .0000 1.000 China 105 .0095 .0976 .0000 .0000 1.000 Denmark 105 .1810 .3868 .0000 .0000 1.000 Finland 119 .2437 .4311 .0000 .0000 1.000 France 175 .8057 .3968 1.000 .0000 1.000 Germany 350 .4657 .4995 .0000 .0000 1.000 Great Britain 1,190 .1756 .3807 .0000 .0000 1.000 India 196 .0306 .1727 .0000 .0000 1.000 Indonesia 112 .0089 .0945 .0000 .0000 1.000 Ireland 98 .1939 .3974 .0000 .0000 1.000 Italy 84 .5357 .5017 1.000 .0000 1.000 Japan 1,890 .0021 .0460 .0000 .0000 1.000 Malaysia 112 .2500 .4523 .0000 .0000 1.000 Mexico 98 .1327 .3409 .0000 .0000 1.000 Singapore 140 .0214 .1453 .0000 .0000 1.000 South-Africa 182 .4670 .5003 .0000 .0000 1.000 Spain 140 .2286 .4214 .0000 .0000 1.000 Sweden 175 .6229 .4861 1.000 .0000 1.000 Switzerland 224 .0670 .2505 .0000 .0000 1.000 The Netherlands 161 .2422 .4298 .0000 .0000 1.000 United States 3,066 .2009 .4007 .0000 .0000 1.000 Note: Table 4 presents the number of observations, mean, standard deviation, median, minimum value and maximum value per country for the critical mass variable. The definition of the variable is presented in Table 1.

Table 3 and 4 display the respective statistics per country of the BGD variables since

these are of central interest to this research. The United States, together with Japan and Great

Britain cover a relatively large part of the sample. Looking at Table 3, European and North-

American firms score higher with respect to the percentage of females on the board than their

Asian and South-American counterparts. Especially, the Scandinavian countries (Denmark,

Finland, and Sweden) score relatively high. Moreover, Finland and Sweden are the only two

countries in the sample with no single firm consisting of solely male board members, while

Sweden also scores best regarding the percentage of females in a single year (58.33%) and

shows the highest mean value (29.95%). Also, there is no country consisting of firms with only

male board members.

Looking at Table 4, it can be concluded that European and North-American firms also

score better with regard to having a critical mass of females on the board. France, Italy, and

Sweden show a median value of one, which implies that more than half of the firms are

characterized by boards constituting of three or more females. While the Scandinavian countries

were ranked among the top performers with respect to the average percentages of females in

the board, they are outperformed by France on the critical mass measure. However, these results

might be difficult to interpret since the critical mass theory suggests the threshold value to be

at least three females, while absolute board sizes might differ across countries. For example, an

22

average Board of Directors in France consists of 14 people while a board in Sweden, Finland,

and Denmark consists of respectively 10, 9, and 8 people. Furthermore, there is no country in

the sample that only consists of firms with boards characterized by a critical mass nor firms

with no critical mass of females in the board.

4.2 Correlation Matrix

Table 5 reports the Pearson’s correlation matrix between the dependent, independent,

moderating and control variables. The correlation coefficients of .145 and .078 indicate that the

percentage of female board members and the presence of a critical mass of female board

members are positively related to CFP. At first sight, this would support the study’s first and

second hypothesis. Furthermore, all cultural interaction terms show positive coefficients except

for %FEMALE*GE (-.01) with regard to Tobin’s Q.

Recently, there has been discussion about multicollinearity in interaction terms due to

high correlations with its independent predictor variables (see e.g. Dawson, 2014). With

correlation coefficients of higher than .90, potential multicollinearity was also present in this

study. One way to deal with this problem is by applying the mean-centring procedure on the

predictor variables before creating the interaction term (Dawson, 2014; Shieh, 2011). This

procedure has also been conducted in this research.

After dealing with the high correlation among the interaction terms, multicollinearity

does not seem to be an issue. Even though a few associations between variables show relatively

high correlations, they are below the 0.7 threshold indicated by Brooks (2014). The only

exception on this threshold is the association between %FEMALE*IC and CRITICAL*IC.

However, since these variables are not simultaneously included in the regression model,

multicollinearity will not be an issue in this study. As an additional check, a multicollinearity

test for the variables has been conducted by using Variance Inflation Factors (VIF). The results

show the highest VIF is 5.53 and the average VIF is 2.35, which is well below the threshold of

10 (Neter, Wasserman & Kutner, 1983). This suggests that multicollinearity may not be a

problem in this study.

23

TABLE 5 Correlation matrix

[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] Dependent [1] TOBINQ 1.00 Independent [2] %FEMALE .145 1.00 [3] CRITICAL .078 .652 1.00 [4] GE .044 .200 .087 1.00 [5] HO .035 -.18 -.19 -.12 1.00 [6] IC -.13 -.19 -.13 .110 .445 1.00 Moderators [7] %FEMALE * GE -.01 .267 .193 .143 .008 .313 1.00 [8] %FEMALE * HO .005 -.12 -.22 .020 .170 .041 -.15 1.00 [9] %FEMALE * IC .113 -.09 -.18 .272 .071 -.04 .228 .425 1.00 [10] CRITICAL * GE .024 .192 .259 .123 .046 .211 .694 -.07 .237 1.00 [11] CRITICAL * HO .013 -.18 -.35 .059 .209 .156 -.05 .695 .361 -.01 1.00 [12] CRITICAL * IC .064 -.17 -.44 .190 .195 .151 .240 .420 .730 .368 .614 1.00 Controls [13] BOARDSIZE .009 .220 .353 -.13 -.19 -.11 .082 -.10 -.19 .073 -.21 -.26 1.00 [14] INDEPENDENT .162 .221 .029 .205 .252 -.21 -.11 .185 .201 -.01 .176 .170 -.10 1.00 [15] DUALCEO .077 .016 .030 -.17 .135 -.07 -.05 .044 -.06 -.00 .034 -.03 .150 .204 1.00 [16] FIRMSIZE -.15 .214 .260 -.15 -.14 -.01 .106 -.08 -.19 .081 -.14 -.21 .576 .002 .156 1.00 [17] AGE -.02 .025 .066 -.01 -.06 .06 .046 -.05 -.09 .036 -.05 -.07 .085 -.03 .026 .085 1.00 [18] LEV -.05 .058 .051 -.01 -.05 -.03 .009 .038 -.04 -.01 .001 -.04 .108 .003 -.01 .147 -.00 1.00 [19] TOBINQ-1 .583 .066 .034 .019 .026 -.06 .037 -.02 .072 .050 -.00 .050 -.05 .053 .014 -.23 -.00 -.07 1.00 Note: The predictor variables for the interaction terms are first mean-centred before the interaction was created. Even though the GE, HO and IC variables are not included in the fixed effects regression due to their time-invariance, they are included in the correlation matrix to show there are no multicollinearity problems among the cultural variables. LEV is winsorized at the 1st and 99th percentile. The definition of each variable is presented in Table 1.

24

4.3 Fixed Effects Regression Analysis This section provides the results of the fixed effects regression analysis concerning the

relationship between BGD and CFP and the moderating effect of national culture. The

regression does not include dummy variables to account for countries or industries since these

are time-invariant and are already incorporated due to accounting for firm and year fixed

effects. The results of the effects between BGD and Tobin’s Q as well as the moderating effect

of national culture are reported in Table 6. Model (1) shows the regression of BGD, which is

measured by the percentage of females, on CFP including control variables while Model (2)

shows the regression between the critical mass of females on the board and Tobin’s Q. Model

(3) shows the regression results of the percentage of females on the board on Tobin’s Q

including the moderating effect of national culture. Model (4) follows the same procedure with

a different measure for BGD: a dummy variable that indicates the presence of a critical mass.

The interaction terms for culture are adapted accordingly.

In Table 6, it can be observed in Model (1) that the percentage of females on the board

has no effect on Tobin’s Q. The critical mass dummy in Model (2), however, is positively and

significantly related to Tobin’s Q. This suggests that greater female board representation does

affect firm performance, but only after a certain threshold is reached. If there are at least three

women seated on the board, the negative aspects will be outweighed by the positive ones and

better financial performance will be achieved.

When considering the effect of national culture, interesting results are observed. Model

(3) and (4) include the relevant measure for BGD, the interaction terms to capture the

moderating effect of national culture, and the controls. Both models provide the coefficient

estimates for the individual cultural dimensions given the fact there has been controlled for the

other cultural dimensions. Model (3) shows the effect of BGD in terms of the percentage of

females on the board with the interaction term for culture being constructed accordingly. While

the interaction term for Institutional Collectivism shows a strongly significant and positive

effect, the influence of Gender Egalitarianism and Humane Orientation appear to be negative

and significant at the one per cent level. In addition, the sign for the percentage of females

remains positive and becomes significant at the ten per cent level. Moreover, the coefficient for

the BGD indicator becomes stronger than in Model (1), which indicates that including the

moderating effect of culture in the model helps to better predict the effect of BGD on CFP. The

same results and argumentation can be applied to Model (2) and (4) where the critical mass

dummy represents the relevant BGD measure. In model (4), the coefficients of the interaction

25

terms for Gender Egalitarianism and Humane Orientation are both negative and strongly

significant while the Institutional Collectivism coefficient is positive and strongly significant.

Also, the coefficient for the critical mass variable becomes stronger and is now significant at

the one per cent level instead of ten per cent.

Since the control variables show identical results in all models, I will discuss these

variables at once instead of separately per model. Firm size is significant and positively related

to CFP. This is in line with the argumentation provided in the previous section regarding the

economies of scale and increased market power that characterizes larger firms. It could also be

related to the Resource dependence theory since larger firms generally possess a larger variety

of resources, which might enhance firm performance. Second, firm age is negatively related to

CFP and significant at the five per cent level. Implying that the benefit of having more

experience does not outweigh the downside of becoming more prone to bureaucracy and

corporate slack. Furthermore, Table 6 shows the significant and negative effect of a firm’s

degree of financial leverage on CFP. This supports the view that corporate governance

mechanisms and financial leverage might be substitutes to reduce the agency costs. The proxy

for board independence is positive in all models but only significant in Model (3). In relation

to the arguments provided by the agency theory, this result was expected since independent

boards are better able to monitor management which might increase financial performance.

Lastly, board size and the dual function of CEO/Chairman have no effect on firm performance.

Furthermore, all models show a negative constant. Although this might look

problematic at first, this does not have to be a problem. A negative constant is likely to happen

if e.g. the independent variables are not reaching negative or very low values, which is the case

in this research. While Tobin’s Q can reach negative values, the dependent variables, interaction

terms, and most controls show only positive values.

26

TABLE 6 Fixed Effects Regression Estimates of the relationship between BGD and CFP, and the subsequent influence of National Culture. CFP is measured by the natural logarithm of

Tobin’s Q. Independent variables (1)

TOBINQ (2)

TOBINQ (3)

TOBINQ (4)

TOBINQ

%FEMALE

.004 (0.06)

.186* (2.28)

CRITICAL

.039* (2.49)

.071*** (3.95)

%FEMALE * GE -1.317*** (-4.12)

%FEMALE * HO -1.229*** (-7.88)

%FEMALE * IC 1.159*** (5.96)

CRITICAL * GE -.279*** (-7.38)

CRITICAL * HO -.143*** (-5.81)

CRITICAL * IC .169*** (7.45)

BOARDSIZE -.013 (-0.52)

-.022 (-0.86)

-.012 (-0.46)

-.019 (-0.70)

INDEPENDENT .061 (1.89)

.061 (1.85)

.072* (2.40)

.064 (1.98)

DUALCEO

-.014 (-1.73)

-.013 (-1.71)

-.014 (-1.64)

-.015 (-1.81)

FIRMSIZE

.049* (2.17)

.050* (2.22)

.054* (2.44)

.050* (2.30)

AGE

-.160** (-3.13)

-.158** (-3.11)

-.147** (-3.01)

-.157** (-3.05)

LEV

-.007*** (-6.30)

-.007*** (-6.44)

-.006*** (-5.97)

-.007*** (-6.66)

TOBINSQ–1 .311*** (9.40)

.311*** (9.43)

.310*** (9.41)

.311*** (9.41)

Constant -.561* (-2.32)

-.562* (-2.39)

-.710** (-2.93)

-.585** (-2.56)

Within R2 .197 .198 .200 .199 Between R2 .665 .669 .676 .671 Overall R2 .545 .547 .553 .549 Observations 7,125 7,125 7,125 7,125 F-statistic 231.25 354.30 56.33 368.82 Year effects yes yes yes yes Firm effects yes yes yes yes t-Statistics in parentheses: ***indicates p < .01, **indicates p < .05, and *indicates p < .10 Standard errors are robust to heteroskedasticity and serial correlation. Tobin’s Q is the dependent variable, measuring firm performance. %FEMALE and CRITICAL are the independent variables measuring gender diversity in the board. The moderator variables are all interaction terms. The other variables are the controls. All independent-, moderator-, and control variables are lagged by one year.

27

4.4 Robustness Check An additional test is conducted to validate the results of the main analysis. Next to

Tobin’s Q, there are two other commonly used performance measures: ROE and ROA. The

results can be found in Table A.1 and A.2 in the appendix.

Looking at Model (1) and (2) of Table A.1 and A.2, it can be concluded that the results

for the first two hypotheses are similar for all performance indicators. No effect on firm

performance can be found for the percentage of females present on the board, while the presence

of a critical mass of females on the board shows a significant and positive effect on firm

financial performance. These results indicate that the regression results of Tobin’s Q are robust

to the other two performance measures with respect to Hypotheses 1 and 2. From these results,

it can be concluded that the relationship between BGD and CFP is robust to both market-based

as well as accounting-based performance measures.

In contrary to the main analysis, the moderating effect of culture shows different results

for the other performance indicators. Taking a look at Model (3) of Table A.1 and A.2, it can

be found that Gender Egalitarianism has no effect on the BGD–CFP relationship while there

was a negative relationship found in the main analysis. Also, the moderating effect of

Institutional Collectivism became negative when CFP is measured by both ROE and ROA

instead of the positive effect shown in the main analysis. In contrast, the moderating effect of

Humane Orientation shows to be robust to all performance measures. However, caution is

required by interpreting these results. Since there appears to be no effect of BGD on CFP, the

moderating effect of culture can be hard to interpret and might not make much sense.

Furthermore, by assessing the moderation of culture regarding the critical mass, results

also deviate from the main analysis. Model (4) of Table A.1 shows no moderation effect of

culture for any of the dimensions in terms of ROE as the performance indicator. Looking at

Model (4) of Table A.2, opposing results are found for the moderation of national culture.

Whereas the effect of Gender Egalitarianism was negative in the main analysis, it shows a

positive effect when performance is measured by ROA. Also, the moderation effect of

Institutional Collectivism switched signs. While the effect was positive in the main analysis,

the effect becomes negative if ROA is used as the indicator for performance. Humane

Orientation changed from a negative effect to no effect.

In summary, it can be concluded from the regression results of Table A.1 and A.2 that

Hypotheses 1 and 2 are robust to different performance measures. However, the moderating

28

effect of national culture diverges significantly when different performance indicators are

investigated.

5. Conclusion and Discussion The purpose of this paper is to provide empirical evidence on the moderating effect of

national culture on the BGD-CFP link as well as assessing the sole effect of gender diversity

on the board on firm financial performance. The dependent variable, CFP, is measured through

the natural logarithm of Tobin’s Q. Two indicators are used to measure the BGD construct: the

percentage of females on the board and the presence of a critical mass of females on the board.

The moderating effect of culture is measured through three cultural dimensions developed in

the GLOBE study. These dimensions are Gender Egalitarianism, Humane Orientation, and

Institutional Collectivism. Besides, there has been controlled for several corporate governance

mechanisms and firm characteristics as well as previous performance. The models are tested

using a fixed effects regression model including both year- and firm effects. The hypotheses

were developed from a few theories. Hypotheses 1 and 2 are built upon the Resource

dependence theory and Agency theory, while hypotheses 3a, 3b, and 3c are using cultural

dimensions from the GLOBE study and are based upon the social categorization process.

Taking a step back to the conceptual model presented earlier in this research, a positive

sign for all hypotheses was expected. The first and second hypotheses expect BGD to have a

positive effect on CFP. While hypothesis 1 measures BGD by using the percentage of females

present on the board, the second hypothesis investigates the effect of a critical mass of females

seated on the board. It appears the hypothesized positive effect of BGD on CFP is partly

supported by the empirical results. More specifically, no relation has been found between the

percentage of females present on the board of directors and firm performance, but a significant

positive effect of the critical mass of females on CFP was present. This indicates that women

on the board of directors do affect CFP, but only after a certain threshold value is reached. If a

critical mass of at least three women on the board of directors is reached, they will positively

affect a firm’s financial performance. These results are in line with Joecks et al. (2013), Kramer

et al. (2006), Rose (2007) and others.

Furthermore, this study tested the moderating effect of national culture on the BGD-

CFP link. Separate hypotheses are developed to measure the effect of Gender Egalitarianism,

Humane Orientation, and Institutional Collectivism, respectively. All dimensions were

29

expected to have a positive moderating effect. While the first two dimensions show

significantly negative effects on the BGD-CFP relationship, Institutional Collectivism suggests

a significantly positive effect. This means the results for Gender Egalitarianism and Humane

Orientation are contradictory to the expected results. Albeit there are arguments that might

explain the negative effect of Gender Egalitarianism and Humane Orientation, no theory has

been developed yet to support these explanations. A positive moderation effect was expected

based on the belief that cultures possessing specific characteristics of Gender Egalitarianism

and Humane Orientation were able to diminish the social or gender categorization present in

societies, which would enable better cooperation and hence increase performance. However, in

high gender egalitarian countries there is almost no presence of gender categorization and

consequently no difference in gender. This might imply that gender diversity does not matter

anymore if everyone is equal since there exists no difference between groups. The same

argument holds for Humane Orientation. Furthermore, high humane oriented societies are

characterized by their openness, which might enhance performance at first due to the

acceptance of new resources and perspectives brought by increased BGD. However, too many

different perspectives in the board might hamper the group process and distort the balance in

the group, subsequently decreasing performance. Also, high humane oriented societies tend to

value cooperation and care for others most. Although this could enhance the group process, it

could also lead to a reduced sense of one’s own responsibilities. People in low humane oriented

societies, on the other hand, value achievements and assertiveness and are primarily interested

in achieving their goal, thereby increasing CFP. In contrast to the first two dimensions,

Institutional Collectivism shows to mitigate the gender categorization process, thereby

enhancing an effective group process leading to increased performance. The moderating effects

of culture show similar results for both models, indicating the effect of culture is robust to

different measures of board gender diversity.

In summary, while hypothesis 1 needs to be rejected, hypothesis 2 can be accepted.

Although the percentage of females on the board does not affect firm performance, a critical

mass of at least three females positively affect CFP. Hypotheses 3a and 3b need to be rejected

since Gender Egalitarianism and Humane Orientation appear to negatively influence the BGD-

CFP relationship, while hypothesis 3c can be accepted since Institutional Collectivism

positively moderates the relationship between BGD and CFP.

One of the most important practical implications of this study is the support for the most

recent attempt of the European Commission, the legislative body of the EU, to push the gender

quota for females in corporate boards to 40% (The Guardian, 2017). Since this study found that

30

a critical mass of females on the board significantly enhances corporate performance, an almost

equal presence of men and women on the board might help to boost the economy. However,

firms should not make the mistake that simply appointing one or two women in the board will

increase their financial performance. This study did not found any effect on CFP if the number

of females on the board is below the threshold value of three.

The contribution of this study to the extant literature is present in several ways. While

the relationship between BGD and CFP has been investigated thoroughly, existing research is

either US based or focused on a very small set of particular countries. This study presents a

broader perspective by incorporating a relatively large set of countries across all regions. In

addition, only very few studies have investigated data on a time frame of seven years.

Furthermore, the effect of national culture on the BGD–CFP link has, to the best of my

knowledge, not yet been investigated. Even though existing research mentions the importance

of contextual factors in the relationship between diversity and performance, this effect has not

been investigated on a large scale. In short, this study offers new insights in the BGD–CFP area

by studying the effects of one of most prevalent contextual factors: national culture. In addition,

by showing that the effect of BGD on CFP is dependent on national culture, this study provides

empirical evidence for the call to further investigate the influence of contextual factors on the

BGD–CFP relationship.

Despite the contributions, this study has some limitations too. First, culture is assumed

to be stable over time and represents general norms and values that apply to each and every

individual within the same culture. However, the sample firms are assigned to the national

culture where their headquarters is situated. This does not mean that all directors possess the

same nationality, and even if so, individuals with foreign experience due to expat positions or

international contacts might act differently from the general norms and values of a particular

country. Second, one of main criteria in the sample selection process was the availability of

data for the independent variables. There is a plausible chance that the sample firms were the

ones that are generally better firms. This could impede the interpretation and generalisation of

the results (Nguyen et al., 2014). Lastly, although a positive effect is found, there is no clarity

through which channels BGD has an effect on CFP.

Naturally, some of the limitations also provide new avenues for further research. The

above limitation regarding the specific effect through which BGD positively affects CFP would

be interesting to investigate more thoroughly. Studying the specific personality traits of female

board members would further develop our understanding of the real impact of female presence

on the board of directors. Furthermore, this study used only three specific dimensions of the

31

GLOBE study. It would be interesting to see whether the results are robust to other measures

of culture (e.g. Hofstede’s cultural dimensions) in order to create a more complete view on the

effect of national culture. Also, the robustness section showed deviating results in terms of the

moderation effect of culture on different performance indicators. An interesting avenue for

further research would be to investigate the cause of these differing results. Moreover, the note

about the lack of theoretical support for the negative effect of Gender Egalitarianism and

Humane Orientation could be an interesting avenue for further research. It would be interesting

to explore through which cultural attributes the negative effect evolves. Finally, as already

mentioned above, this study showed that the effect of BGD on CFP might be dependent upon

the effect of national culture. This strengthens the call for further research on other contextual

factors influencing the BGD–CFP relationship.

32

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Appendices

TABLE A.1 Fixed Effects Regression Estimates of the relationship between BGD and CFP, and the

subsequent influence of National Culture. CFP is measured by ROE. Independent variables (1)

ROE (2)

ROE (3)

ROE (4)

ROE

%FEMALE

-.034 (-0.88)

-.068 (-1.38)

CRITICAL

.018* (2.31)

.020* (2.49)

%FEMALE * GE -.147 (-1.76)

%FEMALE * HO -.169** (-2.92)

%FEMALE * IC -.189*** (5.16)

CRITICAL * GE .009 (0.68)

CRITICAL * HO .007 (0.46)

CRITICAL * IC .004 (0.28)

BOARDSIZE -.001 (-0.88)

-.005 (-0.63)

.001 (0.06)

-.005 (-0.65)

INDEPENDENT -.014* (-2.38)

-.014* (-2.36)

-.013* (-2.03)

-.014* (-2.33)

DUALCEO

.009** (2.98)

.009** (3.00)

.008** (2.96)

.009** (2.97)

FIRMSIZE

-.095*** (-15.06)

-.095*** (-15.04)

-.094*** (-14.78)

-.095*** (-15.02)

AGE

-.014 (-0.90)

-.013 (-0.82)

-.010 (-0.62)

-.013 (-0.83)

LEV

.042*** (8.96)

.041*** (6.33)

.042*** (9.19)

.041*** (8.87)

ROE–1 .230*** (6.32)

.231*** (6.33)

.230*** (6.31)

.231*** (6.32)

Constant 1.561*** (12.33)

1.558*** (12.22)

1.532*** (11.92)

1.561*** (12.07)

Within R2 .102 .103 .104 .103 Between R2 .079 .084 .080 .084 Overall R2 .054 .058 .055 .058 Observations 7,218 7,218 7,218 7,218 F-statistic 376.47 414.10 200.45 28.64 Year effects yes yes yes yes Firm effects yes yes yes yes t-Statistics in parentheses: ***indicates p < .01, **indicates p < .05, and *indicates p < .10 Standard errors are robust to heteroskedasticity and serial correlation. ROE is the dependent variable, measuring firm performance. %FEMALE and CRITICAL are the independent variables measuring gender diversity in the board. The moderator variables are all interaction terms. The other variables are the controls. All independent-, moderator-, and control variables are lagged by one year. ROE is, both as the dependent variable measure as well as the lagged control variable, is winsorized at the 1st and 99th percentile.

37

TABLE A.2 Fixed Effects Regression Estimates of the relationship between BGD and CFP, and the

subsequent influence of National Culture. CFP is measured by ROA. Independent variables (1)

ROA (2)

ROA (3)

ROA (4)

ROA

%FEMALE

.031 (1.24)

.021 (0.74)

CRITICAL

.012*** (4.34)

.008* (2.40)

%FEMALE * GE -.054 (-1.35)

%FEMALE * HO -.073* (-2.29)

%FEMALE * IC -.046** (-2.75)

CRITICAL * GE .035*** (5.03)

CRITICAL * HO .007 (1.71)

CRITICAL * IC -.012* (-2.13)

BOARDSIZE -.007** (-3.12)

-.009** (-3.68)

-.007** (-3.11)

-.009*** (-3.92)

INDEPENDENT -.003 (-0.49)

-.003 (-0.57)

-.003* (-0.42)

-.003 (-0.59)

DUALCEO

-.009*** (11.76)

.009*** (12.22)

.009*** (11.26)

.009*** (12.71)

FIRMSIZE

-.058*** (-12.58)

-0.58*** (-12.47)

-.058*** (-12.01)

-.058**** (-12.45)

AGE

-.031*** (-5.63)

-.030*** (-5.57)

-.029*** (-5.28)

-.030*** (-5.48)

LEV

-.001 (-0.58)

-.001 (-0.64)

-.001 (-0.54)

-.001 (-0.64)

ROA–1 .192** (2.73)

.191** (2.73)

.191** (2.73)

.191** (2.73)

Constant 1.053*** (12.72)

1.055*** (12.42)

1.04*** (12.12)

1.056*** (12.34)

Within R2 .068 .069 .069 .069 Between R2 .018 .017 .018 .018 Overall R2 .019 .019 .019 .019 Observations 7,449 7,449 7,449 7,449 F-statistic 4871.07 272.22 814.12 180.39 Year effects yes yes yes yes Firm effects yes yes yes yes t-Statistics in parentheses: ***indicates p < .01, **indicates p < .05, and *indicates p < .10 Standard errors are robust to heteroskedasticity and serial correlation. ROA is the dependent variable, measuring firm performance. %FEMALE and CRITICAL are the independent variables measuring gender diversity in the board. The moderator variables are all interaction terms. The other variables are the controls. All independent-, moderator-, and control variables are lagged by one year.