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Does the presence of independent and female directors
impact firm performance? A multi-country study
of board diversity
Siri Terjesen •Eduardo Barbosa Couto •
Paulo Morais Francisco
Springer Science+Business Media New York 2015
Abstract This study empirically analyzes whether gender diversity enhances
boards of directors’ independence and efficiency. Using data from 3,876 public
firms in 47 countries and controlling for a wide set of corporate governance
mechanisms, we find that firms with more female directors have higher firm per-
formance by market (Tobin’s Q) and accounting (return on assets) measures. The
results also suggest that external independent directors do not contribute to firm
performance unless the board is gender diversified. These results hold with respect
to different estimation models and robustness tests. Overall, our findings provide
evidence that the female directors enhance boards of directors’ effectiveness.
Finally, we find that firms that are concerned with board independence, and that
firms in more complex environments are more likely to have gender-balanced
boards.
Keywords Board of directors Female directors Firm performance Independent
directors Return on assets Tobin’s Q
S. Terjesen (&)
Kelley School of Business, Indiana University, 1309 E. 10th St., Bloomington, IN 47405, USA
e-mail: terjesen@indiana.edu
S. Terjesen
School of Management & Economics, Lund University, Lund, Sweden
E. B. Couto P. M. Francisco
ISEG-School of Economics and Management, Technical University of Lisbon, Rua Miguel Lupi,
20, 1249-078 Lisbon, Portugal
e-mail: ecouto@iseg.utl.pt
P. M. Francisco
e-mail: paulofrancisco@iseg.utl.pt
123
J Manag Gov
DOI 10.1007/s10997-014-9307-8
1 Introduction
The board of directors is tasked with guiding and authorizing the firm’s strategic
decisions, including mergers, acquisitions, alliances, hiring/firing executives, and
capital structures. These strategies, in turn, impact the firm’s financial performance
and overall capital expenditures. Recent corporate scandals (e.g., Lehman Brothers,
Glitnir, and Dynegy) have led to even closer scrutiny of boards of directors’
decisions and composition. Around the world, there are calls to diversify boards of
directors. Two distinct types of board of directors characteristics are the directors’
status as independent (e.g., external, non-executive) to the firm and gender (e.g.,
female). There is also significant pressure from certain stock exchanges and large
institutional investors. For example, in the U.S., the NYSE and NASDAQ
exchanges both stipulate that a substantial share of a firm’s directors should be
independent.
A separate but related issue concerns the appointment of women to boards.
Sixteen national corporate governance codes encourage the appointment of female
directors; fourteen countries mandate gender quotas for publicly traded firms (e.g.,
Norway and Spain) or state-owned enterprises (Terjesen et al. 2014; authors’
calculations). The presence of independent and female directors varies by country,
industry, and firm; however, the share on both populations is on the rise. For
example, recent data from the UK indicates that independent and female directors
are 72 and 15 % respectively and that women comprise 24.7 % of new
appointments (Sealy and Vinnicombe 2013). Among the U.S. Fortune 1000, female
directors comprised 5.6 % in 1990 and 12.3 % in 1999 (Farrell and Hersch 2005).
By 2014, this share has risen to approximately 16.9 % (Catalyst 2014).
A large and growing stream of research investigates how the composition of a
firm’s board affects outcomes, however the results are mixed with respect to the
impact of independent (Dalton et al. 1998) and female (Terjesen et al. 2009)
directors. Despite significant interest from practitioners, policymakers, and
academics, research has failed to explore board independence structure in a
gender diversity framework. Scholars have called for further investigation of
board gender diversity-firm outcome relationships (Adams et al., 2015; Bilimoria
2008; Terjesen et al. 2009) and multi-country studies (Grosvold and Brammer
2010; Terjesen and Singh 2008) to supplement the mainly one nation studies (e.g.,
Dezso
¨and Ross 2012; Kang et al. 2010; Ntim 2013). Furthermore, scholars have
called for rigorous explanations of global corporate governance phenomena
(Aguilera et al. 2008).
The present study aims to fill this gap by examining: Is the effect of independent
directors on reducing agency costs enhanced by the board’s gender balance? That is,
if a firm’s board of directors is composed of a large proportion of outside directors
and all of these directors are male, can anyone (and stakeholders in particular) be
certain that these directors are independent from the firm’s management? If males
and females in a firm have similar educational backgrounds and levels of workforce
participation in a particular economy, why are so few females present on the firm’s
board? If the overall labor market is balanced, why should the market for directors
be unbalanced? One might argue that this issue of gender representation on boards is
S. Terjesen et al.
123
cultural and social in nature such that the society in a particular country views top
management functions as more appropriate for men and that other jobs, such as
housework, are more suitable for women (Gerson 1985; Schein et al. 1996). Despite
the various reasons that a board of directors may be gender-imbalanced in favor of
males, the message that this imbalance conveys to the public is that its selection was
biased, at least in terms of gender. A board selected under biased conditions
provides fewer guarantees of its independence and may have negative effects on
firm performance. Our research explores this argument and analyzes the effect of
board structure in terms of gender and outside membership on reducing agency
costs and improving firm performance.
This study offers four contributions to the literature. First, we reconcile prior
inconsistent and inconclusive findings by considering the conditions under which
independent directors impact firm performance. Second, we consider a gender
perspective, informing the debate on code recommendations and quota legislation
for appointing independent directors and female directors. Third, our data from
3,876 public firms in 47 countries supplements the mostly single country studies.
Finally, our research identifies a set of firm and country characteristics associated
with greater numbers of female directors.
The remainder of the paper is organized as follows. Section 2outlines the
theoretical background and hypotheses. We then describe the data and methodology
in section three. Sections 4and 5present and discuss the results. Section six
concludes with a discussion of limitations and suggestions for future research.
2 Theoretical background and hypotheses
Our research examines two components of board composition: status as an
independent outsider and female gender. While both types of members are expected
to bring unique contributions to boards, their exact mechanisms are distinct. We
begin by theorizing about how independent directors may influence firm outcomes,
and then consider the influence of female directors on firm outcomes and board
efficiency. There is not one universal theoretical framework; we draw on several
theories to develop hypotheses.
2.1 Independent directors and firm performance
The board of directors’ primary function is to advise on strategy formulation and
decision-making (Holmstrom 2005; Adams and Ferreira 2007). An important
component of these board tasks is monitoring executive management to ensure that
managers pursue shareholders’ best interests (Fama 1980; Fama and Jensen 1983).
There is nearly universal agreement in academic research, policy, and practice that
independent (also referred to as outside or non-executive) directors increase board
transparency and monitoring. For example, around the world, corporate governance
codes such as the Sarbanes–Oxley Act strongly suggest and often mandate that a
board should be comprised of a significant share of independent directors. A large
Multi-country study of board diversity
123
literature analyzes the impact of independent directors on firm performance, with
inconclusive findings.
1
There are three key theoretical perspectives that suggest how independent
directors may positively influence firm outcomes: agency theory, resource
dependency theory, and upper echelons theory (Ruigrok et al. 2006). Agency
theory focuses on the inherent conflicts between owner’s interests and management
interests. An agent theoretical perspective suggests that independent directors (from
outside the corporation) have fewer potential conflicts of interest and can thereby
provide greater integrity and offer impartial judgment (Fama 1980; Rosenstein and
Wyatt 1997). Within this framework, Hermalin and Weisbach (1998) provide a
theoretical model for analyzing board composition and effectiveness as a function of
board independence. According to this framework, the CEO has incentives to
influence the selection of a board that enables him/her to maximize his/her personal
benefits. In contrast, directors have incentives to maintain their own independence,
preventing them from being complacent about the CEO. In this context, the board’s
independence level emerges from a dynamic negotiation between the CEO and
board of directors. Hermalin and Weisbach (1998) emphasize that exogenously
requiring the addition of more outsiders to the board does not necessarily to a board
that is more independent from the CEO. In fact, unless the new outside directors
could influence the bargaining process, the board’s independence would remain the
same. Nevertheless, independent directors are expected to be more likely to
represent shareholder interests and potentially take a stand against the CEO (Adams
et al. 2010). These independent directors value their personal reputations, and will
go to great lengths to preserve their reputations. According to Adams et al. (2010:
94), Fama’s (1980) arguments suggest that ‘‘concern for his [director’s] reputation
will cause an agent to act more in his principal’s interests than standard approaches
to agency might suggest…strong reputation presumably aids in getting more board
seats or retaining the ones already held, a weak reputation the opposite.’’
Independent directors come to their boards with prior experience that may enable
them to be more effective as monitors (Fama and Jensen 1983), particularly when
they constitute the majority of the board (Adams et al. 2010; Fama and Jensen
1983).
A second key perspective is resource dependency theory which considers the role
of external resources in affecting firm behaviors (Pfeffer and Salancik 2003).
According to resource dependency theory, independent directors have access to
valuable knowledge and relationship resources such as particular expertise, social
1
For example, Brickley et al. (1997), Luan and Tang (2007), Florackis and Ozkan (2009), Kim and Lim
(2010), Jackling and Johl (2009), and Pombo and Gutie
´rrez (2011) report a positive relationship between
the percentage of independent directors and firm performance. In contrast, Hermalin and Weisbach
(1991), Barnhart and Rosenstein (1988), Bhagat and Black (2002), Vafeas and Theodorou (1998), Klein
(1998), and Arosa et al. (2010) find that the presence of independent directors does not increase firm
value. Moreover, Agrawal and Knoeber (1996), Bebchuk and Cohen (2005), and Shan and McIver (2011)
find that independent directors decrease value. Faleye et al. (2011: 177) report that intense monitoring by
independent directors may negatively affect firm value, thus ‘‘suggesting that the costs of weak advising
outweigh the board’s monitoring.’’ Nguyen and Nielsen (2010) find that the death of an independent
director decreases shareholder value. Kang et al. (2007) report mixed results. Still other studies find no
significant differences.
S. Terjesen et al.
123
networks, and legitimacy which can be leveraged in their roles on the board
(Hillman et al. 2002). Furthermore, independent directors’ unique experiences
garnered in other companies can be useful for high-level board decision-making
(Finkelstein et al. 2009). Taken together with human capital theory concerning the
role of the individual’s cumulative education and experience (Becker 1994) and
social capital theory concerning social networks as a key advantage (Coleman
1988), independent directors with unique education and work experience (external
to the firm) may offer insightful knowledge to their boards and contribute to the
success of the firm. Taken together, independent directors expand their firms’
boundaries through linkages to important external resources (Hillman and Dalziel
2003).
Third, upper echelons theory describes how executives’ behavior may be
explained by personal experiences and values (Hambrick and Mason 1984).
Executives’ prior experiences are especially salient in board roles (Hambrick 2007)
such that independent directors should be more likely to leverage their vast and
diverse sets of knowledge and skills and thereby improve performance. Taken
together, we suggest:
Hypothesis 1 The greater the firm’s proportion of independent directors on its
board, the better its performance.
2.2 Female directors and firm performance
Despite the substantial theoretical rationale, existing research provides mixed
evidence with respect to the relationship between the board’s gender structure and
firm performance.
2
There are three key theories that suggest that greater gender diversity may further
contribute to better board effectiveness and performance: agency theory, resource
dependency, and gender role theory (Terjesen et al. 2009).
From an agency theory perspective, Francoeur et al. (2008: 84) suggest that
‘‘women (like external shareholders, ethnic minorities, and foreigners) often bring a
fresh perspective on complex issues, and this can help correct informational biases
in strategy formulation and problem solving.’’ A recent Finnish study reports that
female board members are, compared to their male counterparts, more likely to take
active roles on their boards (Virtanen 2012). Other work indicates that women are
more likely to ask questions (Bilimoria and Wheeler 2000), debate issues (Ingley
and Van der Walt 2005), display participative leadership and collaboration skills
(Eagly and Johnson 1990), and generally hold their organizations to higher ethical
2
Erhardt et al. (2003), Carter et al. (2003), Campbell and Mı
´nguez-Vera (2008,2010), Carter et al.
(2010), Kang et al. (2010), Gul et al. (2011) and Mahadeo et al. (2012)Lu
¨kerath-Rovers (2013), Ntim
(2013), among others, report a positive relationship between gender-diversified boards and firm
performance. Sun et al. (2011) find no association between gender diversity of independent audit
committees and the ability to constrain earnings management. Similarly, Kang et al. (2007) find no
relationship. The lack of consistent findings may be due to prior studies’ limited and non-harmonized
measures of firm performance and lack of control variables. A meta-analysis of over eighty studies finds
some support for gender (Post and Byron 2015). A more recent stream of research examines female CEOs
and Chairs, finding a positive relationship to performance (Peni 2014).
Multi-country study of board diversity
123
standards (Pan and Sparks 2012). Women’s ability to influence board decisions
increases with their numbers, particularly boards with more than one woman
(Fondas and Sassalos 2000) or three women (Konrad and Kramer 2006; Torchia
et al. 2011). There is other evidence that boards with more women have greater
levels of public disclosure (Gul et al. 2011), better oversight of management
reporting that enhances earnings quality (Srindhi et al. 2011), and more board
development evaluations and programs (Nielsen and Huse 2010). Female board
members are more prepared for meetings (Pathan and Faff 2013) and attend more
board meetings (Adams and Ferreira 2009). High levels of oversight are expected to
lead to better performance outcomes.
Resource dependency theory is a second guiding perspective as female directors
bring unique and valuable resources and relationships to their boards. In the case of
networks, early work revealed that compared to male managers, female managers
generally have more diverse networks (Ibarra 1992,1993). More recent work on
Italian directors suggests that female directors’ networks are defined by the
important role of families and that when women grow their networks over time,
female directors do not possess a very high position in a global network of
interlocking directors except in those cases of a female director on a family firm
(Drago et al. 2011). Taken together with other research, there is evidence that
women may understand certain markets and consumers better than their male
counterparts (Arfken et al. 2004). Prior research also indicates that female directors
are more likely to have non-business backgrounds that include a portfolio of
experience (Hillman et al. 2002; Singh et al. 2008). This diversity of perspectives
can enhance overall creativity and innovation with respect to problem solving.
Gender role theory (Eagly 1987) suggests that an individual’s gender determines
his/her behavior and its effectiveness with respect to influence. Furthermore, the
theory suggests that males and females’ behavior are assessed in terms of how it
ascribes (or diverges) from expectations of the respective gender. Individuals who
use tactics that are aligned to their gender tend to be perceived better by others
(Eagly et al. 1995). Gender role theory describes how men and women have
normatively prescribed behavior with respect to communication, including influence
tactics. For example, women are expected to ascribe to more feminine roles such as
sympathy and gentility (Eagly 1987). By contrast, men are expected to be more
assertive and aggressive. Another gender role associated with women is flexibility
which leads to a greater ability to manage ambiguous situations (Rosener 1995).
Gender roles are relevant for the board as directors must use communication tactics
that are effective in terms of influence. Furthermore, gender roles are particularly
salient in male-dominated realms (Alderfer and Smith 1982) such as the board of
directors where esteem is critical to effectiveness (Forbes and Milliken 1999). As
such, we expect to see a positive relationship between the board gender diversity
and firm performance:
Hypothesis 2 The greater the firm’s proportion of female directors on its board,
the better its performance.
S. Terjesen et al.
123
2.3 Female directors, board independence and firm performance
This study’s main hypothesis is that the composition of a board of directors will
impact firm performance. As argued in Hypothesis 1, boards with greater shares of
outside directors should be viewed more positively by the public than a board
comprised of fewer outsiders. However, when the level of outsiders is fixed, the
percentage of women on the board may be important when assessing outsiders’
perceived independence. That is, regardless of the number of outsiders, a
shareholder (or any stakeholder) can reasonably suspect that a board composed
mainly of men is more closely aligned with the executive management than is a
gender-diverse board. A large board of directors with few women directors may be
interpreted as being selected by the executive management network or as a sign that
internal agents (executive officers) wield significant power over the selection of
outside agents. In reality, a board with a gender imbalance may be independent of
the executive management to the same degree as a gender-diverse board, but the
lack of women increases doubts from appointed directors, shareholders, and any
stakeholders who interact with the firm regarding the board’s independence.
These stakeholders’ perceptions have implications at various levels of the firm.
First, at the shareholder level, this perception leads to a lack of confidence in the
efficacy of outside directors as monitors of executives. Moreover, it signals that the
CEO has some power over the selection of the board and thus is entrenched and
costly to replace. It may also signal that the CEO is performing poorly and using his/
her bargaining power to maintain a friendly board to avoid being criticized or fired
(Hermalin and Weisbach 1998). At the board level, outside directors view their
colleagues as aligned with executives and less motivated to ‘swim against the tide’
(and thus provide valuable advising and monitoring services) (Faleye et al. 2011).
Furthermore, to protect his/her career, a director may be unwilling to cause trouble
for the CEO because of the perceived power of the CEO in the market for directors.
Perhaps most importantly, employees, suppliers, customers, and virtually all other
stakeholders will see the board as ‘friendly,’ influenced by internal agents who wish
to circumvent legal requirements for a minimum number of outside independent
directors. An inability to provide these signals will cause the stakeholders to view
management as self-serving agents and be less willing to share the firm’s goals. For
example, employees will see a gender-imbalanced board as one that is selected
based on the network hypothesis, indicating that the firm does not value the success
of its women. In sum, the board’s gender composition is an issue of business ethics.
Establishing a(n) (im)balanced gender board sends an (un)ethical signal to the
stakeholders, which negatively (positively) affects the board’s effectiveness and the
firm’s performance. As such, we conjecture that gender diversity might enhance the
independence of the board and improve its efficiency (Fig. 1). Taken together, we
expect:
Hypothesis 3 Ceteris paribus, the positive effect of independent directors on firm
performance is higher when the board is comprised of a greater proportion of female
directors.
Multi-country study of board diversity
123
3 Data and methodology
We collected accounting, stock market, and corporate governance data from 3,876
listed companies in 47 countries in 2010 (see Table 1for sample descriptives). By
including firms in countries with different institutional environments, we increase
the heterogeneity of the dependent variables, and therefore also the robustness and
generalization of the results. Overall, the average number of females directors is less
than 1 (.90) and average number of independent directors is 5.40.
3.1 Variables
3.1.1 Dependent variable
We use two proxies for firm performance: Tobin’s Q (a market valuation indicator)
and return on assets (ROA) (an accounting-based indicator). Both variables come
from the Bloomberg database which computes and discloses financial information
on listed companies worldwide.
Tobin’s Q has been extensively used in the empirical literature as a proxy for firm
performance (e.g., Agrawal and Knoeber 1996; Amman et al. 2011; Anderson and
Reeb 2003; Barnhart and Rosenstein 1988; Carter et al. 2003; Combs et al. 2005;
Florackis et al. 2009; Ika
¨heimo et al. 2004; Lefort and Urzu
´a2008; Maury 2006;
Kim and Lim 2010, among others). Tobin’s Q is defined as the sum of total assets
less the book value of equity plus the market value of equity, divided by total assets
and provides an indication of the firm’s expected performance. A Tobin’s Q greater
that one means that the shareholders believe the company is worth more than its
book value; a value smaller than one means that the market is expecting the
company to destroy shareholders’ value in the future.
ROA is the ratio of net income to the book value of the firms’ assets, and is
commonly used in studies of board composition and firm performance (e.g.,
Easterwood et al. 2012). Since we are using a data set that includes only listed
companies, these firms are generally obliged to adopt International Financial
Reporting Standards (IFRS) or U.S. generally accepted accounting principles
Board Independence Firm Performance
Gender Diversity
Hypothesis 1 +
Hypothesis 2 +
Hypothesis 3 +
Fig. 1 Model of hypotheses
S. Terjesen et al.
123
Table 1 Sample characteristics
Country # of
firms
Average # of
directors
Average # of
female directors
Average # of
independent directors
Australia 294 6.84 0.65 4.46
Austria 12 12.67 1.00 8.67
Belgium 18 11.83 1.17 4.89
Brazil 15 9.53 0.60 3.87
Canada 233 9.83 1.06 7.63
China 292 8.86 0.80 3.65
Colombia 1 9.00 1.00 6.00
Cyprus 1 15.00 1.00 6.00
Denmark 21 8.81 0.90 4.38
Estonia 3 6.33 0.00 2.67
Finland 39 7.56 1.67 6.00
France 83 12.86 1.64 6.55
Germany 27 13.44 1.07 8.37
Greece 6 12.67 0.83 4.00
Hong Kong 56 11.75 1.04 4.54
Hungary 1 9.00 0.00 6.00
India 438 8.22 0.36 4.35
Indonesia 2 6.00 0.00 2.50
Ireland 23 11.30 1.17 7.43
Israel 3 10.67 1.33 5.67
Italy 35 14.00 0.77 7.46
Japan 543 9.97 0.09 1.38
Lithuania 1 7.00 2.00 2.00
Luxembourg 6 9.83 1.33 5.33
Malaysia 15 9.33 0.87 4.00
Mexico 2 11.50 0.00 7.50
Netherlands 34 7.68 0.85 6.12
New Zealand 10 7.70 0.70 5.10
Norway 17 9.24 3.35 5.59
Pakistan 7 10.00 0.14 4.71
Papua New G. 1 9.00 0.00 7.00
Philippines 5 11.00 0.20 2.40
Portugal 8 16.63 0.63 6.63
Russia 13 10.85 0.69 4.23
Singapore 41 9.63 0.76 5.76
South Africa 45 12.73 2.31 6.89
South Korea 19 7.11 0.11 3.21
Spain 31 14.06 1.58 5.81
Sri Lanka 8 8.13 0.50 3.63
Sweden 54 9.65 2.33 6.02
Switzerland 58 8.95 0.79 7.67
Multi-country study of board diversity
123
(GAAP) when disclosing their accounts. As such, the issue of comparability
between the ROA of different countries is negligible.
3.1.2 Independent variables
We use two independent variables: percentage of independent directors and
percentage of female directors, both measured in terms of percentage of the board.
When a company has a supervisory board and a management board, the board
structure is defined in terms of the supervisory board.
3.1.3 Control variables
We follow prior research in including controls for board, firm, and country level. At
the board level, we control board size,number of board meetings, and CEO/chair
duality (e.g., Di Pietra et al. 2008; Finkelstein and D’aveni 1994; Florackis and
Ozkan 2009). Large boards and frequent meetings may create burdensome
coordination costs that allow more CEO influence (Jensen 1993). Prior research
indicates that when the CEO is also the Board Chair, power is highly concentrated
and independent directors are less able to effectively monitor executives (Yermack
1996; Carter et al. 2003; Coles et al. 2008; Duchin et al. 2010) and there are
negative impacts on firm performance (Bhagat and Bolton 2008).
We also control for the firm’s debt-to-assets ratio,a dividends dummy,
percentage of free-float,percentage of institutional ownership,insider ownership,
and book value of assets.Sector dummy variables are included to extract any
potential sector bias. Our capital expenditures model includes all of these controls,
as well as the book value of the assets (log) to control for investments in place and
the number of employees (log) because capital-intensive firms can have less human
capital and vice versa. Debt usage and dividends may mitigate agency problems
(Easterbrook 1984; Jensen 1986). Moreover, firms with dispersed ownership may
have free rider problems (Admati et al. 1994); however, institutional investors can
be efficient monitors of management (Shin and Seo 2011) and are included to
Table 1 continued
Country # of
firms
Average # of
directors
Average # of
female directors
Average # of
independent directors
Taiwan 8 9.13 1.13 1.88
Thailand 8 12.25 1.00 5.50
Turkey 7 9.43 1.00 1.71
U. Arab Em. 5 7.00 0.20 3.20
U. Kingdom 326 9.10 0.86 5.11
United States 1,001 10.06 1.40 8.05
Total sample 3,876 9.54 0.90 5.40
This table reports per country means of firms’ size of the boards of directors, the number of female
directors, and the number of independent directors
S. Terjesen et al.
123
control for shareholder activism calling for more women on the board (Farrell and
Hersch 2005). Finally, there is evidence that larger firms have more entrenched
managers who are more difficult to assess (Coles et al. 2008).
At the country level, women’s appointments to boards may be subject to the
institutional environment (Terjesen and Singh 2008). We control for gross domestic
product per capita (GDPPC) and the ratio of market capitalization to GDP as
developed countries with more advanced financial markets may have better
corporate governance devices (Gugler et al. 2003). Several variables are logged to
account for skewness in the data. We also include working women % (percentage of
women in the workforce; source: World Bank) and common law dummy. Table 2
provides a description of each of these variables. Table 3depicts the correlation
matrix of the variables used in the analysis.
3.2 Methodology
We test our hypotheses with the generalized method of moments (GMM) (Hansen
1982) regression which directly computes standard errors that are robust to
heteroskedasticity of unknown form (Wooldridge 2001,2002).
Following Hermalin and Weisbach (2003), all board-related variables, including
the percentages of women and independent directors on the board and board size, are
assumed to be endogenously related to firm performance and are thus instrumented.
The combination of instruments should be correlated with the endogenous variable
being instrumented, but not with the error term (except throughout the endogenous
variable). The natural choice would be to use the lagged levels of the endogenous
regressors following the same rational of Arellano and Bond’s (1991) dynamic model,
as well as other potential exogenous variables to guarantee the validity of the
instruments. We select the lag percentages of independent and female directors on the
board (as of 2009 fiscal year end), the lag of the board size, the number of employees
(log), and the country’s working women index as the initial set of instruments. The
model will then choose the best linear combination of these instruments for each
instrumented independent variable. To determine whether these variables are
endogenous, we apply the GMM C statistic (Baum et al. 2007). The results are
rejected at any significance level, thus suggesting that board-related variables are
endogenously related to firm performance. Furthermore, to assess the instruments’
validity, we computed the Hansen’s (1982) J statistic v
2
test for each of the estimated
models. The results strongly suggest that the set of instruments is valid.
4 Results
4.1 Independent and female directors
Tables 4and 5depict our main findings. Model 1 simultaneously considers the
board’s independence and gender structures. Models 2 and 3 investigate the effect
of the share of female and independent directors on the firms’ Tobin’s Q and ROA.
Model 4 analyzes the interaction. As 52 % of the firms have at least one female
Multi-country study of board diversity
123
Table 2 Variables
Variable Description # of
obs.
Mean Std.
dev.
25th perc. 50th perc. 75th perc.
Panel A: board structure
# women on board Number of women on the firm’s board of directors,
as reported by the company
3,876 0.90 1.08 0.00 1.00 1.50
C1 female director
(dummy)
Dummy: 1 if the firm’s board of directors has at
least one female member; 0 otherwise
3,876 0.53 0.50 0.00 1.00 1.00
% women on board Ratio: number of women to number of directors on
the firm’s board (board size)
3,876 8.95 10.45 0.00 7.69 15.38
# independents on
board
Number of independent directors on the firm’s
board, reported by the company (independence is
defined according by company’s own criteria)
3,876 5.40 3.16 3.00 5.00 8.00
% independents on
board
Ratio: number of independent directors to number
of total directors (board size).
3,876 57.25 28.59 16.67 60.00 80.00
Board size Total number of directors on the firm’s board (if
firm has supervisory and management boards,
only total members of the supervisory board)
3,876 9.54 3.20 7.00 9.00 11.00
Board meetings Number of board meetings held in 2010. 3,876 9.62 5.20 6.00 8.00 12.00
CEO/chair duality Dummy: 1 if the company’s Chief Executive
Officer is also Board Chair; 0 otherwise
3,876 0.32 0.47 0.00 0.00 1.00
Panel B: firm specific
Tobin’s Q (log) Log of the sum of total assets less the book value of
equity plus the market value of equity, divided by
total assets
3,876 0.34 0.49 6.72E-03 0.22 0.59
ROA (log) Log of the firm’s gross return on assets (ROA)
(defined as one plus the ratio of the net income to
the book value of the firm’s assets)
3,874 0.05 0.11 0.01 0.04 0.08
Debt-to-asset ratio Ratio of total book value of debt financing (short-,
medium- and long-term debt) to total book value
of the firm’s assets
3,876 24.91 20.30 9.03 22.42 36.39
S. Terjesen et al.
123
Table 2 continued
Variable Description # of
obs.
Mean Std.
dev.
25th perc. 50th perc. 75th perc.
Dividends Dummy: 1 if the company paid any dividends
during 2010 and 0 otherwise
3,876 0.73 0.44 0.00 1.00 1.00
% free float Percentage of the firm’s shares that are freely
traded, calculated as the total number of shares
not held by any controlling shareholder divided
by the total number of shares outstanding
3,876 72.88 26.48 51.17 81.58 97.49
% institutional
ownership
Percentage of outstanding shares held by
institutions
3,876 53.80 35.76 23.56 51.23 83.63
% insider ownership Percentage of outstanding shares held by insiders 3,876 4.75 11.77 0.09 0.59 2.80
Capital expenditures
(log)
Log of the value of the firm’s purchases of
(tangible) fixed assets, excluding purchases of
investments during 2010
3,763 5.50 2.74 3.81 5.44 7.23
# of employees (log) Log of the firm’s total number of employees, as
reported by the firm, in 2010
3,580 8.38 2.02 7.20 8.54 9.74
Revenue (log) Log of the total value of firm’s operating revenues,
sales or turnover, as reported by the firm, during
2010
3,876 8.52 2.69 6.93 8.34 10.19
Assets (log) Log of the book value of the firm’s assets, as
reported by the firm, at the end of 2010
3,876 21.79 2.26 20.54 21.91 23.15
Panel C: country specific
GDP per capita (log) Log of the per capita GDP (USD) of the country
where the firm is based
3,876 10.06 1.21 7.30 10.67 10.76
Market cap.-to-GDP
ratio (log)
Log of the total market capitalization divided by
the gross domestic product
3,876 4.64 0.51 4.39 4.76 4.91
% working women
index
Percentage of female participation in a country’s
labor force rate as of 2009
3,876 53.65 9.63 32.80 58.40 58.40
Multi-country study of board diversity
123
Table 2 continued
Variable Description # of
obs.
Mean Std.
dev.
25th perc. 50th perc. 75th perc.
Common law Dummy: 1 if the company is incorporated in a
common law country and 0 otherwise
3,876 0.65 0.48 0 1.00 1
All data were obtained from Bloomberg except for the country-specific variables which were gathered from the World Bank. All values are in 2010 USD unless otherwise
specified
S. Terjesen et al.
123
Table 3 Correlations
Variable (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
1. # women on board 1
2. C1 female director
(dummy)
0.766*** 1
3. % women on board 0.935*** 0.778*** 1
4. # independents on
board
0.532*** 0.525*** 0.418*** 1
5. % independents on
board
0.367*** 0.419*** 0.384*** 0.823*** 1
6. Board size 0.350*** 0.275*** 0.135*** 0.443*** -0.0615*** 1
7. Board meetings -0.105*** -0.166*** -0.104*** -0.262*** -0.314*** -0.000272 1
8. CEO/chair duality -0.0237 -0.0591*** -0.0307 -0.0307 -0.0763*** 0.0107 0.0643*** 1
9. Tobin’s Q (log) 0.0803*** 0.130*** 0.111*** 0.119*** 0.210*** -0.0909*** -0.214*** -0.0974*** 1
10. ROA (log) 0.0342* 0.0347* 0.0399* 0.0336* 0.0361* -0.00683 -0.136*** 0.00728 0.317*** 1
11. Debt-to-asset ratio 0.0399* 0.0455** 0.0266 0.0694*** 0.0262 0.106*** 0.0178 -0.0539** -0.0987*** -0.200*** 1
12. Dividends 0.0653*** 0.0451** 0.0182 0.00176 -0.152*** 0.221*** 0.0699*** 0.0177 -0.0437** 0.151*** -0.0317
13. % free float 0.189*** 0.206*** 0.176*** 0.348*** 0.365*** 0.0594*** 0.0250 0.0961*** 0.0515** -0.00235 -0.0225
14. % institutional
ownership
0.200*** 0.257*** 0.191*** 0.345*** 0.354*** 0.0687*** -0.120*** -0.00382 0.196*** 0.0944*** -0.0263
15. % insider
ownership
-0.0846*** -0.0673*** -0.0417* -0.0943*** -0.00761 -0.174*** -0.151*** 0.00103 0.0663*** 0.0300 -0.0455**
16. Capital
expenditures (log)
-0.0286 -0.113*** -0.120*** -0.108*** -0.359*** 0.375*** 0.241*** 0.137*** -0.176*** 0.0278 0.161***
17. # of employees
(log)
0.313*** 0.267*** 0.214*** 0.307*** 0.0600*** 0.463*** 0.00767 0.0695*** 0.0163 0.102*** 0.0486**
18. Revenue (log) 0.00220 -0.0857*** -0.0846*** -0.132*** -0.409*** 0.386*** 0.279*** 0.183*** -0.234*** 0.0449** 0.0553**
19. Assets (log) 0.342*** 0.291*** 0.211*** 0.414*** 0.128*** 0.563*** 0.133*** 0.0458** -0.123*** 0.0127 0.0902***
Multi-country study of board diversity
123
Table 3 continued
Variable (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
20. GDP per capita (log) 0.147*** 0.151*** 0.138*** 0.183*** 0.175*** 0.0688*** 0.183*** 0.112*** -0.000162 -0.0592*** -0.0830***
21. Market cap.-to-GDP (log) 0.131*** 0.157*** 0.133*** 0.167*** 0.245*** -0.0651*** -0.207*** -0.0722*** 0.125*** 0.0635*** -0.0785***
22. % working women index 0.236*** 0.267*** 0.265*** 0.248*** 0.338*** -0.0708*** -0.0642*** 0.0161 0.258*** 0.0547** -0.0930***
23. Common law 0.172*** 0.235*** 0.175*** 0.450*** 0.558*** -0.0791*** -0.307*** -0.136*** 0.175*** 0.0289 0.00987
Variable (12) (13) (14) (15) (17) (18) (19) (20) (21) (22)
12. Dividends 1
13. % free float 0.0264 1
14. % institutional ownership -0.0359* 0.488*** 1
15. % insider ownership -0.0966*** -0.254*** -0.173*** 1
16. Capital expenditures (log) 0.323*** -0.0520** -0.143*** -0.227***
17. # of employees (log) 0.241*** 0.169*** 0.226*** -0.189*** 1
18. Revenue (log) 0.355*** -0.0401* -0.121*** -0.224*** 0.593*** 1
19. Assets (log) 0.245*** 0.277*** 0.258*** -0.259*** 0.671*** 0.517*** 1
20. GDP per capita (log) 0.0437** 0.524*** 0.388*** -0.162*** 0.164*** -0.00982 0.379*** 1
21. Market cap.-to-GDP (log) -0.000456 0.148*** 0.217*** 0.0601*** -0.0324 -0.198*** 0.0144 0.138*** 1
22. % working women index -0.119*** 0.345*** 0.284*** -0.00593 0.0772*** -0.316*** 0.181*** 0.413*** 0.219*** 1
23. Common law -0.123*** 0.269*** 0.419*** 0.0669*** -0.125*** -0.430*** -0.0904*** 0.0301 0.488*** -0.00415
This table reports Pearson correlations between the variables used in the analysis. Significance levels are computed as two tailed pvalues: * p\0.05, ** p\0.01,
*** p\0.001
S. Terjesen et al.
123
Table 4 GMM estimation of a multiple linear regression of Tobin’s Q
Explanatory variables Dependent variable: log (Tobin’s Q)
(1) (2) (3) (4) (5)
% women on board
a
0.0573*** 0.0349*** – – –
(6.330) (7.741)
% independents on board
a
-0.0096*** – 0.0068*** -0.0207*** -0.0097***
(-4.974) (5.327) (-4.794) (-5.045)
% women 9% independent
a
– – – 0.0011*** –
(5.227)
C1 female director (dummy)
a
– – – 1.2584***
(6.329)
Board size
a
-0.1459*** -0.1013*** -0.1969*** -0.2226*** -0.1480***
(-4.128) (-4.010) (-6.018) (-4.728) (-4.325)
Board meetings -0.0185*** -0.0095*** -0.0155*** -0.0303*** -0.0113***
(-4.586) (-3.482) (-4.461) (-5.207) (-3.051)
CEO/Chair duality -0.0737*** -0.0688*** -0.0757*** -0.1741*** -0.0483*
(-2.777) (-3.323) (-3.243) (-4.632) (-1.867)
ROA (log) 0.9524*** 0.9758*** 0.5729** 0.9450*** 1.0441***
(3.749) (4.109) (2.191) (3.419) (4.261)
Debt-to-asset ratio 0.0002 0.0000 -0.0006 0.0002 0.0001
(0.314) (0.023) (-0.819) (0.169) (0.135)
Dividends 0.0362 0.0772*** 0.1489*** 0.0025 0.0011
(1.032) (2.783) (4.899) (0.054) (0.031)
% Free float -0.0003 -0.0015*** -0.0023*** -0.0014 -0.0000
(-0.415) (-2.670) (-3.451) (-1.529) (-0.016)
% Institutional ownership 0.0012** 0.0016*** 0.0018*** 0.0015** 0.0007
(2.417) (4.148) (4.401) (2.373) (1.337)
% Insider ownership 0.0001 0.0003 -0.0007 0.0000 0.0008
(0.052) (0.250) (-0.523) (0.022) (0.501)
Assets (log) 0.0819** 0.0422 0.1558*** 0.1438*** 0.0554
(2.303) (1.596) (4.897) (3.208) (1.595)
GDP per capita (log) -0.0404** -0.0376** -0.0655*** -0.1000*** -0.0335*
(-1.968) (-2.375) (-3.473) (-3.691) (-1.753)
Market cap.-to-GDP (log) -0.0980*** -0.0309 -0.0195 -0.1056** -0.0824**
(-2.759) (-1.350) (-0.602) (-2.276) (-2.440)
Common law 0.1785*** -0.0240 -0.1196** 0.2215*** 0.1075**
(3.503) (-0.723) (-2.507) (3.019) (2.313)
Constant 0.6096* 0.4414* -0.8652*** 1.2935*** 0.8927***
(1.880) (1.749) (-3.886) (2.680) (2.637)
Industry dummies Yes Yes Yes Yes Yes
Observations 3,579 3,579 3,874 3,579 3,579
Wald v
2
(pvalue)
412.797
(0.000)
679.267
(0.000)
487.573
(0.000)
228.392
(0.000)
444.456
(0.000)
GMM C statistic v
2b
(pvalue)
101.001
(0.000)
158.591
(0.000)
160.657
(0.000)
122.382
(0.000)
96.9996
(0.000)
Multi-country study of board diversity
123
director, model 5 analyzes the effect of a dummy variable with the value of 1 if the
board has at least one female member while maintaining the variable share of
independent directors.
Model 1 in Table 4shows that when simultaneously considering the percentages
of female and independent directors, the percentage of female directors is positively
associated with Tobin’s Q, but the percentage of independent directors is negatively
related to Tobin’s Q. Furthermore, ceteris paribus, a 1 % increase in female
directors increases Tobin’s Q by 5.7 %; a 1 % increase in independent directors
reduces Tobin’s Q by 0.9 %. If we assume that the model is correctly specified (i.e.,
linear), our results indicate that female directors’ presence is more important to firm
performance than is independent directors’ presence.
We further explore the relationship between board structure and Tobin’s Q in
models 2 and 3. Both coefficients are positive and statistically significant, providing
support for Hypothesis 1 and 2 that a firm’s greater share of independent and female
directors is associated with superior financial performance. The change in sign
implies that there is a positive relationship between the percentage of female
directors and the percentage of independent directors. Nevertheless, the marginal
effect of female directors on Tobin’s Q is much higher than that of independent
directors, supporting the previous results indicating that a gender diverse board is
more important to firm performance than is a board with independent directors. In
model 2, a 1 % increase in female directors results in a 3.5 % increase in Tobin’s Q.
In model 3, a 1 % increase in the independent directors increases Tobin’s Q by
approximately 0.7 %. One possible explanation is that most countries require listed
firms to maintain a non-optimal minimum percentage of independent directors
(Coles et al. 2008). Further corroboration comes from model 4’s interaction of the
percentages of independent directors and of female directors.
3
The results show that
Table 4 continued
Explanatory variables Dependent variable: log (Tobin’s Q)
(1) (2) (3) (4) (5)
Hansen’s J v
2c
(pvalue)
0.760834
(0.3831)
0.591412
(0.4419)
1.67064
(0.4337)
0.667229
(0.4140)
1.00007
(0.3173)
Heteroscedastic robust z statistics in parentheses
*, ** and *** refer to significance at the 10, 5 and 1 % levels, respectively. See Table 2for variable
definitions
a
Instrumented with the following variables: lag % women on board, lag % independents on board, lag
board size, number of employees (log), debt-to-equity ratio, working women index and revenue (log)
b
H0: instrumented variables are exogenous
c
H0: instruments are valid
3
This model does not include the variable percentage of female directors and the interaction term
because they are highly correlated and it is impossible to interpret their segregated effects. The
implication of dropping the percentage of female directors from this model is that we do not consider the
individual effect of this variable on firm performance, which then leads to an omitted variable problem.
The instrumental variable regression model (GMM) solves this problem and the estimated coefficients
remain robust.
S. Terjesen et al.
123
Table 5 GMM estimation of a multiple linear regression of ROA
Explanatory variables Dependent variable: log (1 ?ROA)
(1) (2) (3) (4) (5)
% women on board
a
0.0024** 0.0019*** – – –
(2.007) (3.042)
% independents on board
a
-0.0002 – 0.0003*** -0.0004 -0.0000
(-0.661) (2.769) (-0.873) (-0.151)
% women 9% independent
a
– – – 0.0001* –
(1.711)
C1 female director (dummy)
a
– – – – 0.0374*
(1.893)
Board size
a
-0.0018** -0.0015** -0.0016** -0.0018** -0.0025***
(-2.563) (-2.566) (-2.575) (-2.403) (-2.698)
Board meetings -0.0019*** -0.0018*** -0.0021*** -0.0021*** -0.0017***
(-4.039) (-3.735) (-4.652) (-4.316) (-3.587)
CEO/Chair duality 0.0053 0.0053 0.0053 0.0022 0.0063*
(1.446) (1.476) (1.442) (0.494) (1.748)
Debt-to-asset ratio -0.0008*** -0.0008*** -0.0008*** -0.0008*** -0.0008***
(-4.361) (-4.470) (-4.700) (-4.270) (-4.302)
Dividends 0.0387*** 0.0390*** 0.0449*** 0.0366*** 0.0393***
(9.014) (9.097) (9.721) (7.583) (8.745)
% free float -0.0000 -0.0001 -0.0001 -0.0001 -0.0000
(-0.294) (-0.615) (-1.247) (-0.740) (-0.403)
% institutional ownership 0.0004*** 0.0004*** 0.0004*** 0.0004*** 0.0004***
(4.751) (4.740) (5.252) (5.035) (4.635)
% insider ownership 0.0003 0.0003 0.0003 0.0003 0.0003
(0.745) (0.784) (1.042) (0.828) (0.749)
Assets (log) 0.0018 0.0017 0.0032* 0.0018 0.0021
(0.872) (0.794) (1.714) (0.827) (1.017)
GDP per capita (log) -0.0141*** -0.0143*** -0.0139*** -0.0160*** -0.0145***
(-4.997) (-5.054) (-4.508) (-5.822) (-5.215)
Market cap.-to-GDP (log) 0.0057 0.0069* 0.0083** 0.0070* 0.0064*
(1.501) (1.848) (2.332) (1.894) (1.741)
Common law -0.0098** -0.0122*** -0.0143*** -0.0104** -0.0134***
(-1.991) (-2.717) (-3.136) (-2.049) (-2.727)
Constant 0.0945*** 0.0881** 0.0542* 0.1271** 0.0899***
(2.696) (2.565) (1.954) (2.529) (2.619)
Industry dummies Yes Yes Yes Yes Yes
Observations 3,579 3,579 3,874 3,579 3,579
Wald v
2
636.480 640.845 559.085 609.242 564.336
(pvalue) (0.000) (0.000) (0.000) (0.000) (0.000)
GMM C statistic v
2b
(pvalue)
7.63722
(0.0220)
7.40141
(0.0065)
3.15124
(0.0759)
6.47187
(0.0393)
6.40341
(0.0407)
Multi-country study of board diversity
123
the board’s independence structure has a positive and statistically significant effect
on firm performance when the board is more gender diversified, thus supporting
Hypothesis 3. In models 4 and 5, the coefficients are negative and statistically
significant, suggesting that when a board has few or no women, the presence of
independent directors is detrimental to firm performance. Taken together, our results
indicate that a gender-imbalanced board signals to shareholders that management is
less independent and more entrenched, resulting in lower firm market values.
With respect to the controls, ROA is positive and statistically significant. This
result is expected because accounting profitability explains a significant fraction of
shareholders’ firm valuation (measured here as Tobin’s Q). Furthermore, we find
that large boards with many meetings and in which the CEO is also the Chair have
lower valuations. Firms that pay dividends have greater firm values. However, we
find no significant evidence regarding the relationship between the use of debt and
firm value, as predicted by Jensen (1986). Higher levels of ownership performance
are associated with lower levels of firm value, as predicted by the free-rider
hypothesis (Admati et al. 1994). Consistent with Ferreira and Matos (2008), we find
a positive relationship between institutional investors’ ownership and Tobin’s Q,
supporting the view that institutional investors are effective monitors of executive
management. Insiders’ ownership has no effect on firm performance.
We find that larger firms have higher Tobin’s Q values. With respect to country-
level controls, the results do not support the view that countries with higher GDPPC
and more developed financial markets have firms with higher values, as perceived
by the shareholders. This may be because investors in developing countries have
higher growth expectations and thus higher Tobin’s Q values.
The effects of gender and independent board structure on ROA (see Table 5) are
similar to those for Tobin’s Q (Table 4). When analyzed separately, the proportions
of independent directors and female directors are both positively associated with
ROA. Moreover, similar to the Tobin’s Q results, the coefficient of the percentage
of female directors is much higher than that of the percentage of independent
directors (models 2 and 3 in Table 5); ceteris paribus, a 1 % increase in female
directors results in a 0.2 % ROA increase; the same increase in independent
Table 5 continued
Explanatory variables Dependent variable: log (1 ?ROA)
(1) (2) (3) (4) (5)
Hansen’s J v
2c
(pvalue)
1.18949
(0.7555)
0.749835
(0.6873)
0.582977
(0.7472)
3.01271
(0.3897)
2.06776
(0.5585)
Heteroscedastic robust z statistics in parentheses
*, ** and *** refer to significance at the 10, 5 and 1 % levels, respectively. See Table 2for variable
definitions
a
Instrumented with the following variables: lag % women on board, lag % independents on board, lag
board size, number of employees (log), debt-to-equity ratio, working women index and revenue (log)
b
H0: instrumented variables are exogenous
c
H0: instruments are valid
S. Terjesen et al.
123
directors results in a 0.03 % ROA increase. Nevertheless, when a board has fewer or
no female directors, the effect of independent directors is negatively associated with
ROA (models 4 and 5).
Regarding the controls, similar to the Tobin’s Q analysis, ROA is negatively
affected by board size and the number of board meetings. We find a positive but not
significant relationship to CEO/Chair duality, suggesting that a Chair who is not
also the CEO has a greater effect on shareholders’ confidence than on operating
performance. Highly indebted firms are negatively associated with ROA. Similar to
the Tobin’s Q analysis, dividends are positively associated with a higher ROA. This
suggests that dividends may be a good governance mechanism (Easterbrook 1984);
however, there is no statistical relationship between ownership dispersion and
operating performance. Institutional ownership is strongly positively associated
with higher levels of firm operating performance, providing further evidence that
institutional investors are good monitors of internal agents. We find no evidence that
insiders’ ownership affects operating performance. Firms with more assets are
generally more profitable (higher ROA), but this effect is not statistically significant.
Firms based in higher GDPPC countries have lower operating performance. Finally,
there is a positive but not significant relationship between market development and
ROA.
4.2 Female directors, board of directors and ownership features
Given the previous results, where we provide some evidence that women enhance
the relationship between the independence of the board and firm performance, we
now investigate the interrelationship between the percentage of female directors
with other features of the board of directors and firm ownership. We are particularly
concerned with the interaction between gender diversity and the variables: board
meetings, CEO/chair duality, % free float, % institutional ownership, and % insider
ownership. The arguments suggest that there is a positive impact of the interactions
on firm performance as measured by Tobin’s Q and ROA.
Tables 6and 7provide the results of these tests. As expected, in Table 6, the
coefficients of all interaction terms are positive and statistically significant. This
reveals that the negative association between the board size, number of meetings,
and CEO/Chair duality to firm performance (measured by the firms’ Tobin’s Q) is
mediated by the level of board gender diversity. Furthermore, the association
between institutional ownership and insider ownership is highly dependent on the
level of board gender diversity. The results provided in Table 7are generally similar
to Table 6, corroborating the view that the extent of a board’s gender diversity plays
an important role in explaining firm performance.
4.3 Determinants of female presence on corporate boards
Given our finding that independent directors’ effectiveness depends on the board’s
gender composition, an important question is: What factors lead to females’
appointments on boards of directors? Prior research indicates that larger boards and
firms are more likely to have female directors (Bernardi et al. 2004,2006; Sealy and
Multi-country study of board diversity
123
Table 6 Interactions analysis—dependent variable Tobin’s Q (log)
Explanatory variables (1) (2) (3) (4) (5) (6)
% women 9board size
a
0.0058***
(6.287)
% women 9board meetings
a
0.0052***
(6.252)
% women 9CEO/Chair duality
a
0.1486***
(6.031)
% women 9% free float
a
0.0008***
(5.946)
% Women 9% institutional own.
a
0.0016***
(4.422)
% women 9% insider ownership
a
0.0107***
(3.445)
% independents on board
a
-0.0096*** -0.0106*** -0.0097*** -0.0118*** -0.0157*** -0.0009
(-4.917) (-5.184) (-4.741) (-4.902) (-4.017) (-0.544)
Board size
a
-0.1903*** -0.1333*** -0.0719* -0.1823*** -0.2569*** -0.0291
(-5.266) (-3.875) (-1.932) (-4.677) (-4.539) (-0.382)
Board meetings -0.0184*** -0.0631*** -0.0001 -0.0225*** -0.0317*** -0.0012
(-4.663) (-7.028) (-0.031) (-4.864) (-4.581) (-0.161)
CEO/chair duality -0.0866*** -0.0041 -1.4536*** -0.1146*** -0.1675*** -0.1210**
(-3.280) (-0.141) (-6.582) (-3.772) (-3.572) (-2.259)
ROA (log) 0.9882*** 0.9157*** 0.9797*** 0.8806*** 0.9369*** 1.4228***
(3.871) (3.574) (4.037) (3.354) (2.940) (3.778)
Debt-to-asset ratio 0.0008 -0.0002 -0.0001 0.0002 0.0010 0.0003
(0.973) (-0.254) (-0.065) (0.276) (0.859) (0.272)
Dividends 0.0468 0.0431 0.0554 0.0310 0.0753 0.1174*
S. Terjesen et al.
123
Table 6 continued
Explanatory variables (1) (2) (3) (4) (5) (6)
(1.402) (1.219) (1.352) (0.785) (1.273) (1.871)
% free float -0.0004 0.0006 -0.0014* -0.0077*** -0.0010 0.0001
(-0.570) (0.848) (-1.906) (-5.878) (-0.970) (0.121)
% institutional ownership 0.0014*** 0.0012** 0.0011** 0.0013** -0.0131*** 0.0012
(2.998) (2.393) (2.064) (2.305) (-3.817) (1.600)
% insider ownership 0.0004 0.0002 -0.0003 0.0002 0.0000 -0.0828***
(0.275) (0.163) (-0.175) (0.130) (0.022) (-3.135)
Assets (log) 0.0734** 0.0709** -0.0009 0.1110*** 0.1696*** -0.0057
(2.119) (2.028) (-0.022) (2.909) (3.159) (-0.071)
GDP per capita (log) -0.0334* -0.0132 0.0465** -0.0266 -0.0491* -0.0507
(-1.678) (-0.674) (1.975) (-1.268) (-1.797) (-1.082)
Market cap.-to-GDP ratio (log) -0.1122*** -0.0767** 0.0037 -0.0900** -0.1140** 0.0015
(-3.013) (-2.411) (0.107) (-2.387) (-2.168) (0.025)
Common law 0.1431*** 0.1304*** -0.0532 0.1263** 0.1316* 0.1963**
(2.952) (2.741) (-0.968) (2.289) (1.783) (2.294)
Constant 1.1943*** 0.8279** 1.0187** 0.8368** 0.9053* 0.7132
(3.217) (2.489) (2.407) (2.280) (1.731) (0.934)
Industry dummies Yes Yes Yes Yes Yes Yes
Observations 3,579 3,579 3,579 3,579 3,579 3,579
Wald v
2
377.448 382.514 334.110 306.089 157.787 302.429
(pvalue) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)
GMM C statistic v
2b
(pvalue)
121.415
(0.0000)
124.648
(0.0000)
134.063
(0.0000)
125.926
(0.0000)
120.712
(0.0000)
131.895
(0.0000)
Multi-country study of board diversity
123
Table 6 continued
Explanatory variables (1) (2) (3) (4) (5) (6)
Hansen’s J v
2c
(pvalue)
0.808408
(0.3686)
0.695258
(0.4044)
0.278976
(0.5974)
0.690288
(0.4061)
.616388
(0.4324)
0.576487
(0.4477)
Heteroscedastic robust z statistics in parentheses
*, ** and *** refer to significance at the 10, 5 and 1 % levels, respectively. See Table 2for variable definitions
a
Instrumented with the following variables: lag % women on board, lag % independents on board, lag board size, number of employees (log), debt-to-equity ratio,
working women index and revenue (log)
b
H0: instrumented variables are exogenous
c
H0: instruments are valid
S. Terjesen et al.
123
Table 7 Interactions analysis—dependent variable: 1 ?ROA (log)
Explanatory variables (1) (2) (3) (4) (5) (6)
% women 9board size
a
0.0003***
(2.619)
% women 9board meetings
a
0.0003***
(2.699)
% women 9CEO/chair duality
a
0.0057**
(2.355)
% women 9% free float
a
0.0000***
(2.581)
% women 9% institutional own.
a
0.0001**
(1.997)
% women 9% insider ownership
a
0.0004*
(1.835)
% independents on board
a
-0.0003 -0.0003* -0.0003 -0.0004* -0.0004 0.0000
(-1.598) (-1.701) (-1.373) (-1.656) (-1.321) (0.410)
Board size
a
-0.0042*** -0.0017*** -0.0020*** -0.0022*** -0.0026*** -0.0016**
(-3.308) (-2.619) (-2.807) (-3.006) (-2.860) (-2.219)
Board meetings -0.0019*** -0.0042*** -0.0015*** -0.0020*** -0.0022*** -0.0017***
(-4.073) (-4.442) (-2.939) (-4.321) (-4.455) (-3.358)
CEO/chair duality 0.0043 0.0085** -0.0474** 0.0031 0.0016 0.0034
(1.139) (2.248) (-2.079) (0.803) (0.366) (0.835)
Debt-to-asset ratio -0.0008*** -0.0008*** -0.0007*** -0.0008*** -0.0007*** -0.0007***
(-4.256) (-4.400) (-4.185) (-4.315) (-4.107) (-3.959)
Dividends 0.0389*** 0.0381*** 0.0385*** 0.0367*** 0.0385*** 0.0423***
(8.975) (8.733) (8.764) (8.100) (8.247) (9.190)
% free float 0.0000 0.0000 -0.0001 -0.0004** -0.0000 0.0000
Multi-country study of board diversity
123
Table 7 continued
Explanatory variables (1) (2) (3) (4) (5) (6)
(0.056) (0.455) (-0.555) (-2.304) (-0.302) (0.117)
% institutional ownership 0.0004*** 0.0003*** 0.0003*** 0.0004*** -0.0002 0.0003***
(4.827) (4.563) (4.128) (4.681) (-0.610) (4.362)
% insider ownership 0.0003 0.0003 0.0002 0.0003 0.0004 -0.0025
(1.062) (0.912) (0.706) (1.015) (1.103) (-1.519)
Assets (log) 0.0014 0.0016 0.0017 0.0018 0.0023 0.0031
(0.675) (0.780) (0.795) (0.855) (1.079) (1.474)
GDP per capita (log) -0.0138*** -0.0127*** -0.0115*** -0.0131*** -0.0141*** -0.0159***
(-4.768) (-4.235) (-3.480) (-4.422) (-4.867) (-5.150)
Market cap.-to-GDP ratio (log) 0.0044 0.0061* 0.0083** 0.0064* 0.0067* 0.0077**
(1.140) (1.681) (2.285) (1.744) (1.778) (1.979)
Common law -0.0092** -0.0097** -0.0134*** -0.0110** -0.0121** -0.0042
(-2.028) (-2.167) (-2.776) (-2.406) (-2.477) (-0.748)
Constant 0.1262*** 0.1060*** 0.0917** 0.1166*** 0.1204*** 0.0672*
(3.026) (2.869) (2.486) (2.934) (2.648) (1.769)
Industry dummies Yes Yes Yes Yes Yes Yes
Observations 3,579 3,579 3,579 3,579 3,579 3,579
Wald v
2
588.819 582.731 602.533 587.862 498.002 583.739
(pvalue) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)
GMM C statistic v
2b
(pvalue)
7.00186
(0.0081)
6.38728
(0.0115)
5.98307
(0.0144)
6.07764
(0.0137)
4.29923
(0.0381)
4.75547
(0.0292)
S. Terjesen et al.
123
Table 7 continued
Explanatory variables (1) (2) (3) (4) (5) (6)
Hansen’s J v
2c
(pvalue)
2.08365
(0.7204)
1.79756
(0.7729)
3.06481
(0.5470)
2.58808
(0.6289)
4.78858
(0.3097)
3.96886
(0.4102)
Heteroscedastic robust z statistics in parentheses
*, ** and *** refer to significance at the 10, 5 and 1 % levels, respectively. See Table 2for variable definitions
a
Instrumented with the following variables: lag % women on board, lag % independents on board, lag board size, number of employees (log), debt-to-equity ratio,
working women index and revenue (log)
b
H0: instrumented variables are exogenous
c
H0: instruments are valid
Multi-country study of board diversity
123
Vinnicombe 2013). We expect that female directors are more prevalent in firms with
more independent directors, a split of CEO and Chair roles, and a more complex
firm environment, as measured by the log of the firm’s assets, board size, number of
employees, and Tobin’s Q. We investigate the presence of female firms in terms of
three variables: (1) dummy where 1 =board includes at least one woman and
0=otherwise, (2) total number of female directors, and (3) percentage of female
directors. We employ three models: (1) logit, (2) Tobit (left censored), and (3) Tobit
(left and right censored) (see Table 7). We find that female representation is
positively associated with the total number of independent directors, board size, and
environmental complexity, and negatively related to CEO-Chair duality. Further-
more, larger boards are more likely to have female directors. All variables
representing high levels of complexity in the firm’s environment are positively
associated with greater female board representation (Table 8).
With respect to the controls, debt financing is positively associated with greater
female representation but is not significantly different from zero. Another
interesting finding is that firms that pay dividends are more likely to have female
directors, possibly because firms that pay dividends interact more with the financial
market and are thus more motivated to provide signals about board effectiveness.
There is no specific evidence as to whether institutional ownership and insider
ownership promote gender-diversified boards. With respect to the country-level
controls, firms in countries with more females in the labor market are more likely to
have firms with female board members. Surprisingly, female representation on
boards is not a characteristic of richer countries; rather, there is a negative
relationship between a country’s GDPPC and female board representation. Finally,
firms in countries with more developed financial markets have more women on their
boards. Again, this finding is consistent with the argument that a firm with more
corporate governance concerns is more likely to pay attention to board gender
structure.
4.4 Robustness checks
The previous analyses assume a linear relationship between board structure and firm
performance; however, the effect of gender diversity on firm performance may vary
by level of board independence. We re-estimate the regressions in Tables 4and 5
for two groups of board structures: (1) an outsider-dominated board ([50 %
independent) and (2) an insider-dominated board (\50 % independent). The results
are generally maintained; however, the effect of the percentage of women on firm
performance is stronger when the board is insider-dominated.
We also re-estimated the regressions for different levels of women’s participa-
tion. As our sample has a significantly lower level of female directors, we conduct a
sensitivity analysis with two groups: (1) firms with no or one female director and (2)
firms with two or more female directors. The results hold, but the magnitudes of the
effects of the percentages of female and independent directors are stronger when the
board has fewer women.
Although we include many important industry and country level controls, other
factors may impact firm performance. The estimated standard errors (which are
S. Terjesen et al.
123
Table 8 Determinants of female participation on boards of directors
Explanatory variables Model (dependent variable)
Logit
[dummy (women on
board)]
Tobit, left censored
(# of women on
board)
Tobit, left and right
censored
(% women on board)
% independents on board 0.03076***
(8.974)
0.01774***
(4.298)
0.18275***
(5.354)
CEO/chair duality -0.18525**
(1.982)
-0.11724**
(1.973)
-1.26536**
(2.086)
Assets (log) 0.12905**
(2.574)
0.11875***
(3.485)
1.01347***
(3.031)
Board size 0.23959***
(11.957)
0.17456***
(14.463)
0.85509***
(7.663)
Employees (log) 0.17392***
(4.798)
0.15578***
(5.648)
1.55681***
(5.617)
Tobin’s Q (log) 0.17652*
(1.849)
0.16165***
(2.582)
1.55772**
(2.299)
Debt-to-assets ratio 0.00321
(1.356)
0.00250
(1.585)
0.02882*
(1.832)
Capital expenditures (log) -0.19233***
(6.404)
-0.15287***
(5.650)
-1.49876***
(6.146)
Dividends 0.34528***
(3.199)
0.15551**
(2.312)
1.77696**
(2.495)
% institutional ownership 0.00100
(0.679)
0.00031
(0.323)
0.00112
(0.112)
% insider ownership -0.00281
(0.717)
-0.00205
(0.723)
-0.01486
(0.478)
GDP per capita (log) -0.17205***
(3.352)
-0.15240***
(4.320)
-1.40896***
(3.837)
Market cap.-to-GDP ratio
(log)
0.27847***
(3.037)
0.24290***
(4.069)
1.95542***
(3.404)
% working-women index 0.03305***
(5.195)
0.02881***
(6.474)
0.29367***
(6.407)
Constant -8.73768***
(9.670)
-6.82055***
(10.488)
-55.71631***
(8.753)
Industry dummies Yes Yes Yes
Observations 3,490 3,490 3,490
Wald v
2
(pvalue)
675.69
(0.000)
––
F-Stat
(pvalue)
– 56.33
(0.000)
44.26
(0.000)
Pseudo R
2
0.2860 0.1632 0.0686
Heteroscedastic robust z statistics in parentheses
*, ** and *** refer to significance at the 10, 5 and 1 % levels, respectively
Multi-country study of board diversity
123
robust to heteroscedasticity of unknown form) are more accurate when clustered in
countries and industries, although the coefficient estimates remain the same and
continue to be efficient (Wooldridge 2002). To address this potential improvement,
we re-estimate all models with z statistics computed from standard errors clustered
by country and industry. The results are generally the same: the board composition z
statistics (the percentage of female directors and independent directors) are still
highly significant, however other controls, particularly country-level, reveal
significantly lower z statistic values.
Finally, we conduct two sensitivity tests: (1) we re-estimate the models by
excluding financial firms because banks may be subject to different forces that
mediate firm performance; and (2) we exclude all observations from the United
States and the United Kingdom.
4
The estimates reveal robust and qualitatively
similar results.
5 Discussion
Taken together, our research raises a number of important issues for policy,
practice, and theory. Although some countries have realized the importance of
gender-balanced boards of directors, the governance debate has given much more
attention to boards’ independence structures. That is, virtually all corporate
governance codes address the need for firms to have boards composed of outside
‘independent’ directors, whereas only a few codes address boards’ gender structure.
Given this study’s finding that a more gender-diversified board is likely to enhance
its independence and effectiveness, corporate governance codes worldwide should
give at least the same importance to gender diversity as they give to the structure of
board independence. In fact, acknowledging the role of women in corporate
governance best practices can potentially increase the effectiveness of independent
directors as it decreases the negative signal of an unbalanced gender board. We
stress, however, that the results reported do not suggest that board independence is
irrelevant. The empirical results merely indicate that board independence becomes
secondary when gender diversity is not addressed.
Thus, in terms of practical implications, this paper supports the notion that
gender diversity is an important corporate governance issue. In fact, if firms wish to
provide correct signals regarding board effectiveness, they should also consider
gender diversity. Exogenously requiring the addition of outside directors to a board
does not necessarily lead to a more independent board. The qualitative aspects of the
board independence and effectiveness such as gender diversity should also be
considered when analyzing the board independence and effectiveness. Our results
also support the notion that gender diversity might act as a substitute for board
independence.
From a theoretical perspective, our findings suggest that a multi-theoretical lens
explanation can be quite powerful. We find support for theories of agency, resource
dependency, upper echelons, and gender roles.
4
We thank a reviewer for this suggestion.
S. Terjesen et al.
123
Before concluding, we wish to acknowledge four limitations that point to future
research directions. First, given the cross-sectional data, panel studies with longer
time spans would provide greater insights into the proposed relationships.
Unfortunately, this data is not available for a significant number of countries.
Future research could examine one particular country’s firms and the evolution of
the share of gender board diversity over time. This line of research could consider
the impact of the speed and scope of gender board quota regulations on firm
performance and other outcomes. Second, further research should classify female
directors as independent and non-independent, extending research by Zelechowski
and Bilimoria (2004). This data was also unavailable for the large number of
countries in the present analysis. This work could be extended by considering
directors who may be classified as independent but who are actually affiliated with
the firm through prior employment or ongoing business. Third, our findings would
benefit from considering different types of governance models, such as the one-tier
system in which executive managers are part of a firm’s board of directors of the
two-tier system which includes supervisory and management boards. Investigating
this knowledge void could advance our understanding of comparative corporate
governance systems. Fourth, while we included many important controls, several of
which were omitted in prior studies, other factors may influence financial
performance. For example, firm age as unavailable in our data. Future research
should consider firm age as there is considerable evidence of differences in
corporate governance structures and performance between new ventures and larger,
established counterparts (Gabrielsson and Huse 2004).
Finally, our study suggests several promising avenues for future research. First,
researchers could investigate other types of board diversity (e.g., education and
work background, ethnicity, age). This research could meaningfully extend our
study of observable (gender) and non-observable (independence) diversity by
examining other combinations of diversity. The concept of faultlines (Lau and
Murnighan 1998) may be useful here as a group such as a corporate board can be
divided along several lines. For example, following the gender board quotas in
Norway and Spain, the new directors were more likely to be female, younger, and
possess a graduate degree (Ahern and Dittmar 2012; Gonza
´lez Mene
´ndez and
Martı
´nez Gonza
´lez 2012). Second, firm performance could be measured in non-
financial terms, e.g., social performance in terms of the pipeline of women and
minority managers (e.g., Bilimoria 2006) or environmental sustainability practices
or other social responsibility practices. This line of enquiry would extend the
present focus of the ‘business case’ on financial performance to other firm outcomes
which are relevant to society. Third, longitudinal research could examine the human
capital, social capital, and other resources that independent and female directors
contribute to their boards. This analysis would shed light on how directors build
meaningful stocks of resources from the initial venture through various firm stages
such as initial public offering or acquisition. Fourth, researchers could access
boardrooms (and other material normally outside the public domain) to examine
how independent and female directors contribute to board governance processes.
Building on work by Nielsen and Huse (2010), researchers could examine the
interplay of power dynamics, gender roles, conflict, and agency. Future research
Multi-country study of board diversity
123
could also consider how strategic designs affect corporate governance (Shen and
Gentry 2014), including the composition of the board.
6 Conclusion
This study examines the role of female directors in enhancing the independence and
effectiveness of boards. Our results suggest that female directors send a positive
signal to the public regarding a firm’s ethical behavior. Firms with female directors
have better financial performance. Furthermore, the positive firm performance effect
of many independent directors is only positive if that board is also gender
diversified. This evidence is important because recent studies questioned whether
board independence improves performance. Our study also offers new insights into
the determinants of greater female presence on boards. We find that firms with
concerns about board independence and effectiveness and those operating in
complex environments are more likely to have female directors. Virtually all
national corporate governance codes address the need for boards to be composed of
independent directors; yet only sixteen national codes and thirteen national quotas
address boards’ gender structure. Our results indicate that board independence is
secondary when gender diversity is not addressed- thus board gender diversity is an
important corporate governance issue.
Acknowledgments We thank Editor Roberto Di Pietra and the three anonymous reviewers for helpful
comments on earlier versions.
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Siri Terjesen is an Assistant Professor at the Kelley School of Business at Indiana University and a
Visiting Research Fellow at the School of Economics and Management at Lund University. She is an
Associate Editor of Academy of Management Learning and Education and Small Business Economics.
Her research interests include corporate governance and entrepreneurship. She holds a Ph.D. from
Cranfield and Masters from the Norwegian School of Economics (NHH).
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Eduardo Barbosa Couto is Associate Professor and Vice-President of ISEG-Instituto Superior de
Economia e Gesta
˜o, in University of Lisbon. He has a Ph.D. in Business Administration (Finance) from
the Manchester Business School, University of Manchester, UK. He has numerous academic and
professional activities, including: Supervision of Undergraduate; Master and Postgraduate Courses in
Financial Investments, Accounting, Taxes and Corporate Finance; Supervisor of doctoral and Master
students; Member of Academic and professional Committees; Supervision of ERAMUS Programme for
undergraduate students in Finance; Member of Scientific Committee in Portuguese Banking School of
Management; Invited Associate Professor in Portuguese Banking Institute. He has published academic
papers in corporate finance and entrepreneurship and worked with the banking sector, capital market, and
corporate consultancy.
Paulo Morais Francisco is an invited assistant professor in the Lisbon School of Economics &
Management. He also holds a position of economist at the Portuguese Securities Market Commission
(CMVM). He received his undergraduate education in management (2003), Masters in Business
Administration (2008) and Ph.D. in Management and Finance (2013) at the Lisbon School of Economics
& Management, University of Lisbon in Portugal. His research interests are in corporate governance and
corporate finance.
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