From Symbolism to Integration: New Evidence on
Female Directors and Firm Performance
Colin P. Green
Lancaster University
Swarnodeep Homroy*
Lancaster University
June 15, 2015
Abstract
There is an increasing focus on enhancing female represenation on corporate
boards. Existing evidence …nds little e¤ect of board gender diversity on …rm performance. We return to this issue using Europe-wide data on listed …rms, where
the key advantage is a wider variation in levels of female representation not only
on boards, but also on key governance committees. There is a positive impact of
gender diversity on corporate boards on …rm performance. This positive association
is particularly strong for …rms with higher female representation on key committees.
Our results suggest that performance-enhancing e¤ect of integrating the female representation on boards, over and above the symbolic tokenism.
Key Words: G30, G34, J16
JEL Codes: Board of Directors, Female Director, Diversity, Performance
*Corresponding Author: [email protected]
1
1
1. Introduction
Women are underrepresented on corporate boards. For example, while women make up
over 40% of the workforce in the UK, US and EU, membership on corporate boards ranges
from 8% to 14.8% across these jurisdictions (Equal Opportunity for Women in the Workplace agency, 2010). Moreover, while female workforce participation and employment has
grown markedly, there has been only a sluggish change in female representation on boards.
This ongoing under-representation of women on boards, relative to their male counterparts, calls into question the e¢ ciency and equity of the board recruitment process. The
lack of gender diversity in boardrooms can have domino e¤ect on the gender-diversity
in the workforce. Board gender diversity is a salient issue for …rms and policy makers.
Apart from the obvious economic ine¢ ciencies associated with labour market discrimination (Becker, 1957), it is now perceived as an important criterion for institutional
investment and listings by such socially responsible indices as the FTSE4Good or Domini
400. Publicly listed …rms in some European countries are mandated to have at least
40% representation of women on the board. The European Union is examining the possibility and implications of similar legislations. The next wave of governance regulations
in the EU member states is likely to address the issue of mandated gender diversity in
boardrooms for all listed …rms by the year 2020 (European Union, 2012).
It is unclear if female representation on boards enhance corporate governance outcomes
and …rm performance.(Ahern and Dittmar, 2012; Strovik and Tiegen, 2010; Nielsen and
Huse, 2010). Apart from the standpoints of equity and moral justice the rationale of female representation of corporate boards is not well understood. Sharder et al (1997) …nd
no signi…cant association between board gender diversity and …rm performance. A recent
study on US …rms …nds a negative impact of gender diversity on …rm performance, despite
better attendance records and more e¤ective monitoring in …rms with more gender equi-
2
table boards (Adams and Ferreira, 2009). Gregory-Smith et al. (2014) …nd no evidence
in favour of the argument that board gender diversity enhances …rm performance. While
the economic implications of board gender diversity are ambiguous, decisions to increase
female representation on boards may be the result of social and political pressures. The
meagre evidence on the impact on …rm performance of gender-diverse boards are based on
samples of …rms with ’token’female representation of either a single individual or a couple
of individual directors on the board. Not surprisingly, these papers report no signi…cant
impact of such diversity on …rm performance (O’Reilly and Main, 2012).
This paper is di¤erent in estimating the economic impact of the diversity on corporate
boards, over and the above the symbolic tokenism. We do this in two ways. First we
employ a sample of large European …rms with a wider variation in the female representation on corporate boards. Second, in addition to the traditional measure of board gender
diversity, i.e., the fraction of female directors, we use the fraction of female directors on
key governance committees. This allows us to examine the impact of female directors on
…rm performance, when they are in a position to do so.
The central …nding of this paper is that female representation on corporate boards
enhances …rm performance. This association is of a higher order of magnitude where
there is a high proportion of women appointed on key corporate governance committees.
The results add to the literature by providing evidence that higher degree of integration of female directors through committee appointments is value-enhancing. Our results
provides evidence of impact on …rm performance of female representation on …rm performance, over and above the token-representation. The impact of female directors, if any, is
more likely to be manifest in enhanced …rm performance when female directors are placed
in key decision-making committees. This paper also reconciles the existing evidence by
comparing the results for UK and non-UK European …rms.
3
The article is structured as follows: Section 2 reviews the literature on the gender
composition of corporate boards, Section 3 introduces the sample and the estimation
methods employed for the analysis; Section 4 presents the results and Section 5 concludes.
2
2. Gender Diversity on Corporate Boards
Arguments in favour of increased representation of women on corporate boards traditionally stem from concerns of equity and moral justice. However, a more gender diverse board
may also lead to productivity gains through improved decision making, displacement of
less able male directors and more e¢ cient monitoring (see Hermalin and Weisbach, 2003;
Adams et al. 2007). The productivity gain can be manifest in the form of better attendance of directors on the board, performance sensitive CEO pay and CEO turnover
and generally better corporate governance (Adams and Ferreira, 2009). In addition to
the case for more female representation on corporate boards from an equity standpoint,
it is therefore important to understand if increased female representation also leads to
productivity gains.
The apparent incongruence of the female representation on boards and female representation in the labour force can be due to supply side factors, discrimination, or a
combination of both. Powell and Butter…eld (1994) argue that discriminatory practices
hinder the career progression of women to corporate boards. In contrast Mincer and
Polachek (1974) propose that family formation decisions result in a restricted supply of
quali…ed female candidates for board positions. Farrell and Hersch (2005) examine the
appointment of new directors on boards and …nds that the proportion of female appointments on boards is signi…cantly higher if the immediate predeccessor was a female director.
This highlights that the board appointment processes may not be gender neutral. Hence,
4
the small proportion of female directors persists over a period of time.
If lack of gender-neautrality in female board appointments is discriminatory in nature, then …rms engaging in such practices are likely to face a competitive disadvantage.
Empirical evidence suggests that board composition has no signi…cant e¤ect on …rm performance and that the average e¤ect of board gender diversity on …rm performance can
be negative (Larcker, et al. 2007; Adams and Ferreira, 2009; Ahern and Dittmar, 2012;
Gregory-Smith et al. 2014). However, these results are either based on boards with only
one female director or following an enforcement of mandatory female representation. Thus
these papers may capture the nature of tokenism in female board representation rather
than the causal link of the impact of female representation on …rm performance.
This analysis is based on a sample of …rms with much wider dispersion of female
representation on boards. In this way, we are able to better examine the impact of female
directors on …rm performance. Using data on committee assignments and the network
size of directors, we are also able to examine a possible transmission mechanism for the
impact of female board representation on …rm performance.
3
3.1
3. Data
3.1 Data Source
The primary database used in the analysis is BoardEx, which provides information on
board composition and director networks for listed European …rms. We use a sample of
EuroTop 100 …rms for the period 2006-2013. EuroTop 100 are large …rms listed in any of
stock exchanges of the European Union. Firms that appear at least once in the EuroTop
100 are followed till the end of the sample period as long as they remain listed. We use
5
information on individual directors on the boards of these …rms. We drop observations on
individual directors whom we observe in only one period in a given …rm. We augment this
database with a range of …nancial performance metrics using Datastream/Worldscope.
Firms where …nancial performance metrics were unavailable were excluded. The …nal
sample consists of an unbalanced panel of 118 …rms with 16,647 director-year observations.
We note the directors’ gender and role classi…cations from BoardEx. Table 1 presents
descriptive statistics for selected …rm, board and individual director characteristics. Table
2 summarizes key variable for …rms with at least one female director and …rms with
no female directors. All monetary variables are converted to year 2003 dollars using
Harmonized Indices of Consumer Prices published by the European Central Bank.
About 35% of our sample …rms are from the UK. Therefore, it is only natural to
di¤erentiate between the sub-sample of UK-…rms, and the sub-sample of non-UK …rms.
This is particularly important to position our …ndings with respect to the evidence from
UK …rms. In the following sub-sections, we present details about how the two sub-samples
of …rms compare with each other. On average, UK …rms are comparable in size to other
European …rms, with lower pro…tability and lower volatility of stock prices.
3.2
3.2.1
3.2 Key Variables and Summary Statistics
Female Representation on Corporate Boards
The standard measures of board gender diversity are a binary indicator for at least one
female director, and the fraction of female directors. We use three measures of female
representation: AnyFemale, %FemaleDirectors, and %FemaleonCommittees. AnyFemale
is a binary indicator of the presence of at least one female board members in a given
…rm-year. This captures the e¤ect of having at least one female director on the board.
6
To examine the impact of increasing female representation on …rm performance, we use
%FemaleDirectors, which is the ratio of number of female directors to the total number
of directors expressed as a percentage. Finally, to understand if female directors on key
committees have di¤erential impact, we use %Female On Committees i.e. the ratio of the
combined number of female directors on three key committees (Audit, Nomination and
Remuneration) to the combined number of directors across these committees, expressed
as a percentage. This is an important variable for our empirical strategy: this measures
the extent to which female directors are integrated in the governance mechanisms of the
…rm. There has been a steady, albeit incremental, increase in the gender diversity on
European boards over the last decade. We present this in Figures 1&2 for our sample
period. It seems that the fraction of …rms with at least 20% female representation on the
board has increased over the sample period, but female representation on key governance
committees have been very stable throughout. This can possibly explain the empirical
evidences of no signi…cant relationship between female directors and …rm performance.
The time-covention of the measure of female representation is not immediately apparent. Some studies use contemporaneous female representation (Adams and Ferreira,
2009), whereas some other uses lagged measures (Gregory-Smith, et al. 2014). All measures of female representation used in this paper is lagged by one period.1 We control
for a range of board characteristics, viz. board size2 , board independence (percentage of
independent directors on the board),3 and an indicator for a female CEO.
It is critical to understand the comparability of the measures of board gender diversity
for the two sub-groups. In Figures 3 and 4, we present the comparison of the proportion
1
We check the robustness of our sample using contemporaneous measures of gender diversity. The
results are very similar to the baseline estimates and are available on request.
2
In the case of two-tier boards, board size is the linear summation of the number of directors on both
the management and the supervisory board.
3
The de…nition of an independent director varies marginally across countries. However, the basic
remains that for a director to be considered independent, she will not be a current (or a former) employee,
a relative of a current executive, or has business relations with the …rm.
7
of female on the board and the proportion of females on committees, for the UK and
non-UK …rms. A larger proportion of UK …rms have at least 10% and 50% female directors compared to non-UK …rms. However, a larger fraction of non-UK …rms have more
than 20%, and more than 50% female representation on governance committees. This
highlights a possible di¤erence in the extent to which female directors are integrated in
the governance mechanisms.
3.2.2
Firm Characteristics
The association between board gender diversity and performance often varies with the
choice of …rm performance measure (Erhardt, et al. 2003; Smith et al. 2006). The
primary measure of …rm performance for this analysis is Return on Assets (ROA). To test
for the robustness of the results, we also use other measures of performance: Tobin’s Q
approximated by market-to-book value ratio (MTBV) and Returns on Equity (ROE). We
control for the risk in a …rm’s information and operation environment by the standard
deviation of monthly stock returns over the previous 12 month period. Natural logarithm
of annual sales is used as a proxy for …rm size.
3.2.3
Director Characteristics
Annual compensation of directors in our sample comprises of an annual retainer fee,
fees for attending board meetings and some equity compensation. The compensation
schedule is similar for all the directors. A priori, it is not clear if nominal pay di¤erences
may impact upon the association between female representation and …rm performance.
Therefore we d not use the pay information in our empirical models. Summary statistics
are presented in Tables 1 and 2. The selection of individual directors on committees and
their impact on …rm performance may be driven by the skills and experience. We include
8
the age of the directors, the time in current role and the time on the board to mitigate
the unobserved heterogeneity in director ability.
4
4. Empirical Methods
The central question is whether female participation is associated …rm performance. To
do that we estimate the following
F irmP erf ormance = F emaleDirectorsonBoard + Z
where
(1)
captures the e¤ect of female directors on …rm performance and Z is a vector
of all …rm and director characteristics. The primary measure of …rm performance used for
this analysis is Return on Assets (ROA) and the primary measure of female participation
in boards is the % of female on the board in a given …rm-year. We test for the robustness
of our results using alternative measures of …rm performance and female representation.
Next we aim to understand the transmission mechanism of female director representation on …rm performance. We analyse the probability of individual female directors’
appointment on key governance committees- viz. audit, nomination and remuneration.
We examine how the network of female directors impacts upon their appointment in these
committees and through these appointments on …rm performance. We estimate the following probit model to estimate the likelihood of female directors being appointed on
committees:
CommitteeAppointment = F emale + Z
9
(2)
The dependent variable is a binary indicator of a female director being appointed
on one of the three committees in a given …rm-year.
is the linear probability of an
individual female director being appointed on committees and Z is a vector of all …rm
and director characteristics.
Adams and Ferreira (2009) argue that the positive association of …rm performance and
female representation on boards may be driven by potential endogeneity in female appointments. Endogeneity concerns arise from omitted unobservable characteristics which may
simultaneously a¤ect …rm performance and the appointment of female directors. We address this concern by employing a range of econometric techniques. We use …rm …xed
e¤ects to control for any time-invariant omitted variables. It may be argued that the
direction of causality is actually reverse: more successful …rms hire more female directors.
Although it is not immediately apparent why that might be true, we address potential
reverse-causality concerns using instrumental variables. We use the network size4 of the
female directors and the square of the network size as instruments. Whilst the network
size may be expected to drive female appointment on boards, it is unlikely to independently impact upon …rm performance, except through the control variables included in
the regression.
Further, the …rm performance indicators are likely to be serially correlated. Therefore
we estimate the above speci…cations with lagged dependent variables using GMM. All
indicators of female representation on boards and …rm level characteristics are also lagged
by one period. This is control for potentially endogenous choices made by the board in
view of expected performance.
4
BoardEx reports the network size of individual directors which is equal to the number of other
directors a given individual is "related" to. A relation between two individuals is established if one or
more of the following is true:
They have graduated in the same class
They have worked in the same …rm together
They sit on the same boards at the same time
They share familial relationship.
10
5
5. Results and Analysis
5.1
5.1 Female Directors and Firm Performance
In Table 3, we present the results of female representation on corporate boards and its
e¤ect on …rm performance. In column (1) we estimate the e¤ect of proportion of female
directors on boards, lagged by one period, on …rm performance (ROA). We progressively
add …rm-level and board-level characteristics in columns (2) and (3), and …nally country
and year …xed e¤ects in column (4). In all the speci…cations, proportion of female directors
on board is positively associated with …rm performance. This suggests that having more
female on corporate boards may be value-enhancing. However, this association may be
endogenous; better performing …rms may appoint more female directors.
To address the concern that the positive correlation between female directors and …rm
performance might be endogenous, in Table 4 we present the headline results of female
board representation and …rm performance using a range of econometric techniques. In
all the speci…cations, the dependent variable is ROA. In speci…cations (1) and (2) we
present the OLS and …xed e¤ects estimates respectively. There is a positive and significant association between %Female directors and …rm performance. If endogeneity were
driving these results, we would expect to see di¤erent results in speci…cations (3) and
(4) where we present the results of IV and GMM estimates. The positive association
of …rm performance and female representation on boards persists even when we correct
for endogeneity. In speci…cation (4), this association is large but not statistically signi…cant. Therefore it does not seem that our central result is driven solely by endogenously
determined female representation on boards and …rm performance.
To test the robustness of the results we use three di¤erent measures of female representation. In Table 5, we present the results of these regressions with ROA as the dependent
11
variable. The measures of female representation in boards used in the three speci…cations
are % female directors on board, at least one female director in a given …rm-year and
% female directors on committees, respectively. All measures of board gender diversity
are positively associated with …rm performance. However, the positive e¤ect of a larger
proportion of female directors on key committees is an order of magnitude higher than
that of the baseline speci…cation. It seems that having female directors more integrated
in the functioning of the boards generates value over and above symbolic tokenism.
We use a range of …rm performance measures to test the robustness of the results. In
Table 6, we present the Arellano-Bond one-step estimates using three di¤erent measures
of …rm performance: ROA (column 1), Tobin’s Q, approximated by market-to-book value
ratio (column 2) and return on equity (column 3). All variables are lagged and lead to loss
of precision of the estimates. However, the positive association between our measure of
gender diversity (% female on the board) and all three …rm performance measures persist.
Thus our results suggest that gender diverse corporate boards is associated with productivity gain for …rms which is manifest in the form of enhanced …rm performance.
However, our results may not necessarily support the idea of gender quotas for boards
as short term supply constraints may counterbalance any productivity gained from such
diversity.
5.2
5.2 Committee Assignments of Women Directors
The role of the committees is to specialize in narrowly-de…ned tasks. The number and
functions of these committees vary across …rms and functions are sometimes combined.
We focus on three key committees- the audit committee that focuses on appointment of independent auditors and managing internal …nancial performance, nomination committee-
12
that recommends appointment of new directors on board and remuneration/compensation
committee-that focus on compensation and bene…ts for executives. A priori, a director
who is a member of one or more of these committees has more in‡uence on the strategic
choices made by the …rm. We test whether the likelihood of female directors being on
these committees is di¤erent from that of men conditional on the proportion of female on
the board. This allows an examination of the mechanism of the impact of female board
representation. The sample is restricted to only non-executive directors. We present the
results in Table 7. The key variable of interest is Female, an indicator for an individual
director being of the eponymous gender. The number of observations varies across speci…cations because not all …rms in the sample have all the three committees. The dependent
variable in each speci…cation is a binary indicator of whether an individual director is a
member of any of the three committees (1), audit committee (2), nomination committee
(3) and remuneration committee (4) respectively. All speci…cations present the marginal
e¤ects from probit regressions with …rm …xed e¤ects and year dummies and the standard
errors are clustered at …rm level.
The results suggest that the likelihood of female directors being appointed on committees are di¤erent from that of male directors. Female directors are only more likely to
be appointed on audit committees. Unsurprisingly, female directors are more likely to be
appointed on committees when the proportion of female directors on the board is high.
The point estimate of the likelihood of female directors to be appointed on nomination
committee is negative, although this is not statistically signi…cant at conventional levels.
Intuitively, if more female directors were to be appointed on nomination committees, it
might be plausible that more females would be nominated to be on the boards. However,
we can’t provide any de…nitive results on this.
13
5.3
5.3.1
5.3 Additional Results and Robustness
A. U.K. vs Non-U.K. sample
About 35% of our observations are for UK …rms. To ensure that our results are not
driven by the disproportionate presence of …rms from one country, we run our baseline
regressions separately for UK and non-UK …rms. The results are presented in Table 8. We
provide results for both measures of board gender diversity, viz. percentage of females on
the board, and the percentage of females on the committee. This exercise provides some
interesting insights. First, the e¤ect on …rm performance of percentage female directors
on the board is much stronger for the non-UK sample. The parameter estimate for the
UK sample is statistically insigni…cant. This is consistent with the results of GregorySmith et al (2014) who …nds no evidence of board gender diversity on the performance of
UK …rms. Therefore, it seems our baseline results are downard-adjusted due to the large
proportion of UK-…rms in the sample.
Second, and perhaps more interesting insight comes from the e¤ect on …rm performance of the proportion of female directors on key committees. As above, the e¤ect is
much stronger for the non-UK sample. However, the parameter estimate for the UK sample is now both signi…cant and positive. This suggests that whilst the traditional measures
of board gender diversity has no e¤ect on …rm performance for UK …rms, having female
directors integrated in the governance mechanism is value-enhancing.5 These results underscores the fact that the current evidence on female representation on corporate boards
shows the returns to tokenism, rather than the full economic bene…ts of internalizing the
diversity.
5
The regressions for Table 8 contains the full set of controls as the baseline regressions. In the interests
of brevity, we only report the estimates of the key variables.
14
5.3.2
B. Excluding …nancial crisis years of 2008 and 2009
Even though our baseline results include year dummies, to ensure that our results are not
a¤ected by the …nancial crisis, we exclude observations from 2008 and 2009. The results
with the reduced sample are very similar to that of the baseline estimates. For the sake
of parsimony, the tables are not presented here, but are available on request.
6
6. Conclusion
Gender diversity on corporate boards is likely to be one of the central themes of future
governance reforms. However there is no clear agreement on the economic bene…ts of recruiting more women on boards. A growing body of literature examines the consequences
of increasing board gender diversity. In this paper we attempt to provide new evidence
on the impact of board gender diversity on …rm performance using data from large European …rms with a wider dispersion in women representation on board. We also examine
a possible transmission mechanism of female representation on …rm performance. The
results of this paper suggest that increasing female representation on corporate boards
is associated with enhanced …rm performance. This association is particularly strong in
…rms with a high proportion of female directors ion key committees.
More generally, our results add to the literature in providing evidence of how increasing
female representation on boards, over and above symbolic tokenism, might positively
impact upon …rm performance. This augments the existing case for increasing gender
diversity of boards from a standpoint of morality and equity and extends an economic
case for it. These results also provide support to policy initiatives aimed at increasing
board gender diversity.
15
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18
Table1: Summary Statistics
The sample consists of an unbalanced panel of 18499 director-level observations from
118 …rms for the period 2006-2013. Director level data is obtained from Execucomp
and …rm level data is obtained from Datastream. All variables are winsorized at the
1%-level.
Variable
N
Mean
Std. Dev.
Min
Max
Firm Characteristics
Return on Assets
Log Sales
Tobin’s-Q
Stock Price Volatility
16647
16647
16647
16647
6.643
17.558
2.866
23.939
6.108
0.921
5.792
6.091
-09.28
14.39
-58.37
13.05
38.95
20.02
86.00
49.38
16647
16647
16647
16647
16647
16647
16.963
47.743
18.531
3.941
4.208
3.432
5.942
27.786
14.489
2.473
1.461
1.949
6.00
0.00
0.00
0.00
0.00
0.00
36.00
100.00
88.89
16.00
8.00
9.00
16647
3861
16647
16647
16647
1048.079
2276.805
5.756
4.535
58.115
2483.93
3356.398
5.269
4.238
8.097
0.00
0.00
0.00
0.00
26.00
67891.00
64906.00
54.90
47.72
90.00
Board Characteristics
Board Size
%Non-executive
% Female
Nomination Committee Size
Audit Committee Size
Remuneration Committee Size
Director Characteristics
Total Pay
Equity Pay
Time on Board
Time in Role
Executive Age (years)
19
Table 2: Comparisons of Firms with and without at least one Female Directors
This table presents key summary statistics for …rm-years with no female directors and
…rm-years with at least one any female director. Firms with no-female directors are
smaller and have smaller boards. There is no statistically signi…cant di¤erence in
any other attributes. All variables are winsorized at the 1%-level.
Variable
Mean-No
Female Directors
Mean-At Least One
Female Director
p-value
Log Sales
Tobin’s-Q
Return on Assets
Volatility
17.296
3.025
5.869
23.824
17.614
2.819
6.697
23.949
0.000
0.272
0.000
0.000
Board Size
% Non-Executive
Age (years)
Nomination Committee Size
Audit Committee Size
Remuneration Committee Size
15.140
47.109
59.035
3.849
3.283
3.541
17.152
47.811
58.013
3.950
4.308
3.420
0.272
0.281
0.000
0.066
0.000
0.010
20
Figure 1: Yearly Trends in Board Gender Diversity
This …gure shows that there has been a rise in female representation
on corporate boards. There seems to be an increase in the proportion
of …rms with more than 20% female directors.
21
Figure 2: Yearly Trends in Female Representation
on Governance Committees
The fraction of female directors on key governance committees seems
to have remained relatively stable over our sample period.
22
Figure 3: Female Representation on Boards:
UK vs Non-UK Firms
This …gure compares the female representation on boards of UK and
non-UK European …rms in our sample. It seems that a higher fraction
of non-UK …rms have 10% female directors, whereas a higher fraction
of UK …rms have over 50% female directors on board.
23
Figure 4: Female Representation on Governance
Committees: UK vs Non-UK Firms
This …gure compares the female representation on key governance
committees of UK and non-UK European …rms in our sample. A higher
fraction of non-UK …rms seems to have more female representation on
governance committees.
24
Table 3: Female Representation and Firm Performance
This table presents the results of the impact on …rm
performance of female representation on boards
using three di¤erent measures of female representation,
viz. %Female directors on the board (1), whether there
is at least one female director in a …rm-year (2) and the
% of Females on committees (3). All three measures
suggest a positive association of female directors with
…rm performance. All speci…cations include year dummies
Robust standard errors in parentheses. Asterisks indicate
signi…cance at 0.01 (***), 0.05 (**) and 0.10 (*)
levels.
Dependent Variable
% Femalet
1
Log Salest
1
Volatilityt
1
Board Sizet
ROA
(1)
(2)
(3)
(4)
0.052***
(0.003)
0.0428***
(0.003)
0.7290***
(0.0510)
-0.2642***
(0.0076)
0.005**
(0.002)
0.033***
(0.007)
0.000
(0.026)
-0.016***
(0.003)
0.0757***
(0.015)
5.008***
(0.804)
No
No
16.647
4.15
24.99***
(0.920)
No
No
16,647
10.58
0.0148***
(0.003)
0.3373***
(0.049)
-0.2158***
(0.007)
-0.4778***
(0.0102)
0.066***
(0.002)
-1.689***
(0.989)
28.69***
(0.884)
No
No
16,647
19.76
1
% Non-Executivet
Chairman-CEOt
1
1
Constant
Firm Fixed E¤ects
Year Dummies
Observations
Adjusted R2
25
4.70***
(0.593)
Yes
Yes
16,647
20.80
Table 4: Female Directors and Firm Performance-Comparison
This table presents the results of the e¤ect of female directors on …rm
performance using di¤erent estimation techniques. Only the key covariates
are reported in all speci…cations. The main variables of interest is %Female
Column (1) presents the OLS estimates; column (2) includes …rm …xed e¤ects;
column (3) presents IV estimates with network size of individual directors as
an instrument and column (4) presents the result of Arellano-Bond
one step regression. All speci…cations include year dummies. Robust
standard errors in parentheses. Asterisks indicate signi…cance at 0.01 (***),
0.05 (**) and 0.10 (*) levels.
(1)
(2)
(3)
(4)
OLS
FE
IV
GMM
Dependent Variable
% Femalet
%Fd
emale
0.023**
(0.003)
1
Log Salest
1
Volatilityt
1
Board Sizet
ROA
1
% Non-Executivet
Constant
Firm Fixed E¤ects
Year Dummies
Observations
Adjusted R2
1
-0.300***
(0.049)
-0.206***
(0.007)
-0.472***
(0.010)
-0.064**
(0.002)
26.98***
(0.898)
No
Yes
16,647
25.50
0.005**
(0.002)
0.033***
(0.007)
0.000
(0.026)
-0.016***
(0.003)
0.0757***
(0.015)
48.03***
(0.927)
Yes
Yes
16,647
20.80
26
0.098**
(0.044)
0.364***
(0.057)
0.580***
(0.163)
-0.103**
(0.038)
-0.0301*
(0.015)
0.237**
(0.079)
11.98**
(4.166)
Yes
Yes
16,647
0.737**
(0.306)
-0.0918**
(0.0483)
-0.0244**
(0.0095)
0.0100
(0.0130)
16.77**
(7.42)
Yes
Yes
16,647
Table 5: Di¤erent Measures of Female Representation
This table presents the results of the impact on …rm
performance of female representation on boards
using three di¤erent measures of female representation,
viz. %Female directors on the board (1), whether there
is at least one female director in a …rm-year (2) and the
% of Females on committees (3). All three measures
suggest a positive association of female directors with
…rm performance. All speci…cations include year dummies
Robust standard errors in parentheses. Asterisks indicate
signi…cance at 0.01 (***), 0.05 (**) and 0.10 (*)
levels.
Dependent Variable
(1)
% Femalet
0.402**
(0.148)
1
% Female in
Committeet 1
Log Salest 1
1
Board Sizet
(3)
0.005***
(0.002)
1
Any Femalet
Volatilityt
ROA
(2)
1
% Non-Executivet
Constant
Firm Fixed E¤ects
Year Dummies
Observations
Adjusted R2
1
0.033***
(0.007)
0.000
(0.026)
-0.016***
(0.003)
0.0757***
(0.015)
48.03***
(0.927)
Yes
Yes
16,647
20.80
27
0.098**
(0.048)
-0.228***
(0.007)
-0.433***
(0.014)
0.050***
(0.002)
17.63***
(0.978)
Yes
Yes
16,647
29.24
0.035**
(0.013)
0.100***
(0.049)
-0.225***
(0.007)
-0.424***
(0.014)
0.011***
(0.002)
17.91***
(0.988)
Yes
Yes
16,647
28.13
Table 6: Female Directors and Firm Performance-GMM
This table presents the results of GMM estimation of the
e¤ect of female directors on …rm performance. The dependent
variable in each speci…cation is mentioned. All variables are
lagged to control for potential endogeneity. Standard errors
are provided in brackets. Asterisks indicates signi…cance at
0.01 (***), 0.05 (**) and 0.10 (*) levels.
Dependent Variables
% Femalet
yt
1
1
Log Salest
1
Volatilityt
1
Board Sizet
1
% Non-Executivet
Any Femalet
Observations
No AR(2)
Sargan Test
1
1
(1)
(2)
(3)
ROA
Tobin’s Q
ROE
0.0644**
(0.003)
0.062**
(0.0275)
0.007***
(0.0005)
-0.035
(0.029)
-0.014**
(0.006)
0.067**
(0.002)
0.913*
(0.448)
663
0.436
0.334
28
0.059**
(0.0102)
-0.076
(0.683)
0.026**
(0.009)
-0.048
(0.033)
-0.006**
(0.002)
0.086*
(0.043)
0.674
(0.415)
663
0.232
0.190
0.189**
(0.085)
0.774**
(0.375)
0.008**
(0.003)
-0.011**
(0.005)
-0.033***
(0.008)
0.009**
(0.002)
0.620
(0.388)
663
0.455
0.218
Table 7: Assignment of Women Directors on Key Committees
This table presents the probability of individual female directors to be assigned to key
governance committees-audit, nomination and remuneration. The sample consists of an
unbalanced panel of 18499 directors for the period. 2006-2013. The main variable of
interests are Female and Female*%Female. Female is a binary indicator for a
female director. The results suggest that female directors are more likely to be
chosen on any committees when the % of Female directors on the board is high. All
columns show marginal e¤ects of a probit model with …rm …xed e¤ects and year
dummies. Robust standard errors in parentheses. Asterisks indicate signi…cance at
0.01 (***), 0.05 (**) and 0.10 (*) levels.
(1)
(2)
(3)
(4)
Dependent Variable
Any
Committee
Audit
Committee
Nomination
Committee
Remuneration
Committee
Time in Role
-0.000721*
(0.000432)
0.000487**
(0.000244)
-0.00248***
(0.000770)
-0.00578
(0.00407)
0.000243
(0.000168)
0.000314**
(0.000156)
-2.00e-05
(0.000121)
-0.000215
(0.000283)
-0.00469**
(0.00236)
-0.000377
(0.000305)
0.0023***
(0.0011)
-0.00125
(0.00177)
0.00464***
(0.00112)
-0.00943***
(0.00251)
0.101***
(0.0306)
0.00102
(0.000630)
0.00021**
(0.00012)
-0.000763*
(0.000449)
-0.000461
(0.00134)
-0.0102
(0.00955)
0.000411
(0.00116)
0.0038**
(0.0017)
-0.000458
(0.00221)
0.00693***
(0.00133)
-0.0105***
(0.00322)
-0.0214
(0.0213)
0.00228**
(0.000935)
0.000366
(0.000358)
0.000426
(0.000723)
-0.000999
(0.00208)
-0.0199
(0.0197)
0.00171
(0.00263)
0.0022
(0.0019)
-0.00258
(0.00202)
0.00634***
(0.00107)
-0.0163***
(0.00236)
0.000932
(0.0242)
0.00105**
(0.000497)
0.000308
(0.000317)
0.000884**
(0.000444)
-0.00202
(0.00132)
-0.0154
(0.00946)
-0.000165
(0.00111)
0.0016
(0.0023)
Yes
16,171
Yes
16,171
Yes
16,171
Yes
16,171
Age (Years)
Board Size
Female
% Female Directors
Female*
% Female Directors
% Non-Executive
Directors
Return on Assets
Log Sales
Volatility
Network Size
Year Dummies
Observations
29
Table 8: UK vs. Non-UK Sample
This table presents the results of the impact on …rm performance
of female representation on boards for the UK and the non-UK
sub-samples. Two measures of female representations are used:
viz. %Female directors on the board (1) and (3), and % of Female
directors on committees (2) &(4). The dependent variable in all
speci…cations is ROA. The results suggest a stronger impact of
female represenation on …rm performance for the non-UK sample.
All speci…cations include year dummies. Robust standard errors
in parentheses. Asterisks indicate signi…cance at 0.01 (***), 0.05
(**) and 0.10 (*) levels.
UK
Non-UK
Dependent Variable
ROA
(1)
% Femalet
1
% Female in
Committeet 1
Constant
Firm Fixed E¤ects
Year Dummies
Observations
Adjusted R2
(2)
0.007
(0.004)
26.18***
(1.609)
Yes
Yes
5,794
28.29
(3)
(4)
0.033***
(0.005)
0.011*
(0.006)
26.095***
(1.621)
Yes
Yes
5,794
28.29
30
30.07***
(1.233)
Yes
Yes
10,580
22.22
0.037***
(0.003)
29.414***
(1.262)
Yes
Yes
10,580
22.02