Impact of Board Diversity on Bank Performance – Empirical Evidence from
the European Context
Ângelo Miguel Martins Morgado
Dissertation
Master’s in Finance
Supervised by
Professor Jorge Bento Ribeiro Barbosa Farinha, PhD
September 2020
I
Acknowledgments
I would like to take this opportunity to thank my supervisor, Professor Jorge Farinha, for his invaluable contribution, guidance and help throughout this entire process.
Furthermore, I would also like to express my deepest gratitude to my family. I will always do my best to make you proud. A very special mention to Rui and Mara for the unconditional support and motivation. Without you, this would be impossible.
II
Abstract
Board diversity has been an extensively debated topic and a core subject in corporate governance. In more recent years, several countries have implemented political initiatives to promote diversity in the boardroom, such as the mandatory quotas. Previous empirical studies have tried to establish a relationship between board diversity and performance, but researchers have come to different conclusions. Moreover, the vast majority of these papers focus on non-financial companies, with a lack of studies in the banking sector.
In light of this, the purpose of this dissertation is to analyze the impact of board gender, nationality and age diversity on bank performance. In this study, we used a sample of 45 listed banks from 10 European countries over the period 2012 to 2018. The estimation method used to empirically test our hypotheses was the dynamic two-step system GMM. This process controls all the potential sources of endogeneity, such as the unobservable heterogeneity bias, simultaneity and the dynamic nature of the board diversity/bank performance relationship.
Our results suggest that the board gender and nationality diversity have a significantly negative impact on bank performance. On the other hand, the relationship between board age diversity and bank performance is also statistically significant but positive. This empirical evidence is consistent with the existing literature. It is also worth mentioning that our estimated results are robust to the alternative measure of bank performance and the different structures adopted by the board of directors.
Key-Words: Board Diversity; Gender; Nationality; Age; Performance; Banks; Endogeneity. Jel-Code: G21; G30; G34; M14.
III
Resumo
A diversidade no conselho de administração tem sido um tópico amplamente debatido e um assunto importante na governação das empresas. Nos últimos anos, diversos países têm implementado iniciativas políticas para promover a diversidade no conselho, como, por exemplo, as quotas obrigatórias. Vários estudos empíricos tentaram estabelecer uma relação entre a diversidade no conselho de administração e o desempenho das empresas, mas os investigadores têm chegado a diferentes conclusões. Além disso, a grande maioria destes papers focam-se em empresas não-financeiras, com uma escassez de estudos no setor bancário.
Tendo isto em consideração, o objetivo desta dissertação é analisar o impacto da diversidade no conselho de administração em termos de género, nacionalidade e idade na
performance dos bancos. Neste estudo, usamos uma amostra composta por 45 bancos cotados
na bolsa de valores provenientes de 10 países europeus referentes ao período de 2012 a 2018. O método de estimação usado para testar empiricamente as nossas hipóteses foi o dynamic
two-step system GMM. Este procedimento controla todas as fontes de endogeneidade, como a
heterogeneidade não-observada, a simultaneadade e a relação dinâmica entre a diversidade no conselho administração e a performance do banco.
Os nossos resultados sugerem que a diversidade de género e nacionalidade no conselho de administração têm um impacto significativamente negativo na performance dos bancos. Por outro lado, a relação entre diversidade de idade no conselho e o desempenho dos bancos é também estatisticamente significativa mas positiva. Estas evidências empíricas são consistentes com a literatura existente. É importante também mencionar que os nossos resultados são robustos às diferentes medidas de performance do banco e às diferentes estruturas adotadas pelo conselho de administração.
Palavras-Chave: Diversidade no Conselho de Administração; Género; Nacionalidade; Idade; Performance; Bancos; Endogeneidade.
Classificação JEL: G21; G30; G34; M14.
IV
Content Index
1. Introduction ... 1
2. Literature Review ... 4
2.1. The Structure and Role of the Board of Directors ... 4
2.2. Differences Between Financial and Non-Financial Firms ... 4
2.3. Board Diversity... 6
2.4. Theories Related to Board Diversity ... 7
2.4.1. Resource Dependence Theory ... 7
2.4.2. Social Identity Theory ... 8
2.5. Impact of Board Diversity on Performance ... 9
2.5.1. Gender Diversity and Performance ... 9
2.5.2. Nationality Diversity and Performance ... 11
2.5.3. Age Diversity and Performance ... 12
2.6. Contradictory Findings ... 14
3. Methodology and Data ... 15
3.1. Variables Specification ... 15
3.1.1. Dependent Variables ... 15
3.1.2. Explanatory Variables ... 15
3.1.3. Control Variables ... 16
3.2. Endogeneity and Empirical Modelling ... 17
3.3. Sample Construction ... 20 3.4. Descriptive Statistics ... 22 4. Empirical Results ... 26 4.1. Univariate Analysis ... 26 4.2. Multivariate Analysis ... 26 4.2.1. Base Model ... 26
V
5. Extended Analysis and Robustness Tests ... 33
5.1. Alternative Bank Performance Measure ... 33
5.2. The Effect of the Board Tier System ... 35
5.3. Test of Endogeneity ... 37 6. Conclusion ... 38 7. Appendices ... 40 Appendix A ... 40 Appendix B... 43 8. References ... 44
VI
Index of Tables
Table 1 - Sample Distribution by Year ... 22
Table 2 - Sample Distribution by Country ... 23
Table 3 - Descriptive Statistics ... 25
Table 4 - Pairwise Correlation Coefficients ... 27
Table 5 - Dynamic System GMM Regression Analysis: The Effect of Board Gender and Nationality Diversity on Bank Performance Measured by Tobin’s Q ... 28
Table 6 - Dynamic System GMM Regression Analysis: The Effect of Board Gender, Nationality and Age Diversity on Bank Performance Measured by Tobin’s Q ... 31
Table 7 - Dynamic System GMM Regression Analysis: The Effect of Board Gender, Nationality and Age Diversity on Bank Performance Measured by ROA... 34
Table 8 - Dynamic System GMM Regression Analysis: The Effect of the Tier System on the Relationship between Board Diversity and Bank Performance (Tobin’s Q) ... 36
Table 9 - The Durbin–Wu–Hausman Test ... 37
Table 10 - Summary of the Main Empirical Evidence on Board Diversity ... 40
VII
Acronyms List
BoD – Board of Directors CEO – Chief Executive Officer DWH – Durbin-Wu-Hausman FE – Fixed Effects
GMM – Generalized Method of Moments OLS – Ordinary Least Squares
1
1. Introduction
Over the past two decades, the corporate governance mechanisms, mainly the board of directors, have received considerable attention not only from academic researchers, but also from policymakers. To some extent, this interest emerged with the financial scandals involving the companies’ top management, as is the case of Enron and WorldCom (Campbell & Mínguez-Vera, 2008). However, it was the subprime crisis that highlighted the real importance of these mechanisms. The weak governance in the banking sector is usually considered one of the reasons for the global crisis. In particular, the OECD Steering Group on Corporate Governance emphasizes that the weak performance of the board of directors played a key role in the collapse of large financial institutions (Kirkpatrick, 2009).
In light of this, governments from many countries began to establish Corporate Governance Codes to improve board-level governance. Among other board characteristics, these guidelines drew attention to the qualifications, experience and diversity of the directors. Nevertheless, this was not the first time that board diversity has been addressed by active policymaking. Even before the global crisis, some countries, such as Norway and Finland, had established gender quotas aiming to increase the women representation at the board level (Terjesen, Aguilera, & Lorenz, 2015).
Throughout the years, several researchers have been studying the impact of board diversity on company performance, but the results have been divergent. Some studies found that a higher level of board diversity could lead to higher performance (e.g., Carter, Simkins, and Simpson (2003), Campbell and Mínguez-Vera (2008) and Oxelheim and Randøy (2003)), while others reported the opposite, such as Adams and Ferreira (2009) and Masulis, Wang, and Xie (2012). Theories from other research fields, such as organizational behavior and social psychology, are used to explain the empirical results found by these researchers (Carter, D'Souza, Simkins, & Simpson, 2010). Different from the others, some studies posited that board diversity has no impact on financial performance, as it the case of Carter et al. (2010) and Rose (2007).
In view of this, the present dissertation aims to enhance the understanding of the impact of board diversity on financial performance. The concept of board diversity can encompass several dimensions. Previous empirical studies tend to use only one particular characteristic of the directors to measure this notion. Thus, to complement the literature, we incorporate different dimensions of board diversity, including gender, nationality and age.
2 Although there are several studies on the board diversity/performance relationship, only a few pay attention to the perspective of banks. For this reason, this study will focus only on the banking sector. In fact, the corporate governance of banks seems to be different from the other non-financial companies, with distinct challenges arising from the nature of their activities and the regulation (Adams & Mehran, 2003; Macey & O'Hara, 2003). After the subprime crisis, it became more important than ever to understand the governance of banks, as well as their boards. As the Basel Committee on Banking Supervision (2015) advocates, the soundness and safety of the banks are vital to the balance of the financial system and, subsequently, to economic growth. Thus, effective corporate governance in the banking industry becomes even more important.
To establish a relationship between board diversity and bank performance, we need to take into consideration the problem of endogeneity. As the Ordinary Least Squares (OLS) and the fixed effects (FE) regressions do not overcome this issue, their estimated results will be inconsistent and biased. Therefore, in this study, we used the dynamic two-step system Generalized Method of Moments (also known as GMM) estimator developed by Arellano and Bover (1995) and Blundell and Bond (1998). This estimation process does not only control for unobservable heterogeneity, but also for the simultaneity and the dynamic nature of the relationship.
This dissertation employs a sample of unbalanced panel data from 2012 to 2018, encompassing 45 individual banks from 10 European countries. All the data were collected manually, except for accounting and financial information. Regarding the empirical models, our study follows a similar approach taken by García-Meca, Martínez-Ferrero, and Sánchez (2015). Additionally, we use another method considered more appropriate to measure board gender and nationality diversity: the Blau’s Index (Blau, 1977).
In short, our findings suggest that board gender and nationality diversity have a negative and statistically significant impact on bank performance, regardless of how we measure these indicators. On the other hand, we found that a higher level of board age diversity results in increased bank performance.
The present dissertation provides some important contributions to the existing literature on the relationship between board diversity and bank performance. Most of the previous studies on this topic focus on a single country. In contrast, we will perform a European analysis covering several countries, which is lacking in the existing literature. Moreover, unlike the vast majority of the studies, this dissertation controls the dynamic
3 relationship between past performance and the current corporate governance structure, thus improving the accuracy of our inferences.
The remainder of this study is divided as follows. In section 2, we present an overview of the relevant literature and define the main hypotheses that will be empirically tested. Section 3 details the methodology and the data employed in this dissertation. In section 4, we analyze and discuss the empirical results. Section 5 provides an additional analysis with some robustness tests. Lastly, in section 6, we present the main conclusions, as well as some practical implications and suggestions from future studies.
4
2. Literature Review
2.1. The Structure and Role of the Board of Directors
The agency theory lays the foundation for corporate governance. This theoretical concept is based on the separation of ownership (e.g., shareholders) and control (e.g., managers) (Berle & Means, 1933). The primary assumption is that the interests of these two parties may not always coincide, which can lead managers to make decisions based on their own best interests, not maximizing the shareholders’ wealth (Jensen & Meckling, 1976). To protect their interests and to mitigate these agency problems, shareholders should establish governance mechanisms to control the behavior and performance of managers (John & Senbet, 1998).
One of the most common internal mechanisms is the board of directors (also termed as BoD). The boards of directors can use two different structure models: the one-tier and the two-tier system. According to Denis and McConnell (2003), the predominant structure in European countries is the unitary system, a board composed of both executive and non-executive directors. Nevertheless, the two-tier board system is also used, since it is mandatory1 in some countries (e.g., Germany and Austria) and optional in others. In this structure, there is a supervisory board composed of non-executive directors and a management board with executives from the company (Denis & McConnell, 2003).
Overall, the board of directors acts as a representative of the shareholders, being responsible for controlling and monitoring the management team (the supervisory role), providing expert advice and information to managers (the advisory role) and intervening in some important managerial decisions (Adams & Ferreira, 2007; Schwartz-Ziv & Weisbach, 2013). According to Fama and Jensen (1983), the BoD is a powerful and extremely important governance mechanism, controlling the quality of the decisions and the smooth running of the company.
2.2. Differences Between Financial and Non-Financial Firms
In light of the foregoing, the role of the board of directors become even more relevant in the banking system, since financial institutions have distinctive idiosyncrasies that may amplify the governance problems (Adams & Mehran, 2003). In particular, the banking
1 In some countries, it is also required the presence of employees representatives on the supervisory board
5 business is opaquer and more complex than other sectors2 (Macey & O'Hara, 2003), which
aggravates the information asymmetry. Despite being common in all sectors, some researchers claim that the problem of asymmetry of information is more visible in financial firms (Furfine, 2001; Morgan, 2002), which makes it more challenging and difficult to control the management team
Furthermore, banks are significantly more leveraged than nonfinancial companies (Adams & Mehran, 2003). Most of the banks’ capital is provided by debtholders, the vast majority of which are depositors. These stakeholders also have direct interests in the performance of these financial institutions, but they may deviate significantly from those of the shareholders (Macey & O'Hara, 2003). Thus, the conflict between the two parties may intensify the agency problem, affecting the bank’s performance.
The banking sector is also more regulated and supervised than other industries, since banks play a key role in our economic system (Pathan & Faff, 2013). Bank regulators aim to ensure the soundness and safety of the financial system, to protect the depositors’ rights and to mitigate the systemic risk3 (de Andres & Vallelado, 2008). In other words, this means that
regulators also have vested interests in bank performance; however, their interests may not be in line with those of the other stakeholders. According to Adams and Mehran (2003), there is a conflict of interests between shareholders and regulators, or, in other words, between value maximization and banks’ stability.
For all these reasons, it is presumed that the BoDs of banks have a different composition than the boards of other companies. Consistent with this, Adams and Mehran (2003) observed that banks have bigger boards than non-financial institutions4. In their study,
the authors argue that the board composition of banks might be explained by their complex activities and their organizational structure. Another possible explanation may derive from the fact that banks are also subject to requirements and regulatory restrictions5, which may
constraint the board size (Pathan & Faff, 2013).
2 Laeven (2013) stated that the nature of the banks’ assets is not easily perceived, and their risk composition
can be quickly changed. In addition to this, banks operate in different markets and jurisdictions with sophisticated instruments, making the sector more complex (Macey & O'Hara, 2003).
3 For Billio, Getmansky, Lo, and Pelizzon (2012), the systemic risk can be defined as any event that may
undermine the stability and viability of the financial system. Thus, the collapse of bank may infect those who are ‘healthy’, which can jeopardize the financial system.
4 Booth, Cornett, and Tehranian (2002) also found empirical evidence that support this argument.
5 By way of illustration, the state of New York imposes banks to have boards composed of 7 to 25 members,
6 2.3. Board Diversity
Throughout the years, several studies have been focusing their attention on the relation between board composition and company performance. The proposition behind these papers is that the structure of the BoD affects the way that boards play their duties and responsibilities, which consequently influences the company’s performance (Hermalin & Weisbach, 2003; John & Senbet, 1998). Most of the existing literature focuses on board structure features, such as size and independence. Among these studies, the idea that the board composition influences the performance has been widely accepted.
In the same line of thought, another strand of studies has emerged, linking the characteristics of directors with the company’s performance. As a subset of the board composition, the specific features and attributes of the board members may also impact the board's effectiveness and, subsequently, the firm-level outcome (Carter et al., 2010; van der Walt & Ingley, 2003). Under those circumstances, it emerged the notion of board diversity.
The concept of diversity is subject to a variety of definitions. According to Milliken and Martins (1996), a common approach to categorize different types of diversity is to distinguish between observable and non-observable characteristics. In this case, the observable diversity takes into account readily-detected attributes, e.g., gender, age and race, while non-observable diversity considers cognitive features, such as education, experience and personal values (Milliken & Martins, 1996). The empirical studies on board diversity commonly use one specific attribute of the directors as a proxy for diversity, with the vast majority focusing on gender.
The topic of board diversity encompasses two main perspectives: the economic and the ethical (van der Walt & Ingley, 2003). As stated by Brammer, Millington, and Pavelin (2007), the moral viewpoint defends that it is improper and unethical to exclude someone from higher hierarchical levels due to their gender, race or other attributes, since all individuals should have the same equal opportunity. According to the same researchers, diversity is not only important but also desirable, since it is closely related to equality of representation. Therefore, a greater level of diversity in the boardroom helps to reach a more equitable outcome for the shareholder and the society6.
6 This relates with the view that companies have a responsibility not only with the shareholders, but also with
the stakeholders (van der Walt & Ingley, 2003). Therefore, a board composed with diverse directors reflects the structure of a modern and multicultural society.
7 Regarding the business case (i.e., the economic perspective), there is still no consensus about the effect of board diversity on firm performance. Some researchers posit that diversity has a positive impact on the performance of the company, while others assert the opposite. In line with this, the theories mentioned bellow would detail these different points of view.
2.4. Theories Related to Board Diversity
The agency theory provides the basis for the study of corporate governance. However, as pointed by Hermalin and Weisbach (2003), this paradigm does not provide a clear prediction of the relationship between board diversity and firm value. Throughout the years, several studies have been conducted on this matter, but none of them explicitly developed a theoretical framework on this specific relationship (Carter et al., 2010). For this reason, the study of board diversity leads us to adopt a plural approach, considering theoretical concepts drawn from other fields, such as organization theory and social psychology. Thus, in our study, we will delve into two important theories: Resource Dependence Theory and Social Identity Theory.
2.4.1. Resource Dependence Theory
According to the Resource Dependence Theory (Pfeffer & Salancik, 1978), the performance of a company is affected by the external environment, since firms have at their disposal resources that others need to survive and vice versa. Thus, this organizational interdependence results in environmental uncertainties for corporations (Pfeffer, 1972). Under these conditions, the board of directors plays an important role as the linkage between its company and the other external corporations, providing several benefits to reduce uncertainties, such as resources (e.g., information and expertise), legitimacy and channels of communication (Pfeffer & Salancik, 1978).
According to this theory, a board with a higher level of diversity may improve these aspects. Hillman, Cannella, and Paetzold (2000) argue that each director may bring diverse and unique resources to the board. Hence, the inclusion of different directors on board gives access to a wider range of information, perspectives and knowledge, which may improve decision-making and problem-solving7.
7 Supporting this view, Campbell and Mínguez-Vera (2008) state that a diverse board takes into consideration
8 Moreover, a heterogeneous board has the potential to expand its linkages with external companies. For example, Booth and Deli (1999) found that companies whose directors are commercial bankers have greater total debt. According to the same researchers, these firms will benefit from the expertise and linkages that these directors have in the bank debt market. In line with this, Carter et al. (2003) posited that a diverse board has a greater cultural sensitivity, which creates stronger global connections.
Additionally, the company’s ability to penetrate the market will increase if the diversity of a BoD matches the marketplace (Campbell & Mínguez-Vera, 2008). In other words, the diversity of the firm’s directors sends a positive signal to society, which may enhance its credibility and reputation. As a result, this may attract more individuals with different talents from the labor market, improving creativity and innovation (Carter et al., 2003).
2.4.2. Social Identity Theory
Developed by Tajfel (1978), the Social Identity Theory postulates that individuals categorize themselves and others by particular characteristics (e.g., gender or nationality). These categorizations processes work as a way for the individual to define him- or herself, almost like a quick answer to the question: ”Who am I?”(Ashforth & Mael, 1989). According to this theory, the social categorization of ‘self’8 and others create social groups. Thus, the individuals who are similar to the ‘self' are categorized as the in-group, while others belong to the out-group (Stets & Burke, 2000).
Under those conditions, individuals may engage in behaviors, such as stereotypes or ethnocentrism (Hogg & Terry, 2000). As stated by Brewer (1979), the out-group is considered less honest, more uncooperative and less trustworthy. Hence, individuals will be biased and show preference and favoritism for the members of the in-group and neglect those who resemble the out-group (Brewer, 1979).
These categorization processes are expected to take place in a more diverse group, such as a board of directors, generating in- and out-groups. Therefore, a board with members with more distinct characteristics may experience more communication problems and more conflicts, which will create barriers to cooperation (Pelled, 1996). Those barriers may decrease the likelihood that minority perspectives influence the board (Westphal & Milton,
8 According to Tajfel (1978), the self categorization process works as way for individuals to enhance their
9 2000). Under these conditions, the decision-making process will be more time-consuming, which will worsen the company’s performance (Milliken & Martins, 1996).
2.5. Impact of Board Diversity on Performance 2.5.1. Gender Diversity and Performance
Among the various attributes of the directors, gender is the characteristic that has been most examined in empirical studies. Several arguments support the presence of women in the boardroom. Nielsen and Huse (2010) asserted that females directors are different from men in terms of skills and leadership, meaning that they bring different resources and viewpoints to the board. Other researchers stated that the inclusion of women might enhance creativity and innovation (Campbell & Mínguez-Vera, 2008). These factors will improve decision-making and problem-solving processes (Carter et al., 2003). Moreover, Smith, Smith, and Verner (2006) posited that a higher level of board gender diversity strengthens the reputation and legitimacy of the company. All of these arguments are in line with the Resource Dependence Theory (Pfeffer & Salancik, 1978).
Some studies have shown empirical evidence of a positive effect of board gender diversity on company performance. In particular, Carter et al. (2003) examined the impact of the boards on the Fortune 1000 firms and found a positive linear relationship between the presence of female directors and financial performance, which was measured by Tobin’s Q. Campbell and Mínguez-Vera (2008) drawn the same conclusions, using a sample of Spanish companies from 1995 to 2000.
In the same vein, Liu, Wei, and Xie (2014) found that Chinese companies with a gender-diverse board exhibit significantly better performances. However, the authors assert that the positive effect is only statistically significant when the board is composed of at least three women. As a minority in the boardroom, the female directors will not be able to exert their influence on decision-making until a critical mass is achieved, which, in this case, is three women.
Nevertheless, other arguments contest the potential advantages of gender diversity. In groups (such as the board of directors), members may feel a stronger identification with others of the same gender (Richard, Barnett, Dwyer, & Chadwick, 2004), which corroborates with the Social Identity Theory (Tajfel (1978). Thus, a more gender-diverse board with various viewpoints and opinions may experience more conflicts (Smith et al., 2006). As a result, the process of decision-making can be more time-consuming and slow, which can
10 jeopardize companies, especially those who require to react quickly to the changes in the market (Hambrick, Cho, & Chen, 1996).
In line with this, some empirical studies corroborate these arguments. Using a sample of Norwegian firms, Bøhren and Strøm (2010) found a negative and statistically significant relationship between the proportion of female directors and firm performance. Adams and Ferreira (2009) developed a similar study on a sample of American companies over the period 1998-2003. The authors found that gender-diverse boards might lead to over monitoring the companies, which could negatively affect their performances.
In contrast to the results already presented, some studies found no linkage between board gender diversity and company performance. Considering a sample of Danish companies, Rose (2007) posited that the proportion of women on the BoD has no impact on the company performance, without considering the endogeneity problem. The study of Carter et al. (2010) corroborated these findings, but using a sample of S&P 500 index’s companies over a period of 5 years (1998-2002).
Regarding the banking sector, Pathan and Faff (2013) found that gender diversity has a positive impact on the US bank performance in the pre-Sarbanes-Oxley Act (SOX)9 period (1997-2001). However, this effect becomes negative in the subsequent periods, i.e., in the post-SOX (2003-2006) and the crisis (2007-2011). Using a sample of 9 countries, spanning from 2004 to 2010, García-Meca et al. (2015) found a positive link between the percentage of women on the board and bank performance, which was measured as a proxy of Tobin’s Q and Return on Assets (termed as ROA).
Based on the theoretical concepts and the contradictory empirical findings, it is not possible to predict clearly whether the board gender diversity has a positive or negative impact on bank performance. As a result, we formulated the following hypotheses:
Hypothesis 1.1 (H1.1): There is a positive relationship between board gender diversity and bank performance.
Hypothesis 1.2 (H1.2): There is a negative relationship between board gender diversity and bank performance.
9 The financial scandals that occurred at the beginning of the century led the US Congress to approve the
11 2.5.2. Nationality Diversity and Performance
Similar to gender, the empirical findings on the impact of board nationality diversity on financial performance are inconclusive. Some authors argue that a greater heterogeneity will be advantageous for the company performance. In particular, Oxelheim and Randøy (2003) posit that foreign board membership will guide the company towards its internationalization, providing advice and guidance through a more global orientation. Thus, the foreign directors have at their disposal information and linkages with foreign markets, which may benefit decision-making. Moreover, Oxelheim and Randøy (2003) also state that a board composed of directors with different nationalities will attract more foreign investors since the presence of these directors signals a greater commitment with transparency and representation in the BoD. These arguments are consistent with what the Resource Dependence Theory (Pfeffer & Salancik, 1978) advocates.
In line with this, Oxelheim and Randøy (2003) found that Swedish and Norwegian companies show a significantly higher firm value when they have Anglo-American directors (which they categorized as foreign directors). Similar to this, Estélyi and Nisar (2016) also found a positive and statistically significant relationship between board nationality diversity and firm performance, using a dataset of UK companies over a period of 11 years (2001-2011).
On the contrary, other authors argued that foreign board membership might worsen financial performance. According to Hambrick, Davison, Snell, and Snow (1998), national culture has significant implications on individuals’ language and cognitive behavior. As individuals identify with those who can share the same characteristics and values, nationality can become a differentiating factor within a group. Thus, group members with different nationalities may experience more communication and cooperation problems (Hambrick et al., 1998). This may happen on the board of directors, which will affect the decision-making process and, subsequently, the company performance (Milliken & Martins, 1996).
For instance, Masulis et al. (2012) found empirical evidence that the proportion of foreign independent directors (FID) has a negative effect on company performance. In their paper, the authors note that the distance between the company’s headquarters and the FIDs is a very important factor in board effectiveness. According to the Masulis et al. (2012), the longer the distance between the company’s headquarters and the FIDs, the greater the time spent traveling and, therefore, less likely the director attendance to board meetings. Despite
12 this, other studies do not find a statistically significant link between nationality heterogeneity and company performance, as is the case of Rose (2007).
Concerning the financial firms, the existing literature is exceptionally sparse, to the extent that the García-Meca et al. (2015)’s study is the only paper that examines the effect of board nationality diversity on bank performance. In their study, the researchers found that banks with foreign directors exhibit significantly poorer performances. However, they posit that this effect is dependent on the legal and regulatory environment of the country. Thus, the negative impact of board nationality diversity will be greater when countries have higher levels of regulation and investor protection.
The contradictory theories, arguments and empirical evidence make it difficult to define the relationship between board nationality diversity and bank performance. For this reason, we hypothesized the following:
Hypothesis 2.1 (H2.1): There is a positive relationship between board nationality diversity and bank performance.
Hypothesis 2.2 (H2.2): There is a negative relationship between board nationality diversity and bank performance.
2.5.3. Age Diversity and Performance
Among the three characteristics, there is a clear lack of empirical studies on the business case of board age diversity. Nevertheless, the management literature offers some insights into the effect of age on managers, which can also be easily applied to directors.
According to Bantel and Jackson (1989), younger managers usually have more technical knowledge, since it is more likely that they have received their education more recently. Furthermore, younger managers, as well as directors, are more receptive to change and innovation and have a more forward-looking vision (Child, 1974). However, older directors have a vast network and years of experience, which might facilitate taking more complex and ambiguous decisions and might help to achieve higher levels of board effectiveness (Grove, Patelli, Victoravich, & Xu, 2011). In light of this, some authors suggest that pooling the resources of young and senior directors will improve the process of decision-making and problem-solving (Ali, Ng, & Kulik, 2014), which corroborates the Resource
13 Dependence Theory (Pfeffer & Salancik, 1978). Therefore, a board with a higher level of age heterogeneity may improve the performance of the company.
Regarding the empirical studies, Mahadeo, Soobaroyen, and Hanuman (2012) attempted to link board gender diversity and company performance in an emerging country, Mauritius. Without controlling the effect of endogeneity, they found that the higher the level of age diversity among directors, the higher the company performance.
Nevertheless, other arguments contradict a positive relationship between these two aspects. According to Murray (1989), individuals tend to socialize and relate to others of the same age, since they experience similar social and economic events that shaped their values and attitudes. In line with this, a group with a higher level of age heterogeneity may experience more misunderstandings and conflicts between members (Murray, 1989), which in the case of the BoD, makes the process of decision-making more time-consuming10. The study of Ali et al. (2014) developed in the Australia context corroborates with these arguments. The authors found a negative and linear relationship between age diversity and company performance11, despite not taking into account the problem of endogeneity.
In contrast to previous results, the study of Bøhren and Strøm (2010) concludes that there is no significant relationship between firm performance and board age diversity for a sample of Norwegian companies. Regarding the banking sector, the study of Grove et al. (2011) is the only one that addresses the issue of board age heterogeneity. The authors found empirical evidence that the average age of directors has a non-linear relationship with financial performance when measured as ROA. However, they did not control the effect of endogeneity.
All things considered, as it is not possible to precisely define an exact relationship between board age diversity and bank performance, we developed the following hypotheses: Hypothesis 3.1 (H3.1): There is a positive relationship between board age diversity and bank performance.
Hypothesis 3.2. (H3.2): There is a negative relationship between board age diversity and bank performance.
10 This is in line with the Social Identity Theory (Tajfel, 1978)
11 Ali et al. (2014) also developed a model to test a non-linear relationship between ROA and age diversity. The
authors noted that when the board of directors is composed of 10-15% of young directors, the company performance reaches its maximum value.
14 2.6. Contradictory Findings
As shown above, the empirical studies’ results on the relationship between board diversity and company performance are divergent. According to Adams, de Haan, Terjesen, and van Ees (2015), some possible explanations for the mixed findings may lie in the dissimilar methodologies and distinctive samples applied by the researchers. Another possible reason for the inconsistent results may arise from the different ways used to measure diversity (Adams et al., 2015), such as the proportion of directors with the specific characteristics, dichotomous variables and heterogeneity index (as is the case of Blau’s Index)12.
Furthermore, Adams et al. (2015) also state that the endogeneity problem may be another reason for the divergent outcomes. Previous studies on this topic have acknowledged the endogenous nature of board diversity (Hermalin & Weisbach, 2003; Wintoki, Linck, & Netter, 2012). Nonetheless, if endogeneity issues are not overcome, the coefficients will be inconsistent and biased, preventing statistical inference. As previously noted, some studies do not take into account this problem, leading to erroneous and also contradictory results among researchers. The problem of endogeneity between board diversity and bank performance will be further developed in the following sections.
15
3. Methodology and Data
3.1. Variables Specification
In the existing literature, several models were employed to test the relationship between board diversity and company performance, but the vast majority were designed for non-financial companies. Among the few exceptions, García-Meca et al. (2015) developed a model that analyzes the impact of female and foreign directors on bank performance, which suits closely with the purpose of our research. For this reason, the variables13 in our models will be inspired by the approach taken by these authors.
3.1.1. Dependent Variables
Consistent with García-Meca et al. (2015), we will measure bank performance using Tobin’s Q (termed as Tobin), which is defined as the sum of the market value of common equity plus the book value of total assets minus the book value of common equity divided by the book value of total assets. Furthermore, we will also use the return on assets (ROA), calculated as the income before extraordinary items, interest expenses and taxes divided by the average of the two most recent years. These two variables have been used in previous studies to measure the performance of both financial and non-financial companies (e.g., Adams and Ferreira (2009), Bøhren and Strøm (2010), Masulis et al. (2012)). According to García-Meca et al. (2015), both variables should be tested since each assesses a different aspect of bank performance. As a market-based measure, Tobin’s Q offers a forward-looking perspective of bank performance, while ROA – an accounting measure – focuses on past performance.
3.1.2. Explanatory Variables
Regarding the measures for gender and nationality diversity of the board of directors, we will use two different approaches. In agreement with García-Meca et al. (2015), we will consider the percentage of women (%Gender) and foreign members (%National) on the board, calculated as the number of female and foreign nationality directors divided by the total members of the BoD. Nevertheless, some authors argue that these indicators may not be the appropriate approach to measure diversity, as a higher percentage of female or foreign
16 directors will make the board more homogeneous, but in respect of gender or nationality (Campbell & Mínguez-Vera, 2008).
Therefore, we will employ the Blau Heterogeneity Index (Blau, 1977) to measure board gender (BlauGender) and nationality (BlauNational) diversity. Blau’s Index has been suggested as an appropriate method to measure diversity, most commonly used for categorical attributes, e.g., gender or nationality (Campbell & Mínguez-Vera, 2008). This index is defined by equation (3.1).
𝐵𝑙𝑎𝑢′𝑠 𝐼𝑛𝑑𝑒𝑥 = 1 − ∑ 𝑃𝑖2
𝑛 𝑖=1
(3.1)
𝑃𝑖2 represents the fraction of board members in each category and 𝑛 is the number of categories for an attribute of interest. By construction, this index ranges from 0 to 0,5. The higher the value, the greater the level of diversity on the board of directors. When the proportion of board members from both groups is the same (whether women and men or foreign and local directors), Blau’s Index reaches its maximum value.
In addition to gender and nationality, we will consider another dimension of diversity: the directors’ age, thus extending the analysis of García-Meca et al. (2015). Previous studies have used different indicators to measure board age heterogeneity, such as the coefficient of variation14 and the standard deviation. However, the use of the coefficient of variation may be problematic and lead to erroneous results. For example, suppose there is a board of directors that does not change over time. The standard deviation of directors’ age will remain the same, but each passing year, the coefficient of variation will become smaller as the mean increases. Although nothing has changed, the same board of directors will exhibit different levels of heterogeneity.
Considering this, we decided to measure board age diversity using the standard deviation of directors’ age (Age). Hence, the larger the standard deviation, the higher the level of age heterogeneity on the board.
3.1.3. Control Variables
Based on the model of García-Meca et al. (2015), we will also include a group of control variables to prevent biased results. To control the effect of board structure, we will
17 consider features such as size, independence and activity. Board size (Bsize) is measured by the total number of board members. According to Jensen and Meckling (1976), larger boards are less efficient, as they face more communications and free-riding problems. In contrast, Coles, Daniel, and Naveen (2008) claim that larger boards may be beneficial to complex and diversified companies (e.g., banks), considering that more directors may bring additional experience and expertise to the boardroom.
Regarding board independence, we will incorporate two variables: the proportion of independent directors on the board (%Ind) and CEO duality (Dual), represented by a dummy variable equal to one when the CEO is also the Chairman of the board and zero otherwise. According to de Andres and Vallelado (2008), companies may benefit from having more independent directors, since they have fewer conflicts of interest, which makes them more efficient at monitoring management. Concerning CEO duality, Grove et al. (2011) posit that board monitoring will be undermined if the person who makes the strategic decisions is the same who evaluates and controls the management team, which ultimately jeopardize the bank performance.
Consistent with García-Meca et al. (2015), we will incorporate the number of board meetings held annually (Meet) and the number of board subcommittees (SubCom). These variables have also been included in other empirical studies to control the effects of the activity of the board and its organizational complexity.
To control the bank-specific characteristics, we will consider bank size (BankSize), defined as the logarithm of the book value of total assets, and the bank’s loans (Loans), calculated as the loans divided by the bank’s total assets (at book value).
In addition, we will also incorporate a dummy variable for each year of our period of analysis (Year) to control the temporal effects and the regulatory and macroeconomics changes. As a robustness test, we will consider the variable TierSyst to control the structure system adopted by the board of directors. This variable will be represented by a dummy equal to one when the board has a two-tier system and zero when it has a unitary structure.
3.2. Endogeneity and Empirical Modelling
Regarding the estimation process, it is inevitable to consider the endogeneity problem underlying the relationship between board diversity and bank performance. Wintoki et al. (2012) state that part of the endogeneity issues results from unobservable characteristics that affect both financial performance and the firm’s governance structure. A simple OLS
18 regression will ignore the unobservable heterogeneity, resulting in unbiased and inconsistent estimators. Therefore, several studies have been employing the FE model to overcome this econometric issue. However, this method is only consistent when the variables are strictly exogenous (Wintoki et al., 2012).
Apart from the unobserved heterogeneity, the theory argues that the board diversity/performance relation is subject to other sources of endogeneity. Previous studies on this topic provided evidence of a simultaneous relationship between performance and board composition15, meaning that both factors influence each other. Additionally, Wintoki et al. (2012) also claimed that the dynamic nature of this relationship is also a potential source of endogeneity, since the past company performance may influence the current board composition. These two sources of endogeneity violate the assumption of strict exogeneity, which implies that the FE method is inconsistent.
As an alternative, some studies have been using GMM. Introduced by Holtz-Eakin, Newey, and Rosen (1988) and Arellano and Bond (1991), the dynamic two-step difference GMM provides estimators robust to all the sources of endogeneity. This econometric method uses a first-differenced form of the model to overcome the unobservable heterogeneity. Another key point of the difference GMM is the use of the lagged values of the variables as their respective instruments without the need for external instruments, which, in some cases, are complicated or even impossible to find. In other words, this procedure allows us to consider the endogenous variables by using their historical values as instruments. Moreover, the dynamic difference GMM also incorporates a lagged dependent variable as a regressor to control the dynamic nature of the corporate governance/performance relation. On top of that, this method will also produce adjusted standard errors to potential heteroskedasticity and serial correlation.
Nevertheless, the difference GMM has some econometric shortcomings. According to Blundell and Bond (1998), this estimation technique is strongly affected by the finite sample bias and the weak precision of the estimators, since the lagged values of the variables in levels are weak instruments in the first difference equations. In order to improve this model, Arellano and Bover (1995) and Blundell and Bond (1998) developed the dynamic two-step System GMM. This method aims to mitigate the limitations of the difference GMM by combining in an equation system the first difference and the level regressions. Thus, we
19 will be able to use the lagged value of the endogenous variables both in difference and in levels, which will improve the efficiency of the GMM estimators.
Given these points, we decided to employ the dynamic two-step system GMM as our estimation process. Consistent with de Andres and Vallelado (2008), bank size (BankSize), banks’ loans (Loans) and year dummies will be considered as exogenous variables, while all the other variables will be treated as endogenous, using their lagged values as their instruments. Additionally, we will also incorporate a one-year lag of past performance as an explanatory variable to control the dynamic nature of the relationship between board diversity and bank performance. This is line with the model of Pathan and Faff (2013), corroborating the idea that one lag is enough to capture all the influence the past may have on the present.
To ensure the validity of our models and instruments, we will perform two additional tests. We will apply the Arellano and Bond’s (1991) test for first- and second-order serial correlations under a null hypothesis of no autocorrelation. As a result of the use of the lagged dependent variable, we anticipate the presence of first-order serial correlation. However, the residuals in the second difference should not be correlated, as this would invalidate our models. In addition, we will also apply the Hansen test of overidentification restrictions under the null hypothesis of instrument validity, i.e., no correlation between the instruments and the error term.
The variables of our models are inspired by García-Meca et al. (2015); however, we chose not to apply the same estimation method. The authors decided to employ the difference GMM without controlling the dynamic nature of board diversity and bank performance. As outline before, this estimation method may not be the most appropriate approach for modeling this relationship. For this reason, we decided to use the dynamic two-step system GMM, since it exceeds all the limitations presented by the authors’ technique and considers all sources of endogeneity inherent in the board diversity/bank performance relation. Therefore, this estimation procedure will allow us to improve our analysis and the robustness of our results.
In this study, our base empirical model follows the approach of García-Meca et al. (2015), which is represented by equation (3.2).
20 The i and t represent the individual banks and the specific year, respectively. The term 𝜂𝑖 denotes the unobservable effects and 𝜀𝑖,𝑡 denotes the random error term, also
known as idiosyncratic error.
As aforementioned, we intend to improve the analysis of the board diversity/bank performance relation in two ways. In addition to gender and nationality, we will consider a new dimension of diversity, age. The extended version of this empirical model is characterized by equation (3.3). Furthermore, we will also use another approach to measure board gender and nationality diversity, the Blau’s Index, which is represented in equation (3.4).
Performance refers to the variables that we will use to measure bank performance, i.e., Tobin and ROA.
3.3. Sample Construction
To test our hypotheses, we use a sample of 45 publicly traded banks from 10 European countries, more specifically from Spain, France, Germany, Italy, Greece, 𝑇𝑜𝑏𝑖𝑛𝑖,𝑡 = 𝛽0+ 𝛽1𝑇𝑜𝑏𝑖𝑛𝑖,𝑡−1+ 𝛽2𝐺𝑒𝑛𝑑𝑒𝑟𝑖,𝑡+ 𝛽3𝑁𝑎𝑡𝑖𝑜𝑛𝑎𝑙𝑖,𝑡+ + 𝛽4𝐵𝑆𝑖𝑧𝑒𝑖,𝑡+ 𝛽5𝐵𝐼𝑛𝑑𝑖,𝑡+ 𝛽6𝐷𝑢𝑎𝑙𝑖,𝑡+ 𝛽7𝑀𝑒𝑒𝑡𝑖,𝑡+ 𝛽8𝑆𝑢𝑏𝐶𝑜𝑚𝑖,𝑡+ 𝛽9𝐵𝑎𝑛𝑘𝑆𝑖𝑧𝑒𝑖,𝑡+ 𝛽10𝐿𝑜𝑎𝑛𝑠𝑖,𝑡+ ∑16𝑗=11𝛽𝑗𝑌𝑒𝑎𝑟𝑡+ 𝜂𝑖 + 𝜀𝑖,𝑡 (3.2) 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒𝑖,𝑡 = 𝛽0+ 𝛽1𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒𝑖,𝑡−1+ 𝛽2𝐺𝑒𝑛𝑑𝑒𝑟𝑖,𝑡+ 𝛽3𝑁𝑎𝑡𝑖𝑜𝑛𝑎𝑙𝑖,𝑡+ 𝛽4𝐴𝑔𝑒𝑖,𝑡 + 𝛽5𝐵𝑆𝑖𝑧𝑒𝑖,𝑡+ 𝛽6𝐵𝐼𝑛𝑑𝑖,𝑡+ 𝛽7𝐷𝑢𝑎𝑙𝑖,𝑡+ 𝛽8𝑀𝑒𝑒𝑡𝑖,𝑡+ 𝛽9𝑆𝑢𝑏𝐶𝑜𝑚𝑖,𝑡+ 𝛽10𝐵𝑎𝑛𝑘𝑆𝑖𝑧𝑒𝑖,𝑡+ 𝛽11𝐿𝑜𝑎𝑛𝑠𝑖,𝑡+ ∑17𝑗=12𝛽𝑗𝑌𝑒𝑎𝑟𝑡+ 𝜂𝑖 + 𝜀𝑖,𝑡 (3.3) 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒𝑖,𝑡 = 𝛽0+ 𝛽1𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒𝑖,𝑡−1+ 𝛽2𝐵𝑙𝑎𝑢𝐺𝑒𝑛𝑑𝑒𝑟𝑖,𝑡+ 𝛽3𝐵𝑙𝑎𝑢𝑁𝑎𝑡𝑖𝑜𝑛𝑖,𝑡 + 𝛽4𝐴𝑔𝑒𝑖,𝑡+ 𝛽5𝐵𝑆𝑖𝑧𝑒𝑖,𝑡+ 𝛽6𝐵𝐼𝑛𝑑𝑖,𝑡+ 𝛽7𝐷𝑢𝑎𝑙𝑖,𝑡+ 𝛽8𝑀𝑒𝑒𝑡𝑖,𝑡+ 𝛽9𝑆𝑢𝑏𝐶𝑜𝑚𝑖,𝑡+ 𝛽10𝐵𝑎𝑛𝑘𝑆𝑖𝑧𝑒𝑖,𝑡+ 𝛽11𝐿𝑜𝑎𝑛𝑠𝑖,𝑡 + ∑17𝑗=12𝛽𝑗𝑌𝑒𝑎𝑟𝑡+ 𝜂𝑖 + 𝜀𝑖,𝑡 (3.4)
21 Netherlands, Austria, Ireland, United Kingdom and Sweden. In this study, the period of analysis goes from 2012 to 2018. Our sample is restricted to banks located in the European Union within the analysis period16, since they are subject to similar bank regulation and supervision. Due to limitations on the availability of information, it was not possible to collect the necessary data from many European banks, thus being excluded from this analysis. Overall, our sample consists of an unbalanced panel dataset of 300 bank-year observations.
To collect all the information, we used two different procedures. Through the
DataStream database, we retrieved the accounting and market data to measure the structure
(BankSize and Loans) and performance of banks (Tobin and ROA). As our sample is composed of countries with different currencies, we decided to standardize the data. Therefore, we decided to adopt a common currency, the euro (€), to the bank structure information.
For all the other variables, we decided to collect the data manually. The banks’ annual reports provided us the information for the corporate governance indicators, such as BSize,
BInd, Dual, Meet, SubCom and TierSyst. The board diversity data was partly retrieved from
these reports, where a full list of the directors’ names was available and, sometimes, biographies with some important features, such as nationality and birth date. Most frequently, the gender of the directors was easily identified by a picture or by their names. In the biographies, it was also possible to deduct the directors’ gender through the use of specific words, such as he, she, him and her. However, a significant portion of the annual reports did not disclose all the necessary data to our study. In these cases, we conducted a more extended search, using the information found on the internet17 and Bureau van Dijk’s
Orbis database18 for each specific directorship. It is worth mentioning that in two-tier boards, we considered the directors from the supervisory board and the management board. Thus, we were able to identify the gender, nationality and age for the 4511 directorships comprised in our sample. It was important to find these specific characteristics of the directors, as we could only use the board diversity indicators if we had the information for all board members.
16 We still consider the United Kingdom because, at the time of our analysis, it was a member state of the
European Union.
17 The main sources of information were the banks’ website, newspapers and other publications and reports. 18 Bureau van Dijk’s Orbis provide a set of information about particular characteristics of current and former
directors. However, this information is highly incomplete, missing the directorship of previous board members and some important features.
22 3.4. Descriptive Statistics
Table 1 exhibits the sample distribution by year. Regarding the observations, the distribution by year is quite balanced. The years with more observations are 2015, 2016, 2017 and 2018, each representing 15% of the entire sample. As illustrated in this table, the presence of female directors on the board has increased by 14 percentage points, from 17% in 2012 to 31% in 2018. This significant rise could be the result of the legislative initiatives for the inclusion of women on the board of directors (e.g., gender quotas) that has occurred in recent years. The share of foreign directors also rose during the period of analysis, but to a lesser extent, increasing around 6 percentage points. In contrast, it is possible to notice that the variation of the directors’ age has been decreasing over the years. In other words, this implies that the board has become more homogenous in terms of age.
Table 1 - Sample Distribution by Year
Year Obs. (%) Gender National Age
2012 13.00 0.17 0.15 8.44 2013 13.33 0.19 0.17 8.23 2014 13.67 0.23 0.17 8.03 2015 15.00 0.26 0.19 8.01 2016 15.00 0.30 0.21 8.01 2017 15.00 0.31 0.20 8.00 2018 15.00 0.31 0.21 7.74
This table presents the distribution of the observations by year. In this table, it is also reported the mean value of the variables Gender, National and Age in each specific year. The definitions of these variables can be found in Appendix B.
Table 2 conveys the sample distribution by country. In our sample, 24% of all observations consist of Italian banks, followed by 15% and 14% from British and Spanish banks, respectively. Austria, Germany and Ireland are the countries with the fewest observations, each representing 4.7% of the total sample. It is also possible to observe that Eurozone countries represent around 77% of the entire sample. In terms of the presence of
23 female directors, Sweden was the country with a higher percentage of board seats occupied by women, followed by France and Germany. On the other hand, Greece had the lowest number of female directors with an average of 13%. Regarding the different nationalities, Ireland and the United Kingdom had the highest number of foreign directors (39% and 31%, respectively), while Italy has the lowest number (only 6%). As shown in this table, the age difference between directors has a wide degree of variation across countries, with Ireland and Italy presenting the highest levels of diversity in terms of age.
Table 2 - Sample Distribution by Country
Country Obs. (%) Gender National Age
Spain 14.00 0.21 0.10 8.28 France 9.33 0.37 0.16 7.39 Germany 4.67 0.26 0.23 7.13 Italy 24.00 0.27 0.06 9.18 Greece 9.33 0.13 0.29 8.31 Austria 4.67 0.17 0.16 8.60 Netherlands 6.00 0.22 0.20 7.40 United Kingdom 15.00 0.25 0.31 6.88 Sweden 8.33 0.42 0.19 6.69 Ireland 4.67 0.19 0.39 9.85
This table presents the distribution of the observations by country. In this table, it is also reported the mean value of the variables Gender, National and Age in each specific country. The definitions of these variables can be found in Appendix B.
Table 3 presents the descriptive statistics for the variables used in the empirical analysis. The mean value of Tobin’s Q is 1.01, varying between 0.88 and 2.01. The return on assets (ROA) ranges from -7.38% to 5.41%, with a mean value of 0.69%.
Regarding the diversity indicators, the average female representation on the board is about 26%, which is higher than the 8% found by Pathan and Faff (2013) for the American banks and the 10% observed by the international analysis of García-Meca et al. (2015). The mean value of Blau’s Index of gender diversity is slightly lower than expected when the mean presence of female directors is 26%. This can be understood since this index takes lower
24 values when the percentage of women is higher than that of men, i.e. when the board is more homogenous in terms of the female gender. Moreover, it is possible to observe that the maximum value of the proportion of female directors is about 0.57%. This implies that there was at least a bank board with more women than men.
As illustrated in this table, the average percentage of board seats occupied by foreign directors is about 19%. This percentage is slightly higher than that reported by García-Meca et al. (2015) (18%) and by Estélyi and Nisar (2016) for British companies (13%). The maximum value of the proportion of foreign directors reaches 0.63%, implying that there were more foreigners than local directors on a specific board. It is possible to note that, on average, boards appear to be more gender-diverse than nationality-diverse, the opposite of what was observed by García-Meca et al. (2015). Concerning the level of board age diversity, Bøhren and Strøm (2010) reported a slightly higher age difference (8.13) in Norway than that observed in our sample (8.06).
On average, the board of directors is composed of 15 members. Comparing with non-financial companies, this value is higher than the mean number of directors in Norway (6.53) and Spain (10.75), reported by Bøhren and Strøm (2010) and Campbell and Mínguez-Vera (2008), respectively. This is consistent with the theoretical argument that banks have bigger boards than non-financial companies (Adams & Mehran, 2003).
25 Table 3 - Descriptive Statistics
Mean Median Max. Min. Std. Dev. Obs. Bank Features Tobin 1.01 0.99 2.01 0.88 0.09 300 ROA 0.69 0.75 5.41 -7.08 1.30 300 BankSize 11.27 11.33 12.35 9.30 0.72 300 Loans 0.59 0.62 0.91 0.11 0.18 300 Board Diversity Gender 0.26 0.25 0.57 0 0.13 300 National 0.19 0.13 0.63 0 0.18 300 BlauGender 0.35 0.38 0.50 0 0.12 300 BlauNation 0.24 0.23 0.50 0 0.19 300 Age 8.06 7.77 15.72 4.07 1.99 300 Board Structure BSize 15.04 14 32 6 5.35 300 BInd 0.58 0.58 0.88 0.16 0.17 300 Dual 0.03 0 1 0 0.16 300 Meet 14.36 13 42 4 6.60 300 SubCom 4.62 4 9 2 1.45 300 TierSyst 0.19 0 1 0 0.39 300
This table presents the descriptive statistics of our sample composed of 300 bank-year observations from 45 publicly traded banks in 10 European countries, over the period 2012 to 2018. Bank financial data was retrieved from the DataStream database, while the other information was collected manually through annual reports, internet materials and the Bureau van Dijk’s Orbis database. All the variables presented in this table are defined in Appendix B.
26
4. Empirical Results
4.1. Univariate Analysis
Table 4 exhibits the Pearson pair-wise correlation of all the variables used in our models. It is important to note that Gender and BlauGender are significant and positively correlated with ROA, but not with Tobin. Interestingly, National and BlauNation are negative and significantly correlated with all bank performance measures (Tobin and ROA). In contrast, the correlation between board age diversity (Age) and all bank performance measures is statistically insignificant.
As illustrated in this table, the maximum correlation coefficients are 0.96 (between
National and BlauNation) and 0.95 (between Gender and BlauGender). However, this will not
pose any concerns of multicollinearity, since the variables will be used alternatively and not simultaneously. Apart from these variables, none of the other correlation coefficients are very high, which allows us to assume that there are no multicollinearity problems in our models.
4.2. Multivariate Analysis 4.2.1. Base Model
Table 5 displays the estimated results from the model developed by García-Meca et al. (2015) to explain the relationship between bank performance and board gender and nationality diversity using the dynamic two-step system GMM.
Furthermore, it is also reported the results of some diagnostic tests used to examine the robustness of our model and instruments. The Wald test yields a p-value of 0.000, which allows us to accept the hypothesis of joint significance. The Arellano and Bond’s (1991) tests show that the residuals in first-difference are serially correlated. Nevertheless, this was already anticipated, since we use the lagged dependent variable as a regressor. These tests also confirm that there is no second-order serial correlation, which would invalidate our results. Moreover, the Hansen test for overidentifying restrictions rejects the null hypothesis, thus ensuring the validity of our set of instruments. Overall, the robustness tests suggest that our model is well fitted.
Regarding our variables of interest, the coefficient of Gender is negative and statistically significant at a 1% level. Therefore, this suggests that, on average, an increase in the share of female directors leads to a decrease in the performance of banks. This result corroborates the hypothesis (H1.2.). Previous studies have found empirical evidence that
27 Table 4 - Pairwise Correlation Coefficients
Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (1) Tobin 1.00 (2) ROA 0.53* 1.00 (3) Gender 0.11 0.25* 1.00 (4) National -0.23* -0.21* -0.06 1.00 (5) BlauGender 0.06 0.23* 0.95* -0.04 1.00 (6) BlauNation -0.24* -0.20* -0.04 0.96* -0.03 1.00 (7) Age -0.06 -0.10 -0.18* 0.00 -0.19* 0.04 1.00 (8) BSize -0.32* -0.11 -0.09 -0.05 -0.03 -0.01 0.06 1.00 (9) BInd 0.05 0.04 0.15* 0.31* 0.15* 0.31* -0.11* 0.13* 1.00 (10) Dual -0.02 -0.13* -0.01 -0.06 -0.02 -0.07 -0.06 -0.06 0.13* 1.00 (11) Meet -0.11 -0.36* -0.06 -0.09 -0.10 -0.13* 0.14* -0.19* -0.08 0.01 1.00 (12) SubCom -0.33* -0.15* -0.08 0.24* 0.03 0.24* -0.09 0.44* 0.29* -0.07 -0.06 1.00 (13) BankSize -0.35* -0.20* 0.18* 0.33* 0.22* 0.37* -0.17* 0.40* 0.29* 0.12* -0.24* 0.44* 1.00 (14) Loans -0.11 -0.02 -0.04 -0.15* -0.03 -0.14* 0.12* -0.10 -0.06 -0.10 0.34* -0.02 -0.35* 1.00 (15) TierSyst -0.15* 0.05 -0.14* -0.07 -0.08 -0.04 0.00 0.52* 0.15* -0.08 -0.18* 0.40* 0.10 0.04 1.00 This table reports the pairwise correlation coefficients based on our sample composed of 300 bank-year observations from 45 publicly traded banks in 10 European countries, over the period 2012 to 2018. Bank financial data was retrieved from the DataStream database, while the other information was collected manually through annual reports, internet materials and the Bureau van Dijk’s Orbis database. The definitions of the variables presented in this table can be found in Appendix B. Statistical significance is indicated by “*” at a 1% level.
