University of Groningen, Faculty of Economics and Business
PAY DIFFERENCES AMONG DUTCH DIRECTORS:
EVIDENCE ABOUT THE PENALTY FOR PARENTHOOD
Master Thesis for MSc Accountancy
June 25
th, 2018
ABSTRACT:
The recent rise of women towards the top of the corporate ladder introduces a new governance problem which is of major interest for researchers and academics in the field of gender disparity: the gap in director compensation between men versus women, holding equally important positions. The aim of this research is to investigate the differences in compensation among directors of Dutch listed firms in relation to parenthood. We examine whether they somehow get penalized for being a parent. In the Netherlands, firms mainly have two-tier governance structures, with executive directors in the management board and executive directors in the supervisory board. This study focuses on non-executive directors and contributes to existing literature by adding hand-collected data on the director’s background to examine the relation between parenthood and compensation. After controlling for firm-level and director-firm-level variables, findings of our Dutch sample show that non-executives with children receive significantly lower compensation compared to non-executives without children. Additional findings show that women non-executive directors with children, again receive less compensation. Our study provides new evidence on the ‘family-gap-in-pay’ in the upper-echelons of Dutch corporations by showing that directors are penalized for parenthood, and in this aspect, women are more penalized than men in terms of their compensation.
Name: C.W. Schiphorst
Student number: S2484714
E-mail: c.w.schiphorst@student.rug.nl
Supervisor: S. Mukherjee / Co-assessor: N. Hussain
Table of Contents
Introduction ... 4
1. Theoretical Background ... 8
1.1 Literature Review ... 8
1.2 Hypothesis Development... 11
2. Data & Methods ... 13
2.1 The Dataset ... 13
2.2 Summary Statistics ... 15
2.3 Measures of Pay ... 17
2.4 Regression Model ... 17
3. Results ... 20
3.1 Univariate Tests ... 20
3.2 Main Regressions Results ... 20
3.3 Additional Analyses ... 23
4. Discussion & Conclusions ... 26
4.1 Summary of Findings ... 26
4.2 Limitations and Future Research ... 27
References. ... 28
Introduction
Women in the European Union earn on average a good 16 percent less compared to their male counterparts in 2016 (Eurostat, 2018). As a result, women are often paid less than men doing exactly the same job. According to the International Labor Office, it will take more than seventy years to completely close the gender pay gap (ILO, 2016). Meanwhile, a number of Dutch political parties stated that the pay inequality should come to an end, and have therefore submitted a legislative proposal that requires companies to be transparent about their salaries. According to this proposal, a certification system should be in place, requiring Dutch companies with more than fifty employees to publish the employee salary figures every three years. The Netherlands follows the example of Iceland, where laws have been adopted in recent years that require more openness about pay equality (European Commission, 2017).
Reducing pay inequalities is one of the key priorities of gender policies at both EU and national levels. Since the mid-nineties, there has been little change in the full-time gender pay gap in the Netherlands. Differences in earnings between men and women can partly be explained by Becker’s (1965) human capital theory, which refers to the relevant education, skills and experience a person brings to employment (Walby and Olsen, 2002). Other determinants of pay differences include observable factors such as women working more part-time and women being over-represented in a number of industries where wages are lower (Betrand and Hallock 2001; Adams et al., 2007; Carter et al., 2017). Still, there remains an unexplained gap in earnings between men and women. One important aspect closely related to the gender pay gap is the effect of parenthood on earnings. Since the effects of individual director background characteristics, and in particular the effects of having children, are often overlooked in research on pay inequalities, this study aims to fill this gap in existing literature by investigating the effect of parenthood on director compensation.
Whether there is a ‘penalty-in-pay’ coming with parenthood is important for our understanding of pay inequalities and therefore, we will investigate if parenthood can be an explanatory piece of the puzzle that closes the pay gap among directors. Since closing the gap is concerned with equal opportunities for women, which is an issue of human rights, this topic is an important social matter for individuals, firms and governments. As long as there is indistinctness about the existence of gender pay differences, this study’s relevance extends to the society at large (Hutchinson et al., 2017).
Prior research in the field of pay inequality in relation to parenthood mainly focuses on the earnings differences and equal treatment of women at the labor market level or low-to-middle management levels. Interesting studies in this area have been carried out by Waldfogel (1997; 1998), Pal & Waldfogel (2014), and Sigle-Rushton & Waldfogel (2007). By showing a significant difference in the wages between women who have children and women who have none, these studies indicate that women are penalized for combining child-rearing with paid work, which does not disappear when controlling for education, work experience and differences in personal characteristics. This is referred
to as the ‘family-gap-in-pay’. Existing research states that part of the gender pay gap can be explained by this family gap in pay (Waldfogel, 1997; Davies & Pierre, 2005; Baker, 2010; Pal & Waldfogel, 2014). In addition, it is worth noting that most literature on pay inequality is U.S. based (Waldfogel, 1998; Adams et al., 2007; Gul et al., 2017; Pal & Waldfogel, 2014) and existing studies investigating pay inequalities on executive levels do not take the effect of parenthood into account. Besides, while the gender gap between men and women has been narrowing, the gap in pay between women with and women without children has been rising (Waldfogel, 1998). Women without children are increasingly participating in the labor market, moving in the right direction in terms of equality. However, this does not apply to women with children.
In January 2006, Norway, as the very first, implemented mandatory quota law for gender diversity on corporate boards of public limited companies (Ahern & Dittmar, 2012). The law requires a minimum of 40% of each gender in boards of Norwegian PLCs, with enforcement starting from January 2008. Followed by countries as France, Iceland and Belgium, the case of Norway can be seen as an ‘example to follow’ (Seierstad et al., 2017). Moreover, many other European countries have implemented softer initiatives with the same goal of increasing gender diversity in corporate boards. These countries, including The Netherlands, updated their codes and now have either a voluntary quota or a comply-or-explain best practice provision incorporated in their corporate governance code (EWoB, 2016). This massive attention in European politics paid to gender diversity in the corporate context together with countries implementing gender quotas and best practice provisions recently, has led to the increase of women in corporate top positions.
This recent rise of women towards the top of the corporate ladder, introduces a new paradigm which is of major interest for researchers and academics in the field gender disparity: the gap in director compensation between men versus women, holding similarly important positions. As there is a lot of literature focusing on advancement barriers faced by women in reaching corporate top positions, referred to as ‘the glass ceiling’, less research has been conducted on gender pay differences once women have reached this top of the corporate ladder (Adams et al., 2007). From Figure I, it may be clear that women on Dutch corporate boards are underpaid in terms of their compensation. This means that even today, pay inequalities exist. Few studies in the field of pay inequality have focused on the director’s individual background characteristics for explaining differences in compensation among directors. Therefore, the reasons why these inequalities in compensation levels among top positions exist and whether these differences are somehow related with parenthood, remain unclear.
For the purpose of this study, we will focus on directors of Dutch listed firms. Compared to other countries in the European Union, the Netherlands is performing well in terms of gender equality, ranking fourth on the European Gender Equality Index (EIGE, 2017). In this country, extensive legislation on equal treatment and anti-discrimination is in place, stating that all people in the Netherlands should be treated equally in equal circumstances (ETA, 1984). According to figures presented by Eurostat (2018), the ‘unadjusted’ gender pay gap in the Netherlands still exists, covering 16%. Another finding comes
from Verschuren et al. (2014) and indicates that the highest difference in wages is among employees with children. These are interesting facts for a gender equal country as the Netherlands and therefore, it is worth examining the effect of parenthood on pay for this particular country. In addition, the Dutch Corporate Governance Code (hereinafter: Code) contains widely supported views on corporate governance, and this Code is at the forefront in the international context. With the amended Code, which is effective from 2009, the Netherlands has succeeded in adequately responding to the need to further improve the governance structure of Dutch listed companies. On the basis of this amended Code, the supervisory board should strive for a more diverse composition with regard to demographic characteristics such as gender, age, expertise, background, and nationality. Supervisory boards must communicate how diversity is to be shaped within their boards, with gender and age having a prominent place in the Code. The policy on gender equality for Dutch corporations is still based on the company’s own responsibility in realizing a balanced representation of men and women in top positions. Yet, this updated best practice provision has manifested itself in an increase of the percentage of women non-executive directors. The rise of non-non-executive women on Dutch corporate boards in recent years, in combination with the growing awareness of the importance of a diverse board composition, contributed to the amount of data available on the individual directors’ backgrounds, which gives us the opportunity to examine compensation differences in relation to individual director characteristics. To our knowledge, no research in this field ever investigated the pay gap at executive levels in relation with parenthood. By using our hand-collected data, this paper examines the penalty in pay for parenthood among executive levels, with non-executive directors sitting on Dutch boards as our main subject of research.
This study considers two main issues. First, are there parenthood related differences present in compensation among non-executive directors in The Netherlands? In other words, are these directors penalized for the fact of having children? Second, if this is the case, does this difference in compensation varies as a function of gender? Which means, are compensations of men non-executive directors that
3,00 3,50 4,00 4,50 5,00 5,50 6,00 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Source: data obtained from our initial data sample Figure I
Mean Compensation of Dutch directors (in Logs)
have children significantly higher (or lower) than compensations of women non-executive directors that have children? To obtain answers to these questions and come to our findings, we perform a longitudinal panel data study, covering a period of 15 years. In our main sample, we include 1.361 non-executive directors from listed companies in the Netherlands. Our model contains multiple firm and director-level variables and additional information on the directors’ backgrounds. This additional background information comes from the data we have hand-collected ourselves, and which was not available yet in this quantity in the databases used. This data gives us a deepening on the director’s educational background (i.e. their profession), whether they have children or not, and their marital status, and will be very meaningful for our study.
To answer our first main issue, we perform OLS regression analyses and find strong evidence that supports the hypothesis that parenthood is negatively related to director compensation. Non-executive directors who have children receive substantially less compensation compared to directors who have no children. Our additional analyses investigate the effect that the executive’s gender has on this established relationship. The regression results show our findings to the second research issue. These findings indicate that if non-executive directors with children are women, they again receive lower compensation levels compared to men with children and to all non-executive directors without children. With these findings, we contribute to the literature on the family gap in pay, stating that Dutch directors are somehow penalized in their compensations for having children. Our results indicate that the parenting responsibilities coming with the fact of having children, are reflected into lower director compensation levels, indicating the ‘penalty-in-pay’ for parenthood among Dutch directors. These findings apply to the group of non-executive directors for the years 2000-2015 and the results remain unchanged after controlling for firm and individual director characteristics. If this penalty-in-pay is a sign of pay inequality, meaning that this penalty exists regardless of the fact that equal performance is delivered for both the director with and the director without children, has to be further explored in future research, in which time spent and individual responsibilities related to the directors’ roles should be taken into account.
This thesis will proceed as follows. In section 1, we will discuss the theoretical background and the existing literature related to this topic. Next, besides a description of the data sample and the methods used, section 2 includes a deepening on the data present in our dataset. In section 3, our findings on the director pay gap will be presented. Section 4 concludes.
1. Theoretical background
1.1 Literature Review
Differences in acquirements of human capital
European women in the 21st century are increasingly participating in the labor market (Gender Studies, 2007). Ever since the turn of the century, the gap in the education level of Dutch women has disappeared. Recent developments show that women nowadays receive high education levels and succeed more often in acquiring top positions (Emancipation monitor, 2016), bearing a greater deal of responsibilities. When it comes to the participation of women in the labor market, the Netherlands is at the forefront compared to other European countries. The average employment rate in 2015 for Dutch women is 60% compared to 70% for men (CBS, 2015). This increasing participation of women in paid employment goes hand in glove with the decline in fertility rates. Together with several equal opportunity policies which are deeply embedded in the Dutch constitution, these factors are slowly fading the traditional inequality between men and women in corporate life.
Pay levels differ because the individual’s acquirements in human capital differ. Human capital is defined by Walby & Olsen (2002) as ‘all the skills and experience that a person brings to employment that are relevant to the employment’. This well-known theory, first initiated by Becker (1965), states that the provision of formal education and gaining experience can be considered as investments in human capital. According to Schippers & Siegers (1988) and Cassells et al. (2009), differences in acquirements of the main quantities of human capital play an important role in explaining part of the pay inequalities. These are differences between men and women in acquiring education, work experience and training. Pay differences can be partly attributed to these acquired endowments. In addition, it is generally known that the amount of time worked and the continuity of work experience traditionally differs considerably between the sexes. Women are more likely than men to alternate their working career with periods of work-life withdrawals for parenting and child-rearing reasons (Drolet, 2001). A great deal of studies related to gender differences in earnings note women’s responsibility for raising children as an important explanation for the existence of the undervaluation of women compared to men (Waldfogel, 1998; Sigle-Rushton & Waldfogel, 2007). The related work-life withdrawals have negative consequences on women’s pay, since work-life withdrawals are inseparably linked to shorter periods of job tenure, depreciation of previously acquired human capital, and reduced promotion opportunities. Also, women facing work-life withdrawals may decide not to participate in training and retraining activities and may choose to accept lower wages (Drolet, 2001; Cassells et al., 2009). Therefore, the lower level of acquirements in human capital for women with children is one of the main reasons that women receive lower wages than men (Davies & Pierre, 2005).
In the Netherlands, despite the fact the men and women are equally educated, a lot of talent remains unused, as women often still not reach the top. A declaration that is often mentioned for the fact that there are far less women than men possessing top executive positions, is that women work more
part-time, mainly because they want to be able to combine care and work well. Women who foresee to have children and are expecting difficulties in combining this with work would invest less in human capital and consequently will receive lower wages (Sigle-Rushton & Waldfogel, 2007). Studies conducted by Waldfogel (1995; 1997; 1998) revealed evidence that wages for U.S. women with children were much lower than wages for women without children and men, even after controlling for age, experience, and education. In these studies, the presence of children resulted in women working more part-time or even participating less in the labor market. As Olsen & Walby (2004) pointed out, part-time work is associated with lower rates of acquisition in human capital. Likewise, women on their way to higher corporate positions may decide not to have children. In investigating the possible determinants of pay inequalities, it is important to understand whether parenthood, or motherhood when speaking about women, is linked to any penalty in pay.
Promoting equality in top positions
Traditionally, men in low gender equal countries are expected to prioritize paid work and women are expected to prioritize family. In these countries, high employment among women does not corresponds with the societal expectation that women should focus on family responsibilities. For these women, this makes it difficult to combine care with paid work and achieve balance. Consequently, it will diminish women’s ambition to achieve top positions. In contrast, more gender equal countries, like the Netherlands, differentiate less between gender roles and expected priorities (McDaniel, 2008; Lyness & Judiesch, 2014). In these countries, parenting responsibilities are more accepted for both men and women and therefore, work-life balance levels between men and women are more similar. Nowadays, however, it remains difficult combining a top function with having a family. Compared to men, women in the Netherlands still spend less time on paid work and more time on raising children and domestic work (Emancipation monitor, 2016). In addition, less full-time working women than men have the ambition to be promoted to senior positions. There are also indications that there are some barriers from the corporate culture that make it difficult for women to move to the top. These barriers cannot be noted at first glance, but are invisible and incorporated in everyday practices, unintentionally favoring men over women (Ellemers, 2014). On the way to equality of men versus women directors in terms of their proportions on the board as well as their compensations, government and companies should ensure there are enough women in the pipeline for executive positions. By the time appointments are going to be made, the pool of both men and women should be large enough to choose from. In this way, women are appointed on the basis of fair competition instead of positive discrimination, and are equally compensated for their efforts. Since culture is moving slowly, the emphasis of stimulating women in acquiring top positions should be placed on getting a substantial portion of senior women in executive-director roles. These senior women can act as role models for women through the entire organization (Price, 2018). They can influence and change the ‘old-boys-network’-culture to retain women and to stimulate their ambition, even if these women have children or prefer more flexible work patterns. This
said, mandating gender quotas on corporate boards may not solve the culture problem, since non-executive women sitting on numerous boards will not be fully able to influence the culture of all these organizations to achieve equality.
Instead, equality and equal chances for women should be promoted in the steps towards cultural change in corporate life. In 1980, the Equal Treatment Act was introduced in the Netherlands, stating that all persons in the Netherlands should be treated equally in equal circumstances. Also in the western modern society, it is a generally accepted principle that people have equal opportunities in the pursuit of their goals. For this ideal of equality, the Dutch government stimulates women in acquiring top positions by promoting the visibility of highly educated top women by means of an instrument that can contribute to women achieving higher corporate levels, called the ‘Top-Women-Database’. This is an idea to boost the flow of women towards top positions, initiated by the Dutch minister of Education, Culture, and Science, J. Bussemaker at the end of 2014 (Topvrouwen, 2018). Highly qualified women with talent and ambition can sign up for this database to come into contact with companies looking for executive and non-executive directors. According to companies, the Dutch government should also encourage and support the careers of women through policies on work versus childcare and family policies.
Remuneration structures
Director compensation consists of a range of elements, which vary between executive and non-executive directors. For executive directors, total compensation consists of one part base pay and of one part variable pay. Base pay is independent of a director’s individual performance, but largely determined by the function one holds. In short: base salaries. The variable pay component of cash payments includes pay components as board fees, annual bonuses, and other annual payments. In addition, variable compensation can consist of long-term incentive arrangements such as share options, values realized from exercising stock options, and performance plans (Gregory-Smith et al., 2013). In the Netherlands, companies are predominantly having a two-tier governance structure, which means that management and supervision are separated into two governance bodies: the management board and the supervisory board. Non-executive directors in the Netherlands should assure independent supervision. Having a one-tier governance structure is permitted, only if supervision by non-executives is properly carried out and their independence can be assured (Dutch Code, 2016). The Dutch Code further specifies five best practice provisions which apply to companies with the one-tier board structure. However, guidelines found in the Dutch Code as well as in the codes of other European countries are not very specific on the determination of non-executive director compensation (Hahn & Lasfer, 2011). Yet, they do provide some restrictions on the non-executive director’s compensation structure. In several European countries, like the Netherlands and the U.K., the possibility to reward non-executive directors in the form of shares is already included in the corporate governance code. The Dutch Code (2016) for instance,includes a best practice provision that prescribes that the remuneration for non-executive directors should in
principle not be in the form of (rights to) shares or other instruments that are related to firm performance. Awarding remuneration in the form of share options is related to the results of the company. Therefore, linking long-term incentive arrangements to non-executives remuneration is inappropriate since it can have some restrictive effects on their independence. From this, we conclude that the compensation of non-executive directors in the Netherlands will essentially be in the form of fees or cash remunerations, reflecting the time spent and the responsibilities of the individual’s role (Gregory-Smith et al., 2013; Dutch Code, 2016).
1.2 Hypothesis Development
Our null hypothesis states that ‘the average compensation for Dutch directors does not vary with the fact of director’s having children’. However, prior research investigating the family gap in pay at the labor market level and low-to-middle management levels, shows clear evidence that after controlling for, inter alia, acquirements in human capital, wages for women with children are much lower than wages for women without children (Waldfogel, 1997; Waldfogel, 1998; Lundberg & Rose, 2000; Davies & Pierre, 2005; Baker, 2010; Waldfogel & Pal, 2014; Pal & Waldfogel, 2015). If directors are also penalized for the fact of having children, has not been studied yet. Since non-executive director compensations are determined on the basis of one’s responsibilities on the board and the time spent on their role (Gregory-Smith et al., 2013; Dutch Code, 2016), it can be expected that directors with children have accompanying parenting responsibilities and will spend less time and effort on their roles. Consequently, they will receive lower compensation levels. If the actual performance of directors with children is equal to the performance of directors without children, than non-executive directors will be penalized for the biased perceptions that having parenting responsibilities aside from their board responsibilities will simultaneously result in lower levels of spent efforts. This said, we expect the pay inequalities related to parenthood to exist among Dutch directors, and state that directors somehow get penalized for the parenting responsibilities coming with the fact of having children. Therefore, we propose the following hypothesis.
Hypothesis 1 Compensation for non-executive directors is lower when these directors have children
Highly educated and ambitious women in a gender equal country as the Netherlands do not necessarily have to choose between their professional career and their family roles, it can be a combination. Evidence states that women even experience this combination as a mutual enrichment instead of conflicting (Steenbergen & Ellemers, 2009). This being said, we should note the fact that behavioral science consistently reveals the differences between gender stereotypes – including the differences due to family commitments – resulting in biased expectations among society. A possible reason for the existence of gender inequalities related to career and corporate success is that companies tend to favor men over women (Ellemers, 2014). As there are laws established for equal rights for men and women,
this seems unlikely. However, despite the equality polices and equal opportunities policies incorporated in Dutch law, organizational decision makers may be biased in terms of director’s gender. Therefore, they may differ in the treatment of men versus women and consequently, performance expectations and performance appraisals when determining compensation may differ (Ellemers, 2014). This can result in negative consequences for the compensation levels of women directors with children. We expect that once qualified women have reached top positions, gender stereotypes present in society will unintentionally bias the performance evaluations of directors concerning men and women, leading to higher penalties related to parenthood for women directors in comparison with men directors. With respect to determining the influence of gender on the relationship from Hypothesis 1, we propose the following hypothesis.
Hypothesis 2 Women non-executive directors with children receive lower compensations compared to men non-executive directors with children and all non-executive directors without children
2. Data & Methods
2.1 The Dataset
The two main sources of data used in this study are the databases BoardEx and Thomson Reuters Worldscope. These databases provide extensive information on corporate boards, including data on directors’ compensations, and detailed financial statements information and market data. Since these two are combined for our dataset, a major advantage of our dataset is the variety of variables present to include in our model. Together with a group of peer-academics, we hand-collected additional data on the backgrounds of corporate directors. This involved collecting data on the directors’ educational backgrounds, marital status and whether they have children or not. The initial data sample in this study consists of 38 unique Dutch listed companies and the sample of directors covers 592 unique individuals. The period span the years 2000-2015 and the initial sample set consists of 2.522 director observations, of which 1.161 executive and 1.361 non-executive directors. The gender variable included in our dataset shows us that 182 of the 2.522 observations are women-director observations, which covers 7.2% of all observations in the total sample. Table I provides a summary of the data from the initial dataset, including the percentages of executives and non-executives that are women.
Notes. The sample above consists of a total of 38 unique companies listed on Euronext Amsterdam (AEX). The composition of companies in the sample for which data is available varies from year to year, with the least data being available for the year 2000. From that year on, the data available has increased and has remained fairly stable from the year 2009.
Looking at our dataset, there is an increase in the percentage of women non-executive directors as of 2009. Where the percentage of women non-executives in 2008 was only 6.8%, it increased to 11.5% a year later, and to even 23% in 2015. This significant increase can be a result of the incorporation of the best practices provision on the composition of the supervisory board in the amended Dutch Code (2009). Although the representation of women non-executive directors has improved over our sample period
Executives Non-executives All
2000 4 64 48 16 2.08 12.50 4.69 2001 12 110 74 36 1.35 11.11 4.55 2002 17 164 101 63 1.98 7.94 4.27 2003 18 171 101 70 0.99 7.14 3.51 2004 18 163 83 80 1.20 6.25 3.68 2005 20 198 101 97 1.98 6.19 4.04 2006 27 239 123 116 1.63 7.76 4.60 2007 28 236 119 117 3.36 7.69 5.51 2008 22 196 93 103 2.15 6.80 4.59 2009 14 139 52 87 1.92 11.49 7.91 2010 14 134 48 86 2.08 11.63 8.21 2011 15 136 46 90 2.17 11.11 8.09 2012 16 146 48 98 0.00 15.31 10.27 2013 16 146 45 101 2.22 19.80 14.38 2014 16 141 40 101 0.00 20.79 14.89 2015 16 139 39 100 2.56 23.00 17.27 Total N = 38 2522 1161 1361 1,81% 11,83% 7,22% Table I
Percentage of Women on Board of the Dutch companies in the sample
Year Firms (N) Total director
observations Executives Non-executives
(161 out of 1.361; 11.8%), this cannot be said for the representation of women executive directors. The percentage of women executive directors of our Dutch sample did not grow along with the overall trend. Only 21 of the 1.161 executive directors (1.8%) in the sample are women, and from only 8 of them is known that they have children (Appendix VI). Since the number of women executive directors is this small, regression results will lack statistical power and therefore, we are not able to derive conclusions from it. Consequently, our main sample only includes the 1.361 non-executive directors.
Hand-collected variables
We obtained additional data on the director level. We extended our dataset by searching for information on the individual director’s educational background (i.e. their profession), whether they have children or not, and their marital status, if available. We were able to search for this additional information using the individual’s unique Director ID and later match this with the existing director-level data from BoardEx1.
Occupational categories
Occupational gender segregation is present when ‘women and men are differently distributed across occupations than is consistent with their overall shares of employment’ (Watts, 2003). Jobs traditionally performed by women tend to be less well paid than jobs traditionally performed by men, even if these jobs are equally important. Since this occupational segregation can often be a determinant of the undervaluing of women in terms of compensation, it is an important factor to include in the analysis of the gender pay gap (Watts, 2003). However, this research focuses on pay differences on director levels and we expect the influence of occupational segregation on the pay gap to be limited for our sample. Instead, we are interested in the importance of occupational differences at the top, i.e. the vertical segregation in boards. We will control for job titles to the extent that some director roles are more likely to be occupied by men and some by women.
Our dataset covers a variety of individual roles among the top executives, enabling us to explore occupational segregation related issues. With this data present, we are able to construct occupational categories to control for occupational segregation matters. We will control for job titles to the extent that some executive roles are more likely to be occupied by men and some by women. Our sample includes a total of 71 different ‘individual role’-titles. Since some of these roles represent similar occupations, we broke these individual roles down into six occupational categories, based on the first individual role reported (Bertrand & Hallock, 2001). These categories being the role of CEO (Chairman), Vice Chairman, CFO, COO, other ‘Chief Officer’ positions, and the sixth category including other individual roles and all ‘regular’ board members. Our occupational breakdown is reported in Table II.
Notes. Column (1) shows the total number of both executive and non-executive directors per occupational category, columns (2) & (4) show them separately; columns (3) & (5) show the total number of women for both executives vs. non-executives. Column (6) reports the ratio of average total compensation per category relative to the average compensation of the full sample. Given that we continue with a main sample containing only non-executive directors, columns (4) & (5) are of major interest. *TAC = total annual compensation.
The most important fact to note here, is the under-representation of women in the top occupational levels. The percentage of women possessing specific roles at the top levels is scarce, covering less than 1%. Except for two single women vice presidents and a few women CFO’s, our data sample does not include any more women in specific individual roles other than just being a normal board member. Especially, it is interesting that none of the 481 CEO’s is a woman. Women who made it to the board, are less likely than men to be at the very top executive levels (Betrand & Hallock, 2001). Once again, this table also shows the poor representation of women executive directors. Next, we continue with our main non-executive sample.
2.2 Summary Statistics
Table III shows us the sample statistics important for the main purpose of this study. The total number of non-executive directors who have children covers 651 (47.83%) director observations, of which 100 are women (7.35% of the total non-executive sample). The total number of non-executive directors who are married covers 812 (59.66%), of which 138 are married women (10.14% of the total non-executive sample)2. Note that our hand-collected child variable is a dummy variable that equals ‘1’ if the individual director has at least one child, and ‘0’ when the individual director has no children, or when information on parenthood is not available or could not be found during our data collection. For the married variable this means that ‘1’ equals being married and ‘0’ equals not being married, or that information on marital status is not available or could not be found.
Table IV provides summary statistics for the main sample of non-executive directors. The way in which we constructed our variables is reported in Table B, Appendix II. From Table IV, we find that the age of non-executives varies from 37.5 to 71.5 years old, with the average age being 63 and an average board tenure of 4.26 years. The average board size is almost 12, and the board independence ratio is relatively high, being 59%.
2 For our additional variables, the numbers of F vs. M and Ex. vs. N-Ex. observations in the sample are displayed in Table E, Appendix VI.
(1) (2) (3) (4) (5) (6) 1 481 317 0 164 0 1,19 2 278 191 0 87 2 1,11 3 120 120 7 0 0 1,35 4 30 30 0 0 0 1,33 5 15 15 0 0 0 1,35 6 1.598 488 14 1.110 159 0,89 Total 2.522 1.161 21 1.361 161 Occupational category Nr. Executives in Occupation Non-exec. in Occupation F non-exec. in Occupation TAC* in Occupation F executives in Occupation
Individual Roles divided into Occupational Categories
Table II
Number in Occupation Vice Chairman/Vice President
CFO COO
Other 'Chief Officer' Positions Other/'Regular' Board Member CEO/Chairman/President
Notes. Numbers of yearly non-executive observations presented for the full sample, followed by the number of yearly observations for the hand-collected variables child & married dummy, separated for both the full non-executive sample and for women (F) non-non-executives. The numbers are then followed by % of women having a child or being married measured as a percentage of the total number of yearly non-executive observations.
Notes. *Compensation data is presented in natural logarithms. All the variables listed in the table are winsorized at the 1% and 99% tails.
Variable N Mean SD Minimum Median Maximum
Total Cash Annually 1361 4.2141 0.7105 1.6094 4.2407 8.1242
Non-executive years Age 1361 61.04 7.20 37.50 63 71.50 Board Tenure 1361 4.26 3.23 0 4 16 Qualifications 1361 1.97 1.11 0 2 5 Affiliations 1361 5.19 3.56 1 4 20 Time in Company 1361 4.17 3.49 .10 3.50 31.90 Board Size 1361 11.92 4.0340 2 12 25 Board Independence 1361 .5898 .1792 0 .6154 1 Assets*0.001 1361 197538 342289 61.3057 27255 1047062 Tobin's Q 1361 .5416 .5053 .0175 .4289 2.3012 Debt Ratio 1361 .6525 .2148 .1705 .6318 .9715 Operating ROA 1361 .0647 .0805 -.6179 .0725 .2963 Investment Intensity 1361 0.0433 0.0442 0.0000 0.0285 .2623 Firm years Table IV Summary Statistics
Panel B: Descriptive statistics: individual director charateristics
Panel C: Descriptive statistics: firm characteristics Panel A: Descriptive statistics: total compensation Director year observations*
Child Married 2000 16 10 0 16 2 0,00% 12,50% 2001 36 19 2 25 4 5,56% 11,11% 2002 63 23 2 36 5 3,17% 7,94% 2003 70 28 2 45 5 2,86% 7,14% 2004 80 30 2 48 5 2,50% 6,25% 2005 97 44 3 62 6 3,09% 6,19% 2006 116 52 5 69 8 4,31% 6,90% 2007 117 56 5 68 8 4,27% 6,84% 2008 103 55 5 61 7 4,85% 6,80% 2009 87 54 8 62 10 9,20% 11,49% 2010 86 50 8 57 10 9,30% 11,63% 2011 90 48 8 55 10 8,89% 11,11% 2012 98 47 10 55 12 10,20% 12,24% 2013 101 47 13 53 15 12,87% 14,85% 2014 101 43 13 49 15 12,87% 14,85% 2015 100 45 14 51 16 14,00% 16,00% Total 1.361 651 100 812 138 7,35% 10,14%
Yearly observations (N) of the main sample
Table III Year Non-executives having child F non-exec. having child Non-executives being married F non-exec. being married N % of female non-executives
2.3 Measures of Pay
In examining the pay gap, we can exert multiple measures of pay. The wider measure is the variable of total annual compensation, which is a combined measure of the total cash salary plus bonuses and the equity linked compensation, if available. Equity linked compensation consists of long-term incentives such as share options and performance share plans (Gregory-Smith et al., 2013). This long-term reward component of compensation comprises a large part of the total compensation for executive directors, and is especially relevant as total compensation measure for performing research on the executive director group. Since we excluded the executive-group from our main sample, we will use a different measure of total compensation in our regression model.
In the Netherlands, with the two-tier governance structure as being the main board structure, non-executives should assure independent supervision. Since the use of share options is perceived as a threat to the non-executives’ independence, and the Code prescribing that remuneration of the supervisory board should in principle not be in this equity linked form, the most appropriate measure of pay for our non-executive sample would be in the form of fees and/or cash remunerations. In addition, less than 5% of the observations in our main sample includes data on the equity linked compensation variable. Therefore, we restrict our regressions for non-executive directors to the smaller measure of total compensation, consisting of ‘total cash salary plus bonuses’. We labelled this smaller measure with the abbreviation TCA, which stands for ‘total cash annually’.
2.4 Regression Model
In investigating the possible determinants for the existence of difference in pay among non-executive directors, we control for factors that affect compensation such as experience, firm size, firm performance, time, industry, or profession. Before examining our hypotheses, we estimated a basic regression model, which is the following:
LN (PAYi) = β0 + β1CHILD + β2FEMALE i + β3 LN_AGE + β4 LN_AGE_SQ + β5 LN_TENURE + β6 LN_TIME_IN_COMPANY + β7 LN_QUALIF + β8LN_AFFIL + β9 BRD_INDP + β10LN_BOARD_SIZE + β11LN_TA + β12TOBINS_Q + β13OP_ROA + β14 LN_TL_TA + β15 CAPEX_TA + i.FF48 + i.SEG_IR + i.YEAR + εi
Where PAY is total cash annually per directori, including cash salary plus bonuses and excluding equity linked compensation. We regress this dependent variable against individual director characteristics of which we think will probably affect pay, including our primary variable of interest for directors with children (CHILD) and a dummy for the director’s gender (FEMALE). The child-dummy variable in our model, will reflect the influence of having a child on director compensation, and takes the value of ‘1’ if the individual director has at least one child, and ‘0’ when the individual director has no children, or when information on parenthood is not available or could not be found during our data collection. The female variable in our model, will reflect the influence of gender on director compensation, and takes
the value of ‘1’ when the director is a woman and ‘0’ for a man. The explanatory variables arefurther supplemented with a set of firm-level variables. The error term isdenoted by εi. For the second analysis, we include the interaction term ‘FEMALE x CHILD’ and the BACKGROUND dummy into our main model. To ensure our results are not influenced by a small number of influential observations, i.e. the outliers, we winsorized our continuous variables at the top and bottom 1-percentiles. Consequently, there are no outliers in our research influencing our results. For most variables, including the dependent variable of pay, we take the logarithm value since this reduces the impact of outliers as well and it results in a distribution of the data closer to the normal distribution – an important requisite for empirical testing. In addition, economic theories and empirical research suggest that the logarithm of total compensation is more appropriate in regression analysis than the monetary value of pay (Heckman & Polachek, 1974).
Individual characteristics
Apart from gender, we included additional data on individual director characteristics. These individual characteristics are the explanatory variables that might explain parts of the pay inequality. In his research on understanding the pay gap and the limitations of human capital models, Lips (2012) stated that some part of the gap is not due to discrimination, but can be explained by the differences in investments of employment/human capital. This is consistent with statements of Drolet (2001) and Cassells et al. (2009) from our theory section. Therefore, we use the main quantities from the human capital theory as control variables, i.e. age, board tenure, time in company, number of qualifications and outside affiliations. These are our proxies for experience.
Directors are compensated with a mix of multiple performance measures, including large returns on their board experience. Where top executives are very similar with respect to their job commitment, women differ significantly in terms of age and their seniority within the firm (Betrand & Hallock, 2001). We use individual data on age, in the form of the logarithm of age (LN_AGE) and the age-squared (LN_AGE_SQ), on tenure, in the form of the logarithm of the time on board variable (LN_TENURE), and on director’s time in the company (LN_TIME_IN_COMPANY). The slightly lower age and seniority of women could be expected as important determinants of pay inequality among directors. In appendix V, we report summary statistics divided for the child variable and for the director’s gender. On average, the women in our sample, which amount to 161 women versus 1.200 men, are about 5.4 years younger than men (56.4 versus 61.8 years old) and are sitting on the board of their company for a shorter period of time (3.6 versus 4.4 years). In addition, when performing t-tests on the differences between non-executives who have a child and who have none, we note that the 651 directors with children are on average sitting on larger boards in relation to the 710 directors without children or of which information on parenthood was not available, with mean board sizes equal to 13.3 versus 10.6, respectively. Also, directors with children are board members in larger sized firms, with mean total assets covering $296mln versus mean total assets of $103mln for directors without children. Since all
these differences are statistically significant, we will account for these observable differences in director and firm characteristics in our regression model.
Firm characteristics
Given the richness of our dataset, we are able to add multiple measures to control for firm characteristics. We include several measures reflecting firm characteristics. To control for firm size, we used the logarithm of the firm’s total assets * 0.001 (LN_TA). Other firm variables are internal measures of the firm’s financial performance. We included Tobin’s Q (TOBINS_Q), operating ROA (OP_ROA), debt ratio (LN_TL_TA), and the company’s investment intensity (CAPEX_TA). Also, we included board size (LN_BOARD_SIZE) and a measure for the board independence (BRD_INDP). All the firm variables are winsorized at the 1% and 99% levels.
Industrial segregation
The effect of segmentation of industries is important to consider when doing research on pay inequalities. Studies show that the industrial segregation has a widening effect on the gender pay gap (Miller, 1994; Drolet, 2001; Grimshaw & Rubery, 2002; Daly et al., 2006; Cassells et al., 2009). Therefore, we use the forty-eight industries as defined by Fama & French (1997) to control for industry-level differences in pay (FF48).
Dummy variables
Finally, besides the industry and background dummies, we included dummy variables to control for possible differences in pay related to time (YEAR), to capture the overall growth in director compensations during the years of our sample period. In addition, as stated in section 2.1, we included a set of occupational dummies (SEG_IR), to control for the possibility that women are systematically holding lower executive job titles compared to men, or that some executive functions are more likely to be occupied by men and some by women (Hutchinson et al., 2017). By categorizing each of the individual directors based on their individual roles into one of the six occupational categories, and subsequently adding these six labels in our dataset, we were able to create this dummy variable.
3. Results
3.1 Univariate Tests
Tables D.I and D.II in Appendix V provide univariate comparisons of the mean differences in our non-executive sample between directors with and without children, and between men and women directors, respectively. The means for total compensation, as measured by TCA, are $84.460 for directors with children and $58.890 for directors without children. This difference in means shows a statistically significant relationship at the .01 level. The mean for directors without children is much lower, which is interesting since we expected directors without children to receive higher compensation. We expect this difference will be explained by our compiled list of explanatory variables after we include them into our main regression model, and therefore we stay with our hypotheses. The other director-level variables listed show that directors with children, on average, are older, have longer board tenure and a longer time-in-company. All these differences in means are statistically significant. As stated in the method section, with respect to the firm characteristics, we noted that directors with children are sitting on larger boards within larger firms. These both differences are statistically significant.
The means for total cash annually are $74.270 for women directors compared to $82.570 for men directors, indicating that women directors receive much less than men directors. However, these difference between gender are not statistically significant. Though, on average, women directors are younger, have shorter board tenure and shorter time-in-company, and fewer current outside affiliations. All these differences in means are statistically significant for our non-executives sample. Also notable is the slightly higher number of qualifications for women compared to men. This difference is statistically significant for our non-executive sample (-0.3540; P < 0.01). Focusing on the firm characteristics, we note that, on average, women are sitting on boards of larger firms, measured by the firm’s total assets. In addition, women are sitting on larger boards with higher independence ratios. Except for our variable investment intensity, all the comparisons between men and women at firm level are statistically significant.
3.2 Main Regression Results
In our examination of pay inequalities in relation to parenthood, we take into account a wide range of variables. First, by making use of our hand-collected child variable, we utilize the OLS regression model for investigating the effect on executive pay coming from parenthood. Afterwards, we perform additional analyses by including the interacting term ‘Child x Female’ into the model. Table V presents the main regression results of our non-executive sample, with log values of total cash compensation (TCA) as the dependent variable.
Men directors in our sample, inter alia, are older, have more experience in their companies and within their boards, and are occupied among higher executive titles. Therefore, we include the gender variable and the other individual characteristics into our regression analysis. After controlling for
individual director and firm-level characteristics, regression results in Table V, model (2), indicate that there is a penalty in pay related to parenthood. Subsequently controlling for year, industry, and occupation strengths our findings given this penalty. Our reported findings in model (3) show that executive directors with children receive on average 18 percent less compensation compared to the non-executives without children (-0.180; P < 0.01). The relation between non-executive director compensation measured in total annual cash compensation and parenthood is negative and statistically significant for models (2) and (3). Next, after controlling for the director’s background by including this background dummy into our full model (4), the penalty in pay related to parenthood is equal to 14.2% and is statistically significant at the .1 level. From model (1) to (4), we note that the R-squared is increasing, indicating that the explanatory variables included in our full model explain a large proportion of the variance in total compensation, namely 78.3% at large.
Since our hand-collected child-variable is a binary variable which equals ‘1’ if the individual director has children, and ‘0’ when the individual director has no children or when information on parenthood was not available during, there is a moderate chance that our sample groups considerably differ from reality, which can significantly influence our regression results. Therefore, we must be cautious in deriving conclusions from it.
Notes. Definitions of the variables are provided in Appendix II. ***, ** and * indicate statistical significance at the 0.01, 0.05 and 0.1 level, respectively. The P-values for our main variable of interest ‘Child’ and for our ‘Female’ variable are presented in the parentheses. We clustered our standard errors at firm-level.
(1) (2) (3) (4) 0.320 -0.081 -0.180 -0.142 (0.800) (0.032)** (0.002)*** (0.066)* -0.166 -0.056 -0.042 (0.002)*** (0.142) (0.499) Age -7.534* 3.613 5.918 Age Squared 0.916 -0.464 -.772 Board Tenure 0.239 0.367*** 0.297** Time in Company -1.094 -0.236* -0.162 Qualifications 0.009 0.028 0.149*** Affiliations -0.057** 0.019 0.030 Board Size -0.613*** -0.338*** -0.389*** Board Independence 0.941*** 0.132 0.076 Firm Size 0.207*** 0.155*** 0.142*** Tobins Q 0.019 0.008 -0.032 Operating ROA 1.578*** 0.215 0.124 Debt Ratio -0.611*** -0.356*** -0.639*** Investment Intensity 2.777*** 0.553 0.193 YEAR dummies No No Yes Yes INDUSTRY dummies No No Yes Yes OCCUPATIONAL dummies No No Yes Yes
BACKGROUND dummies No No No Yes CONSTANT 4.059 18.701 -3.479 -7.544 P-value (0.000) (0.042) (0.590) (0.350)
N (obs.) 1.361 1.069 989 564
R² 0.0510 0.4501 0.756 0.783
Additional variables
Main Regression Results for Parenthood - Non-Executive directors
Total Cash Annually (TCA)
Table V
Individual-level controls
Female
Firm-level controls
3.3 Additional Analyses
For our next analyses, we created an interaction term of ‘Child’ with the gender variable to test for our Hypothesis 2. In performing the regressions, we included this ‘Female x Child’ interaction variable into our main model. As previously established, the number of non-executive directors in our sample that are women equals 161 out of 1.361, almost 12%, and the number of women non-executive directors having children equals 100 out of 1.361, almost 7.5%. Table VI reports the results of our second regression. In model (3) we include the large set of individual and firm-level controls and in model (4) also the dummy variable on the director’s background is included. In line with our second hypothesis, the results show that the relation between women non-executive directors who have children and their pay levels is negative and statistically significant (-0.147; P < 0.05). Meaning that on average, the compensations of women non-executives with children is lower compared to men non-executives with children and non-executives without children. Again, R-squared increases as we fill in our full model, indicating that the variables included in model (4) explain 78.4% of the variance in total compensation. From the other variables, it is found that firm size shows a positive and highly significant effect on pay throughout all our models. It is stated that compensation rises as firm size rises, a relation also found by Muñoz-Bullón (2010). This is consistent with an earlier statement by Kostiuk (1990), who found that in larger firms, higher paid directors are employed. Also noteworthy are the negative relations for the effect of board size on compensation. For both our main results and our additional regressions, board size is negative and statistically significant related with pay, indicating that non-executive directors who are sitting on larger boards, receive lower levels of compensation.
Marital status regressions
Since we have the data at hand, it may be interesting to examine if marital status is also related to the penalty in pay. By replacing the child dummy with the married dummy, regression analyses show us the same results. The full model results reported in model (3), Table VII, show a negative and statistical significant relation between the married dummy and total compensation (-0.389; P < 0.01). By creating the ‘Female x Married’ interaction term and adding the variable to our model, subsequent regression results indicate a negative and statistically significant relation between married women non-executive directors and their compensation levels (-0.221; P < 0.10). Also for these additional results, we should note that our hand-collected married-variable is a binary variable which equals ‘1’ if the individual director is married, and ‘0’ when the individual director is not married, or when information on marital status is not available or could not be found during data collection. Cases of ‘ever been married’ are not taken into account in this study, and since some directors were untraceable, there might be a chance that our sample groups significantly differ from reality. This could influence our regression results, meaning that we have to be cautious in deriving conclusions from it.
Notes. Definitions of the variables are provided in Appendix II. ***, **, and * indicate statistical significance at the 0.01, 0.05, and 0.1 levels, respectively. The p-values for our variables of interest – Child and Female, and our main variable of interest: the interaction term Female x Child – are presented in the parentheses. We clustered our standard errors at firm-level.
. (1) (2) (3) (4) 0.326 0.294 -0.170 0101 (0.185) (0.084)* (0.257) (0.326) 0.099 0.055 -0.023 0.029 (0.287) (0.352) (0.536) (0.614) -0.080 -0.105 -0.058 -0.147 (0.504) (0.144) (0.320) (0.019)** Age 8.715*** 3.626 6.260 Age Squared -1.100*** -0.466 0.817 Board Tenure -0.202* 0.366 0.290 Time in Company 0.360*** -0.235 0.158 Qualifications 0.048* 0.028 0.145** Affiliations 0.078*** 0.020 0.030 Board Size -0.341** -0.394** Board Independence 0.129 0.069 Firm Size 0.155*** 0.141*** Tobins Q 0.207 -0.038 Operating ROA 0.001 0.109 Debt Ratio -0.364 0.667*** Investment Intensity 0.548 0.164
YEAR dummies No Yes Yes Yes INDUSTRY dummies No Yes Yes Yes OCCUPATIONAL dummies No Yes Yes Yes
BACKGROUND dummies No No No Yes CONSTANT 4.051 -13.833 -3.494 8.094 P-value (0.000) (0.019) (0.668) (3.46) N (obs.) 1.361 1.227 989 564 R² 0.0518 0.7002 0.7563 0.7842 Firm-level controls Additional variables Female
Table VI
Regression results for Motherhood - Non-Executive directors
Total Cash Annually (TCA)
Child
Female x Child
Notes Definitions of the variables are provided in Appendix II. ***, **, and * indicate statistical significance at the 0.01, 0.05, and 0.1 levels, respectively. The p-values for our variables of interest – Child, Married and the interaction term Female x Married – are presented in the parentheses. We clustered our standard errors at firm-level. (1) (2) (3) (4) 0.273 -0.234 -0.389 0.350 (0.000)*** (0.000)*** (0.005)*** (0.010)*** -0.118 -0.025 0.156 (0.028)** (0.633) (0.212) -0.221 (0.066)* Age -9.482** 6.126 6.416 Age Squared 1.172** -0.785 -0.825 Board Tenure 0.283 0.311 0.316 Time in Company 0.125 -0.166 -0.165 Qualifications 0.016 0.153** -0.158** Affiliations -0.064** 0.037 0.027 Board Size -0.501*** -0.302** -0.305** Board Independence 0.811*** 0.071 0.043 Firm Size 0.230*** 0.178*** 0.178*** Tobins Q 0.054 0.025 0.014 Operating ROA 1.770*** 0.262 0.233 Debt Ratio -0.649*** -0.551*** -0.563*** Investment Intensity 3.514*** -0.116 -0.126
YEAR dummies No No Yes Yes
INDUSTRY dummies No No Yes Yes
OCCUPATIONAL dummies No No Yes Yes
BACKGROUND dummies No No Yes Yes
CONSTANT 4.049 22.078 -8.496 -9.001 P-value (0.000) (0.015) (0.336) (0.312) N (obs.) 1.361 989 564 564 R² 0.0342 0.4638 0.7875 0.7887 Firm-level controls Additional variables Female x Married
Table VII
Additional Regression Results for Marital Status - Non-Executive directors
Total Cash Annually (TCA)
Married
Female
4. Discussion & Conclusions
4.1 Summary of Findings
To our knowledge, no study has ever researched pay inequalities in director compensations in relation to individual director characteristics associated with parenthood before. This study contributes to existing research in the field of the family gap in pay by examining director compensation, using a large sample of non-executive directors sitting on boards of Dutch listed companies for the years 2000-2015. The outcomes of our research validate our expectations of the existence of pay differences among directors throughout the Netherlands. After controlling for director’s individual characteristics and firm characteristics, including dummies for year, industry, occupation, and background, we find that directors with children earn substantially less compensation compared to directors without children. This corresponds to our Hypothesis 1. Hypothesis 2 states that women non-executive directors with children will be less compensated than men non-executive directors with children and those directors without children. In subsequent analyses, we find that when non-executive directors with children are women, again, they earn substantially less compensation compared to men and non-executives without children, supporting our second hypothesis.
Our findings are consistent with prior research of Waldfogel (1997), Davies & Pierre (2005), and Waldfogel & Pal (2014). We extend the literature by investigating the penalty for parenthood among executive levels and by adding new hand-collected director-level data to our model. Our research reveals that there is a significant difference in non-executive pay between directors who have children and directors who have none, and this ‘penalty-in-pay’ related to parenthood is even larger when these non-executives are women. For a highly gender equal country as the Netherlands, in which equality policies have long been enacted, the education gap between men and women has disappeared, and with its high rates of women participating in paid employment, this finding is interesting.
By stating that the compensation of non-executive directors in the Netherlands is to a large extent determined by the time spent and the responsibilities of the individual’s role, the family gap in executive compensation could be due to the fact that directors with children have to deal with parenting responsibilities, and are therefore likely to spend less time and taking fewer responsibilities within their boards, resulting in lower compensations. However, if performance of directors with children is equal to the performance of directors without children, non-executive directors are penalized for having parenting responsibilities aside from their board responsibilities. Altogether, since the informativeness of our parenthood data is limited, we have to be cautious in interpreting our findings. Quantitative research or research including data on the yearly time spent and the responsibilities related to the director’s individual role, will enable us to control for these determinants of non-executive director compensation levels, and could therefore provide us with more informative insights and explanations related to the established penalty in pay for parenthood among directors.
4.2 Limitations and Future Research
This study has some shortcomings. One is the limited information that can be extracted from our hand-collected variables. Our variable for parenthood is a binary variable equal to 1 when the individual director has at least one child and equal to 0 when the director has no children or when this data was not available. We should note that there is a moderate chance that more directors from our sample have children, but for which the data was untraceable during data collection. This can significantly influence our regression results. Therefore, we must be cautious in interpreting our findings. Since our additional data does not cover the number and age of the director’s children, further research that includes more comprehensive information on parenthood should be performed in order to achieve more evident results to derive conclusions from.
Next, while working with the data, we determined a limited representation of women executive directors. Women in our executive sample represent 1.8%. This is such a small number, that the following results will lack statistical power and we are not able to derive conclusions from it. Therefore, we excluded the executive directors from this study. Future research including larger numbers of women directors can produce more enhancing evidence. These studies can make use of larger samples, concerning several countries. Since this study examines the issue in the particular context of non-executives sitting on Dutch boards, findings are not generalizable for broader director groups. For cases as Norway, with mandatory quotas requiring a minimum percentage of each gender on boards, women directors are better represented and therefore, evidence on the pay gap can be more telling. Also, due to the increasing attention paid to gender diversity in corporate boards, more data on director’s individual characteristics will be publicly available. This enables future studies to perform a deepening on the influences of parenthood in relation to director pay. Evidence on the determinants of director pay can be enhanced by including more – and more specific – background data. For example, the number of children, their age, the director’s marital status, and employment of the director’s partner. With respect to marital status, some studies have linked the fact of being married to a larger penalty for parenthood (Budig & England, 2001; Budig & Hodges, 2010). Other studies found the family gap in pay decreases over time for married women with children (Glauber, 2007; Pal & Waldfogel, 2014). The extent of the gap possibly differs with these factors, which makes it an interesting area for further research.
A final limitation is the method we used, which can be argued to fall short. Some studies are using complementing methods as fixed-effects-models or the Oaxaca-Blinder decomposition method. This sophisticated method follows a threefold decomposition and unriddles the pay gap into the effects of differences in returns to individual characteristics (Muñoz-Bullón, 2010). However, Oaxaca-Blinder results on the existence of the unexplained part of pay gap should be interpreted carefully. The remaining unexplained part of the gap is not per se due to discrimination, but can be due to variables that are unobservable or not included. Reflecting on our estimated model, we control for a large set of factors related to human capital and other individual-level and firm-level characteristics, which provides us with a high R-squared for the full model. Therefore, we can conclude that our model fits the data well.
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