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In the wake of the recent debt crisis in Europe, we investigate the influence of board diversity on financial fragility and performance of European banks. Corporate governance codes in Europe recommend unitary and dual-board systems; therefore, we believe that the influence of board diversity may vary across governance mechanisms and that no other studies have addressed these variations and their influence on financial fragility across European countries. The results show that a critical mass of female representation on both the supervisory board and the board of directors may reduce banks’ vulnerability to financial crisis. However, interestingly, we find evidence that female directors on the management board are not risk averse. We argue that the degree of risk taking for female directors may vary based on their roles (non-executive or executive) and that female and male executive directors may have the same risk taking behaviour. Our empirical results provide guidelines to the regulators in Europe with respect to the recently approved proposal by the European Parliament on female representation.
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1
Board Diversity and Financial Fragility: Evidence from
European Banks
Hisham Farag
1
Birmingham Business School, University of Birmingham, Edgbaston Park Road,
Birmingham, UK, B15 2TT. h.farag@bham.ac.uk
Christine Mallin
Norwich Business School, University of East Anglia, UK.
ABSTRACT
In the wake of the recent debt crisis in Europe, we investigate the influence of board diversity
on financial fragility and performance of European banks. Corporate governance codes in
Europe recommend unitary and dual-board systems; therefore, we believe that the influence
of board diversity may vary across governance mechanisms and that no other studies have
addressed these variations and their influence on financial fragility across European countries.
The results show that a critical mass of female representation on both the supervisory board
and the board of directors may reduce banks’ vulnerability to financial crisis. However,
interestingly, we find evidence that female directors on management board are not risk averse.
We argue that the degree of risk taking for female directors may vary based on their roles and
that female and male executive directors may have the same risk taking behaviour. Our
empirical results provide guidelines to the regulators in Europe with respect to the recently
approved proposal by the European parliament on female representations.
Keywords: Corporate Governance, Corporate Finance, Board Diversity, Board Structure.
This version December 2016
Accepted for Publication in the International Review for Financial Analysis
Journal
1
Corresponding author
2
1. Introduction
World economies have experienced a deep recession due to the global financial crisis. The
wave of banks’ collapses and scandals in the last decade has fuelled the drive for improved
corporate governance. In particular, there has been an increased emphasis on board diversity
with the main focus being on gender diversity. The concept of board diversity as a means for
improving corporate governance practices in the financial sector has proliferated in recent
years following the onset, and the aftermath, of the financial crisis, such that there is a
growing intervention by the regulators to implement quotas
1
for corporate boards, a primary
example of this approach being that of Norway (Mateos de Cabo et al, 2012).
Recently, the EU Commission (2012) agreed a proposal for a Directive to improve the gender
balance of non-executive directors (NEDs) in listed companies by 1 January 2020. The
European Parliament overwhelmingly approved proposals that all EU listed companies
except small and medium size enterprises (SMEs) should substantially increase the number of
women on EU corporate boards by setting a minimum objective that 40% of NEDs should be
of the ‘under-represented gender’, generally women.
There has been an on-going debate in the literature regarding the impact of diversity for many
years. Jensen (1993) argued that more diverse boards with different perspectives and varied
skills may lead to more efficiency in resource utilisation. The proponents of board diversity
argue that diversity brings a variety of backgrounds, skills and perspectives to the boardroom,
therefore directors and companies may benefit from these diverse social and occupational
experiences in developing new products and strategies (Anderson et al., 2011). On the other
hand, the opponents of diversity claim that the cost of diversity in terms of communication,
co-ordination and conflict among directors with different backgrounds - exceeds its benefits
(Putnam, 2007).
The existing body of the literature tends to focus more on board diversity for non-financial
companies. Adams and Mehran (2012) argue that little is known about board effectiveness in
the financial sector as the vast majority of the existing literature tends to exclude financial
companies from their samples. Few studies have been conducted on board diversity in the
banking sector. Those studies have tended to focus only on one specific country namely US
e.g. Muller-Kahle and Lewellyn (2011), Berger et al., (2014) and Pathan and Faff (2013).
3
In the European Union, corporate governance codes recommend a unitary board system in 8
countries e.g. UK and Sweden and a dual-board system in 10 countries e.g. Germany and
Netherlands, though there might be some exceptions
2
. Therefore, we argue that using pooled
data from European banks with different governance mechanisms may lead to biased results.
No other studies- to the best of our knowledge- have addressed the variations in governance
mechanisms as the proportion of female directors may vary between the board of directors in
the unitary governance mechanism and the supervisory and management boards within the
dual board mechanism. Moreover, our study is timely and has clear policy as the empirical
results provide guidelines to the regulators in Europe with respect to the recently approved
proposal by the European parliament on female representations. Finally and most importantly,
none of the existing studies investigate the influence of board diversity on the financial
fragility. We try to fill these gaps in the literature using a unique hand collected dataset from
17 European countries.
In this paper, we investigate the influence of board diversity on both financial fragility and
performance using a sample of 99 European banks from 17 countries over the period 2004-
2012. We find that beyond a critical mass of 18% and 21% female directors on the board of
directors and the supervisory boards respectively, banks’ vulnerability to financial crisis is
significantly less. However, interestingly, we find evidence that female directors are not risk
averse as diversity- financial fragility nexus on management boards is also non-linear but has
a U shape relationship and that appointing a female director beyond a critical mass of 24%
increases banks’ risk. This result is consistent with Adams and Funk (2012) and Farag and
Mallin (2016) as they argue that female directors are not risk-averse compared with their
male counterparts. We argue that the degree of risk taking for female directors may vary
based on their roles and that female and male executive directors may have the same risk
taking behaviour. Finally and consistent with the resource dependence theory, we find a
positive and significant relationship between the proportion of female directors and financial
performance for both the board of directors and the supervisory boards.
The remainder of the paper is structured as follows. The next section discusses the
theoretical perspectives deriving board diversity followed by a section on the literature and
hypotheses development. We then present the data and the empirical models followed by the
results and the robustness tests. Finally, we conclude the paper with a discussion of the main
findings and the policy implications.
4
2. Board Diversity: Theoretical Perspectives
Several theoretical frameworks from different disciplines provide insights into the economic
benefits and the influence of board diversity (Carter et al., 2010) e.g. agency, resource
dependence, human capital, and social psychology theories. Agency theory assumes that a
higher proportion of independent NEDs may lead to a better monitoring function of the board.
Therefore, boards should include the appropriate mix of experience and backgrounds to better
exercise their monitoring role and to evaluate management and assess business strategies
(Hillman and Dalziel, 2003 and Adams and Ferreira, 2009). Female representation on the
board may improve the board’s monitoring role and this may lower agency costs (Carter et al.,
2003; Hillman and Dalziel, 2003; Farag and Mallin, 2016). Carter et al. (2003) and Carter et
al. (2010) argue that more diverse boards with different backgrounds are more independent
and thus provide a better monitoring role. Nonetheless, agency theory does not provide strong
support for the link between board diversity and financial performance (Carter et al., 2003).
According to the resource dependence theory, the presence of female directors on the board
brings different benefits and resources to the company (Carter et al., 2010). Moreover,
females bring forward new opinions and perspectives that would not otherwise be
demonstrated if the board were to be homogeneous, and this may improve financial
performance (Mateos de Cabo et al., 2012). Therefore, the resource dependence theory
provides the foundation and convincing theoretical argument with regard to board diversity
and suggests that diverse boards have a broader range of more talented and well-connected
directors. Moreover, board diversity per se may send a positive signal to the labour market
(Carter et al., 2010).
Furthermore, different types of directors provide different experiences, backgrounds and
different human capital which may lead to a higher ability to address different environmental
dependencies (Hillman et al., 2000). Human capital theory states that directors with different
experiences, sets of skills and educational backgrounds may lead to more diverse boards and
thus benefit the overall performance of the company (Terjesen et al., 2009). Moreover, more
diverse boards with different perspectives and varied skills may lead to more efficiency in
resource utilisation (Jensen, 1993), better management quality (unique human capital) and
hence better financial performance (Terjesen et al., 2009). Therefore, human capital theory
5
complements the resource dependence theory in that board diversity may influence
companies’ financial performance (Carter et al., 2010).
According to contingency theory, internal and external circumstances are one of the main
determinants of human capital and hence the influence of gender diversity on financial
performance may vary based on companies’ internal and external environments (Adams and
Ferreira, 2009). On the other hand, the social psychological concept of minority status, which
is derived from social impact theory, states that majority status groups have a remarkable
influence on the decision making process (Carter et al., 2010). Therefore females, being
usually in the minority on diverse boards, may not have the power to influence the board as
the result of the internal group dynamics of the board (Westphal and Milton, 2000). Moreover,
more diverse boards may lead to more conflict and diverse opinions which make the decision
making process time-consuming and less effective (Campbell and Vera, 2008, Lau and
Murnighan, 1998 and Carter et al., 2010).
Drawing on the critical mass theory of Kanter (1977a, 1977b), Joecks et al (2013) argue that
the skills that female directors (minority) may bring into the group are not the main
determinant of board composition unless a critical mass of female directors has been
appointed
3
. Kogut et al (2014) argue that female quotas might create a critical mass of female
directors to tip the equilibrium to structural equality defined as “the degree to which women
directors are connected without relying upon male intermediaries”.
3. Literature Review and Hypotheses Development
3.1 Board Diversity in the Banking Industry
The literature on corporate governance, and board diversity in particular, is limited for
financial institutions. The existing literature has tended to focus on the influence of board
diversity on non- financial companies. Therefore, relatively little is known about the
influence of board diversity in financial institutions (Adams and Mehran, 2012). However,
there have been a few studies which have focussed on the impact of board diversity in the
banking industry; these studies have tended to focus on the US; see for example Richard
(2000); Adams and Funk (2012); and Hagendorff and Keasey (2012). Board diversity in the
European banking sector has received scant attention except for the studies by Mateos de
Cabo et al, (2011 and 2012). Moreover, no other studies-to the best of our knowledge - have
6
addressed the variations in governance mechanisms across European countries. Therefore, we
believe that there remains a gap in the literature regarding the influence of board diversity on
financial fragility and performance in European banks.
3.2 Board Diversity and Financial Fragility
World economies have experienced a deep recession due to the global financial crisis 2007-
2008. The crisis hit Europe by the contagion effect and concerns were raised about the
financial fragility of various financial institutions. Subsequently, a large number of financial
institutions collapsed or were bailed out by governments during the global financial crisis e.g.
RBS and HBOS in the UK; Dexia, Fortis, Hypo Real Estate and UBS in continental Europe
(Ivashina & Scharfstein, 2010 and Erkens et al., 2012). Grove et al. (2011) define financial
fragility as a bank’s vulnerability to a financial crisis measured by Loan quality measures e.g.
Non-Performing Assets (NPA). Beltratti and Stulz, (2012) use other measures of financial
fragility e.g. the percentage of liquid assets to total assets. They argue that banks with more
liquid assets will be in a better position to cope with financing difficulties. Moreover, earlier
Eng and Nabar (2007) used the percentage of loan loss reserve to gross loans as an alternative
measure of financial difficulties.
The stereotype that women are more risk averse than men may explain the low proportion of
females sitting on the banks’ boards (Sunden and Surette, 1998). Moreover, this stereotype is
the main reason for the “Glass Ceiling” on the corporate promotion ladder in banks (Mateos
de Cabo et al., 2012). Adams and Ferreira (2009) argue that boards of directors tend to be
more homogeneous and less diverse when companies are operating in riskier environments.
Therefore, there might be less likelihood of hiring female directors in banks due to the high
financial risk associated with this industry. Moreover, firms with more gender diverse boards
have been found to be less involved in sub-prime lending (Muller-Kahle and Lewellyn, 2011).
Furthermore, female CEOs might be seen as more risk averse compared with their male
counterparts as they may rely on less leverage (Graham et al., 2013), less long-term debt, and
their companies have less earning volatility, higher survival rate (Faccio et al., 2016) and less
involved in acquisitions (Huang and Kisgen, 2013). Female CEOs also used to exercise their
share options early compared with their male counterparts (Huang and Kisgen, 2013). Arun
et al (2015) find that the higher the proportion of female independent directors the more
7
restrained earnings management practices in the UK. Sila et al (2016) find that unobserved
company heterogeneity may derive the negative genderrisk relation.
Adams and Funk (2012) find that female and male directors have substantial differences with
respect to their risk attitude. This might be due to the belief that women may not perform well
in less competitive environment (Gneezy et al., 2003 and Niederle & Vesterlund, 2007).
Consistent with the existing literature, Adams and Funk (2012) find that female directors are
more benevolent and universally concerned but less power oriented than male directors.
However, Adams and Funk (2012) show that some of the "typical" population gender gaps
appear to reverse for directors, in Sweden, since female directors are found to be more open
to change and less risk-averse than their male counterparts. Therefore, appointing a female
director need not lead to less risk-averse decisions as female directors are more risk-loving
than male directors (Adams and Funk, 2012).
Mateos de Cabo et al., (2012) find that the proportion of female directors in boardrooms is
higher for lower-risk banks; in addition, banks with a growth orientation are more likely to
appoint female directors. The above discussion shows that the findings of the existing
literature support the negative relationship between board diversity and the attitude towards
risk. To the best of our knowledge, there are no other studies that investigate the influence of
diversity on financial fragility in European banks. Therefore, based on the above discussion
we formulate our first hypothesis:
H1: There is a negative relationship between the proportion of female directors and
bank’s financial fragility.
3.3 Board Diversity and Financial Performance
The board diversity-financial performance nexus has been investigated in the academic
literature for non-financial companies, however, there is mixed evidence and no real
agreement on the impact of board diversity on firm performance.
This could be due to the discrepancies in sample sizes, time periods, and industries in
addition to the econometrics problems e.g. endogeneity. The diversity- performance nexus is
more problematic when quotas are applied due to some methodological issues e.g. the exact
date of the quota event, the choice of control group in the context of experimental studies,
8
sample selection and the influence of other confounding effects e.g. other governance-related
reforms (Ferreira, 2015). Moreover, there is no formal theory that interprets the diversity-
performance nexus for financial companies therefore the existing literature largely relies on
the results of the empirical studies of non-financial companies (Pathan and Faff, 2013).
A few studies find no positive impact of board diversity on financial performance. Randøy et
al. (2006) investigate the impact of gender, age and ethnic diversity on the financial
performance of the top 500 companies in Denmark, Norway and Sweden and find no
significant impact on companies’ financial performance. Similarly, Farrell and Hersch (2005)
and Francoeur et al. (2007) find that more gender diverse boards have no impact on company
performance in the US and Canada respectively. However, Ryan and Haslam (2005) find that
during a period of poor market performance, companies who appointed female directors had
tended to have negative performance during the preceding five months compared with
companies who appointed male directors.
Moreover, Adams and Ferreira (2009) find that female directors have an overall negative
effect on firm performance in the US although they enhance the overall effectiveness of the
board. On the other hand, a large strand of the literature finds that there is a positive influence
of board diversity on financial performance, mostly in the US; see for instance, Erhardt et al.
(2003); Miller and Triana (2009) in addition to Campbell and Vera (2008) in Spain. The latter
study highlights that the causal relationship between these two endogenous variables runs
from board diversity to financial performance. Moreover, the diversity-performance nexus
can be partially mediated by both innovation and company reputation (Miller and Triana
(2009).
There have been relatively few studies that investigate the relationship between board
diversity and financial performance in the financial sector. Pathan and Faff (2013) study large
US bank holding companies over the period 1997-2011 and find that pre-Sarbanes-Oxley
(SOX), i.e. 1997-2002, gender diversity improves bank performance; however this positive
effect declines post-SOX (2003-2006) and the financial crisis (2007-2011) periods
respectively. Kim and Starks (2016) find that directors’ heterogeneity and the proportion of
female directors in particular result in higher company valuation. Similarly, Bantel and
Jackson (1989) find that innovative banks are characterised by heterogeneous boards and this
9
facilitate decision making process. Board diversity in the financial sector is also found to
have a positive influence on corporate social performance (Siciliano, 1996); and company’s
competitive advantage (Richard, 2000). Moreover, positive announcement returns to mergers
are reported by more occupationally diversified boards (Hagendorff and Keasey, 2010 and
2012).
We believe that board diversity creates both costs and benefits to companies. Drawing on the
resource dependence and the human capital theories, we believe that female directors may
bring to the board different backgrounds, experience and opinions and this may lead to better
financial performance. Therefore, we expect that more diverse boards may have better
financial performance if the benefits of diversity - in terms of better advisory and monitoring
roles - exceed the costs of communication and conflict between managerial levels. Based on
the above discussion we formulate our second hypothesis:
H2: There is a positive relationship between the proportion of female directors and
bank’s financial performance
4. Methodology
4.1 Data and Sample
We hand collect data on board diversity, financial fragility, financial performance and
governance characteristics for a sample of listed and private European banks over the period
2004-2012. We constrain our sample to banks located in the EU as they are broadly subject to
similar regulatory and governance backgrounds. Our sample also includes banks operate in
Switzerland as part of the single market. Swiss banks are the most widely regarded in Europe as
they have unique reputation in banking sector globally. Our main source is the The Bankers top
1000 World Banks” report which includes financial institutions from all over the globe from 6
continents. The total number of banks included in the report from EU countries and Switzerland
is 223 banks. We exclude EU courtiers with less than 2 banks e.g. Bulgaria, Hungary, Malta,
Slovakia and Luxemburg (11 banks). To be consistent with the literature we exclude credit
institutions and real estate and mortgage banks due to the differences in their operating structures
(58 institutions.) Moreover, we excluded 55 banks with missing data either from Bankscope,
Thomson One Banker and Datastream databases or the annual reports and the websites of the
respective banks. Thus our final sample is 99 banks
4
. Our sample banks is located in 17 countries
namely Austria, Belgium, Denmark, Finland, France, Germany, Greece, Cyprus, Italy, Ireland,
10
Netherlands, Poland, Portugal, Spain, Sweden, Switzerland, and the UK
5
. We excluded Norway
as it introduced a compulsory gender quota for listed companies in 2008 by which the percentage
of female NEDs sitting on the board had to be at least 40%. Moreover, Norway is not a member
state in the EU
6
.
Our sample includes both board structures, i.e. unitary and dual boards Therefore, we classify our
sample into 53 banks with unitary boards and 46 dual board banks for which a complete set of
information is available. Our dataset is unbalanced panel data and consists of 462 and 393 bank-
year observations for unitary and dual board structures respectively over the period 2004-2012.
We measure gender diversity by the percentage of female directors sitting on the board
7
.
Moreover, as the appointment of additional female directors may enhance financial
performance or reduce risk, we use the squared percentage of female directors as an
independent variable in the estimation. We define financial fragility as a banks vulnerability
to a financial crisis. Grove et al. (2011) use Non-Performing Assets (NPA) ratio as a measure
of financial fragility. NPA ratio is calculated by dividing the level of non-performing assets
to total loans. Grove et al. (2011) argue that loan quality measures e.g. NPA are often used by
rating agencies to assess the overall ratings of the banks and are considered to be an essential
credit quality measure with respect to the banks’ lending practices. However, we use a stricter
measure of banks’ financial fragility namely the ratio of impaired loans to gross loans.
Moody’s rating agency argue that impaired loans are a better measure of asset quality than
non-performing assets, as they are more comprehensive, globally comparable, and less prone
to regulatory discretion
8
. Other measures of financial fragility are also used as a robustness
check e.g. NPA ratio, the percentage of liquid assets to total assets following Beltratti and
Stulz, (2012) who argue that banks with more liquid assets will be in a better position to cope
with financing difficulties. We also use the percentage of loan loss reserve to gross loans as
an alternative measure of financial fragility following Eng and Nabar (2007).
We use the return on total assets (ROA), and return on equity (ROE) as measures of a bank’s
financial performance. We calculate ROA as net income divided by the average of the two
most recent years of total assets, while we define ROE as net income divided by the average
of the two most recent years of total equity. We also use the interest rate margin as an
alternative proxy for banks financial performance. Interest rate margin is the ratio of net
interest revenue divided by total earning assets. This study incorporates a comprehensive set
of bank-specific characteristics to control for bank and country heterogeneity. We control for
11
governance characteristics proxied by board size, board independence and CEO/chair duality.
We measure the board of directors’ size and both supervisory and management board size by
the total number of board members. We also control for board independence by using the
percentage of independent non-executive directors sitting on the board of directors and the
supervisory board. We believe that board independence may have a positive impact on
diversity and that more independent boards are more likely to embrace diversity. Moreover,
combining the roles of CEO/Chair for unitary boards might be seen as an indication of power
vested in a single individual and hence lead to less diversity. CEO/Chair duality is defined by
a dummy variable equal to 1 where the roles of the CEO and Chairman are conducted by the
same person, and zero otherwise.
We argue that larger banks tend to have larger boards and are expected to have more diverse
boards (Andres and Vallelado, 2008; Aebi et al., 2012). Therefore, we control for bank size,
defined by the natural logarithm of total assets in euros. We also control for bank age defined
as number of years since the bank’s foundation. Moreover, we control for whether the bank is
listed or privately held by creating a dummy variable which takes the value of 1 for private
banks and 0 otherwise.
Furthermore, we control for the total capital ratio as a regulatory requirement in banking
sector. Moreover, to address the differences in legal environments, we create a dummy
variable that takes the value of 1 if a bank’s headquarter is located in a common law country
and 0 otherwise. We also use Hofstede’s culture framework (2001) to control for the cultural
differences across EU countries. We use the individual cultural dimensions of Hofstede (2001)
separately and presented the results using the Power Distance dimension (Frijns et al., 2016
and Aggarwal and Goodell, 2009). Moreover, we control for bank internationalisation
following the study Ekman et al (2014) by creating a dummy variable that takes the value of
1 if a bank has overseas branches and 0 otherwise.
We use The Bank Regulation and Supervision Survey, carried out by the World Bank
formulated in 2003, 2007, and 2012. This is a unique survey on how banks are regulated and
supervised for 143 jurisdictions around the world. The survey includes questions on banking
regulations and supervision including disclosure and enforcement dimensions. There are 32
and 20 Yes/No questions on disclosure and enforcement respectively. Therefore, we
12
developed two indices namely disclosure and enforcement by creating dummy variables take
the value of 1 if the answer to a question is yes and 0 otherwise. The sum of each dummy is
the disclosure and enforcement indices respectively
9
. We also control for the macroeconomic
indicators by using the natural logarithm of country’s GDP in euros. Finally, country and year
dummies are used to capture country and time heterogeneity respectively.
Table 1 presents a description for the variables used in the empirical analysis.
Insert Table 1 about here
4.2 Endogeneity
There has been a long debate in the empirical literature about the endogeneity between board
diversity and financial performance and in particular their causal relationship. Endogeneity
results in biased and inconsistent coefficients and this makes statistical inference virtually
impossible (Wintoki et al, 2012). The existing body of the literature has investigated two
main sources of endogeneity namely unobservable heterogeneity and simultaneity (reverse
causality) e.g. the causality between board diversity and financial performance; see for
example Adams and Ferreira (2009 ); Carter et al (2010) and Pathan and Faff (2013).
Researchers usually use static panel data (fixed effects model) to control for company
heterogeneity and any other unobservable company characteristics that may drive the
results
10
(e.g. managerial ability); see for example Adams and Ferreira (2009).
Wooldridge (2002) argues that in the case of a dynamic nature of independent variables (e.g.
gender diversity) and a past dependent variable (e.g. ROA), the fixed effects model may be
biased. Wintoki et al (2012) claim that the dynamic nature of the governance-performance
nexus is a potential source of endogeneity. They argue that the current governance
characteristics (e.g. board size and independence) are a function of past financial performance
and ignoring this link may have serious consequences for statistical inference. Hermalin and
Weisbach (1998) argue that higher past financial performance leads to higher CEO ability
and bargaining power and this may lead to less board independence. We agree with Hermalin
and Weisbach (1998) and argue that higher past financial performance/ fragility may also
result in less diverse boards when the CEO has greater bargaining power.
13
4.3 Empirical modelling
To overcome the above econometrics problems and to capture the alternative possible sources
of endogeneity, we use a dynamic panel data model namely the two-step system GMM.
Moreover, as a robustness check, we also estimate the fixed effects models. The system
GMM combines in a system the equation in first-differences with the same equation
expressed in levels as in equations 1, 2 and 3 respectively.
ititiitittitiit vYearxFPBDFFFF
'
.1.0
(1)
ititiitittitiit vYearxFFBDFPFP
'
.1.0
(2)
ititiitittitiit vYearxFFFPBDBD
'
.1.0
(3)
Where, FF is bank financial fragility, FP is bank financial performance, BD is bank board
gender diversity,
it
x
is a
k*1
vector of corporate governance characteristics (board size,
independence, CEO power), loan quality and other control variables in addition to bank-and
country-specific effects.
1
'
is a
k*1
vector of parameters to be estimated,
is the panel
unobservable heterogeneity (which may be correlated with the covariates), and
it
is
independent and identically distributed (i.i.d.) over the whole sample with variance
2
.
and
it
is assumed to be independent for each i over all t. We use the adjustment for small
samples introduced by Windmeijer (2000) to improve the robustness of our results and to
avoid any potential bias in the estimated asymptotic standard error.
We use lagged levels instruments for the regression in differences, and lags of the first-
differenced variables for the equation in levels. Therefore, we use three lags of financial
performance, financial fragility, board size, board independence, and the proportion of female
directors as instruments in the equation in first-differences, and two lags of their difference as
instruments in the equation in levels (Andres and Vallelado, 2008; and Wintoki et al., 2012).
Roodman (2009) and Wintoki et al. (2012) claim that it may be possible to use a set of
historical values of suspect endogenous variables as a valid internal instrument to control for
simultaneity and other sources of endogeneity and this eliminates the need for external
instruments
11
(Wintoki et al., 2012). We carry out rigorous tests to assess the validity of the
orthogonality assumptions and the strength of our instruments. We calculate the Arellano and
14
Bond test for first- and second-order autocorrelation with a null hypothesis of no
autocorrelation. Rejecting the null in the first-differenced errors for the second or higher
order suggests that the moment conditions used are not valid (Roodman, 2009).
To test for the over-identifying restrictions, we report the Hansen test results. The null
hypothesis associated with the Hansen test is that the instruments are exogenous.
Insignificant values for the Hansen test indicate that the instruments are adequate and that the
model is correctly specified. Finally, as the residuals may be correlated across banks and
across time and therefore the standard errors can be biased, we estimate, following Roodman
(2009), clustered standard errors to produce more robust, reliable and unbiased coefficient
estimates.
5. Empirical Results
Table 2 presents the descriptive statistics of the pooled sample for the main variables used in
the empirical analysis. We present in Panels A and B the descriptive statistics for the unitary
and the two tier board banks respectively. The figures presented in Panel A show that the
average proportion of female directors ranges from 0 % to 58.3% with an average of 10%
across the unitary boards sample. The average ROA is 0.28% and ranges from -22.4% to
9.7%, while the average impaired loans to gross loans is 5.7% with standard deviation of 3.7%
and ranges from 0.05% to 62.4%. Table 1 also shows that the mean value of the board of
directors’ size is 14.7 directors with a standard deviation of 4.4 and a range from 4 to 31
directors during the period of study. The average proportion of the independent non-
executive directors across the sample is 46.4% with a standard deviation of 20.9% and the
CEO/Chair duality prevails in 3.5% of our sample. Furthermore, the average capital ratio is
12.2% and 72% of the banks has international branches. Finally, 19.3% of the sample banks
are privately held while the average bank age across the sample is 100 years.
Insert Table 2 about here
Figure 1 presents the average proportion of female directors sitting on European banks with
unitary boards over the period 2004-2012 by country. We notice that Sweden has the highest
proportion of female directors of 34.4% followed by Finland and France with average
proportions of female directors of 22.2% and 17.5% respectively. However, Cyprus, Greece,
15
Italy and Portugal have the lowest proportions of female directors of 4.4%, 4.3%, 3.6% and
3.3% respectively. Figure 2 presents the average proportions of female directors in European
banks with unitary boards from 2004-2012 and shows that the average female representation
increased from 7.6% in 2004 to 15.3% in 2012.
Insert Figures 1 and 2 about here
Panel B of Table 1 shows the descriptive statistics for the two-tier board sample banks. We
notice that the average proportions of female directors sitting on the supervisory and
management boards are 13.1% and 3% respectively. We also notice that the financial
performance of dual board banks on average is relatively higher than those of their unitary
board counterparts as the average ROA is 0.57% and ranges from -2.5% to 2.9%, while the
average impaired loans to gross loans is 5.3% with a standard deviation of 10.44% and ranges
from 0.03% to 73.2%. Panel B also shows that the average size of the supervisory board is
12.6 directors with a standard deviation of 5.6% and ranges from 4 to 29 directors. However,
the average size of the management board is remarkably much lower with 5.3 directors with a
maximum of 16 directors during the period of the study. Moreover, the average proportion of
the independent non-executive directors across the supervisory boards is 68% with a standard
deviation 18.7%. The average capital ratio as the regulatory requirement is 14.11% and 65%
of the banks with dual boards has overseas branches. Finally, 29.5% of the sample banks are
privately held while the average bank age across the sample is 79.4 years.
Figure 3 presents the average proportions of female directors on the supervisory and
management boards over the period 2004-2012 by country. We notice that the average
proportion of female directors on the supervisory board is much higher than those on the
management board across all countries. Germany has the highest female representation on the
supervisory board of 18.6% followed by Denmark and Austria with average proportions of
females of 16.3% and 15.4% respectively. On the other hand the lowest female representation
is found in Italy and Portugal with averages of 3.5% and 2% respectively. Moreover, Figure 3
shows that Austria has the highest female representation on the management board (6.3%)
while there are no female directors sitting on the management board in Portugal. Figure 4
presents the average proportion of female directors sitting on each of the supervisory and
management boards over the period 2004-2012. Figure 4 shows that the proportion of female
16
directors on the supervisory board increased from an average of 11.5% in 2004 to 15.8% in
2012. Moreover, we notice that there is a modest increase in the proportion of female
directors on the management board from 2.6% in 2004 to 3.7% in 2012. We also notice that
the proportion of female directors on the supervisory board is higher than those sitting on the
board of directors. To sum up, Table 3 presents a cross country analysis for board structure
and diversity for the unitary and dual board sample banks over the period of study.
Insert Figures 3 and 4 and Table 3 about here
Tables 4 and 5 present the correlation matrixes for the main variables used in the empirical
analysis for the unitary and dual board sample banks respectively. The results show that there
is no evidence of multicollinearity.
Insert Tables 4 and 5 about here
Table 6 presents the results of the system GMM estimator for the influence of female
directors on EU banks’ financial fragility as defined in Equation 1. Panels A and B present
the results for the unitary and dual board respectively.
Insert Table 6 about here.
The results presented in Table 6 reject the null hypothesis that lagged endogenous variable
(impaired loans to gross loans) is zero in Panels A and B for the unitary and dual board banks
respectively. This implies rejection of a static panel data model in favour of a dynamic model.
The results of Model 1 show that there is a positive but insignificant relationship between the
proportion of female directors and the ratio of impaired loans to gross loans as a proxy for
banks financial fragility.
However, given the low proportion of female representation on boards and drawing on the
critical mass theory of Kanter (1977), we believe that appointing a critical mass of female
directors may have an influence on financial fragility. Therefore, we control for the quadratic
term of the proportion of female directors as presented in Model 2. We find that, the
diversity-financial fragility relationship is non-linear and has an inverted U shape. This
suggests that female directors apparently have a positive impact on banks’ financial fragility.
17
However, appointing a female director beyond a critical mass of 18% may reduce banks’
vulnerability to financial crisis
12
. This result is consistent with Mateos de Cabo et al, (2012)
and Jianakoplos and Bernasek (1998) as they argue that female directors tend to be more risk
averse and this stereotype of being risk averse is the main reason for the “Glass Ceiling” on
the corporate promotion ladder. Based on the above discussion we cannot reject our first
hypothesis when a critical mass of female director has been appointed in banks with unitary
boards.
With respect to dual boards’ banks, the results presented in Model 3 show that there is a
positive but insignificant relationship between the proportion of female directors on the
supervisory board and the ratio of impaired loans to total loans. Moreover, consistent with the
results for the unitary boards, we find that diversity-financial fragility relationship is non-
linear and has an inverted U shape as the coefficient on female directors on supervisory
boards is positive and highly significant while its quadratic term is negative and highly
significant as presented in Model 4. This suggests that beyond a critical mass of 21%,
appointing an additional female director may reduce banks’ vulnerability to financial crisis.
Again, this result is consistent with Mateos de Cabo et al, (2012) and Jianakoplos and
Bernasek (1998).
On the other hand, we find an insignificant relationship between the proportion of female
directors on the management boards and banks’ financial fragility. However and interestingly,
when we control for the quadratic term of the proportion of female directors on the
management boards as in Model 4, we find that the coefficient on the proportion of female
directors is negative and highly significant however, its quadratic term is positive and highly
significant. This suggests that diversity- financial fragility nexus on management boards is
non-linear and has a U shape. This also implies that beyond a critical mass of 24%, appointing an
additional female director increases banks’ risk. This result is consistent with the study of Adams
and Funk (2012) in which they argue that female directors are more open to change compared
with their male counterparts. Therefore, appointing a female director need not lead to less
risk-averse decisions as female directors are more risk-loving than male directors (Adams and
Funk, 2012).
The above results are interesting, as we argue that the degree of risk taking behaviour for
female directors may vary based on their roles. Global statistics shows that female directors
18
are mainly appointed as NEDs and/or INEDs on either board of directors or supervisory
boards. Table 1 shows that the proportion of female directors on supervisory and
management boards are 13% and 3% respectively. Therefore, we argue that female executive
directors may have the same risk taking behaviour as their male counterparts. Based on the
above results we cannot reject our first hypothesis when a critical mass of female directors
has been appointed in the supervisory board. However, we reject our first hypothesis with
respect to management boards when a critical mass of female directors has been appointed.
Finally, the tests regarding serial correlation reject the absence of first order, but not second
order serial correlation. The models are well specified as the Hansen test does not reject the
over-identifying restrictions.
Table 7 presents the results of the system GMM estimator for the influence of female
directors on EU banks’ financial performance as defined in Equation 2. Panels A and B
present the results for the unitary and dual board respectively.
Insert Table 7 about here.
The results presented in Table 7 reject the null hypothesis that lagged endogenous variable
(ROA) is zero in Panels A and B. This implies rejection of a static panel data model in favour
of a dynamic model. The results presented in Model 1 show that there is a positive and
significant relationship at the 5% level between diversity and financial performance of
unitary board banks. This suggests that the higher the proportion of female directors the
higher the bank’s financial performance. Kandel and Lazear (1992) and Anderson et al. (2011)
argue that operationally complex companies may benefit from more diverse boards as the
different perspectives and viewpoints of board members lead to better monitoring benefits for
the shareholders and a stronger advisory role for managers. In Model 2, we estimate the
effect of appointing an additional female director on financial performance. Drawing on the
critical mass theory of Kanter (1977), Joecks et al (2013) argue that the influence of female
directors is not the main determinant of board composition unless a critical mass of female
directors has been appointed. Therefore, we expect that diversity-performance relationship
might be non-linear and appointing a critical mass of female directors may have an influence
on financial performance.
19
Interestingly, when we control for the quadratic term of the proportion of female directors in
Model 2, we find that there is a positive and significant relationship at the 5% level between
boards’ gender diversity and banks’ financial performance. Moreover, we find a negative
and significant (P<5%) relationship between the quadratic term of the proportion of female
directors and financial performance. This implies that the performance-diversity relationship
is non-linear and has an inverted U shape; meaning that appointing up to 21% female
directors may increase financial performance after which appointing an additional female
director may result in a decrease in financial performance
13
.
This result is consistent with those presented in Table 6 as appointing additional female
directors may lead to lower risk and hence lower financial performance. Furthermore, Lang
(1986), Arrow (1998), Putnam (2007), O’Reilly et al. (1989) find that diversity may cause
communication problems and increases the inter-group conflicts and this may lead to lower
financial performance. Our result is also consistent with Carter et al. (2010) who argue that,
according to contingency theory, the net effect of gender diversity can be either positive or
negative from a financial performance perspective. Based on the above results we reject our
second hypothesis when a critical mass of female director has been appointed in banks with
unitary boards.
With respect to dual boards, the results presented in Panel B show that there is a positive and
significant (P<5%) relationship between the proportion of female directors on supervisory
boards and banks’ financial performance as in Model 3. This suggests that the higher the
proportion of female directors the better the financial performance. This result is consistent
with the resource dependence theory and human capital theory. However, we find that the
coefficient on the quadratic term of female directors on the supervisory board is negative and
highly significant as in Model 4. This suggests that the diversity-performance relationship is
non-linear and has an inverted U shape and that appointing an additional female director
beyond a critical mass of 23% may reduce the financial performance.
By contrast for management boards, we find that diversity-performance has a U shape
relationship and appointing an additional female director beyond a critical mass of 27% may
have a positive impact on financial performance as presented in Model 4. The above results
are consistent with Lang (1986), Arrow (1998), Putnam (2007), O’Reilly et al. (1989).
20
Moreover, it is consistent with our arguments regarding the degree of risk attitude of female
directors on management boards. Based on the above discussion we reject our second
hypothesis when a critical mass of female directors has been appointed in supervisory board.
However, we cannot reject our second hypothesis with respect to management boards beyond
a critical mass of female directors. Finally, the tests regarding serial correlation reject the
absence of first order, but not second order serial correlation. The models are well specified
as the Hansen test does not reject the over-identifying restrictions.
Table 8 presents the results of the system GMM estimator for the main determinants for the
proportion of female directors on EU banks as defined in Equation 3. Panels A, B and C
present the results for the board of directors (unitary board), supervisory and management
boards (dual boards) respectively.
Insert Table 8 about here.
Again, the results presented in Table 8 reject the static panel data model in favour of a
dynamic model. In Panel A, we find a negative but insignificant relationship between banks’
financial fragility and the proportion of female directors. On the other hand, the results show
that there is a negative and significant (P<5) relationship between financial performance and
the proportion of female directors on European banks with unitary boards. This may imply
that the higher the financial performance the lower the board diversity.
We agree with Adams and Ferreira (2009) that diverse boards are likely to be associated with
stronger governance characteristics. Looking at our results in Model 1, we find a positive and
significant (P<5%) relationship between both board size and independence and the proportion
of female representation on the board of directors. This suggests that female directors are
likely to be appointed in larger and more independence boards. This result is consistent with
Brammer et al. (2007) and Conyon and Mallin (1997) as they find that larger boards and
boards with a higher proportion of NEDs are more likely to have a higher percentage of
female directors.
With respect to the main determinants of the female representation on supervisory boards, the
results presented in Model 2 are similar to those of the board of directors presented in Model
21
1 and thus board size and independence are the main determinants for the proportion of
female directors. Moreover, we find that big banks tend to have higher proportion of female
directors compared with smaller banks. Furthermore, the results show that there is a positive
and significant relationship between power distance index and female representation on the
supervisory board. The index is concerned with the expectations of less powerful members in
a society with respect to equal distribution of power. This suggests that in countries with dual
board banks people accept a hierarchical order in which everybody has a place and the power
is distributed equally (Hofstede, 2001).
With respect to the main determinants of female representation on management boards, we
find a negative and highly significant relationship between banks’ financial fragility and the
proportion of female directors on management boards. This suggests that the higher the banks’
financial fragility the lower the proportion of female directors. This may imply that banks
with higher risk and more vulnerability to financial crisis (e.g. due to the poor loan quality)
are likely to be associated with less diverse management boards. This may also suggest that
high risk and more financially fragile banks are less likely to appoint female directors and
this due to the belief that females are more risk averse and would tend not to condone more
risky decisions. We also find a positive and highly significant relationship between financial
performance and the female representation on management boards.
Moreover, we find a negative and highly significant relationship between management board
size and gender diversity. This result is consistent with Adams and Ferreira (2009) as they
argue that boards tend to be more homogeneous and less diverse when companies are
operating in riskier environments. Table 2 shows that the average proportion of female
directors on management board is 3% and this suggests that management boards are maily
homogenous and male dominated. Adams and Ferreira (2007) also argue that in riskier
environments homogeneous boards may reduce monitoring process as board heterogeneity
may be considered as a potential source of conflict and difficulties in decision making.
Furthermore, the results also show that, listed companies are likely to have a higher
proportion of female directors on management boards. Our models are well specified as the
tests regarding serial correlation reject the absence of first order, but not the second order and
the Hansen test does not reject the over-identifying restrictions.
22
As robustness checks, we estimate the fixed effects regressions for both unitary and dual
boards’ banks and obtained similar results. We also re-estimate the regression models pre and
post the global financial crisis and found that our results are more robust during the period
post crisis as we find that the higher the proportion of female directors the lower the banks’
vulnerability to financial crisis.
6. Discussion and Conclusion
There has been an ongoing debate about the rationale and importance of board diversity.
Female under-representation has long been a global phenomenon in developed and
developing countries despite the benefits that female directors may bring to boardrooms. For
instance the proportion of female CEOs in the US is 3% while the proportion of female
directors ranges between 10-15% (Kogut et al., 2014). Female directors’ under-representation
might be partially caused by fact that women tend to be strongly represented in some non-
board roles e.g. human resources and customer care (Higgs, 2003). However, there is a
remarkable increase in the proportion of female directors over the past few years in particular
during, and after, the financial crisis. This might be due to the changes in legislation e.g.
female quotas.
In this paper, we investigate the influence of board diversity on both financial fragility and
performance for a sample of 99 banks from 17 countries over the period 2004-2012. The
results of the system GMM estimator show that the diversity-financial fragility relationship is
non-linear and has an inverted U shape. This suggests that beyond a critical mass of 18% and
21% appointing an additional female director on the board of directors and the supervisory
boards respectively may reduce banks’ vulnerability to financial crisis. This result is
consistent with Mateos de Cabo et al, (2012) and Jianakoplos and Bernasek (1998) as they
argue that female directors tend to be more risk averse and this stereotype of being risk averse
is the main reason for the “Glass Ceiling” on the corporate promotion ladder.
However interestingly, we find evidence that female directors are not risk averse as diversity-
financial fragility nexus on management boards is also non-linear but has a U shape and that
appointing an additional female director beyond a critical mass of 24% increases banks’ risk.
Adams and Funk (2012) argue that female directors are not less risk-averse. Therefore,
appointing a female director need not lead to less risk-averse decisions as female directors are
more risk-loving than male directors (Adams and Funk, 2012). We argue that the degree of
23
risk taking behaviour for female directors may vary based on their roles. Farag and Mallin
(2016) find that female CEOs are not risk averse compared with their male counterparts.
Therefore, we argue that female and male executive directors may have the same risk taking
behaviour.
We also find a positive and significant relationship between the proportion of female
directors and financial performance for both the board of directors and the supervisory boards.
This result is consistent with resource dependence theory and human capital theory.
Moreover, we find that diversity- performance nexus is non-linear and have an inverted U
shape. This implies that beyond a critical mass of 21% and 23%, appointing an additional
female director on the board of directors and the supervisory boards respectively decreases
financial performance. Board diversity may cause communication problems and increases the
inter-group conflicts and this may lead to lower financial performance (Lang, 1986; Arrow,
1998; Putnam, 2007; O’Reilly et al., 1989).
On the other hand, we find that diversity- performance nexus on management boards is non-
linear and has a U shape. Therefore, appointing a female director beyond a critical mass of 27%
may lead to better financial performance. This result is consistent with Carter et al. (2010) as
the net effect of gender diversity can be either positive or negative from a financial
performance perspective. The result is also consistent with our argument on the risk-taking
behaviour of female directors with respect to their role as executive directors.
We also find that board size and independence are the main determinants for the proportion
of female directors on the board of directors and the supervisory boards. This result is
consistent with Brammer et al. (2007) and Conyon and Mallin (1997). On the other hand,
management boards seem to be more homogenous and less diverse. Adams and Ferreira
(2009) argue that boards tend to be more homogeneous and less diverse when companies are
operating in riskier environments. Finally, we find that banks with higher risk and more
vulnerability to financial crisis (e.g. due to the poor loan quality) are likely to be associated
with less diverse management boards.
This study has a number of policy implications especially. The relationship between board
diversity and bank risk may potentially have important implications for the stability and
24
increased confidence in the banking sector. Our empirical results provide support for the calls
by various government reports e.g. Lord Davies Report in 2011 and its subsequent annual
updates for more board diversity in the UK and the European Commission (2012)
recommendations on board diversity. However, given the striking results of the influence of
critical mass of female directors, policy makers should carefully address the concerns
regarding the economic impact of the call for more diverse boards or imposing female quotas.
Although it is not easy to draw a conclusion on the impact of female quotas on financial
performance (Ferreira, 2015), in Norway for instance, once the law was passed, there was a
remarkable decline (23%) in the proportion of public limited companies whilst a higher
proportion of the Norwegian companies listed in London (Kogut et al., 2014). Moreover,
imposing the 40% quota in Norway was associated with lower financial performance (Ahern
and Dittmar, 2012). Kogut et al (2014) argue that a small quota (between 10% and 20%) can
achieve large structural consequences and social justice. We agree with Kogut et al (2014)
that small quotas may be preferable as they are the key to better structural equality as female
quotas may enhance their network and connectivity and this may lead to a better position for
female directors.
Future research might investigate the relationship between banks’ specific characteristics and
the propensity to appoint female directors, and to investigate the impact of the appointment of
a new female director on board dynamics and on the bank’s overall risk and return.
Moreover, we believe that a further analysis of the influence of board diversity on corporate
sustainability and risk-taking behaviour may provide additional insights to the results of our
empirical study.
25
ENDNOTES
1
In January 2006 Norway enforced a gender quota requirement on listed companies with the target of 40% females on the
board by 2008. Whilst the UK and many other countries have not introduced binding gender quotas to facilitate board
diversity, nonetheless there has been a move by governments towards targets for gender representation on boards, for
example the Davies Report (2011) and its subsequent annual updates in the UK.
2
In the remaining 9 countries a hybrid system applies and companies can choose between a one and two-tier approach.
Moreover, in some European countries e.g. registered companies in Italy, there is the choice to follow one of three
governance models: a unitary governance systems; a dual governance system with distinct supervisory and management
functions; or the traditional model in Italy with a decision-making board and a separate board of auditors.
3
Kanter (1977b) suggests that group interaction can be classified into 4 areas namely uniform, skewed, tilted, and balanced
groups. In the uniform groups, all members have the same characteristics i.e. male or female in the context of gender. When
the male type dominates, the group is identified as skewed. Joecks et al (2013) report that the proportion of females in
skewed groups is up to 20%. However, the tilted group has less extreme distribution compared with the skewed group as
females (as the minority) can impact the group culture. Female representation in the tilted group ranges from 20-40%
(Joecks et al., 2013). Finally, the balanced group focuses on the pool of talent and skills and not on the proportion of males
and females (sub-groups). In the balanced group, the female representation ranges from 40-60% on average and the
performance of the balanced group is expected to be higher than the skewed group (Kanter, 1977 and Joecks et al., 2013).
4
Andres and Vallelado (2008- JBF p2572) investigated the role of the board of directors using a sample of 65 banks from six
countries over the period 1996-2006.
5
Some countries have recently introduced gender quota e.g. France (2016), Italy (2015), Spain (2015), Germany
(2016) and the Netherlands (2016). For more details, see http://ec.europa.eu/justice/gender-
equality/files/womenonboards/factsheet_women_on_boards_web_2015-10_en.pdf
6
We estimate our models with and without Sweden as obvious outlier with respect to the proportion of female
directors and find similar results.
7
We also use Blau index as an alternative measure of board diversity. Blau index is calculated as the percentage
of board members in each category (male/female). The index values range from 0 to 0.5 which occurs when the
board is equally balanced.
8
See for instance https://www.moodys.com/research/Moodys-Impaired-loans-better-gauge-of-Taiwanese-banks-asset-
quality--PR_257689
9
For more details please see
http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/0,,contentMDK:20345037~pagePK:64214825~piPK:
64214943~theSitePK:469382,00.html#Original_Database_by_country__40kb_each_
10
Fixed effects model has a strict exogeneity assumption in which, for instance, current board diversity and
governance characteristics are independent of past financial performance variables.
11
Although the higher order of lag lengths result in more exogenous instruments, the use of internal instruments
may cause the problem of weak instruments as the number of lags increases (Wintoki et al., 2012). However, we used
different lag lengths as an empirical trade-off.
12
We find similar results when we use both the ratio of non-performing loans to total assets and the ratio of loan loss reserve
to gross loans.
13
We find similar results when we use ROE and interest margin as alternative proxies for financial performance; however
the results are marginally significant when we use ROE.
26
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29
Table 1: Variables Description
Variable
Description
Female
Proportion of female directors sitting on the board of directors.
FemaleSB
Proportion of female directors sitting on the supervisory board.
FemaleMgtB
Proportion of female directors sitting on the management board.
ROA
Ratio of net income divided by the average of the two most recent years of
total assets.
Impaired Loans/Gross Loans (%)
The ratio of impaired loans/gross loans as a proxy for financial fragility.
B.Size
Total number of directors sitting on the board directors
SB.Size
Total number of directors sitting on the supervisory board;
Mgt.B.Size
Total number of directors sitting on the management board.
INED
Proportion of independent non-executive directors.
CEO/Chair
Dummy variable takes the value of 1 where the role of the CEO and Chairman
are conducted by the same person, and zero otherwise.
LnTA
Natural logarithm of bank total assets as a proxy for bank size.
BankAge
Bank age calculated as the number of years since bank’s foundation.
ListDummy
Dummy variable takes the value of 1 if the bank is privately held and 0
otherwise.
Total capital ratio
Total capital ratio as a regulatory requirement in banking sector.
Power Distance
A dimension from Hofstede’s culture framework (2001) to control for the
cultural differences across EU countries.
Disclosure Index
Sum of dummy variables take the value of 1 if the answer to 32 questions on
disclosure from the Bank Regulation and Supervision Survey, carried out by
the World Bank is yes and 0 otherwise.
Enforcement Index
Sum of dummy variables take the value of 1 if the answer to 20 questions on
enforcement from the Bank Regulation and Supervision Survey, carried out by
the World Bank is yes and 0 otherwise.
Overseas Branches
Dummy variable takes the value of 1 if a bank has overseas branch(es) and 0
otherwise as a proxy for internationalisation.
Law
Dummy variable takes the value of 1 if the respective banks headquarter is
located in a common law country and 0 otherwise.
lnddp
Natural logarithm of gross domestic product in euros.
30
Table 2: Descriptive Statistics for the Pooled Sample over the period 2004-2012
Mean
Median
SD
Min
Max
N
Panel A: Unitary Boards
Female
0.100
0.071
0.107
0.000
0.583
449
ROA (%)
0.281
0.540
2.331
-22.429
9.783
446
Impaired Loans/Gross Loans (%)
5.778
3.777
7.410
0.048
62.373
417
B.Size
14.712
15.000
4.389
4.000
31.000
458
INED
0.464
0.500
0.209
0.105
0.933
456
NoCom
3.717
4.000
1.542
1.000
6.000
435
CEO/Chair
0.035
0.000
0.184
0.000
1.000
458
LnTA
11.410
11.150
1.668
7.781
14.882
447
Bank Age
100.263
82.000
93.533
3.000
540.00
460
List Dummy
0.193
0.000
0.395
0.000
1.000
462
Total capital ratio
12.231
11.500
3.451
8.101
31.558
451
Power Distance
48.318
50.000
13.447
28.000
68.000
462
Disclosure Index
20.977
21.000
1.433
19.000
23.000
455
Enforcement Index
13.036
14.000
3.801
7.000
18.000
453
Overseas Branches
0.716
1.000
4.511
0.000
1.000
462
Panel B: Two-Tier Boards
FemaleSB
0.131
0.111
0.113
0.000
0.511
392
FemaleMgtB
0.029
0.000
0.087
0.000
0.500
392
ROA
0.574
0.465
0.772
-2.574
2.989
376
Impaired Loans/Gross Loans (%)
5.391
3.189
10.445
0.030
73.275
322
SB.Size
12.620
11.000
5.604
4.000
29.000
392
Mgt.B.Size
5.349
4.500
2.809
2.000
16.000
392
INED
0.680
0.667
0.187
0.167
1.000
392
LnTA
10.626
10.421
2.030
6.436
14.625
377
Bank Age
79.471
75.000
64.382
3.000
275.00
393
List Dummy
0.295
0.000
0.457
0.000
1.000
393
Total capital ratio
14.111
13.000
4.588
8.712
37.167
343
Power Distance
33.793
35.000
17.695
11.000
68.000
393
Disclosure Index
21.468
22.000
1.273
20.000
23.000
393
Enforcement Index
15.442
15.000
2.247
12.000
18.000
393
Overseas Branches
0.646
1.000
0.478
0.000
1.000
393
Female: proportion of female directors sitting on the board of directors; FemaleSB: proportion of female directors
sitting on the supervisory board; FemaleMgtB: proportion of female directors sitting on the management board;
ROA: ratio of net income divided by the average of the two most recent years of total assets. Impaired
Loans/Gross Loans (%): The ratio of impaired loans/gross loans as a proxy for financial fragility; B.Size: total
number of directors sitting on the board directors; SB.Size: total number of directors sitting on the supervisory
board; Mgt.B.Size: total number of directors sitting on the management board; INED: proportion of independent
non-executive directors; CEO/Chair: dummy variable takes the value of 1 where the role of the CEO and
Chairman are conducted by the same person, and zero otherwise; LnTA: natural logarithm of bank total assets as a
proxy for bank size; BankAge: bank age calculated as the number of years since bank’s foundation; ListDummy:
dummy variable takes the value of 1 if the bank is privately held and 0 otherwise; Total capital ratio: capital ratio
as a regulatory requirement in banking sector; Power Distance: A dimension from Hofstede’s culture framework
(2001) to control for the cultural differences across EU countries; Disclosure and Enforcement Indexes: sum of
dummy variables take the value of 1 if the answer to questions on disclosure and enforcement from the Bank
Regulation and Supervision Survey, carried out by the World Bank, is yes and 0 otherwise; Overseas Branches:
dummy variable takes the value of 1 if a bank has overseas branch(es) and 0 otherwise as a proxy for
internationalisation.
31
Table 3: Board Structure and Diversity for Unitary and Dual Board Sample Banks
Belgium
Cyprus
Finland
France
Greece
Ireland
Italy
Portugal
Spain
Sweden
UK
Panel A: Unitary Boards
Female
0.076
0.044
0.222
0.175
0.050
0.114
0.036
0.033
0.097
0.344
0.105
B.Size
18.630
12.471
9.000
17.333
13.738
9.906
16.736
25.692
14.655
13.074
14.653
INED
0.284
0.493
0.451
0.511
0.243
0.578
0.528
0.278
0.456
0.631
0.510
Panel B: Dual Boards
Austria
Denmark
Germany
Italy
Poland
Portugal
Netherland
Switzerland
FemSB
0.154
0.163
0.186
0.035
0.079
0.020
0.113
0.126
FemMgtB
0.063
0.022
0.025
0.005
0.034
0.000
0.017
0.025
SB.Size
17.583
10.206
16.783
19.750
8.400
16.846
8.809
9.824
Mgt.B.Size
4.139
3.079
6.033
10.750
6.756
5.923
4.506
8.500
INED
0.645
0.676
0.736
0.735
0.613
0.556
0.711
0.690
Female: proportion of female directors sitting on the board of directors; B.Size: total number of directors sitting on the board directors; INED: proportion of independent
non-executive directors; FemaleSB: proportion of female directors sitting on the supervisory board; FemaleMgtB: proportion of female directors sitting on the
management board; SB.Size: total number of directors sitting on the supervisory board; Mgt.B.Size: total number of directors sitting on the management board. During
the period of study, some countries follow a mixture of unitary and dual board structure.
32
Table 4: Correlation Matrix for Unitary Board Sample Banks
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
1
ROA
1.000
2
Female
0.112
1.000
3
B.Size
0.098
-0.166
1.000
4
INED
0.038
0.324
-0.116
1.000
5
CEO/Chair
0.010
-0.112
0.018
0.142
1.000
6
LnTA
0.024
0.349
0.354
0.356
-0.176
1.000
7
Impaired Loans/Gross Loans
-0.423
-0.142
-0.225
-0.008
0.010
-0.197
1.000
8
Bank Age
-0.018
-0.089
0.082
0.081
-0.068
0.231
-0.001
1.000
9
List Dummy
0.047
-0.223
-0.183
-0.223
0.177
-0.347
0.012
-0.129
1.000
10
Power Distance
-0.027
-0.327
0.437
-0.376
0.024
-0.026
0.053
-0.076
-0.130
1.000
11
Disclosure Index
-0.063
-0.204
-0.083
0.239
0278
-0.331
0.174
0.035
0.179
-0.045
1.000
12
Enforcement Index
-0.271
-0.337
0.038
-0.155
0.155
-0.386
0.366
-0.067
-0.036
0.434
0.437
1.000
13
Total Capital Ratio
0.184
0.208
-0.137
0.101
-0.145
0.054
0.071
-0.024
-0.025
-0.091
-0.189
-0.320
1.000
14
Law
-0.048
0.048
-0.290
0.222
-0.117
0.150
0.002
0.102
0.145
-0.444
0.308
-0.411
0.096
1.000
15
Overseas Branches
0.151
0.132
0.242
0.114
-0.119
0.451
-0.241
0.175
-0.350
0.035
-0.172
-0.296
0.089
-0.003
1.000
16
lnGDP
0.187
0.274
0.225
0.268
0.139
0.427
-0.321
0.266
0.104
-0.165
-0.129
-0.383
-0.119
0.013
0.293
1.000
ROA: ratio of net income divided by the average of the two most recent years of total assets; Female: proportion of female directors sitting on the board of directors; B.Size: total
number of directors sitting on the board directors; INED: proportion of independent non-executive directors; CEO/Chair: dummy variable takes the value of 1 where the role of
the CEO and Chairman are conducted by the same person, and zero otherwise; LnTA: natural logarithm of bank total assets as a proxy for bank size; Impaired Loans/Gross Loans
(%): The ratio of impaired loans/gross loans as a proxy for financial fragility; BankAge: bank age calculated as the number of years since bank foundation; ListDummy: dummy
variable takes the value of 1 if the bank is privately held and 0 otherwise. Power Distance: A dimension from Hofstede’s culture framework (2001) to control for the cultural
differences across EU countries; Disclosure and Enforcement Indexes: sum of dummy variables take the value of 1 if the answer to questions on disclosure and enforcement from
the Bank Regulation and Supervision Survey, carried out by the World Bank, is yes and 0 otherwise; Total capital ratio: capital ratio as a regulatory requirement in banking sector;
Law: dummy variable takes the value of 1 if the respective banks headquarter is located in a common law country and 0 otherwise; Overseas Branches: dummy variable takes the
value of 1 if a bank has overseas branch(es) and 0 otherwise as a proxy for internationalisation; lnddp: natural logarithm of gross domestic product in euros; Bold figures indicate
significance at the 5% level or below.
33
Table 5: Correlation Matrix for Dual Board Sample Banks
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
1
ROA
1.000
2
FemSB
-0.248
1.000
3
FemMgtB
0.022
0.100
1.000
4
SB.Size
-0.295
0.074
0.006
1.000
5
Mgt.B.Size
0.0004
-0.105
-0.090
0.119
1.000
6
INED
-0.144
0.205
0.063
0.150
0.230
1.000
7
LnTA
-0.327
0.078
-0.095
0.364
0.452
0.321
1.000
8
Impaired Loans/Gross Loans
0.088
-0.176
0.026
-0.092
-0.009
-0.129
-0.200
1.000
9
Bank Age
-0.059
0.204
-0.062
0.221
-0.061
0.271
0.022
-0.152
1.000
10
List Dummy
-0.133
0.053
-0.053
-0.331
-0.254
-0.025
-0.346
-0.087
-0.271
1.000
11
lnGDP
-0.013
0.136
-0.090
-0.073
0.093
0.130
0.279
0.074
-0.198
-0.141
1.000
12
Power Distance
0.285
-0.281
-0.106
-0.256
0.400
-0.046
0.136
0.294
-0.342
-0.132
0.199
1.000
13
Disclosure Index
0.054
-0.088
-0.082
-0.090
0.378
0.101
0.327
0.202
-0.278
-0.050
0.346
0.422
1.000
14
Enforcement Index
-0.223
0.085
-0.091
-0.217
-0.365
0.138
0.001
-0.274
0.105
0.387
0.219
-0.343
-0.125
1.000
15
Total Capital Ratio
0.008
0.212
0.141
-0.218
0.054
0.019
-0.004
-0.050
-0.057
0.070
0.054
-0.015
0.020
-0.065
1.000
16
Overseas Branches
0.055
-0.080
0.111
0.092
0.222
0.102
0.308
-0.285
-0.171
-0.046
-0.132
0.172
0.088
-0.039
0.044
1.000
ROA: ratio of net income divided by the average of the two most recent years of total assets; FemaleSB: proportion of female directors sitting on the supervisory board;
FemaleMgtB: proportion of female directors sitting on the management board; SB.Size: total number of directors sitting on the supervisory board; Mgt.B.Size: total number of
directors sitting on the management board; INED: proportion of independent non-executive directors; LnTA: natural logarithm of bank total assets as a proxy for bank size;
Impaired Loans/Gross Loans (%): The ratio of impaired loans/gross loans as a proxy for financial fragility; BankAge: bank age calculated as the number of years since bank
foundation; ListDummy: dummy variable takes the value of 1 if the bank is privately held and 0 otherwise; lnddp: natural logarithm of gross domestic product in euros; Power
Distance: A dimension from Hofstede’s culture framework (2001) to control for the cultural differences across EU countries; Disclosure and Enforcement Indexes: sum of
dummy variables take the value of 1 if the answer to questions on disclosure and enforcement from the Bank Regulation and Supervision Survey, carried out by the World Bank,
is yes and 0 otherwise; Total capital ratio: capital ratio as a regulatory requirement in banking sector; Overseas Branches: dummy variable takes the value of 1 if a bank has
overseas branch(es) and 0 otherwise as a proxy for internationalisation.. Bold figures indicate significance at the 5% level or below.
34
Table 6: The Influence of Female Directors on Financial Fragility for EU Banks:
System GMM Estimator
Panel A
Panel B
Unitary Boards
Dual Boards
Model 1
Model 2
Model 3
Model 4
L. Impaired Loans/Gross Loans
1.154***
(0.076)
1.237***
(0.064)
0.793***
(0.053)
0.826***
(0.042)
Female
6.654
(8.829)
25.520**
(12.826)
Female sq
-72.078**
(34.480)
FemSB
3.471
(4.320)
22.814***
(6.893)
FemSB sq
-54.393***
(17.569)
FemMgtB
4.123
(3.835)
-21.127***
(4.912)
FemMgtB sq
43.791***
(16.622)
ROA
-0.306
(0.921)
-2.010**
(0.809)
-0.040
(0.977)
-0.461*
(0.274)
B.Size
0.196
(0.295)
-0.001
(0.189)
SB.Size
0.227**
(0.108)
-0.019
(0.192)
Mgt.B.Size
-0.354
(0.465)
0.211
(0.414)
INED
9.304
(5.892)
0.975
(3.108)
1.369
(3.406)
0.898
(3.976)
CEO/Chair
-2.729
(4.012)
-3.298
(3.544)
LnTA
-0.040
(0.566)
-0.280
(0.527)
0.896
(0.861)
-0.071
(0.471)
Bank Age
0.003
(0.003)
-0.001
(0.002)
0.009
(0.016)
-0.031**
(0.013)
Total Capital Ratio
-0.752***
(0.269)
0.218*
(0.125)
-0.038
(0.069)
0.083
(0.085)
List Dummy
15.508***
(4.801)
1.591
(3.231)
3.714
(4.421)
-7.593**
(3.048)
lnGDP
-2.564**
(1.154)
0.293
(0.543)
0.646
(1.453)
-3.260**
(1.397)
Power Distance
-0.376***
(0.135)
-0.014
(0.067)
0.102
(0.075)
-0.029
(0.056)
Disclosure Index
-2.554**
(1.067)
0.246
(0.506)
-1.136
(1.190)
1.355*
(0.703)
Enforcement Index
0.573*
(0.317)
-0.240
(0.239)
-0.572
(0.531)
1.072**
(0.514)
Overseas Branches
10.297***
(2.921)
-0.750
(2.142)
-7.282***
(1.857)
-4.606**
(1.870)
Law
-9.110**
(3.954)
-1.463
(1.975)
Constant
93.959***
(35.424)
-6.219
(15.424)
15.513
(14.577)
4.363
(10.079)
35
Time dummy
Yes
Yes
Yes
Yes
Bank type
Yes
Yes
Yes
Yes
Wald test p.value
0.000
0.000
0.000
0.000
Arellano-Bond test for AR(1) p.value
0.038
0.043
0.020
0.014
Arellano-Bond test for AR(2) p.value
0.443
0.669
0.405
0.933
Hansen test p.value
0.881
0.473
0.937
0.508
Female: proportion of female directors sitting on the board of directors; FemaleSB: proportion of female
directors sitting on the supervisory board; FemaleMgtB: proportion of female directors sitting on the
management board ROA: ratio of net income divided by the average of the two most recent years of total
assets. Impaired Loans/Gross Loans (%): The ratio of impaired loans/gross loans as a proxy for financial
fragility; B.Size: total number of directors sitting on the board directors; SB.Size: total number of
directors sitting on the supervisory board; Mgt.B.Size: total number of directors sitting on the
management board; INED: proportion of independent non-executive directors; CEO/Chair: dummy
variable takes the value of 1 where the role of the CEO and Chairman are conducted by the same person,
and zero otherwise; LnTA: natural logarithm of bank total assets as a proxy for bank size; BankAge:
bank age calculated as the number of years since bank foundation; ListDummy: dummy variable takes
the value of 1 if the bank is privately held and 0 otherwise; lngdp: natural logarithm of gross domestic
product in euros; Total capital ratio: capital ratio as a regulatory requirement in banking sector; Power
Distance: A dimension from Hofstede’s culture framework (2001) to control for the cultural differences
across EU countries; Disclosure and Enforcement Indexes: sum of dummy variables take the value of 1 if
the answer to questions on disclosure and enforcement from the Bank Regulation and Supervision
Survey, carried out by the World Bank, is yes and 0 otherwise; Overseas Branches: dummy variable
takes the value of 1 if a bank has overseas branch(es) and 0 otherwise as a proxy for internationalisation.
Law: dummy variable takes the value of 1 if the respective banks headquarter is located in a common law
country and 0 otherwise. ***, **, and * indicates significance at the 1%, 5% and 10% levels respectively.
Clustered robust standard errors are present.
36
Table 7: The Influence of Female Directors on Financial Performance for EU Banks:
System GMM Estimator
Panel A
Panel B
Unitary Boards
Dual Boards
Model 1
Model 2
Model 3
Model 4
L. ROA
-0.046**
(0.021)
0.065***
(0.018)
0.207***
(0.029)
0.033***
(0.012)
Female
5.443**
(2.641)
11.682**
(4.761)
Female sq
-27.672**
(13.609)
FemSB
2.420**
(0.968)
10.955***
(3.717)
FemSB sq
-23.500***
(8.800)
FemMgtB
-2.295
(1.454)
-7.388**
(3.418)
FemMgtB sq
13.434**
(6.711)
Impaired Loans/Gross Loans
-0.035
(0.041)
0.007
(0.049)
0.005
(0.014)
0.018
(0.016)
B.Size
-0.066
(0.081)
-0.071
(0.093)
SB.Size
-0.104***
(0.025)
-0.158***
(0.038)
Mgt.B.Size
0.235**
(0.120)
0.260**
(0.121)
INED
-0.475
(1.703)
-0.412
(1.717)
3.262***
(1.159)
3.250***
(1.065)
CEO/Chair
-1.344
(1.297)
-0.800
(1.334)
LnTA
-0.220
(0.263)
-0.214
(0.243)
-0.495***
(0.157)
-0.459***
(0.174)
Bank Age
-0.0004
(0.002)
-0.001
(0.001)
-0.008**
(0.004)
-0.005
(0.005)
Total Capital Ratio
0.133***
(0.047)
0.145***
(0.049)
-0.013
(0.013)
-0.005
(0.017)
List Dummy
-0.424
(2.086)
-0.917
(2.036)
-1.932*
(1.108)
-1.108
(1.130)
lnGDP
0.437
(0.408)
0.554
(0.382)
-0.639*
(0.352)
-0.602*
(0.356)
Power Distance
0.026
(0.039)
0.023
(0.037)
-0.032**
(0.016)
-0.026
(0.019)
Disclosure Index
0.140
(0.313)
0.177
(0.326)
0.374
(0.282)
0.319
(0.308)
Enforcement Index
-0.141*
(0.075)
-0.122
(0.102)
0.036
(0.171)
-0.015
(0.159)
Overseas Branches
-0.387
(1.094)
-0.182
(1.236)
0.359
(0.775)
0.794
(1.006)
Law
-0.552
(1.323)
-0.905
(1.366)
37
Constant
-6.419
(9.889)
-9.217
(9.619)
5.550
(4.003)
5.736
(4.117)
Time dummy
Yes
Yes
Yes
Yes
Bank type
Yes
Yes
Yes
Yes
Wald test p.value
0.000
0.000
0.000
0.000
Arellano-Bond test for AR(1)
p.value
0.038
0.043
0.031
0.035
Arellano-Bond test for AR(2)
p.value
0.266
0.264
0.711
0.887
Hansen test p.value
0.732
0.931
0.617
0.901
Female: proportion of female directors sitting on the board of directors; FemaleSB: proportion of female
directors sitting on the supervisory board; FemaleMgtB: proportion of female directors sitting on the
management board ROA: ratio of net income divided by the average of the two most recent years of total
assets. Impaired Loans/Gross Loans (%): The ratio of impaired loans/gross loans as a proxy for financial
fragility; B.Size: total number of directors sitting on the board directors; SB.Size: total number of
directors sitting on the supervisory board; Mgt.B.Size: total number of directors sitting on the
management board; INED: proportion of independent non-executive directors; CEO/Chair: dummy
variable takes the value of 1 where the role of the CEO and Chairman are conducted by the same person,
and zero otherwise; LnTA: natural logarithm of bank total assets as a proxy for bank size; BankAge: bank
age calculated as the number of years since bank foundation; ListDummy: dummy variable takes the
value of 1 if the bank is privately held and 0 otherwise; lngdp: natural logarithm of gross domestic
product in euros; Total capital ratio: capital ratio as a regulatory requirement in banking sector; Power
Distance: A dimension from Hofstede’s culture framework (2001) to control for the cultural differences
across EU countries; Disclosure and Enforcement Indexes: sum of dummy variables take the value of 1 if
the answer to questions on disclosure and enforcement from the Bank Regulation and Supervision
Survey, carried out by the World Bank, is yes and 0 otherwise; Overseas Branches: dummy variable
takes the value of 1 if a bank has overseas branch(es) and 0 otherwise as a proxy for internationalisation;
Law: dummy variable takes the value of 1 if the respective banks headquarter is located in a common law
country and 0 otherwise. ***, **, and * indicates significance at the 1%, 5% and 10% levels respectively.
Clustered robust standard errors are present.
38
Table 8: The Determinants of the Proportion of Female Directors in EU Banks: System
GMM Estimator
Panel A
Panel B
Panel C
Board of Directors
Supervisory Board
Management Board
Model 1
Model 2
Model 3
L. Female
0.955***
(0.096)
L.FemSB
0.798***
(0.129)
L.FemMgtB
0.852***
(0.025)
Impaired Loans/Gross Loans
-0.001
(0.001)
0.0001
(0.001)
-0.003***
(0.001)
ROA
-0.016**
(0.008)
-0.027
(0.033)
0.015***
(0.004)
B.Size
0.008**
(0.004)
SB.Size
0.017**
(0.008)
Mgt.B.Size
-0.003***
(0.001)
INED
0.116**
(0.057)
0.401**
(0.201)
CEO/Chair
-0.022
(0.042)
LnTA
-0.005
(0.008)
0.033**
(0.015)
0.003
(0.002)
Bank Age
0.0004
(0.004)
-0.001
(0.0004)
-0.001***
(0.0003)
Total Capital Ratio
0.001
(0.001)
0.006**
(0.003)
0.001***
(0.0002)
List Dummy
-0.061
(0.053)
-0.122
(0.108)
-0.028**
(0.013)
lnGDP
-0.022
(0.022)
-0.015
(0.037)
-0.005
(0.006)
Power Distance
0.001
(0.001)
0.004**
(0.002)
-0.0003
(0.0002)
Disclosure Index
-0.004
(0.011)
-0.010
(0.025)
0.001
(0.001)
Enforcement Index
-0.003
(0.004)
0.032
(0.020)
0.007***
(0.001)
Overseas Branches
0.032
(0.052)
0.027
(0.101)
0.024**
(0.012)
Law
-0.053
(0.046)
Constant
0.196
(0.204)
-0.330
(0.440)
-0.035
(0.091)
Time dummy
Yes
Yes
Yes
Bank type
Yes
Yes
Yes
Wald test p.value
0.000
0.000
0.000
Arellano-Bond test for
AR(1) p.value
0.000
0.016
0.039
Arellano-Bond test for
0.799
0.418
0.927
39
AR(2) p.value
Hansen test p.value
0.940
0.922
0.986
L. Female: lagged proportion of female directors sitting on the board of directors; L.FemaleSB: lagged proportion of
female directors sitting on the supervisory board; L.FemaleMgtB: lagged proportion of female directors sitting on the
management board ROA: ratio of net income divided by the average of the two most recent years of total assets.
Impaired Loans/Gross Loans (%): The ratio of impaired loans/gross loans as a proxy for financial fragility; B.Size:
total number of directors sitting on the board directors; SB.Size: total number of directors sitting on the supervisory
board; Mgt.B.Size: total number of directors sitting on the management board; INED: proportion of independent non-
executive directors; CEO/Chair: dummy variable takes the value of 1 where the role of the CEO and Chairman are
conducted by the same person, and zero otherwise; LnTA: natural logarithm of bank total assets as a proxy for bank
size; BankAge: bank age calculated as the number of years since bank foundation; ListDummy: dummy variable
takes the value of 1 if the bank is privately held and 0 otherwise; lngdp: natural logarithm of gross domestic product
in euros ;Total capital ratio: capital ratio as a regulatory requirement in banking sector; Power Distance: A dimension
from Hofstede’s culture framework (2001) to control for the cultural differences across EU countries; Disclosure and
Enforcement Indexes: sum of dummy variables take the value of 1 if the answer to questions on disclosure and
enforcement from the Bank Regulation and Supervision Survey, carried out by the World Bank, is yes and 0
otherwise; Overseas Branches: dummy variable takes the value of 1 if a bank has overseas branch(es) and 0 otherwise
as a proxy for internationalisation; Law: dummy variable takes the value of 1 if the respective banks headquarter is
located in a common law country and 0 otherwise. ***, **, and * indicates significance at the 1%, 5% and 10% levels
respectively. Clustered robust standard errors are present.
40
0.076 0.074 0.08 0.08 0.093 0.101 0.113
0.13
0.153
0
0.05
0.1
0.15
0.2
2004 2005 2006 2007 2008 2009 2010 2011 2012
Figure 2: Average Proportion of Female Directors
sitting on European Banks with Unitary Boards 2004-
2012
0.154 0.163 0.186
0.035
0.113
0.079 0.02
0.126
0.063 0.022 0.025 0.005 0.017 0.034 0 0.025
0
0.05
0.1
0.15
0.2
Figure 3: Average Proportion of Female Directors
sitting on European Banks with Dual Boards by
Country
FemSB FemMgt
0.115 0.124 0.127 0.117 0.128 0.124 0.132
0.15 0.158
0.026 0.024 0.033 0.022 0.026 0.032 0.031 0.033 0.037
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
2004 2005 2006 2007 2008 2009 2010 2011 2012
Figure 4: Average Proportion of Female Directors sitting on
European Banks with Dual Boards 2004-2012
FemSB FemMgt
0.344
0.222
0.175
0.114 0.105 0.097 0.076 0.044 0.043 0.036 0.033
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Figure 1: Average Proportion of Female Directors sitting
on European Banks with Unitary Boards by Country
... In fact, prior empirical literature on the impact of gender diversity on bank performance is inconclusive. Thus, while some studies report a positive association (EBA, 2020;García-Meca et al., 2015;Owen and Temesvary, 2018), others find negative or mixed effects (Berger et al., 2014;Farag and Mallin, 2017;Liao et al., 2019;Pathan and Faff, 2013). The inconclusiveness of prior literature might be due, inter alia, to the diverse: a) institutional, geographical and/or industrial contexts where the relevant research was conducted, b) research constructs employed, ☆ We are grateful to the editor Professor Iftekhar Hasan and two anonymous referees for the valuable and developmental comments during the review process. ...
... More related to our own institutional framework, studies conducted in Europe are more conclusive. Farag and Mallin (2017) investigate the impact of gender diversity on both risk and operating performance, while considering the different corporate governance mechanisms that exist in Europe. The authors find that, beyond a critical mass, female directors on BoDs and supervisory boards lead to lower risk and lower performance, while the appointment of additional female directors on management boards increases risk and performance. ...
... We test a threshold beyond which the presence of women on BoD is associated with higher shareholder value in the context of M&A. Drawing on tokenism and critical mass theories, discussed in Section 2.1, the empirical literature suggests that the critical mass of female directors on BoD is reached when there are three women (Fan et al., 2019;Konrad et al., 2008;Liu et al., 2014) or when they represent 15-30% of the board (Farag and Mallin, 2017;Joecks et al., 2013;Owen and Temesvary, 2018). Thus, we expect that the effect of female directors on the wealth gains of acquiring banks becomes more pronounced when they reach a critical mass. ...
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We explore the association between board gender diversity and shareholder value creation. Specifically, we investigate the impact of gender diversity on the economic impact of bank mergers and acquisitions (M&A). We employ a multi-year sample of M&A announced by European listed banks and find that: (i) the presence of women on the board of directors has a positive and statistically significant effect on acquirer gains; and (ii) boards with three or more women, or where women represent more than 25% of the board, have a stronger impact on acquirer gains than in the opposite case, consistent with critical mass theory. Moreover, banks with a critical mass of female directors perform better in undertaking value-enhancing M&A after the global financial crisis. Policy makers and practitioners could benefit from the findings by exploiting the advantages of board heterogeneity in terms of gender.
... Two other theories that are relevant in our context are the resource-based and stakeholder theories. The former suggests that more diverse boards provide unique information and essential resources for management decision making process, which, in turn, increase the financial and social performance of firms (García-Meca et al., 2015;Shaukat et al., 2016;Liu et al., 2014;Hillman and Dalziel, 2003;Farag and Mallin, 2017;Nguyen et al., 2015;Hafsi and Turgut, 2013). The latter argues that more diverse boards contribute to the firm financial and social performance by strengthening public image, enhancing communication with the stakeholders and wider society, and building stronger external relations which may not be achieved in all male boards (Hillman and Dalziel, 2003;Shaukat et al., 2016). ...
... Recently, interest has been in examining the role of gender diversity on bank boards. Prior research shows that gender diversity promotes bank profitability (Farag and Mallin, 2017), improves efficiency (Ramly et al., 2017;Andries et al., 2018), and reduces financial fragility (Owen and Temesvary, 2018). Several other studies find that banks with greater proportion of women on their 7 Empirical studies presented in this section relies on various alternative or parallel theories as follows: 1) Gender socialization theory (Ben-Amar et al., 2017;Liu, 2018;Harjoto and Rossi, 2019;McCright and Xiao, 2014;Cumming et al., 2015); 2) Diversity theory (Campbell and Mínguez-Vera, 2008;Gul et al., 2011;Atif et al., 2020;Liu, 2018); 3) Critical mass theory (Joecks et al., 2013;Torchia et al., 2011;Huse et al., 2009;Farag and Mallin, 2017;McGuinness et al., 2017;Jia and Zhang, 2013;Atif et al., 2020); 4) Social identity theory (Chen et al., 2016;Terjesen et al., 2009;Li and Zhang, 2019), 5) Agency theory (Erhardt et al., 2003;Liu et al., 2014;Carter et al., 2003;Francoeur et al., 2008;Hillman and Dalziel, 2003;Liao et al., 2015;Ramly et al., 2017;Andries et al., 2018;Nguyen et al., 2015;Hafsi and Turgut, 2013;Frias-Aceituno et al., 2013;Liu, 2018); 5) Resource dependence theory (García-Meca et al., 2015;Shaukat et al., 2016;Liu et al., 2014;Hillman and Dalziel, 2003;Farag and Mallin, 2017;Nguyen et al., 2015;Hafsi and Turgut, 2013), 6) Stakeholder theory (Frias-Aceituno et al., 2013;Harjoto et al., 2015;Francoeur et al., 2008;Liao et al., 2015); 7) Other theories (Hillman et al., 2002;García Lara et al., 2017;Lanis et al., 2017;Boulouta, 2013;Muller-Kahle and Lewellyn, 2011;Bernardi et al., 2006). ...
... Prior research shows that gender diversity promotes bank profitability (Farag and Mallin, 2017), improves efficiency (Ramly et al., 2017;Andries et al., 2018), and reduces financial fragility (Owen and Temesvary, 2018). Several other studies find that banks with greater proportion of women on their 7 Empirical studies presented in this section relies on various alternative or parallel theories as follows: 1) Gender socialization theory (Ben-Amar et al., 2017;Liu, 2018;Harjoto and Rossi, 2019;McCright and Xiao, 2014;Cumming et al., 2015); 2) Diversity theory (Campbell and Mínguez-Vera, 2008;Gul et al., 2011;Atif et al., 2020;Liu, 2018); 3) Critical mass theory (Joecks et al., 2013;Torchia et al., 2011;Huse et al., 2009;Farag and Mallin, 2017;McGuinness et al., 2017;Jia and Zhang, 2013;Atif et al., 2020); 4) Social identity theory (Chen et al., 2016;Terjesen et al., 2009;Li and Zhang, 2019), 5) Agency theory (Erhardt et al., 2003;Liu et al., 2014;Carter et al., 2003;Francoeur et al., 2008;Hillman and Dalziel, 2003;Liao et al., 2015;Ramly et al., 2017;Andries et al., 2018;Nguyen et al., 2015;Hafsi and Turgut, 2013;Frias-Aceituno et al., 2013;Liu, 2018); 5) Resource dependence theory (García-Meca et al., 2015;Shaukat et al., 2016;Liu et al., 2014;Hillman and Dalziel, 2003;Farag and Mallin, 2017;Nguyen et al., 2015;Hafsi and Turgut, 2013), 6) Stakeholder theory (Frias-Aceituno et al., 2013;Harjoto et al., 2015;Francoeur et al., 2008;Liao et al., 2015); 7) Other theories (Hillman et al., 2002;García Lara et al., 2017;Lanis et al., 2017;Boulouta, 2013;Muller-Kahle and Lewellyn, 2011;Bernardi et al., 2006). 8 Examining the COVID-19 effects on the firms' stock performance, Zolotoy et al. (2021) also argue that board gender diversity was perceived by the market as a positive signal regarding firm's ability to weather the implications of the pandemic. ...
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... Bellucci et al. (2010) argued that their study did not find evidence of a reduction in risk level in banks with a high proportion of female directors. However, Farag and Mallin (2017) reported that where the proportion of female directors on the board exceeds 23.6%, there is less chance of the firm being vulnerable to a financial crisis. The analysis so far shows inconclusive evidence on the effect of female representation on the board and bank risk-taking behaviour. ...
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... The impact of internal corporate governance mechanisms on firm performance accounts for a major stream of research in the finance field. Several corporate board attributes have been studied over the last decades (Cunha & Rodrigues, 2018), such as: i) board independence (Black, Carvalho, & Gorga, 2012;Coles, Daniel, & Naveen, 2014;Falato, Kadyrzhanova, & Lel, 2014); ii) board diversity (Farag & Mallin, 2017;Owen & Temesvary, 2018;Pathan & Faff, 2013); and iii) the effects of CEO attributes on market and accounting performance (Brodmann, Unsal, & Hassan, 2019;Fang, Francis, & Hasan, 2018;Nguyen, Hagendorff, & Eshraghi, 2018). ...
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Purpose This study aims to examine the effect of gender board diversity on corporate fraud. Particularly, it is to gain empirical evidence whether firms with more female corporate leaders are more (less) likely to engage in corporate fraud. Design/methodology/approach The authors use data of fraud firms from Accounting and Auditing Enforcement Releases. As a focus of the study, the authors take the fraud sample observations from the last 10 years, from 2011 to 2021. The idea is that the number of firms sectioned due to corporate fraud reached a peak in such periods. Findings In the context of non-state-owned enterprise environments, the authors find female corporate leaders are less likely to engage in corporate fraud. However, among firms with a state-owned background, the authors’ empirical evidence shows that the roles of female corporate leaders remain under-represented in the boardrooms. As reported, the presence of female corporate leaders does not bring a significant impact on enhancing group ethical decision-making and governance quality. This situation does appear when political connections between firms and governments or politicians are prevalent. Research limitations/implications This study has practical and theoretical implications. Given the increased pressure on companies around the globe to have more females in their boardrooms, this study provides insight into the effect of female corporate leaders on the prevalence of corporate fraud. As such, this study offers critical consideration for policymakers and regulators. Moreover, an analysis of whether and when the gender board diversity is associated with the firm’ propensity to perpetrate corporate fraud, particularly from the US corporate fraud, is sorely lacking. This study contributes to such gaps. Originality/value This study provides insightful discussion about the topical issue of whether, and under what circumstances, female corporate leaders influence (or do not influence) corporate fraud.
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Purpose This paper aims to uncover the global trend on the relationship between board gender diversity and firm risk. In addition, this paper investigates how country characteristics affect the relationship between board gender diversity and firm risk. Design/methodology/approach This study uses a large sample of firms in 45 countries for the period from 2002 to 2018. Ordinary least square regression is used as a baseline methodology, along with firm fixed effects. Difference-in-differences regression, two-stage least squares regression (instrumental variables approach) and change-on-change regression are adopted to better mitigate endogeneity. Findings This study finds that board gender diversity is associated with lower firm risk worldwide. In addition, the negative effect of board gender diversity on firm risk is more pronounced for firms that can more easily attract female directors, and for countries with lower power distance and greater preference for individualism. Practical implications The findings offer insights into the intense debate in recent years among academics and practitioners on the effect of board gender diversity on firm outcomes. Shareholders and directors may take the findings into account when they consider appointing female directors. The findings should be of interest to policymakers in countries that have not yet promoted board gender diversity. Originality/value By using an international sample with board gender quotas in different countries, this paper provides novel and persuasive evidence regarding the impact of board gender diversity on firm risk. This paper also adds to the literature by showing that the relationship between board gender diversity on firm risk is influenced by country characteristics.
Chapter
This chapter offers a comprehensive literature review of the existing research on board gender diversity (BGD) and performance in banks and other financial institutions. After briefly reviewing the main theories on the role of women in the decision-making process, we analyse different relationships. First, empirical studies investigating the relationship between BGD and bank economic-financial performance are examined. Given the large number of studies, they are grouped into three categories: (1) studies revealing a positive linear relationship, (2) studies supporting non-significant, negative, or non-linear relationships between BGD and bank performance, and (3) studies focused on the Microfinance Institutions (MFIs). Then, the analysis shifts to the studies that examine the associations between BGD and bank efficiency, bank corporate social responsibility (CSR) performance and bank risk-taking. The final section of the chapter is dedicated to other areas of research on bank gender diversity that would benefit from an in-depth exploration.
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