Do some political directors capture the era’s
political zeitgeist? Evidence from UK board
gender diversity
Master Thesis Accountancy
Personal Details
Name John Noorland
Student number S3858804
Email J.J.Noorland@student.rug.nl
University University of Groningen
Faculty Economic and Business
Master Accountancy
Supervisor Dr. S. Mukherjee
Date January 20, 2020
2 Abstract
In this study, I examine if political directors on United Kingdom’s (UK) corporate boards enable women’s representation. Resource dependency theory suggests that both political directors and women directors are beneficial for firms in their own right, but does not suggest whether one is associated with the other. I suggest that political directors bring their political insight to the board, with which they are more likely to capture the era’s political zeitgeist. In recent years, the overwhelming concern among UK corporate boards is in favor of greater gender diversity, as evidenced by the Board Gender Targets (BGT) published by The Davies Review in 2011. Therefore, I suggest that political directors, who are likely to anticipate the era’s political zeitgeist, are positively associated with greater board gender diversity. Further, I argue that this relationship is mainly driven in the post-BGT period. Finally, I investigate if some political directors are more likely to catch the era’s political zeitgeist than others, drawing from political science theory. I expect that senior bureaucrats are more associated with the appointment of female directors than others. This because they take their prior attitude in government as a key resource to the board. My findings are consistent with my predictions. This study contributes to resource dependency theory by showing that resources brought in by different groups to the board have an interactive effect.
Key words: political directors, board gender diversity, senior bureaucrats, ministers, resource dependency theory, political science theory
3
Table of content
1. Introduction………... Page 4
2. Theoretical framework & hypotheses……… Page 8
3. Research design……… Page 13
4. Results……….. Page 17
5. Conclusion……… Page 20
References……….. Page 21
Tables………... Page 27
4
1. Introduction
Focus on board gender diversity is growing as a means of improving corporate governance (De Cabo et al., 2012). Even when women have the right educational qualifications and experience (Bilimoria & Piderit, 1994), they must deal with invisible challenges to reaching top positions (Singh & Vinnicombe, 2004) which some scholars call the “Glass Ceiling” (Conyon & Mallin, 1997). Some countries have introduced quotas for women on corporate boards, which is an effective way to increase the number of women on boards relatively quickly (Teigen, 2012). The United Kingdom (UK) preferred to encourage companies to promote women through voluntary BGT as published by The Davies Review (Davies, 2011), avoiding binding legislation (Chandler, 2016). A post-retirement opportunity for government officials is the membership of corporate boards. These directors are more likely to be appointed as non-executive directors, rather than industry experts or in executive roles (González-Bailon et al., 2013). Agrawal & Knoeber (2001) shows that outside directors with background in politics or government are more numerous on the boards of firms for which politics is more important, suggesting that these directors play a political role. In this study, I investigate whether political directors capture the era’s political zeitgeist in relation to the board gender diversity, and enables women’s representation on the board.
The relationship between political directors and the appointment of women on a board is an interesting research topic. British boards are an interesting subject of research on board diversity as the UK has the fifth highest gender diversity on its boards (Goyal et al., 2018). Fan et al. (2007) studied and found that when a CEO is a former Chinese bureaucrat, they are less likely to appoint women to the board. My study is different from the study of Fan et al. (2007) in various ways. Fan et al. (2007) focus on the association between political CEOs and the appointment of other bureaucrats to the board of directors. This study focuses on political directors, not just CEOs. Furthermore, the context of the study of Fan et al. (2007) is
performance of firms with political CEOs, related to that of firms without political CEOs. The context of this study is the era’s political zeitgeist and how political directors respond to it. Agrawal & Knoeber (2001) investigated if the incidence of women on boards is greater for the firms for which politics is more important, but found no evidence for this. This study is different from the study of Agrawal & Knoeber (2001), because Agrawal & Knoeber (2001) investigated the incidence of women on board related to the firm dependency to the government. This study focuses on the relation between political directors and board gender diversity, not in case of dependency to the government.
5
Resource dependency theory suggests that an increase in board diversity may yield benefits by creating a network with the external environment and securing a broader resource base (Wang et al., 2019). Adams & Ferreira (2004) argue that boards with more women should have better overall attendance at meetings, which may make them more effective. Beyond gender as a key resource, a critical source of external interdependency and uncertainty for business is
government (Hillman, 2005). A way to link a firm to the government is by the appointment of former political players to the board of directors (Hillman, 2005). Several prior studies show that political directors are beneficial for the firm (Chiu & Joh, 2004; Correria, 2014; Faccio et al., 2006; Kroszner & Stratmann, 1998). Faccio et al. (2006) argued that politically connected firms are significantly more likely to be bailed out than similar non-connected firms in cases of financial distress. Other benefits come, for example, from preferential access to credit (Chiu & Joh, 2004) and lower penalties for firms if they are prosecuted by the Securities and Exchange Commission (Correia, 2014). Adams & Ferreira (2004) argue that gender diversity may have a political dimension. Politicians are important actors pushing and lobbying for change in board gender diversity in all countries (Seierstad et al., 2017). There are two kind of arguments to promote board gender diversity: utility and social-justice arguments (Seierstad, 2016). Former politicians are considered equality-oriented powerful individuals.
Looking to the specific role political directors had in the government, bureaucrats are appointed for more than one electoral cycle (Alesina et al., 2008), while others (e.g. ministers) are
appointed for one electoral cycle. Ministers are an agent of parliament but at the same time a principal for the bureaucracy that is assigned to their portfolio (Yesilkagit & van Thiel, 2008). Bureaucrats can be considered self-interested and risk-averse agents (Christensen, 1997). For bureaucrats, survival in government is not easy. I expect that if bureaucrats survive in
government, they have to be aware of the political zeitgeist. When they are appointed to a board, they take this political instinct with them as a key resource (Bonardi, 2011). I define political instinct as the natural tendency that a person behaves or react in a socially responsible way related to political sensitive topics. I posit that political directors, and especially bureaucrats, foresee potential political developments, particularly on politically sensitive topics. Board gender diversity is one of the most politically sensitive topics concerning corporate boards in the
present political era (Goyal et al., 2018). Therefore, I posit a positive relationship between political directors, especially for bureaucrats, and board gender diversity, with a strengthening effect after the introduction of the Board Gender Targets (BGT).
6
To test my hypotheses, I use UK listed firm data between the years 2000 and 2015. The sample consist of 10.151 firm-year observations. I use manually collected data on political directors to perform my analysis. With my manually collected data it was possible to identify and segregate political directors based on their prior government experience. To test my predictions, I used a fixed-effect OLS model in a difference-in-difference design. I focused on the proportion of women on a board as my primary measure of board gender diversity. Previous studies to board gender diversity measured this variable in a similar way (Adams & Ferreira, 2004; Agrawal & Knoeber, 2001; Brammer et al., 2007). I used various dummy variables to measure political directors and their specific roles in government. The dummy variables are political directors (regardless of their specific government experience), senior bureaucrats (directors with government experience as senior bureaucrats) and ministers (directors with government experience as ministers). I used the variable BGT to test if the results are mainly driven by the post-BGT period.
Consistent with my predictions, I found a positive and significant relationship between political directors and board gender diversity. I found that directors with experience as senior
bureaucrats mainly drive my main results. This in contrast to directors with experience as ministers. Ministers are negatively related to board gender diversity. The BGT as a moderator has a positive effect on the relation between political directors and board gender diversity, regardless of which specific role the directors had in government. This shows that political directors can capture the eras political zeitgeist.
This study makes contributions to the literature regarding board gender diversity and resource resource-based view in three different ways. First, to the best of my knowledge this is the first study that focuses on the relationship between political directors and board gender diversity. Seierstad et al. (2017) found that ex-politicians recognize the importance of women on board, based on social-justice arguments. Adams & Ferreira (2004) argued that gender diversity on boards may have a political dimension, but they found no empirical support for this. They refer to Agrawal & Knoeber (2001) who investigate this possibility. However, these studies were not focused on political directors on the board related to board gender diversity. Therefore, this research tries to fill this gap in the literature. Based on the resource-based view, I show that political directors are positively associated with board gender diversity.
Secondly, I contribute to the literature by focusing on the specific experience the political directors have in government. Building on political science theory, I found that former senior bureaucrats in the board are able to foresee potential political developments and react positively
7
to board gender diversity. On the other hand, I show that ministers on board are less aware of the potential political developments and therefore they react negative to board gender diversity. So, senior bureaucrats and ministers bring different key resources to the firm. This is consistent with my hypothesis which predicts that senior bureaucrats, because of their political instincts, foresee hidden costs if they do not respond adequately to politically sensitive topics, like board gender diversity.
Third, I contribute to the literature by showing that my results are era driven. I show that the BGT, which recommends more women on board (Goyal et al., 2018), drives political directors to appoint women on board. This is consistent with my hypothesis which predicts that if political directors, especially bureaucrats, bring resources to the board, their political instinct is one of them. They therefore, capture the era’s political zeitgeist with regards to board gender diversity. Therefore, I suggest political directors are able to foresee hidden costs for not complying with the voluntary BGT.
The remainder of this thesis is as follows: The second section will review the literature and develop the testable hypothesis. The third section described the methodology, used in this study. The fourth section describes the results found in this study and the robustness tests. The fifth section contains the discussion of the various results and the concluding remarks.
8
2. Theoretical Framework & Hypotheses
2.1 Political directors and board gender diversity
Gender diversity is growing in importance in corporate governance (De Cabo et al., 2012). Women directors must deal with challenges in receiving board appointments. The glass ceiling is the set of invisible hindrances women face when trying to access top jobs. (Conyon & Mallin, 1997). Bilioria & Piderit (1994) suggests that even though women have the right educational qualifications and experience, they continue to be blocked in their rise to the top. Singh &
Vinnicombe (2004) described these challenges in their paper. These struggles are, for example, organizational barriers, like hidden senior promotion processes (Alimo-Metcalfe, 1995), lower pay for women (Oakley, 2000), gender stereotyping of leadership (Schein & Mueller, 1992) and gendered communication styles (Tannen, 1994). An obvious problem for female recruitment is that female entry can still be considered as being elite-threatening (Heemskerk & Fennema, 2014). Adams & Ferreira (2004) suggest, based on social psychology literature, that increasing diversity decreases director’s identification with other board members, and their willingness to work together. Kanter (1977) argued that changes in the cost of providing formal incentive schemes, will lead to changes in the extent to which both diversity and formal incentive
schemes are used to induce effort. The adoption of nomination committees makes it clear how director appointments are made and therefore assists the main board (Conyon & Mallin, 1997). Furthermore, the nomination process is still not objective. Many participants acknowledge that functioning nomination committees are still not a norm in FTSE companies (Gonyon et al., 2018). Without an open and clear selection procedure for directors, the prospect for enhanced female representation board is perhaps bleak (Conyon & Mallin, 1997).
The Resource Dependency Theory (RDT) focuses on a firm’s need to access resources from the firm’s environment (Stern et al., 1979). Human and social capital are perspectives of the resource dependency theory (Stern et al., 1979). Resource dependence theory advocates that increased board diversity may yield benefits by creating a network with the external environment and securing a broader resource base (Wang et al., 2019). The board of directors are a
mechanism for the organization to draw on external resources (Singh, 2007). In the resource dependence tradition, the role of political directors as providers of important resources is
emphasized (Hillman et al., 2000). By having directors who serve to link the organization with its external environment, a board may act to reduce uncertainty (Hillman et al., 2000). A critical source of external interdependency and uncertainty for business is government. Corporate
9
political strategies are the primary key for the linkage between firms and political decision makers (Hillman, 2005). Beyond gender as a key resource, another strategy to link a firm to the government is appointing former politicians to the board of directors (Hillman, 2005). Politicians are attractive to firms mainly for their human and social capital (Lester et al., 2008). Politicians on boards provide unique information about the public policy process (Hillman et al., 2005), a channel of communication to existing politicians, bureaucrats and other political decision makers (Hillman, 2005), and legitimacy (Galaskiewics & Wasserman, 1989). So, the expertise and network of the political directors are main resources who directors bring to the firm. Resource dependency logic suggests that firms with politicians on the board will outperform those without (Hillman, 2005).
Stern et al. (1979) suggests four primary benefits came from boards: advice and counsel,
channels of communication, preferential access to commitments outside the firm and legitimacy. Reeb & Zhao (2013) suggests that directors bring different expertise, knowledge and social contracts to the board. González-Bailon et al. (2013) argued that former politicians and
bureaucrats might be more likely to be appointed to generalist positions that relate to corporate governance, such as non-executive directorships, rather than to expert industry or executive roles. Prior research showed that political connections of the board are beneficial to the firm. Faccio et al. (2006) found that politically connected firms are significantly more likely to be bailed out than similar non-connected firms in cases of financial distress. Correia (2014) argued that politically connected firms on average are less likely to be involved in securities and
exchange commission (SEC) enforcement actions and face lower penalties if they are
prosecuted by the SEC. These examples showed that board political connections can reduce the risks related to the government. Furthermore, Faccio (2007) suggests other benefits come from political connections: preferential access to credit (Chiu & Joh, 2004) and regulatory protection (Kroszner & Stratmann, 1998).
There are no previous, direct studies on the relationship between politicians on boards and board gender diversity. Adams and Ferreira (2004) argued that board gender diversity may have a political dimension. Companies may care more about diversity when they are concerned about their public image, because they are required to deal with government agencies which have preferences for diversity. Although Adams and Ferreira (2004) found no empirical
evidence for this claim, they refer to Agrawal & Knoeber (2001) who investigated this possibility. Agrawal & Knoeber (2001) found no evidence for the claim that firms, for which politics is more important, have a greater incidence of women on board. Seierstad et al. (2017) described the
10
case of women on board in the United Kingdom. Seierstad et al. (2017) consider former
politicians as equality-oriented powerful individuals. They found that former politicians recognize the importance of increasing the share of women on boards, based on social-justice logics. This in contrast to other actors like the civil society who based their involvement on utility arguments (Seierstad et al., 2017). Politicians are important actors pushing and lobbying for change in board gender diversity in all countries (Seierstad et al., 2017). I argue that political directors are conscious of the political sensitivity of topics and therefore able to foresee political potential development and act careful related to that topics.
H1: political directors are positively associated with board gender diversity
The role that officials played in government differs. Vertzberger (1984) makes distinction between politicians, bureaucrats and military officials. In this study, I distinguish between
ministers, senior bureaucrats and politicians (i.e. ministers, senior bureaucrats and advisors) on the board of directors, based on political science theory. Bureaucrats are unelected government officials (Alesina et al., 2006). Bureaucrats are appointed for periods longer than electoral cycles (Alesina et al., 2006), while other government officials (e.g. ministers) are appointed for one electoral cycle (Laffin, 1997).
Moe (2006) described the relationship between political authorities and bureaucrats as principal and agent, based on agency theory. Ministers are agents of parliament, but at the same time a principal for the bureaucracy that is assigned to their portfolio (Yesilkagit & van Thiel, 2008). Ministers possess authority as the legitimate decision-makers, a role that is bolstered by the powerful conventions of ministerial responsibility and by public perceptions (Laffin, 1997). Ministers are ultimately responsible for the decisions, actions and behavior of bureaucrats under their authority (Yesilkagit & van Thiel, 2008). Ministers are responsible for executing the
coalition agreement. Moury (2011) suggests that a coalition agreement is a tool used by coalition parties to reduce agency loss when delegating to ministers.
Because bureaucrats control the flow of information to politicians, they control or influence, the set of problems and solutions that politicians consider (Blom-Hansen et al., 2018). Bureaucrats are often able to influence, if not decide, the agenda of their presumed masters (Blom-Hansen et al., 2018). The information asymmetry could lead to moral hazard or hidden action (Moe, 2006). Wood (1988) showed that the influence from elected institutions is limited when an agency has substantial bureaucratic resources and a zeal for their use. Under these conditions, bureaucracy can even move outputs in directions completely opposite from what a model of
11
hierarchy would predict (Wood, 1988). Given that, on average, bureaucrats persist longer than politicians do, we might expect them to be able to alter policies over time to suit themselves (Peters, 1981; James et al., 2016). Peters (1981) argued that the motivations of bureaucrats are not necessarily public service and the public interest. Dunleavy (1991) assumes that
bureaucrats (at least senior officials) have private interests that shape the outcome of administrative policy-making processes. Bureaucrats are self-interested, motivated and risk-averse individuals (Christensen, 1997). I argue that senior bureaucrats can survive in
government because of this attitude in combination with their power. When bureaucrats come to a board, they take this political instinct with them as a key resource. I argue that senior
bureaucrats be aware of the political sensitivity of topics, far before it gets on the political agenda. A politically sensitive topic like board gender diversity (Goyal et al., 2018) drives directors with experience as senior bureaucrats to appoint women on the board of directors.
H1a: bureaucrats are positively associated with board gender diversity
2.2 political directors, board directors and BGT
Seierstad (2016) described the need for both utility and social justice arguments related to increase the proportion of women on boards. She argued that the key underlying principle of social justice is that of an equal society. Women should have the right to possess half the seats of power. An argument from utility is that since the total potential of a population is roughly evenly distributed between men and women, the paucity of women in high status positions means that the talent potential is not fully exploited (Seierstad, 2016). Equality-oriented powerful individuals, such as former politicians recognize the importance of increasing the share of women, based on social justice arguments (Seierstad et al., 2017).
Among other countries, Norway introduced quotas for women on corporate boards. This is an effective way to increase the number of women on boards relatively quickly (Teigen 2012). Terjesen et al. (2015) argued that countries with left-leaning governments are more likely to establish gender quotas for boards of directors. The United Kingdom preferred to encourage companies to promote women, eschewing binding legislation (Chandler, 2016). The UK government strategy avoids the threat of an EU law by addressing the issue pre-law at a national level (Terjesen & Sealy, 2016). The BGT is based on the comply or explain rule (Terjesen et al., 2015). The coercive pressure of the “threat” of quota ‘increased shares of women on boards in the UK and Australia’ (Vinnicombe et al., 2015). Board gender diversity matters, because women enhance boards ’legitimacy and trustworthiness (Perrault, 2015).
12
The approach adopted in the United Kingdom, for managing gender diversity on is PLC boards is underpinned by institutional theory (Meyer, 2008). This suggests that a set of processes become authoritative guidelines for social behaviors and are adopted over time and space (Scott, 2004). The strategy has initially delivered favorable results, with the FTSE 100 boards attaining 26% gender diversity in 2015 (Goyal et al., 2018). The success of the UK’s approach is often attributed to the multiple stakeholders tasked by the 2011 Davies report (Davies, 2011). These stakeholders are chairs, CEOs, headhunters, regulatory bodies and institutional investors (Sealy, 2010).
Khemakhem & Dicko (2013) found in their study that political connections positively influence compliance with regulations on the board of directors. They explain this result by the fact that given their probable political exposure and visibility, firms with political connections have an interest in using the very best practices with regard to regulations so they can avoid being accused of conflicts of interest and favoritism. Khemakhem & Dicko (2013) emphasizes that most of these regulations are voluntary. Khemakhem & Dicko suggest that in cases of non-compliance, firms risk being penalized in the financial markets (Gompers et al., 2003) and as a result may see an increase in financing costs (Khemakhem & Dicko, 2013). This shows that political directors will comply to (voluntary) regulation because they foresee potential political costs.
Build on this argument, I expect that political directors will foresee potential hidden costs of not complying with the voluntary BGT. I expect both senior bureaucrats and ministers complying to BGT, for different reasons. Senior Bureaucrats have a political instinct and are aware of the politically sensitive topics. This is different for ministers, because they are responsible to
execute a specific coalition agreement. Moury (2011) argues that a coalition agreement is a tool used by coalition parties to reduce agency loss when delegating to ministers. When countries introduce voluntary targets, it is part of the various policies. Therefore, I expect that the BGT strengthens the effect for both senior bureaucrats and ministers related to board gender diversity.
H2: The positive relationship between political directors and board gender diversity increases in the post-BGT period.
13
3. Research Design 3.1 Sample
The data is collected from various sources. First, the corporate governance data is from
BoardEx. Second, financial accounting and market data is retrieved from Worldscope. The third data source is manually collected data. Three students of the University of Groningen manually collected data on the role of directors in government (ministers, senior bureaucrats, advisors or military officials). With this manually collected data, I complemented the BoardEx database. The manually collected data was not available in online databases. Therefore, the data is unique. The manual collection of the data was necessary, because it made research using the background of the government officials possible. All directors are matched on a unique ID number. After merging the datasets, I excluded observations with missing variables for the firm and year fixed-effect regression analysis. After cleaning the data, I am left with 10.151 firm-year observations. I used United Kingdom data, focusing on the period between 2000 and 2015. Table 1 shows the sample statistics.
The manually collected data was collected as follows. First, I studied the specific role of the various directors in government. I made distinction between ministers, senior bureaucrats, advisors and military. I used different sources to collect this data, such as Bloomberg and Marketscreener. Examples of functions of senior bureaucrats are secretary of state and undersecretary. Next, I focused on the various start and end dates of the period these officials served the government.
3.2 Variables
3.2.1. dependent variable
The focus of the dependent variable within this study is board gender diversity. I used the BRD_GENDER_DIV variable to measure the board gender diversity.
BRD_GENDER_DIV = Female Directors / Board Size
Board gender diversity is the proportion female directors on board per board size. This is comparable with previous studies (Grosvold & Brammer, 2011; Adams & Ferreria, 2004; Brammer et al. 2007).
3.2.2 explanatory variables
To investigate the first hypothesis, I used the POLITICAL_BRD_DUMMY as explanatory variable. A firm is connected with a politician if at least one of its large shareholders (at least
14
10% of voting shares) or one of its top directors is a member of parliament or a minister, or is closely related to a top politician of a party (Faccio, 2007). Boubakri et al. (2009) refer to politically connected boards if at least one member of the board of directors, the CEO, or a member of the supervisory board is or was a politician, i.e. a member of parliament, a minister, or any other appointed top bureaucrat. Comparing both definitions, the definition of Boubakri et al. is closer to this study. In this study, a director is included in the POLITICAL_BRD_DUMMY if the director has experience as a minister, senior bureaucrat or advisor. In this dummy, a firm received “1” if there is at least one political director on the board of directors and “0” otherwise. To investigate hypothesis 1a, I include a second and a third dummy variable. The second explanatory variable is the BUREAUCRAT_BRD_DUMMY. Bureaucrats are unelected officials (Alesina et al., 2008). In this study, a director is included in the BUREAUCRAT_BRD_DUMMY if the director has experience as a senior bureaucrat. A firm received “1” If there is at least one director on the board of directors with experience as senior bureaucrat and “0” otherwise. The third explanatory variable is the MINISTER_BRD_DUMMY. Ministers are appointed for one electoral cycle (Laffin, 1997). In this study, a director is included in the
MINISTER_BRD_DUMMY if the director has experience as a minister. A firm received “1” If there is at least one director on the board of directors with experience as a minister and “0” otherwise.
3.2.3 moderator
The Board Gender Targets (BGT), which recommends board gender diversity, is used as moderator. The value of the BGT is “1” starting from the year in which the BGT “recommended” board gender diversity. For the United Kingdom, BGT is introduced in 2011 (Chandler, 2016). 3.2.4. control variables
In the regression model, various control variables are included that may affect the board gender diversity of a firm. These control variables could be divided into corporate governance variables and financial performance variables.
Board gender diversity is a concern of corporate governance. First, Brammer (2007) found that board size (BRD_SIZE) and board independence (BRD_INDEPENDENCE) are positively related to board gender diversity. The higher the proportion of non-executive directors and the bigger the board size, the higher is the proportion of women on a board. The third control variable related to corporate governance is directors with experience in quoted firms
15
also positive associated with board gender diversity. So, directors with experience in quoted firms are associated with more women on boards. The fourth control variable focuses on the tenure of directors (BRD_TENURE). Singh & Vinnicombe (2004) found a negative relationship between the board tenure of the CEO and women on board. The fifth control variable related to corporate governance is the amount of closely held shares (CLOSELY_HELD_SHARES) related to board gender diversity. Eklund et al. (2009) suggests that the presence of a
controlling owner reduces board heterogeneity, but found no empirical support for this claim. The financial performance of firms has a significant influence on board gender diversity. Various studies shows a relationship between financial performance and board gender diversity. Chen et al. (2018) studied the relationship between female board representation and R&D
expenditures (R&D EXPENDITURES). They found that firms with female directors tend to invest more in innovation and obtain more patents for given R&D expenditures. Harris et al. (2014) found that firms with at least 25% female directors on board are negatively associated with corporate leverage (LEVERAGE). Isidro & Sobral (2015) studied the relationship between women on board and firm value (TOBINS_Q). They found a positive relation between women on board and firm value. McGuinness et al. (2017) suggests a relationship between board gender and foreign ownership (FOREIGN_ASSETS in the CSR performance. The next control variable is generic cash related to total assets (CASH). Politically state-appointed women in the boardroom have a positive effect on cash holdings (CASH) and investment opportunities, because of their use of political network as a support for legitimacy (Bruna et al., 2019). The next control variable is capital expenditures (CAPITAL_EXPENDITURES) related to board gender diversity. Shin et al. (2019) found that female directors play a significant role in reducing future capital expenditures. I also control for operating income related to total assets
(OPERATING_INCOME). Yang et al. (2019) shows that an increase in female directors reduces firm’s operating income to assets by 12%. The last control variable is the log of the total assets (TOTAL_ASSETS) related to board gender diversity. Dowling & Aribi (2013) found that women are less likely to hold their assets in stocks than men.
Next, to the control variables mentioned above, I further control for business segments
(BUSINESS_SEG) and geographic segments (GEOGRAPHIC_SEG). Adams & Ferreira (2009) found that firms with female directors have more business segments (BUSINESS_SEG) than firms without female directors. Chen et al. (2009) found evidence for geographic diversification and some characteristics of board composition.
16 3.3 Empirical Model
I used a firm and year fixed-effect OLS regression model in a difference–in–difference design to test the hypotheses in this research. To test my hypotheses, I use the following firm and year fixed-effect regression in the form of difference-in-difference design. My regression model is:
BOARD GENDER DIVERSITYit= β0 + β1 (Politcal_director) + β2 (Political director * BGT) + Σ
βm CONTROLSit +ΣβnFE +Ɛit
This is a difference–in–difference model because the POLITICAL_BRD_DUMMY takes the value “1” only after the political directors were appointed to the board. The β1 acts as the
treatment * post variable which is standard in a difference–in–difference framework considering treatment and post are subsumed by the fixed-effects (Fauver et al., 2017). The treatment group
is the group which receives “1” and the post group is the group which receives “0”. The
coefficient of Political director * BGT (β2) is the relation of the treatment and Post group related to the BGT. CONTROLSit shows the control variables for firm i in year t. The control variable takes the value near “1” if the variable is highly correlated with the dependent variable and otherwise a value near “0”. I expect a positive relation between political directors and board gender diversity; therefore, I expect the POLITICAL_BRD_DUMMY and the
17 4. results
This section consists of the results of the different tests. Section 4.1 shows the descriptive statistics. Section 4.2 consist of the Pearson correlation matrix. Section 4.3 shows the firm fixed-effect regression. Section 4.4. shows the results of the robustness tests.
4.1 Descriptive Statistics
Table 3 presents the descriptive statistics of the various variables. This table shows the observations, the mean, the standard deviation and the minimum and maximum value of the variables. Most of the variables are winsorized at the 1% level (see table 2). Table 3 shows that the mean of the companies that have senior bureaucrats on their board is 0.514. This means that 51,4% of the companies in the sample has a senior bureaucrat on their board. The mean of the firms that have political directors on board is 0.550. This means that 55,0% of the
companies in the sample has a political director on their board. This means that almost all the political directors in the sample had a position as a senior bureaucrat in government. The mean of the BGT is 0.386. This means that 38.6% of the firms in the sample had to deal with the BGT recommending board gender diversity.
4.2 Correlations
Table 4 shows the Pearson Correlation test. The reason to conduct this correlation test is because of the possible correlation between variables. The Pearson correlation coefficient is a standard statistic for checking for multicollinearity in the independent variables (Kalogirou, 2013). Yu et al. (2015) choose the p-value of 0.7 as warning sign and p-value of 0.9 as indicator of severe multicollinearity in the models. The correlation between the
POLITICAL_BRD_DUMMY and the BUREAUCRAT_BRD_DUMMY is the value of 0.931, higher than the critic value of 0.7 but these variables were not used in the same model. Overall,
multicollinearity is not a problem during the regressions ran in this study.
The Pearson correlation coefficient can also be used to find relations between variables. All variables, except for CEO DUALITY and TOBINS_Q are significantly correlated to
BRD_GENDER_DIV, mostly at the 5% level. The relations are in line with the hypotheses. In addition, the results shows a significant positive relationship between the
POLITICAL_BRD_DUMMY and BRD_GENDER_DIV (β=0.155; p <0.01),
BUREAUCRAT_BRD_DUMMY and BRD_GENDER_DIV (β=0.166; p <0.01) and the BGT and BRD_GENDER_DIV (β=0.177; p <0.01). These results are all in line with the hypotheses.
18 4.3 Regression and Findings
The goal of this study is to determine the relation between politically connected boards and senior bureaucrats and board gender diversity. A firm and year fixed-effect model in a diference-in-difference design is performed to test the hypotheses. Table 5 shows the results of the regression. Panel A presents the regression of POLITICAL_BRD_DUMMY,
BUREAUCRAT_BRD_DUMMY and MINISTER_BRD_DUMMY related to BRD_GENDER_DIV. Panel B presents the same regressions, with the BGT as moderator.
Table 5, panel A presents the significant relation between the POLITICAL_BRD_DUMMY related to BRD_GENDER_DIV. It indicates that political directors on boards lead to more board gender diversity (β=0.008; p <0.05). In this regression, various control variables are included, that also influence BRD_GENDER_DIV. The BGT, which recommends more women on boards also leads to more women on board (β=0.104; p <0.01). The higher the total assets, the higher the presence of women on board (β=0.006; p < 0.05). The higher the amount of closely held shares the lower the presence of women on board. (β=-0.016; p <0.01). The higher the proportion of non-executive directors on board, the higher the presence of women on board (β=0.027; p <0.05). The tenure of directors is negatively associated with board gender diversity (β=-0.015; p <0.01).
Table 5, panel A also presents the significant relation between the
BUREAUCRAT_BRD_DUMMY and BRD_GENDER_DIV. It indicates that senior bureaucrats on boards have a positive relation to board gender diversity (β=0.011; p <0.01).
TABLE 5, panel A also presents the significant relationship between the
MINISTER_BRD_DUMMY and BRD_GENDER_DIV. It indicates that ministers on board are negatively associated with board gender diversity (β=-0.015; p <0.10).
Table 5, panel B presents the significant influence of politically connected directors
(POLITICAL_BRD_DUMMY) on boards related to BRD_GENDER_DIV, with the BGT as a moderator. The results showed that the BGT as moderator, has a positive effect on politically connected directors on board and board gender diversity (β=0.018; p <0.01). The results of the control variables for panel B are similar to the results of panel A.
Table 5, panel B also present the significant relation between senior bureaucrats on board (BUREAUCRAT_BRD_DUMMY) and BRD_GENDER_DIV, with the BGT as a moderator. The moderator strengthens the effect between senior bureaucrats and WBRD_BGD (β=0.02; P <0.01).
19
Table 5, panel B also present the significant relation between ministers on board
(MINISTER_BRD_DUMMY) and BRD_GENDER_DIV, with the BGT as a moderator. The moderator strengthens the effect between ministers and WBRD_BGD (β=0.023; P <0.1). I also conducted an F-test in table 5 for the incremental effect between the BGT and the various dummy variables. All the results are very significant (P <0.01), therefore we can conclude that the results are robust.
4.4 Robustness tests
In table 6, I performed various robustness tests. These robustness tests are shown in table 6. I conducted the same regression as in table 5, but instead of the POLITICAL_BRD_DUMMY, BUREAUCRAT_BRD_DUMMY and MINISTER_BRD_DUMMY I used the percentage political directors, senior bureaucrats and ministers on boards. This test does ensure no reverse causality. I already deal with reverse causality in the moderating effect test in table 5. There I have an exogenous shock of the BGT in a difference-in-difference framework. The test in table 6 is an extension of the same test in table 5.
Most of the results in table 6 are similar to the results in table 5. In table 6, senior bureaucrats are also positively related to board gender diversity (β=0.024; p< 0.1). The BGT as moderator between the relationship of senior bureaucrats and board gender diversity is also significant (β=0.056; p< 0.01).
In contrast to table 5, table 6 shows no significant relationship between political directors and board gender diversity (β=0.02; p< 0.2). The BGT as moderator between the relationship of political directors and board gender diversity is, in line with table 5, a significantly positive association β=0.051; p< 0.01). The results of the control variables of table 6 are in line with the results of table 5. The percentage of ministers on boards, also shows, in contrast to table 5, no significant relationship between ministers on boards and board gender diversity (with or without moderator). The overall conclusion that bureaucrats are more attuned to the political zeitgeist of the era than other government officials is the same after performing the robustness test.
20 Conclusion
In this study I investigate the relationship between various political directors on the board and the appointment of women. I found that senior bureaucrats on a board are associated with increased board gender diversity. So, I found support for my hypothesis which states that some political directors (senior bureaucrats) are more likely to support board gender diversity than others (e.g. ministers). I argued, related to the Resource Dependency Theory, that political directors are able to link the firm to the government, and that senior bureaucrats take their political instinct with them when they come to the board of directors as a key resource. This instinct tells them to tread carefully on politically sensitive topics. Senior bureaucrats foresee the cost of not complying with the political zeitgeist of the era. Ministers in contrast are associated with decreased board gender diversity. Further, I found that the positive relationship between political directors on a board and board gender diversity is strengthened when politics introduce BGT, which recommends board gender diversity.
The findings in this study contribute to existing literature in three ways. First, to the best of my knowledge, this is the first study that investigates the relationship between political directors and board gender diversity grounded on resource dependency theory. Second, I contribute to make distinction between the specific roles the directors had in government, grounded on political science theory. Third, I showed that political directors capture the era’s of political zeitgeist. My research has some limitations. First, my study only focuses on UK firms, so the results might not be generalizable to other countries. Second, this study makes no distinction between
various industries. Future research may focus on the differences between the financial sector and industrial sector.
21
References
Adams, R., & Ferreira, D. (2004). Gender Diversity in the Boardroom. SSRN Electronic Journal
Adams, R. B., & Ferreira, D. (2009). Women in the boardroom and their impact on governance and performance. Journal of financial economics, 94(2), 291-309.
Agrawal, A., & Knoeber, C. (2001). Do Some Outside Directors Play a Political Role?. The Journal Of Law And Economics, 44(1), 179-198.
Alesina, A., & Tabellini, G. (2008). Bureaucrats or politicians? Part II: Multiple policy tasks. Journal of
Public Economics, 92(3-4).
Alimo‐Metcalfe, B. (1995). An investigation of female and male constructs of leadership and empowerment. Women In Management Review, 10(2), 3-8.
Bilimoria, D., & Piderit, S. K. (1994). Board committee membership: Effects of sex-based bias. Academy
of management journal, 37(6), 1453-1477.
Blom-Hansen, J., Baekgaard, M., Christensen, J., & Serritzlew, S. (2018). Politicians and bureaucrats: Reassessing the power potential of the bureaucracy. Manuscript presented at the 2017 IRSPM
(Budapest), NOPSA (Odense), and ECPR (Oslo) Conferences.
Bonardi, J. P. (2011). Corporate political resources and the resource-based view of the firm. Strategic
Organization, 9(3), 247-255.
Boubakri, N., Cosset, J. C., & Guedhami, O. (2009). From state to private ownership: Issues from strategic industries. Journal of Banking & Finance, 33(2), 367-379.
Brammer, S., Millington, A., & Pavelin, S. (2007). Gender and ethnic diversity among UK corporate boards. Corporate Governance: An International Review, 15(2), 393-403.
Bruna, M. G., Dang, R., Scotto, M. J., & Ammari, A. (2019). Does board gender diversity affect firm risk-taking? Evidence from the French stock market. Journal of Management and Governance, 23(4), 915-938.
De Cabo, R. M., Gimeno, R., & Nieto, M. J. (2012). Gender diversity on European banks’ boards of directors. Journal of Business Ethics, 109(2), 145-162.
Chandler, A. (2016). Women on corporate boards: a comparison of parliamentary discourse in the United Kingdom and France. Politics & Gender, 12(3), 443-468.
22
Chen, R., Dyball, M. C., & Wright, S. (2009). The link between board composition and corporate diversification in Australian corporations. Corporate Governance: An International Review, 17(2), 208-223.
Chen, J., Leung, W. S., & Evans, K. P. (2018). Female board representation, corporate innovation and firm performance. Journal of Empirical Finance, 48, 236-254.
Chiu, M. M., & Joh, S. W. (2004). Bank Loans to Distressed Firms: Cronyism, bank governance and economic crisis.Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
Christensen, J. G. (1997). Interpreting Administrative Change: Bureaucratic Self‐Interest and Institutional Inheritance in Government. Governance, 10(2), 143-174.
Conyon, M., & Mallin, C. (1997). Women in the Boardroom: Evidence from Large UK Companies. Corporate Governance, 5(3), 112-117.
Correia, M. (2014). Political connections and SEC enforcement. Journal Of Accounting And Economics, 57(2-3), 241-262.
Davies (of Aberscoch), L. (2011). Women on bards. The davies report, Londen, UK government
Dowling, M., & Aribi, Z. A. (2013). Female directors and UK company acquisitiveness. International
Review of Financial Analysis, 29, 79-86.
Dunleavy, P. (1991). Democracy, bureaucracy and public choice: economic explanations in political science. New York: Harvester Wheatsheaf.
Eklund, J. E., Palmberg, J., & Wiberg, D. (2009). Ownership structure, board composition and investment performance. Corporate ownership and control, 7(1), 117.
Faccio, M. (2007). The characteristics of politically connected firms. Purdue CIBER working papers, paper
51.
Faccio, M., Masulis, R., & McConnell, J. (2006). Political Connections and Corporate Bailouts. The Journal Of Finance, 61(6), 2597-2635.
Fan, J. P., Wong, T. J., & Zhang, T. (2007). Politically connected CEOs, corporate governance, and Post-IPO performance of China's newly partially privatized firms. Journal of financial economics, 84(2), 330-357.
Fauver, L., Hung, M., Li, X., & Taboada, A. G. (2017). Board reforms and firm value: Worldwide evidence. Journal of Financial Economics, 125(1), 120-142.
23
Galaskiewicz, J., & Wasserman, S. (1989). Mimetic processes within an interorganizational field: An empirical test. Administrative science quarterly, 34(3), 454-479.
Gompers, P., Ishii, J., & Metrick, A. (2003). Corporate governance and equity prices. The quarterly journal
of economics, 118(1), 107-156.
González-Bailon, S., Jennings, W., & Lodge, M. (2013). Politics in the boardroom: Corporate pay, networks and recruitment of former parliamentarians, ministers and civil servants in Britain. Political
Studies, 61(4), 850-873.
Goyal, R., Kakabadse, N., & Kakabadse, A. (2018). Achieving gender balance on British boards with the soft-law approach: Directors’ perspective. Journal of Business Diversity, 18(1).
Grosvold, J., & Brammer, S. (2009). Country, Industry, and Firm-Level Influences on the Prevalence of Women on Corporate Boards: An Institutional Approach. Proceedings of the International Association for
Business and Society (Vol. 20, pp. 261-277).
Harris, C. (2014). Women Directors on Public Company Boards: Does a Critical Mass Affect Leverage? Business and Economics Faculty Publications, 29.
Heemskerk, E., & Fennema, M. (2014). Women on Board: Female Board Membership as a Form of Elite Democratization. Enterprise & Society, 15(2), 252-284.
Hillman, A., Cannella, A., & Paetzold, R. (2000). The Resource Dependence Role of Corporate Directors: Strategic Adaptation of Board Composition in Response to Environmental Change. Journal Of
Management Studies, 37(2), 235-256.
Hillman, A. (2005). Politicians on the Board of Directors: Do Connections Affect the Bottom Line?. Journal Of Management, 31(3), 464-481.
Isidro, H., & Sobral, M. (2015). The effects of women on corporate boards on firm value, financial performance, and ethical and social compliance. Journal of Business Ethics, 132(1), 1-19.
James, O., Petrovsky, N., Moseley, A., & Boyne, G. A. (2016). The politics of agency death: ministers and the survival of government agencies in a parliamentary system. British Journal of Political Science, 46(4), 763-784.
Kalogirou, S. (2013). Testing geographically weighted multicollinearity diagnostics. Paper presented at
GISRUK 2013.
Kanter, R. (1977). Some Effects of Proportions on Group Life: Skewed Sex Ratios and Responses to Token Women. American Journal Of Sociology, 82(5), 965-990.
24
Khemakhem, H., & Dicko, S. (2013). Directors' political connections and compliance with board of directors regulations: The case of S&P/TSX 300 companies. International Journal of Business and
Management, 8(24), 117.
Kroszner, R. S., & Stratmann, T. (1998). Interest-group competition and the organization of congress: theory and evidence from financial services' political action committees. American Economic Review, 1163-1187.
Laffin, M. (1997). Understanding Minister–Bureaucrat Relations: Applying Multi‐Theoretic Approaches in Public Management. Australian Journal of Public Administration, 56(1), 45-58.
Lester, R. H., Hillman, A., Zardkoohi, A., & Cannella Jr, A. A. (2008). Former government officials as outside directors: The role of human and social capital. Academy of Management Journal, 51(5), 999-1013.
Li, C. A., & Wearing, R. T. (2001). The glass ceiling and directors of large UK quoted companies.
Department of Accounting, Finance and Management, University of Essex.
Meyer, J. W. (2008). Reflections on institutional theories of organizations. The Sage handbook of
organizational institutionalism, 790-811.
McGuinness, P. B., Vieito, J. P., & Wang, M. (2017). The role of board gender and foreign ownership in the CSR performance of Chinese listed firms. Journal of Corporate Finance, 42, 75-99.
Moe, T. M. (2006). Political Control and the Power of the Agent. The Journal of Law, Economics, and
Organization, 22(1), 1-29.
Moury, C. (2011). Coalition agreement and party mandate: How coalition agreements constrain the ministers. Party Politics, 17(3), 385-404.
Oakley, J. G. (2000). Gender-based barriers to senior management positions: Understanding the scarcity of female CEOs. Journal of business ethics, 27(4), 321-334.
Perrault, E. (2015). Why does board gender diversity matter and how do we get there? The role of shareholder activism in deinstitutionalizing old boys’ networks. Journal of Business Ethics, 128(1), 149-165.
Peters, B. G. (1981). The problem of bureaucratic government. The Journal of Politics, 43(1), 56-82. Reeb, D. M., & Zhao, W. (2013). Director capital and corporate disclosure quality. Journal of Accounting
and Public Policy, 32(4), 191-212.
25
Schein, V. E., & Mueller, R. (1992). Sex role stereotyping and requisite management characteristics: A cross cultural look. Journal of Organizational Behavior, 13(5), 439-447.
Sealy, R. (2010). Changing perceptions of meritocracy in senior women's careers. Gender in
Management: An International Journal, 25(3), 184-197.
Seierstad, C. (2016). Beyond the business case: The need for both utility and justice rationales for increasing the share of women on boards. Corporate Governance: An International Review, 24(4), 390-405.
Seierstad, C., Warner-Søderholm, G., Torchia, M., & Huse, M. (2017). Increasing the number of women on boards: The role of actors and processes. Journal of Business Ethics, 141(2), 289-315.
Singh, V., & Vinnicombe, S. (2004). Why so few women directors in top UK boardrooms? Evidence and theoretical explanations. Corporate governance: an international review, 12(4), 479-488.
Singh, V. (2007). Ethnic diversity on top corporate boards: A resource dependency perspective. The
International Journal of Human Resource Management, 18(12), 2128-2146.
Shin, Y. Z., Chang, J. Y., Jeon, K., & Kim, H. (2019). Female directors on the board and investment efficiency: evidence from Korea. Asian Business & Management, 1-42.
Stern, R., Pfeffer, J., & Salancik, G. (1979). The External Control of Organizations: A Resource Dependence Perspective. Contemporary Sociology, 8(4), 612.
Tannen, D. (1994). Talking from 9 to 5: How women's and men's conversational styles affect who gets heard, who gets credit, and what gets done at work. William Morrow and Company, Inc., 1350 Avenue of
the Americas, New York, NY 10019.
Teigen, M. (2012). Chapter 4 gender quotas on corporate boards: On the diffusion of a distinct national policy reform. Firms, boards and gender quotas: Comparative perspectives (pp. 115-146).
Terjesen, S., Aguilera, R. V., & Lorenz, R. (2015). Legislating a woman’s seat on the board: Institutional factors driving gender quotas for boards of directors. Journal of Business Ethics, 128(2), 233-251. Terjesen, S., & Sealy, R. (2016). Board gender quotas: Exploring ethical tensions from a multi-theoretical perspective. Business Ethics Quarterly, 26(1), 23-65.
Vertzberger, Y. (1984). Bureaucratic-organizational politics and information processing in a developing state. International Studies Quarterly, 28(1), 69-95.
Vinnicombe, S., Doldor, E., Sealy, R., Pryce, P., & Turner, C. (2015). The Female FTSE board report 2015: Putting the UK progress into a global perspective. Cranfield University School of Management.
26
Wang, B., Yan, S., & Wang, L. (2019). Resource dependence or monitoring: a governance perspective on political connections. Asia-Pacific Journal Of Accounting & Economics, 1-26.
Wood, B. D. (1988). Principals, bureaucrats, and responsiveness in clean air enforcements. American
Political Science Review, 82(1), 213-234.
Yang, P., Riepe, J., Moser, K., Pull, K., & Terjesen, S. (2019). Women directors, firm performance, and firm risk: A causal perspective. The Leadership Quarterly.
Yesilkagit, K., & Van Thiel, S. (2008). Political influence and bureaucratic autonomy. Public Organization
Review, 8(2), 137-153.
Yu, H., Jiang, S., & Land, K. C. (2015). Multicollinearity in hierarchical linear models. Social science
27 Table 1: Sample statistics
This table shows the observations of political directors among years.
Year Observations 2000 196 2001 275 2002 337 2003 374 2004 429 2005 542 2006 679 2007 817 2008 887 2009 894 2010 806 2011 815 2012 842 2013 782 2014 726 2015 750 10151
28 Table 2: Variable measurements
Variable Measurement Source
BRD_GENDER_DIV Female directors/Board size BoardEx
POLITICAL_BRD_DUMMY At least one director on the board with minister or senior bureaucrat experience Hand-collected/BoardEx
BUREAUCRAT_BRD_DUMMY At least one director on the board with senior bureaucrat employment Hand-collected/BoardEx
MINISTER_BRD_DUMMY At least one director on the board with minister employment Hand-collected/BoardEx
BGT Coded 1 starting from the year in which a cg code "recommended" BGD BoardEx
CEO DUALITY 1 if ceo_dummy =1 & dir_chairperson =1 BoardEx
TOBINS_Q * Firm value: total assets-common shareholders equity + market cap)/Total Assets Worldscope
TOTAL_ASSETS * Logarithm of the total assets Woldscope
OPERATING_INCOME * Operating income/Total assets Woldscope
LEVERAGE * Total liabilities/Total assets Woldscope
CAPITAL EXPENDITURES * Capital expenditures/Total assets Woldscope
R&D EXPENDITURES * R&D/Total assets Woldscope
CASH * Generic Cash/Total assets Woldscope
CLOSELY_HELD_SHARES * Amount of closely held share/100 Woldscope
FOREIGN_ASSETS * Foreign assets/Total assets Woldscope
BRD_SIZE * Logarithm of total number of board of directors BoardEx
BRD_INDEPENDENCE * Non-executive director/dir_boardsize BoardEx
BRD_TENURE * Total board tenure/Board size BoardEx
BRD_QUOTED_AFFIL * Total years membership boards of quoted companies/Board size BoardEx
BUSINESS_SEG Logarithm of count of Business Segments using 10 SIC codes Worldscope
GEOGRAPHIC_SEG Count of the number of geographic segment 1-10 Assets Worldscope
This table shows the measurements of the dependent variable, the independent variables and the control variables used in this study. When * stands next to the variable, it means that the variable is winsorized at 1% level at the top and the bottom.
29 Table 3: descriptive statistics
Variable Obs Mean Std. Dev. Min Max
POLITICAL_BRD_DUMMY 10,151 0.549 0.497 0 1 BUREAUCRAT_BRD_DUMMY 10,151 0.513 0.499 0 1 MINISTER_BRD_DUMMY 10,151 0.049 0.216 0 1 BGT 10,151 0.385 0.486 0 1 CEO DUALITY 10,151 0.051 0.221 0 1 TOBINS_Q * 10,151 1.628 1.323 0 9.554 TOTAL_ASSETS * 10,151 5.261 2.466 0 12.168 OPERATING_INCOME * 10,151 0.010 0.183 0.863 0.352 LEVERAGE * 10,151 0.450 0.248 0 1 CAPITAL EXPENDITURES * 10,151 0.042 0.057 0 0.348 R&D EXPENDITURES * 10,151 0.023 0.073 0 0.753 CASH * 10,151 0.162 0.192 0 0.935 CLOSELY_HELD_SHARES * 10,151 0.304 0.251 0 0.933 FOREIGN_ASSETS * 10,151 0.219 0.306 0 1 BRD_SIZE * 10,151 1.875 0.354 1.098 2.995 BRD_INDEPENDENCE * 10,151 0.503 0.189 0 1 BRD_TENURE * 10,151 0.901 0.694 0 3.536 BRD_QUOTED_AFFIL * 10,151 0.269 0.146 0 0.875 BUSINESS_SEG 10,151 0.638 0.659 0 2.302 GEOGRAPHIC_SEG 10,151 0.635 0.651 0 2.302
Table 4: Correlation matrix Variables 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 1) BRD_GENDER_DIV 1 2) POLITICAL_BRD_DUMMY 0.155*** 1 3) BUREAUCRAT_BRD_DUMMY 0.0134 0.207*** 1 4) MINISTER_BRD_DUMMY 0.166*** 0.931*** 0.0726*** 1 5) BGT 0.177*** -0.0444*** -0.0508*** -0.0418*** 1 6) CEO DUALITY 0.0155 -0.0444*** -0.00916 -0.0421*** -0.0273** 1 7) TOBINS_Q * 0.0147 0.0209* 0.0272** 0.00943 -0.00666 0.0209* 1 8) TOTAL_ASSETS * 0.241*** 0.383*** 0.102*** 0.396*** -0.00275 -0.0394*** -0.116*** 1 9) OPERATING_INCOME * 0.116*** 0.122*** -0.00161 0.127*** -0.0146 -0.00207 -0.221*** 0.406*** 1 10) LEVERAGE * 0.108*** 0.205*** 0.0761*** 0.200*** -0.104*** -0.0116 -0.0186 0.480*** 0.213*** 1 11) CAPITAL EXPENDITURES * -0.0230* 0.0352*** 0.0236* 0.0307** -0.0380*** 0.0333*** 0.0682*** 0.105*** 0.0636*** 0.0483*** 1 12) R&D EXPENDITURES * -0.0600*** -0.00324 -0.00911 0.00205 -0.0422*** -0.0222* 0.362*** -0.194*** -0.430*** -0.106*** -0.0588*** 1 13) CASH * -0.0810*** -0.0414*** -0.00442 -0.0533*** -0.00410 0.00779 0.359*** -0.274*** -0.351*** -0.296*** -0.103*** 0.352*** 1 14) CLOSELY_HELD_SHARES * -0.112*** -0.206*** -0.0312** -0.211*** 0.0283** 0.0758*** 0.0178 -0.343*** -0.107*** -0.0849*** 0.0181 0.0109 0.129*** 1 15) FOREIGN_ASSETS * -0.0271** 0.0321** 0.0132 0.0220* -0.00458 0.000608 -0.0419*** 0.208*** 0.0584*** 0.00163 0.131*** -0.0680*** -0.0957*** -0.0610*** 1 16) BRD_SIZE * 0.209*** 0.407*** 0.134*** 0.404*** -0.0720*** -0.0679*** 0.0153 0.681*** 0.258*** 0.320*** 0.0690*** -0.0381*** -0.141*** -0.252*** 0.110*** 1 17) BRD_INDEPENDENCE * 0.160*** 0.203*** 0.0370*** 0.210*** 0.152*** -0.0411*** -0.0413*** 0.366*** 0.0842*** 0.0139 0.00895 -0.0244* -0.0569*** -0.216*** 0.172*** 0.237*** 1 18) BRD_TENURE * -0.110*** -0.214*** -0.0779*** -0.199*** 0.0585*** 0.126*** -0.0250* -0.205*** 0.0329*** -0.0684*** -0.0276** -0.00138 0.0141 0.247*** -0.103*** -0.428*** -0.186*** 1 19) BRD_QUOTED_AFFIL * -0.102*** -0.148*** -0.0305** -0.145*** 0.0355*** 0.0251* 0.0308** -0.169*** -0.173*** -0.135*** -0.0248* -0.0263** 0.134*** 0.107*** 0.0754*** -0.542*** 0.110*** 0.243*** 1 20) BUSINESS_SEG 0.117*** 0.170*** 0.0334*** 0.175*** 0.0951*** -0.0257** -0.0539*** 0.381*** 0.194*** 0.321*** -0.0346*** -0.0962*** -0.168*** -0.117*** 0.0469*** 0.288*** 0.0925*** -0.0470*** -0.109*** 1 21) GEOGRAPHIC_SEG 0.0463*** 0.145*** 0.0656*** 0.137*** 0.00238 -0.00809 0.0141 0.372*** 0.188*** 0.233*** 0.0282** -0.0328*** -0.0844*** -0.163*** 0.503*** 0.292*** 0.155*** -0.0860*** -0.0720*** 0.269*** 1 This table presents the Pearson Correlation Coefficients of het variables where * p<0.05, ** p<0.01, *** p<0.001
Table 5: Hypotheses testing
Panel A Panel B
VARIABLES BRD_GENDER_DIV BRD_GENDER_DIV BRD_GENDER_DIV BRD_GENDER_DIV BRD_GENDER_DIV BRD_GENDER_DIV
POLITICAL_BRD_DUMMY 0.008** 0.003 (0.004) (0.004) BUREAUCRAT_BRD_DUMMY 0.011*** 0.005 (0.004) (0.004) MINISTER_BRD_DUMMY -0.015* -0.020*** (0.008) (0.007) POLITICAL_BRD_DUMMY * BGT 0.018*** (0.005) BUREAUCRAT_BRD_DUMMY * BGT 0.020*** (0.005) MINISTER_BRD_DUMMY * BGT 0.023* (0.014) BGT 0.104*** 0.104*** 0.104*** 0.093*** 0.092*** 0.102*** (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) CEO DUALITY 0.009 0.009 0.008 0.009* 0.009* 0.008 (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) TOBINS_Q 0.002* 0.002* 0.002* 0.002* 0.002* 0.002* (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) TOTAL_ASSETS 0.006** 0.006** 0.005** 0.006** 0.006** 0.005** (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) OPERATING_INCOME -0.001 -0.001 -0.001 -0.000 -0.000 0.000 (0.008) (0.008) (0.008) (0.008) (0.008) (0.008) LEVERAGE -0.015* -0.015* -0.014 -0.014 -0.014 -0.014 (0.009) (0.009) (0.009) (0.009) (0.009) (0.009) CAPITAL EXPENDITURES 0.032* 0.032* 0.032* 0.030* 0.031* 0.032* (0.018) (0.018) (0.018) (0.018) (0.018) (0.018) R&D EXPENDITURES 0.007 0.006 0.007 0.007 0.005 0.007 (0.021) (0.021) (0.021) (0.021) (0.021) (0.021) CASH 0.000 -0.000 0.001 0.000 0.000 0.001 (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) CLOSELY_HELD_SHARES -0.016*** -0.016*** -0.016*** -0.015** -0.014** -0.016*** (0.006) (0.006) (0.006) (0.006) (0.006) (0.006) FOREIGN_ASSETS 0.001 0.002 0.001 0.002 0.002 0.001 (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
32 BRD_SIZE -0.019** -0.020** -0.015* -0.018** -0.018** -0.016* (0.009) (0.009) (0.009) (0.009) (0.009) (0.009) BRD_INDEPENDENCE 0.027** 0.027** 0.028*** 0.026** 0.026** 0.028*** (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) BRD_TENURE -0.015*** -0.015*** -0.015*** -0.014*** -0.014*** -0.015*** (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) BRD_QUOTED_AFFIL -0.013 -0.014 -0.010 -0.013 -0.013 -0.010 (0.016) (0.016) (0.016) (0.016) (0.016) (0.016) BUSINESS_SEG 0.003 0.003 0.003 0.003 0.003 0.003 (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) GEOGRAPHIC_SEG 0.004* 0.005* 0.004* 0.005* 0.005* 0.005* (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) Constant 0.024 0.025 0.021 0.025 0.024 0.023 (0.022) (0.021) (0.021) (0.021) (0.021) (0.021)
Year fixed-effects Yes Yes Yes Yes Yes Yes
Firm fixed effects Yes Yes Yes Yes Yes Yes
Observations 10,151 10,151 10,151 10,151 10,151 10,151
R-squared 0.171 0.172 0.171 0.175 0.176 0.172
Number of firm_id 1,693 1,693 1,693 1,693 1,693 1,693
F-test statistic 114.10*** 114.38*** 115.73***
This table shows the results of the hypotheses in this thesis. The measurements of the variables are described in table 2. The values in parentheses are the robust standard errors. *** p<0.01, ** p<0.05, * P<0.1
33
Table 6: Robustness test
Panel A Panel B
VARIABLES BRD_GENDER_DIV BRD_GENDER_DIV BRD_GENDER_DIV BRD_GENDER_DIV BRD_GENDER_DIV BRD_GENDER_DIV
POLITICAL % 0.020 0.007 (0.013) (0.013) BUREAUCRAT % 0.024* 0.009 (0.014) (0.015) MINISTER % -0.072 -0.085 (0.053) (0.052) POLITICAL % * BGT 0.051*** (0.016) BUREAUCRAT % * BGT 0.056*** (0.016) MINISTER % * BGT 0.058 (0.084) BGT 0.105*** 0.105*** 0.104*** 0.097*** 0.097*** 0.104*** (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) CEO DUALITY 0.009 0.009 0.008 0.009 0.009 0.008 (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) TOBINS_Q 0.002* 0.002* 0.002* 0.002* 0.002* 0.002* (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) TOTAL_ASSETS 0.005** 0.005** 0.005** 0.005** 0.005** 0.005** (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) OPERATING_INCOME -0.001 -0.001 -0.001 -0.000 -0.000 -0.001 (0.008) (0.008) (0.008) (0.008) (0.008) (0.008) LEVERAGE -0.015* -0.015* -0.014 -0.015* -0.014* -0.014 (0.009) (0.009) (0.009) (0.009) (0.009) (0.009) CAPITAL EXPENDITURES 0.032* 0.032* 0.032* 0.032* 0.032* 0.032* (0.018) (0.018) (0.018) (0.018) (0.018) (0.018) R&D EXPENDITURES 0.007 0.006 0.006 0.007 0.006 0.006 (0.021) (0.021) (0.021) (0.021) (0.021) (0.021) CASH 0.000 0.000 0.001 0.000 0.000 0.001 (0.007) (0.007) (0.007) (0.007) (0.007) (0.007) CLOSELY_HELD_SHARES -0.016*** -0.016*** -0.016*** -0.015** -0.015** -0.016*** (0.006) (0.006) (0.006) (0.006) (0.006) (0.006) FOREIGN_ASSETS 0.001 0.001 0.001 0.001 0.002 0.001 (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) BRD_SIZE -0.017** -0.017** -0.016* -0.016* -0.016* -0.017* (0.009) (0.009) (0.009) (0.009) (0.009) (0.009) BRD_INDEPENDENCE 0.027** 0.027** 0.028*** 0.026** 0.026** 0.028*** (0.011) (0.011) (0.011) (0.011) (0.011) (0.011) BRD_TENURE -0.015*** -0.015*** -0.015*** -0.015*** -0.015*** -0.015***
34 (0.003) (0.003) (0.003) (0.003) (0.003) (0.003) BRD_QUOTED_AFFIL -0.013 -0.013 -0.011 -0.012 -0.011 -0.011 (0.016) (0.016) (0.016) (0.016) (0.016) (0.016) BUSINESS_SEG 0.003 0.003 0.003 0.003 0.003 0.003 (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) GEOGRAPHIC_SEG 0.004* 0.005* 0.004* 0.005* 0.005* 0.004* (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) Constant 0.022 0.022 0.023 0.021 0.020 0.024 (0.021) (0.021) (0.021) (0.021) (0.021) (0.021)
Year fixed-effects Yes Yes Yes Yes Yes Yes
Firm-fixed effects Yes Yes Yes Yes Yes Yes
R-squared 0.171 0.171 0.171 0.173 0.171 0.171
Number of firm_id 1,693 1,693 1,693 1,693 1,693 1,693
F-test statistic 78.99*** 113.83*** 75.70***
This table shows the robustness tests of the hypotheses in this thesis. The measurements of the variables are described in table 2. The values in parentheses are the robust standard errors. *** p<0.01, ** p<0.05, * p<0.1
