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Do Board Gender Quotas Affect Firm Value? Evidence from California Senate Bill No. 826

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We examine stock market reactions, direct costs of compliance, and board adjustments to California Senate Bill No. 826 (SB 826), the first mandated board gender diversity quota in the United States. Announcement returns average-1.2% and are robust to the use of multiple methodologies. Returns are more negative when the gap between the mandated number and the pre-SB 826 number of female directors is larger. These negative effects are less severe for firms with a greater supply of female candidates, and for those that can more easily replace male directors or attract female directors. For small firms, the annual direct cost of compliance through board expansion is non-trivial, representing 0.76% of market value. Following SB 826, firms significantly increase female board representation, and the increase is greater for firms in California than control firms in other states.
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Do board gender quotas affect firm value? Evidence from California Senate
Bill No. 826
Daniel Greene
Clemson University
Tel: 864-656-2409
Email: dtg@clemson.edu
Vincent J. Intintoli
Clemson University
Tel: 864-656-2263
Email: vintint@clemson.edu
Kathleen M. Kahle
University of Arizona
Tel: 520-621-7489
Email: kkahle@eller.arizona.edu
October 2, 2019
Abstract
We examine stock market reactions, direct costs of compliance, and board adjustments to
California Senate Bill No. 826 (SB 826), the first mandated board gender diversity quota in the
United States. Announcement returns average -1.2% and are robust to the use of multiple
methodologies. Returns are more negative when the gap between the mandated number and the
pre-SB 826 number of female directors is larger. These negative effects are less severe for firms
with a greater supply of female candidates, and for those that can more easily replace male
directors or attract female directors. For small firms, the annual direct cost of compliance through
board expansion is non-trivial, representing 0.76% of market value. Following SB 826, firms
significantly increase female board representation, and the increase is greater for firms in
California than control firms in other states.
JEL Classifications: G34, G38, G14, K22, J20, J21
Keywords: Boards of directors, Female directors, Gender diversity, Gender quota, Corporate
Governance, Regulation
We thank Shane Johnson, Douglas Cumming (the Editor), and two anonymous referees for helpful comments. Taylor
Brown and Dylan Kozin provided excellent research assistance.
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1. Introduction
On September 30, 2018, California became the first U.S. state to mandate a corporate board
gender quota when Governor Jerry Brown signed Senate Bill No. 826 (SB 826) into law. SB 826
requires public companies headquartered in California to have at least one female director by the
end of 2019 and at least two (three) female directors on five (six or more) member boards by the
end of 2021.1 This paper provides important new evidence on the effects of board gender quotas
by examining stock market reactions to announcements regarding the law, direct costs of
compliance, and board adjustments post-SB 826.
SB 826 is an ideal setting to study the impact of corporate board mandates for several
reasons. First, while the endogenous nature of corporate boards has made it difficult to fully
understand the relation between board gender diversity and firm value, SB 826 creates an
exogenous shock to board composition that allows us to study the impacts of gender quotas on
U.S. firms. Evidence in Norway, the first country to enact a gender quota law, suggests a negative
impact of mandated female representation on firm performance (Ahern and Dittmar, 2012; Matsa
and Miller, 2013). Due to cultural differences and a heavier reliance on equity financing, it is not
clear whether U.S. firms should experience similar effects, however. Second, the signing of the
law by Gov. Brown was unexpected, as he offered no public guidance on his views (Fuhrmans and
Lazo, 2018). The unexpected nature of the passage of SB 826 enables us to isolate the stock market
reaction to an exogenous change in board structure. Third, over 12% of all public U.S. firms are
headquartered in California, so the mandate affects a large and diverse set of firms with a combined
1 The motivation for SB 826 is the fact that boards of U.S. public companies are male dominated. Women hold only
18% of board seats in Russell 3000 firms, and 50% of Russell 3000 firms have one or fewer female directors (see
Fuhrmans and Lazo, 2018). While many recently appointed board members are female, overall board representation
continues to be largely male due in part to long incumbent director tenures and low board turnover (Fuhrmans, 2019).
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market capitalization of over $5 trillion. Studying the effects of SB 826 enables us to exploit cross-
sectional variation in firm characteristics in multivariate tests.
We begin by building a sample of all 602 public firms headquartered in California. We
find that 171 (28%) of these firms need to add a female director by the end of 2019 and 531 (88%)
need to add one or more women by 2021. In total, SB 826 requires over 1,000 additional female
directors on corporate boards by 2021. We find a statistically significant and economically large
stock market reaction of -1.2% at the announcement, suggesting that SB 826 is costly for affected
firms. The magnitude of this return is robust to multiple methodologies, including tests that control
for cross-correlation in announcement returns and matching California firms to control firms not
affected by SB 826. Given that California firms represent over $5 trillion of market value, a back
of the envelope calculation provides a total loss in value in excess of $60 billion. Stock returns are
decreasing in the number of female directors needed, with a mean of -1.06% (-1.64%) for firms
that must add one (three) female director(s) by 2021. Multivariate analysis implies a 0.50% decline
in shareholder wealth for every female director that the firm is required to add by 2021.
We develop several cross-sectional predictions of the effects of SB 826, an approach
suggested by Mulherin (2007) when studying the effects of regulation. The mandate forces firms
to either replace existing directors or expand board size. Regardless of which a firm chooses, the
impact of SB 826 depends on the supply of female candidates. Consequently, we examine two
proxies for the supply of female directors: a dummy equal to one if there are no female CEOs in
the industry and a dummy for industries with an above median number of female directors. We
find that the negative effect of SB 826 on stock returns is accentuated for firms with a restricted
supply of female candidates.
3
If the firm chooses to replace existing directors, the negative impact of the law should be
lessened in firms that can more easily do so. In our next cross-sectional tests, we use several
proxies for ease of replacement, including board committee service, director age, and the presence
of directors associated with venture capital (VC) funds. Overall, our results suggest that stock
returns are less negative when directors are easier to replace.
Our final cross-sectional tests examine the reaction to SB 826 based on the firm’s ability
to attract female directors. We predict that younger, lesser-known companies will have more
difficulty attracting female candidates. Indeed, the negative effect of SB 826 is strongest for firms
that are below the median age. However, this negative effect on younger firms is offset for firms
associated with VC funds with a female presence. This finding is consistent with the prediction
that VCs with a female presence can help young firms attract and recruit female directors.
We next estimate the direct costs of compliance for new director appointments, assuming
board expansion. The median firm needs to add two female directors by 2021 at a total annual cost
of $345,636. Although the dollar cost of compliance is higher for larger firms due to higher director
pay, the economic effect of the law is greater for smaller firms. When scaled by market
capitalization, additional annual director compensation averages only 0.0007% of market
capitalization for the largest firms, but 0.76% for the smallest firms, an increase of over 1,000%.
Finally, we compare pre-and post-SB 826 board composition for 488 California firms that
filed proxy statements from January to July 2019. The aggregate number of board seats held by
female directors increases by 23% (143 board seats) from pre- to post-SB 826. This increase is
greater for California firms than for control firms in other states, so it is not driven by a general
trend of increasing female board representation. Of the 136 firms that add a female director, 40%
replace male directors while 60% expand the board. Firms expand (replace) when pre-SB 826
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board size is smaller (greater), suggesting that increasing the board above a certain size is costly.
Surprisingly, 70 of the 488 firms continue to have all male boards as of their 2019 proxy filing.
For these firms, average annual director pay is greater than the $100,000 fine for non-compliance,
suggesting that it may be optimal for some firms to delay appointing a new director or pay the fine.
Our paper is most closely related to Hwang, Shivdasani, and Simintzi (2019) and von
Meyerinck, Niessen-Ruenzi, Schmid, and Solomon (2019), who also study SB 826. Hwang et al.
(2019) study Russell 3000 firms and find that the costs of adding female directors are greater when
the supply of female candidates is limited or when firm governance is weaker. von Meyerinck et
al. (2019) study BoardEx firms and find spill-over effects for firms headquartered outside of
California that are more likely to support similar legislation. A novel contribution of our study is
that we examine all 602 public firms headquartered in California, an increase of 48% and 32%,
respectively, over the samples used in Hwang et al. (2019) and von Meyerinck et al. (2019). Our
sample allows us to more fully examine the impact of SB 826, including the need for over 1,000
additional female directors by 2021 and the higher costs imposed on younger and smaller firms.
More broadly, our paper contributes to the debate on gender quotas for corporate boards.
While multiple papers document negative impacts of Norway’s gender quota (see, for example,
Ahern and Dittmar, 2012; Matsa and Miller, 2013; Bøhren and Staubo, 2014, 2016), Eckbo,
Nygaard, and Thorburn (2019) find that Norway’s gender quota is value-neutral. Moreover,
Ferreira (2015) points out a number of difficulties in using Norway’s law as a natural experiment
including timing issues, sample selection, lack of a suitable control group, and confounding effects.
Our empirical design overcomes these difficulties and provides evidence of a negative impact of
gender quotas on firm value for U.S. firms.
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Our study also adds to the literature that examines the costs of government mandated
legislation. Previous studies document the costs of Regulation Fair Disclosure in 2000 and the
Sarbanes-Oxley Act of 2002 on small and young firms (Gomes, Gorton, and Madureira, 2007;
Wintoki, 2007; Linck, Netter, Yang, 2008; Ahmed, McAnally, Rasmussen, and Weaver, 2010).
We contribute to this literature by identifying the costs of SB 826 and relating these costs to both
stock returns and post-SB 826 changes in board composition.
Finally, we contribute to the literature on corporate board size (Yermack, 1996; Kini,
Kracaw, and Mian, 1995; Boone, Field, Karpoff, and Raheja, 2007; Coles, Daniel, and Naveen,
2008). It is difficult to identify the causal impact of board size on firm value due to endogeneity.
However, Jenter, Schmid, and Urban (2018) find that government-mandated minimum board size
requirements in Germany relate to decreases in firm value, and Bøhren and Staubo (2014) find that
small and young Norwegian firms switch organizational form rather than comply with the gender
quota law. Our evidence suggests that the negative effect of gender quotas can be partly explained
by board expansion. We show that firms that can more easily replace directors, and therefore
maintain their pre-SB 826 board size, are less negatively affected by the mandate.
2. Details of California Senate Bill No. 826
California Senate Bill No. 826 requires any domestic or foreign corporation whose
“principal executive office” (as identified in the firm’s 10-K) is located in California to maintain
a minimum number of female directors or face monetary penalties; legal scholars have generally
interpreted “principal executive office” to mean firm headquarters. SB 826 was introduced into the
California Senate on January 3, 2018 and passed the Senate by a 22-11 vote on May 31, 2018. It
passed the Assembly on August 29, 2018 by a vote of 41-26, and the revised bill passed the Senate
on the same day. The passage by the Senate did not guarantee that SB 826 would become law,
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however, since Gov. Brown had not publicly commented on his position. Without providing any
guidance, Gov. Brown signed the law into effect on Sunday, September 30.
Under the law, each public company must have at least one female director by calendar
year end 2019. By the end of 2021, the requirements increase as a function of board size. The
minimum is one female director for boards with four or fewer directors, while boards with five
(six or more) directors are required to have a minimum two (three) female directors. Firms can
either replace existing directors or add board seats to comply. Penalties for not abiding by the law
are $100,000 for the first violation and $300,000 for each subsequent violation. A violation relates
to each female director deficiency, so a six member board with no female director representation
by 2021 would be short by three female directors, resulting in an annual fine of $700,000.
The legality of SB 826 has been questioned on two grounds: (1) it discriminates based on
sex, and (2) based on the internal affairs doctrine, it does not apply to firms that are headquartered,
but not incorporated, in California (Grundfest, 2018).2 No lawsuits have been filed based on the
latter argument, but in August 2019, three citizens filed a lawsuit based on the former argument
(Sumagaysay, 2019). The lawsuit does not seek to overturn SB 826, but rather prohibit
enforcement and financial penalties on firms. The California Secretary of State, who is responsible
for enforcing SB 826, has not yet responded to the lawsuit in court, but several state legislators
claim that the lawsuit is questionable and politically motivated. Further, some lawyers believe that
SB 826 could be upheld on grounds that it provides equal protection for women (Yoder, 2019).
We discuss these issues further in Section 7.3.
2 The internal affairs doctrine is based in a Supreme Court ruling that a firm's internal affairs, including rules regulating
the composition of its board of directors, are governed by the firm’s state of incorporation and not by the state in which
it is headquartered.
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3. Literature Review
3.1 Board Gender Diversity and Firm Value
The board of directors is responsible for monitoring and advising top management. Various
director-level characteristics such as independence (Hermalin and Weisbach, 1998; Coles, Daniel,
and Naveen, 2014), experience (Wang, Xie, and Zhu, 2015), and connections (Larcker, So, and
Wang, 2013) are associated with better monitoring and advising, and greater firm value. Evidence
also suggests that well-diversified boards are positively correlated with higher firm value. For
example, Anderson, Reeb, Upadhyay, and Zhao (2011) and Bernile, Bhagwat, and Yonke (2018)
create board heterogeneity indices based on multiple factors, including gender, and find that
greater board diversity is correlated with better firm performance. Alternatively, Sila, Gonzalez,
and Hagendorff (2016) use a dynamic model and find no evidence that female board representation
influences equity risk. Other papers suggest why female directors may be beneficial. These reasons
include differing core values and risk attributes (Adams and Funk, 2012), unique skills and
expertise (Kim and Starks, 2016), and better academic and professional qualifications (Field,
Souther, and Yore, 2018).
The literature finds some empirical evidence of the benefits of gender diverse boards. For
example, greater board gender diversity is related to a lower pay gap between male and female
executives (Carter, Franco, and Gine, 2017) and improvements in stock price informativeness
(Gul, Srinidhi, and Ng, 2011). While the presence of a gender diverse board is cited in the press
and by politicians as relating to better firm performance, the academic evidence on the association
between gender diversity and firm value is mixed (Ferreira, 2015). Liu, Wei, and Xie (2014) report
improvements in firm performance for gender diverse firms in China. Adams and Ferreira (2009)
find a positive correlation between gender diversity and performance for firms with weak
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shareholder rights, but a negative correlation for firms with strong shareholder rights. Overall,
while these studies suggest that changes in diversity could impact corporate value and outcomes,
evidence of a causal relation is weak. It is important to note that while greater diversity may be
positively associated with increases in firm value in some settings, gender quota laws may not
have the same affect. Adams and Ferreira (2009) emphasizes that “…our results show that female
directors have a substantial and value-relevant impact on board structure. But this evidence does
not provide support for quota-based policy initiatives.” (pg. 308).
3.2 The Norway Gender Balance Law
In 2003, Norway became the first country to mandate a gender quota, requiring that 40%
of Norwegian firms’ directors be women. Numerous studies exploit this exogenous shock to board
composition to examine the impact of the quota on firm value and performance. Ahern and Dittmar
(2012) suggests that the constraint imposed by this quota results in a significantly negative
announcement return and a large decline in Tobin’s Q over the following years. Matsa and Miller
(2013) finds that short-run operating profitability declines after the quota was adopted. Yang,
Riepe, Moser, Pull, and Terjesen (2019) employs a difference-in-differences approach, using firms
from Finland, Sweden, and Denmark as controls, and finds a negative effect of mandated female
representation on accounting performance and firm risk.
Bøhren and Staubo (2014, 2016) document evidence of the high costs of involuntary board
restructuring. Bøhren and Staubo (2014) find that following the Norway gender quota, half the
firms exit to an organizational form not exposed to the law. Conversion likelihood decreases in the
fraction of female directors, suggesting that forced gender balancing is costly. Bøhren and Staubo
(2016) find that the quota increases board independence and reduces firm value. In both papers,
the effects are strongest in small, young, profitable, non-listed firms with few female directors.
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Overall, these papers suggest that mandatory gender quotas may produce firms with inefficient
organizational forms or inefficient boards.
In contrast, Eckbo et al. (2019) finds little effect of the Norway law on corporate
performance. They suggest that after (1) accounting for the cross-dependence in returns that exists
when the news event affects all sample firms simultaneously in calendar time, and (2) adjusting
Ahern and Dittmar’s instrument so that it is exogenous to the gender quota news announcement,
the quota-induced changes in stock returns and Tobin’s Q are not significant. Eckbo et al. (2019)
also claim that including year fixed effects eliminates the significance of the female director
shortfall found in Bøhren and Staubo (2014). Moreover, after excluding listing changes due to
M&As and going private transactions, they find no change in the number of listed firms. Our study
contributes to this debate by providing new evidence on the impact of gender quotas in a different
but important setting.
4. Hypotheses
4.1 Gender Quotas and Firm Value
In this section, we generate predictions on the expected effect of SB 826 on firm value.
The impact of SB 826 depends on its benefits versus its costs. As outlined in Section 3.1, previous
studies suggest that the presence of women on boards is positively correlated with firm
performance. In the context of a gender quota law, however, for the addition of women to improve
firm performance, one must assume that boards are either (1) unaware of the benefits of diversity,
or (2) not trying to maximize shareholder wealth, otherwise they would have already appointed
more women in order to reap these benefits. Under these conditions, SB 826 may increase firm
performance by forcing these firms to appoint women. Alternatively, SB 826 should have no
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impact on firm value if male and female directors are generally interchangeable and boards can
easily adjust their composition at little or no cost.
On the other hand, SB 826 may be value decreasing if firms are already maximizing value
through their current board composition but face costs in adjusting board structure to meet the
mandate. Under these assumptions, the impact of the law depends on the supply of potential female
directors. If the demand exceeds supply, then firms subject to the law face a constrained
optimization decision that may result in suboptimal outcomes relative to the unconstrained
decision. Ahern and Dittmar (2012) find that following Norway’s gender quota, new female
directors are younger and have less CEO experience, suggesting a constrained supply of potential
female candidates relative to their male counterparts. In our setting, if the supply of female
candidates is restricted, the market should react negatively to SB 826, with constrained firms (i.e.,
those needing female directors to meet the mandate) experiencing a more negative return.
Moreover, firms for which it is more difficult to attract female candidates should suffer more. We
note that our predictions are specific to the setting of a gender quota and firm value is not predicted
to decline when firms voluntarily add female directors.
4.2 Director Replacement Versus Board Expansion
SB 826 forces firms into a difficult decision: to comply, should the firm replace existing
male directors or expand the board to accommodate new female directors? Existing directors add
value through their expertise and knowledge regarding the firm and industry, both from board
committee service and from skills such as financial expertise (Defond, Hann, and Hu, 2005).
Consistent with this idea, director deaths are associated with stock price decreases (Nguyen and
Nielsen, 2010) and this reaction is exacerbated when the director is well connected and sits on an
important committee (Intintoli, Kahle, and Zhao, 2018). Even if the supply of female directors is
11
large enough to satisfy demand, the replacement of existing directors can result in a costly
disruption to board dynamics. A new director, even if highly qualified, requires time and effort to
gain similar knowledge, making the replacement of a valued director costly for firms.
Instead of replacing a director, firms can avoid the loss of expertise by expanding the board.
The direct costs of expansion include director compensation, travel expenses related to board
meetings, and D&O insurance. Although these costs are nominal for large firms, they can be
significant for small firms. Expansion may also result in indirect costs. Firm-specific
characteristics dictate optimal board construction (Boone et al., 2007; Coles et al., 2008), so
increasing board size beyond its optimal level may be costly. Lipton and Lorsch (1992) and Jensen
(1993) suggest that large boards decrease firm value because coordination problems prevent
directors from effectively monitoring the CEO. Consistent with this prediction, Yermack (1996)
finds a negative correlation between board size and firm value and Kini et al. (1995) find that board
size shrinks following disciplinary takeovers. If board size is already optimal, then legal mandates
that change board structure should be value decreasing (Demsetz and Lehn, 1985).
The above discussion suggests that the impact of SB 826 on firm value depends not only
on the supply of female candidates, but also on the costs of adjusting board structure.3 SB 826 may
have no impact on firm value if there is a large supply of female candidates and board structure
can be easily adjusted to meet the mandate. However, the cost of replacing directors is likely to
vary cross-sectionally. Holding the supply of female directors constant, we predict that as the cost
of replacing male directors decreases, SB 826 will have a smaller impact on firm value as boards
can easily swap male directors for female directors. However, as the cost of replacing male
3Alternatively, firms can choose to pay fines for non-compliance, as discussed in Section 7.2.
12
directors increases, firms will be forced into a difficult replace or expand decision, and we predict
a more negative reaction to SB 826.
5. Sample Description and Summary Statistics
5.1 Sample and Key Variables
SB 826 specifies that all public corporations listed on major exchanges whose principal
executive offices are in California must comply with the law. To identify all companies affected
by SB 826, we search Compustat for entities with non-missing total assets (Compustat Item AT)
that are headquartered in California, yielding 827 observations. We then restrict the sample to
firms listed on major exchanges with available stock return data in the Center for Research in
Security Prices (CRSP) database, yielding 614 firms.4
For these firms, we obtain pre-SB 826 board data from Institutional Shareholder Services
(ISS). Because ISS only covers Russell 3000 firms, for the remaining firms we hand collect
information from the last proxy statement filed prior to October 1, 2018, which provides the most
recent publicly available information on board characteristics as of the signing of SB 826. Our
final sample consists of 602 firms with non-missing data on total assets, stock returns, and board
characteristics. We define Gap as the difference between the number of female directors needed
to comply with SB 826 by the end of 2021 and the number on the board prior to the signing of SB
826. For the 24 firms with more female directors than required by the mandate, we set Gap to zero.
We define Gap% as Gap divided by board size. Appendix A provides detail on the number of
female directors needed under both the replace and expand assumptions.
4 California entities listed in Compustat that do not have public equity listed on a major exchange include subsidiaries
(e.g., Toyota Motor Credit), private firms with preferred stock and/or public debt (e.g., Levi Strauss, who subsequently
went public on March 21, 2019), and firms with equity trading on over the counter (OTC) markets (e.g., Mechanics
Bank). These firms are not required to meet the mandate of SB 826 at the time that the bill was signed.
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Our dataset is 48% larger than the sample most often identified as affected by the law in
research and the press, which includes only 407 Russell 3000 firms (e.g., Fuhrmans and Lazo,
2018; Hwang et al., 2019). Thus, we identify 195 additional companies affected. Including all
affected firms is important because smaller firms tend to have fewer female directors. For example,
based on Russell 3000 firms, an additional 650 female directors are needed to comply with SB
826, assuming existing directors are replaced. However, our sample reveals that over 1,000
additional female directors are needed (mean Gap of 1.68 x 602 firms), an increase of 54%.
5.2 Abnormal Return Calculations
We use two approaches to examine the impact of SB 826 on firm value, using Monday,
October 1, 2018 as our primary event date since Gov. Brown signed the bill on Sunday, a non-
trading day. In the first approach, we examine equal-weighted calendar time portfolios of
California firms following the methodology suggested by Jaffe (1974) and used in Eckbo et al.
(2019), which accounts for cross-correlation due to our event day (the passage of SB 826)
occurring on the same day for all firms. To do so, we compute daily excess returns for each firm
by subtracting the daily three-month Treasury bill rate (obtained from FRED). We then average
the excess returns beginning 252 trading days prior to the event day and continuing through the
event day. We require that each firm has a minimum of 100 return observations and a return
observation on October 1st. We estimate the portfolio's daily abnormal return (AR), using the
following return-generating process:
=+
×

+ ×
+
(1)
where Rt is the average daily excess portfolio return, Rmt is the daily excess return on the CRSP
value-weighted index, and Dt is a dummy equal to one on the event day and zero otherwise. Thus,
the event parameter AR is the average daily abnormal portfolio return on the event day.
14
Since the calendar time approach does not provide abnormal returns for individual firms,
our second approach uses a traditional event study methodology in which we calculate the
abnormal stock return to the announcement of SB 826 for each firm. We begin by estimating the
market model parameters β and α over the time period prior to the advancement of SB 826 in the
California Senate. Specifically, we choose April 17, 2018 as the cutoff date for estimating
parameters as this predates the first hearing in the California Senate. We use the CRSP value-
weighted index to estimate market model parameters over the prior 253 trading days (minimum
30 observations). Then we use Equation (2) to calculate the expected return to firm i at time t,
where Rm represents returns to the CRSP value-weighted index:
(

)=
+
×

(2)
Abnormal returns for firm i at time t are calculated as the raw return minus the expected return
(Abnormal Return). The advantage of this approach is that it allows us to control for firm
characteristics and to include interaction terms in cross-sectional tests. We use multiple approaches
to address the concern that event date clustering leads to an over rejection of the null hypothesis
of zero returns. Kolari and Pynnönen (2010) suggest that test statistics adjusting for cross-
correlation have more power than the portfolio approach of Jaffe (1974), so we use the non-
parametric rank test approach of Corrado (1989) and Corrado and Zivney (1992), and the adjusted
test statistic approach of Kolari and Pynnönen (2010).
5.3 Sample Summary Statistics
Panel A of Table 1 reports summary statistics for our sample of 602 firms. Variable
construction is described in Appendix B. The mean (median) Market Value of equity is $8.790
billion ($834 million), while Total Assets is $5.523 billion ($482 million). In aggregate, our sample
represents over $5.2 trillion in market value and accounts for 12.3% of all Compustat firms,
15
demonstrating the importance of California firms to the U.S. economy. California firms average
7.8 board members and 1.2 female directors. Mean (median) Gap is 1.68 (2.00), so more than half
of all California firms are required to add two female directors by 2021. Mean Gap% is 23.60%
and the median is 25.00%, indicating that firms must replace a quarter of the board to satisfy the
requirements of SB 826.
In addition to basic board characteristics, we collect data on director compensation, VC
investment, and VC directors. Specifically, we classify independent directors based on NYSE and
NASDAQ listing standards and calculate the median pay of independent directors for each firm
(Director Pay). We obtain compensation data for S&P 1500 firms from Execucomp and hand
collect this data for other firms from proxy statements. Director Pay averages $181,999 (median
$172,818) in our sample. We use these data in Section 7 to examine the direct costs of expansion.
We gather data on venture capitalists from SDC and proxy filings. Since venture capitalists tend
to exit their investments in the years following an IPO (Krishnan, Ivanov, Masulis, and Singh,
2011), we restrict our analysis to California firms that have been public for ten years or less (i.e.,
firm age ten or less).5 We create an indicator for whether the firm has backing from a venture
capitalist or private equity (PE) firm that is either founded or led by a woman, or has a female
managing partner (Female VC Backed). Firms backed by VCs with a strong female presence
should have a better network of female executives and thus should have an easier time finding
female candidates.6 Further, using a firm’s proxy statement immediately prior to the signing of SB
826, we identify directors with ties to VC/PE funds (VC Directors). Within the sample of firms
5 Conventional wisdom suggests that VC funds have a roughly ten-year lifespan in which to enter and exit all
investments. However, this lifespan has increased in recent years (Bollen, 2015), and Iliev and Lowry (2018) find that
many VCs continue to invest in firms post- IPO. We examine firms for ten years after their IPO for these reasons.
6 Gompers and Wang (2019) find that VCs with more daughters are more likely to hire female partners. The presence
of male VCs with daughters may therefore also relate to the ease of finding female candidates. However, data
limitations prevent us from creating such a measure.
16
aged ten years or younger (268 firms), 63% (168) have VC backing and 14% have a female VC
presence. Of the 168 firms with VC backing, 70% have at least one VC director, 9% have at least
one female VC director, and VC directors hold 16% of board seats, on average.
Panel B examines market model abnormal returns based on pre-SB 826 board composition.
The mean (median) market model Abnormal Return on October 1, 2018 is -1.17% (-1.05%). Given
that our sample represents over $5.2 trillion in market value, the -1.17% equals a wealth loss of
over $60 billion. Mean Abnormal Return is -1.29% (-1.12%) for firms with no (at least one) female
directors. Only 71 California firms (11.8%) meet the 2021 requirements set by SB 826 (i.e., Gap
= 0). Mean Abnormal Return declines monotonically as Gap decreases and is most negative for
firms with Gap of 3 (-1.64%). Further, column (3) shows that firms with Gap of 2 or 3 have returns
that are significantly more negative, on average, than those with Gap of zero. Our conclusions are
unchanged if we use test statistics that account for event-date clustering, event-induced volatility,
and return non-normality, reported in columns (6), (7), and (8), respectively. Overall, these results
indicate that SB 826 has a significantly negative effect on firms, especially those that need to add
more female directors to comply with the 2021 quota.
6. Multivariate Analysis
6.1. Portfolio Abnormal Returns
In Panel A of Table 2, we follow the procedure discussed in Section 5.2 to calculate
calendar-time portfolio abnormal returns by regressing daily portfolio excess returns on daily
CRSP excess returns and on indicators for the four dates in the SB 826 legislative process described
in Section 2. In column 1, the event date is October 1, 2018, the first day of trading following the
signing of SB 826 into law. We find a significantly negative coefficient of -0.011 on the indicator
(t-statistic = -2.458), suggesting that SB 826 is value decreasing for shareholders of California
17
firms.7 In columns 2 through 4, we examine the other three legislative event dates relating to SB
826. If we observe significant market responses on any of these dates, it may indicate that the
market anticipated the signing of the bill. However, much proposed legislation fails to be signed
into law, so the passage of the bill in the House or Senate is not necessarily an indication that it
will ultimately be signed into law. We find no significant stock price reaction on these days, which
suggests that the signing of SB 826 into law by Gov. Brown was unexpected.
While Panel A focuses on October 1st as the event date, in Panel B we perform robustness
tests around alternate windows. In column 1, we find no significant abnormal return on September
28, the trading day prior to the signing of the law. We do find a negative and significant return on
October 2 (column 2). Columns 3 and 4 show that the abnormal returns continue to be negative
and significant if calculated over longer windows.
Panel C separates the sample by director need. Column 1 (3) shows the coefficient on the
October 1st indicator for the firms needing at least one female director by 2019 (2021). Column 2
(4) reports the coefficient on the indicator for firms that already meet the 2019 (2021) mandate.
As in Table 1, excess returns are negative and statistically significant regardless of whether the
2019 quota is already met. However, the coefficient on the October 1st indicator is not significantly
different from zero for firms that meet the 2021 mandate but is negative and statistically significant
for firms whose pre-SB 826 board structure does not meet the 2021 requirement.
In Panel D, we create portfolios based on Gap and repeat the regression in column 1 of
Panel A. For the portfolio of firms with Gap=0, column 1 shows a negative, but statistically
7 In untabulated results, we calculate value-weighted (rather than equal-weighted) portfolio excess returns and regress
them on the value-weighted CRSP index. An issue with this approach is that the portfolio is dominated by a handful
of large companies. Six companies (Apple, Alphabet, Chevron, Visa, Cisco, and Oracle) have a combined weight of
33.34% in the portfolio and have positive returns on October 1. Further, the largest firms in our sample tend to have
low Gap (either 0 or 1), so SB 826 has less impact on them. Potentially due to these issues, we do not find statistical
significance on the October 1 dummy in the full sample when value weighting. We do find negative and statistically
significant coefficients on the October 1 dummy for the firms with Gap = 2 and Gap = 3, however.
18
insignificant, coefficient on the October 1st indicator. For firms with Gap = 1, 2, or 3 (columns 2,
3, and 4, respectively), the coefficient on the October 1st indicator is negative and statistically
significant at the 5% level. Further, the magnitude of the coefficient increases as Gap increases,
suggesting that shareholders are worse off as Gap increases.
6.2. Baseline Cross-sectional Regressions
We next examine the cross-sectional variation in stock market reactions to the signing of
SB 826. Table 3 shows the results of ordinary least squares (OLS) regressions in which the
dependent variable is Abnormal Return. Our key variables of interest across the four columns are:
(1) an indicator equal to one if at least one female director must be added to the board by the end
of 2019 (Add Female Director 2019), (2) an indicator equal to one if at least one female director
needs to be added to the board by 2021 (Add Female Director 2021), (3) Gap, and (4) Gap%. The
regressions control for Board Size, Market Value, industry (based on two-digit SIC code) and
financial characteristics (ROA, Cash to Assets, Leverage, Cash Flow Volatility).
In column 1 of Table 3, we find a negative, but statistically insignificant, coefficient on
Add Female Director 2019. This evidence is in line with the univariate results above and suggests
that the 2019 requirement to have one female director on the board of every firm is value-neutral.
In column 2, we find a negative and statistically significant coefficient (t-statistic = -4.474) on Add
Female Director 2021, which suggests that the more onerous 2021 requirements of SB 826 are
value decreasing for firms. In column 3, the coefficient on Gap is negative and statistically
significant (t-statistic = -3.044) indicating that abnormal returns are worse for firms that are further
from the requirements of SB 826. The economic significance suggests that firms experience a
0.50% decline in value for every additional female director needed. Column 4 shows a negative
coefficient on Gap% (t-statistic = -2.068), again suggesting that the negative effects of SB 826 on
19
firm value increase as more female directors are needed to comply with the mandate. Overall, these
results are consistent with the hypothesis that gender quota laws can be value decreasing. We note
that regardless of the methodology used to examine abnormal returns (portfolios or cross-sectional
tests), the abnormal return is more negative when Gap is larger.
6.3. California Firms versus Control Firms
A concern with our findings is that gender diversity on corporate boards has received
increased attention in all states. Therefore, the changes in value for California firms may simply
reflect overall trends in gender diversity and not specifically the effect of SB 826. To alleviate this
concern, we form a control sample of Russell 3000 firms that are not directly impacted by SB 826.
Since states sympathetic to California’s political ideology may enact similar laws, we exclude
firms headquartered in states that, like California, have voted for the Democratic nominee for
President in each of the past five elections (from 2000 to 2016). To the extent that any of the states
that remain in our control sample are sympathetic to California, it would bias our results
downward. We obtain the board characteristics of Russell 3000 firms from ISS, and for
consistency across treatment and control samples, we also exclude non-Russell 3000 California
firms. In Panel A of Table 4, we repeat the regression specifications of Table 3 on the pooled
sample of 429 California firms and 1,313 non-California control firms. We create a dummy that
equals 1 for California headquartered firms (CA Firm) and we interact this dummy with our main
variables of interest. The interaction term is negative and statistically significant in all four
regressions, indicating that the negative impact of SB 826 is greater for firms headquartered in
California than for control firms.
A concern with the pooled sample is that control firms have different board characteristics
than California firms. For instance, the mean number of female directors is significantly greater
20
for non-California firms (1.55 vs. 1.42) and mean Gap is significantly lower (1.47 vs. 1.59).
Therefore, in Panel B of Table 4, we refine our control sample by matching each California firm
with up to three control firms in the same industry, with the same Gap, and closest in sales. After
matching, the mean number of female directors is similar (1.40 vs. 1.37) and mean Gap is 1.60 for
both groups. Thus, the matched firms have similar pre-SB 826 board structure, are similar in size,
and face similar industry dynamics as California firms.8 Using the matched sample as a benchmark
in Panel B, we again find negative and statistically significant coefficients on the interaction terms.
These tests provide further evidence that SB 826 negatively affects the market value of California
firms.
6.4. Female Director Labor Supply Constraints
Although the average market reaction to SB 826 is negative, our paper does not imply that
the presence of female directors destroys firm value. Instead, the negative reaction is likely driven
by the mandated quota, which constrains board composition and imposes additional costs on the
firm (as discussed in Section 4). In Tables 5 through 7, we conduct cross-sectional tests to explore
how the supply of potential female directors, the ease with which directors can be replaced, and
the ability to attract female directors affect stock market reactions to SB 826. Due to the
endogenous nature of corporate boards, we do not interpret these tests as causal but rather as
providing suggestive evidence on the variation in stock market reactions.9
In Table 5, we examine the role of labor supply constraints on the stock price reaction to
SB 826. To proxy for the supply of female candidates, we first use Execucomp data on female
8 While board characteristics are similar in the matched sample, we continue to find differences in financial
characteristics such as sales and assets (von Meyerinck, et al. (2019) describe a similar issue). In robustness tests, we
match on Gap and closest in sales, and find that the differences in mean sales and assets disappear and the interaction
terms in our regressions remain statistically significant.
9 In Tables 5 - 8, we focus on Gap rather than Gap% because the number of female directors needed is likely more
relevant than the percent. Further, all results are conditional on pre-SB 826 board size since Board Size is a control
variable. The results are robust in 17 out of 19 models if we use Gap%.
21
CEOs. The intuition is that industries with fewer female CEOs may have a lower supply of
candidates. We create dummies for industries with zero female CEOs over the past five years (Zero
Female CEOs) using two different industry definitions: two-digit NAICS and Fama-French 48.
Our results are robust to measuring female CEOs over the past year, however. Because CEOs of
rival firms are unlikely to be candidates, we exclude each firm’s six-digit NAICS code and four-
digit SIC code, respectively, from the analysis.
Columns 1 and 2 of Table 5 report the results of regressions in which the dependent variable
is Abnormal Return and the key independent variables are Gap, Zero Female CEOs, and
interactions between Gap and Zero Female CEOs. The coefficients on both interaction terms are
negative and statistically significant at the 5% level, indicating that the negative effects of SB 826
are accentuated when the supply of potential female directors is constrained.
We also use female director representation within the industry as a proxy for supply. It is
not clear whether a high proportion of existing female directors in an industry indicates that future
female board candidates will be easy or difficult to obtain. On the one hand, more female directors
in an industry may signal that there are many female candidates to choose from, making it easier
to comply with SB 826. On the other hand, an industry with many existing female directors may
indicate a limited supply of available female candidates. Therefore, firms that are not already in
compliance will have difficulty finding female candidates, as the best candidates are already taken
or are busy with their existing directorships.
We use data on Russell 3000 firms to measure female director representation in each two-
digit NAICS and Fama-French 48 industry. High Industry Female Directors is a dummy variable
equal to 1 if the number of female directors divided by the number of firms in the industry is above
the sample median. In columns 3 and 4 of Table 5, the interactions of this dummy variable with
22
Gap are negative and statistically significant, suggesting that the effect of Gap is more negative
for firms in industries with greater female director representation. We interpret these results as
evidence that firms may struggle to find female candidates if they currently fall short of SB 826
mandates and operate in industries where supply is limited.
6.5. Ease of Replacement: VC Directors, Director Committee Assignment, and Age
SB 826 forces firms to choose between replacing existing directors or expanding the board.
As previously discussed, if the cost of replacing male directors is low and the supply of female
candidates high, then SB 826 will have a relatively small impact on firm value. However, we
predict a more negative reaction to SB 826 if the cost of replacing male directors is high, as firms
will be faced with a difficult replace or expand decision. One issue with replacing existing directors
is that board seats rarely become available (Fuhrmans, 2019). However, since VC directorships
are often tied to investor rights agreements that are conditional on the VC’s ownership level, VC
directors typically retire as the firm ages and the VC exits its investment, thus opening up seats
which can be filled by female directors to meet the SB 826 mandates. Consistent with VC directors
retiring over time, 52% of firms age 1 to 4 have at least one VC director compared to only 31% of
firms age 7 to 10. Thus, our first proxy for ease of replacement is the number of male VC directors
relative to the number of female directors needed (Gap). We focus on male VC directors because
replacing a female VC director with another female director does not reduce Gap. In column 1 of
Table 6, we find a positive and statistically significant (5% level) coefficient on this variable,
indicating that abnormal returns are less negative for these firms.10
We next proxy for ease of replacement by examining committee assignments and director
age. Independent directors gain valuable experience by serving on committees and thus should be
10 In untabulated results, we find that the positive effect is driven by older firms, which is consistent with the ability
of these firms to replace male VC directors with female directors as the VCs retire from the board.
23
more costly to replace. In contrast, directors who do not serve on committees are easier to replace
as their presence is less vital to the operation of the board and their replacement less disruptive. In
fact, Nguyen and Nielsen (2010) find that unexpected director deaths result in more negative
market reactions if the director is on the audit or nominating committee. Thus, we create a dummy
variable equal to 1 for firms in which the number of directors with no committee assignments is
equal to or greater than Gap. We also proxy for ease of replacement with director age, creating
dummy variables equal to 1 for firms in which the number of old directors (age 72 or 75 and above,
respectively) is greater than or equal to Gap. In columns 2 through 4 of Table 6, the coefficients
on our committee- and age-related ease of replacement proxies are positive and statistically
significant at the 10% level or better. Overall, this evidence is consistent with positive effects for
firms that can more easily replace directors and therefore do not need to expand the board in order
to satisfy SB 826.11 The last two rows of Table 6 show predicted abnormal returns based on the
regression estimates. Predicted returns are negative for all groups, so the positive coefficients on
our ease of replacement proxies do not signify a positive reaction to the law but indicate that the
response is less negative for firms with directors that are easier to replace.
6.6. Estimating the Ability to Recruit New Directors: Firm Age and VC Representation
In this section, we examine two proxies for the ability of firms to attract female directors:
firm age and firms backed by VCs with a female presence. Younger firms may be less well known
and may find it difficult to recruit candidates. However, VCs provide access to financing, strategic
advice, and play an active role in governance (Celikyurt, Sevilir, and Shivdasani, 2014; Krishnan
11 In untabulated results, we examine the role of director tenure. On one hand, directors with longer tenure could be
easier to replace if they are closer to retirement. On the other, long-tenured directors have more human capital and
firm-specific knowledge that is difficult to replace. We calculate the number and percent of directors with ten or more
years of board service and interact these variables with Gap. The interaction terms are negative and statistically
significant, suggesting that the negative effects of SB 826 are more pronounced for firms with long-tenured directors.
24
et al., 2011), and can aid firms in the director search process. Columns 1 and 2 of Table 7 divide
our sample into below versus above median firm age (13 or below versus 14 or above,
respectively). The results indicate that the negative relation between Gap and Abnormal Return is
only evident for firms with below median age. For firms with above median age, there is no
significant effect of Gap on Abnormal Return. In column 3, we interact Gap with a dummy variable
equal to 1 if firm age is below the median. The interaction term is negative, but not statistically
significant. While the lack of significance is surprising given the strong results in the sub-sample
split, further analysis shows that firm characteristics differ significantly between the two groups.
In particular, the mean and the distribution of Board Size, Female Directors, Market Value, Total
Assets, Sales, ROA, Cash to Assets, Cash Flow Volatility, and Director Pay are all significantly
different at the 1% level. In addition, the industry distribution differs between the two groups.
Thus, the lack of statistical significance is likely driven by the fact that the specification in column
3 forces the control variables to have the same slopes regardless of firm age.
Our second proxy for the ability to recruit female candidates is based on VC backing by
funds with a female presence. Young firms may be able to offset the negative effects of SB 826
by relying on their VC networks to attract female directors. Brush, Greene, Balachandra, and Davis
(2014) report that only 6% of VCs have a female partner, therefore VC backing can be particularly
valuable if the VC has a female presence. We examine the joint effect of firm age and VC backing,
focusing on firms that have been public for 10 years or less for which we collect VC data. To do
so, we interact Gap with an indicator for young firms that are backed by VC funds with a female
presence (Young Female VC Backed). In column 4 (5) of Table 7, we define young based on the
median (lowest tercile) of firm age within the sample of firms with VC data. The interaction terms
are positive and statistically significant in both columns, suggesting that younger firms benefit
25
from connections with female VCs. These connections may offset the negative effect of firm age
on Gap, since female VCs can serve on boards themselves or help recruit female directors. In
summary, Table 7 shows that SB 826 is particularly harmful for younger firms, but this effect is
offset for young firms with connections to female VCs.
6.7. Considering Relevant Bills Signed in Conjunction with SB 826
Gov. Brown decided on several other bills at the same time as SB 826 that impact publicly
traded firms in California. One of the most visible was California’s net neutrality law (SB 822).
Support for the law was mixed. Most broadband providers were in favor of the law, but others
voiced concern that it conflicted with federal regulation (Doubek, 2018). To identify firms most
affected by this law, we create a dummy variable (Telecom) equal to one for firms in the US
Telecom trade group or in SIC code 48 (Communications). Column 1 of Table 8 presents results
from our main cross-sectional regression and adds Telecom to the specification. The negative
coefficient on Gap holds, indicating that the signing of the net neutrality law is not driving our SB
826 results.
We also consider laws related to SB 826 that passed and could affect our results. These
include: (1) SB 1343, which requires mandatory training on sexual harassment and provides easier
access to authorities if an employee is harassed; (2) SB 820, which bans nondisclosure agreements
in sexual harassment, assault, and discrimination cases; and (3) SB 1300, which prohibits
employers from forcing new employees or those seeking raises to sign non-disparagement
agreements or waive their rights to file legal claims. These bills potentially increase costs to firms
and thus could negatively impact stock returns. The governor also vetoed AB 1870, which would
have extended the deadline to file harassment or discrimination complaints from one to three years,
and AB 3080, which would have banned firms from requiring workers to participate in private
26
arbitration to settle disputes such as sexual harassment claims. The vetoing of these bills would
likely positively impact stock prices and bias against finding negative announcement returns.
We use Google Trends to examine public interest in these bills over the two months
surrounding September 30, 2018. If we observe strong interest in these laws, then we may have an
identification concern. Figure 1 shows that compared to the other laws, SB 826 dominates search
interest, receiving a score of 100 (the highest achievable interest score) on October 1st. After SB
826, the bills that generate the most interest are AB 3080 and SB 1343, both of whose scores peak
at 40. Nonetheless, to identify firms most affected by the passage of laws relating to sexual
harassment concerns, we collect information on firms with employees facing #MeToo accusations
using data from Bloomberg (Griffin, Recht, and Green, 2018). If the market perceives such
accusations as being representative of larger firm-level deficiencies (e.g., unfair working
conditions for women in these firms) and these firms lack female board representation, then the
passage of related laws may drive our results. We create a variable (MeToo Firm Dummy) to
identify firms in which employees have been publicly accused of sexual misconduct over the one-
year period beginning on October 7, 2017. Results are reported in column 2 of Table 8. We find
an insignificant coefficient on the Gap x MeToo Firm Dummy interaction, while Gap remains
significant. Overall, these results suggest that the negative announcement returns on October 1st
relate to the signing of SB 826 and not to other bills that were considered simultaneously.
6.8. Robustness Tests
Although we include cash flow volatility as a control variable in all of our tests, it may not
control for all firm risks. For example, Adhikari, Agrawal, and Malm (2019) find that firms with
two or more women in top management face fewer operations-related lawsuits. To proxy for this
type of risk, we follow Adhikari et al. (2018) and add a control for the number of women in the
27
top management team to our regressions. Column 3 of Table 8 includes a dummy for firms with
two or more women among the highest paid executives (Multiple Female Executives). We continue
to find a negative and statistically significant effect on Gap in this specification.
Since fewer females work in high tech and STEM (Science, Technology, Engineering,
Math) industries, it may be difficult for these firms to identify female directors (Adams and
Kirchmaier, 2016). Columns 4 and 5 examine whether the effect of SB 826 is more severe for
firms in these industries, using proxies from Loughran and Ritter (2004) (High Tech) and Adams
and Kirchmaier (2016) (STEM). The coefficients on interactions between Gap and the High Tech
and STEM proxies are not significant. Finally, column 6 of Table 8 examines the sensitivity of our
results to excluding financials and utilities (SIC codes 60-69 and 49). We continue to find a
negative and statistically significant effect on Gap in this sub-sample.
The majority of California firms (82%) are incorporated in Delaware. Grundfest (2018)
speculates that SB 826 will be challenged on the grounds that it only applies to firms incorporated
in California. Consequently, we examine whether the impact of the law is stronger for these firms.
In column 7 of Table 8, we interact Gap with a dummy for firms incorporated in California and
find no evidence of a differential stock price reaction for these firms. We discuss how this finding
sheds light on potential legal challenges to SB 826 in Section 7.3.
7. Direct Costs of SB 826 and Responses to SB 826
7.1. Director Pay and Costs of Compliance
In this section, we examine the direct costs of compliance stemming from adjustments to
the size of the board. Thus, while Section 6 studies market reactions to measure the indirect costs
of SB 826, this section uses director pay to measure the direct costs. We then compare the
28
observable costs of director remuneration to the cost of non-compliance, which is $100,000 for the
first violation and can increase to up to $700,000 for subsequent violations.
Annual director compensation (Director Pay) averages $181,999 across the entire sample,
as shown in Table 1.12 However, there is a wide dispersion in director pay. Table 9 shows a strong
relation between Director Pay and Market Value, with the smallest decile firm paying directors an
average of $77,829 and the largest paying $326,133. While the smallest firms pay the least in raw
dollars, they have the highest relative pay. Average Director Pay represents 0.34% of market value
for the smallest firms but only 0.001% for the largest. Figure 2 plots raw and normalized Director
Pay and shows that pay scaled by market value declines sharply when moving from the first to
third decile and levels off around the sixth decile. Similar patterns are found when scaling by total
assets. When scaling by sales, the impact on small firms is even more apparent, with the smallest
two size deciles incurring additional costs of over 8% of sales.
We next calculate the observable expected costs of expanding the board (see Appendix A
for details). For firms in the smallest decile, the mean of Expand is 2.30 board seats, representing
an average annual cost $176,101 (0.76% of market value and 13.2% of sales). Since small firms
with low sales likely have negative cash flows, expansion is particularly costly for them. These
firms are also likely to have difficulty attracting female directors. Costs of expansion are non-
trivial for many firms in the sample. Untabulated results show that 19% of firms in the bottom two
deciles face direct annual costs of expansion in excess of 1% of market value, while 32% face
costs greater than 1% of sales. Overall, this table highlights the potentially large direct costs of SB
826 on small firms.
12 Director Pay is a lower bound estimate of the cost of adding a new director, since it (1) ignores unobservable indirect
costs such as D&O insurance and travel and lodging expenses for board meetings, and (2) is calculated using firm
median director pay levels, which may underestimate the cost of hiring new board members if their compensation
exceeds the median director’s pay due to initial grants of stock or options.
29
7.2. Measuring the Firm Response to SB 826: Changes to Board Composition
We analyze changes in board composition around the passage of SB 826. We hand collect
data on board size, number of women, and number of independent directors for 488 firms that filed
proxy statements between January and July 2019 and compare pre-SB 826 and post-SB 826 values.
Panel A of Table 10 shows that mean board size, and number and percentage of female directors,
increase significantly after SB 826, while Gap and Gap% fall significantly (all changes are
statistically significant at the 1% level). Specifically, the number of female directors per firm rises
by 0.29, from 1.26 to 1.55, while the percentage rises by 3.4%, from 15.0% to 18.5%. This
evidence shows that California firms have added female directors in response to SB 826.
Panel B shows the frequency distribution of the number of female directors before and after
the passage of SB 826. Prior to SB 826, 129 firms (26.4%) had zero female directors; after SB
826, this falls to 70 firms (14.3%). These 70 firms are not in compliance with the 2019 mandate
as of their 2019 proxy filing. One explanation for the lack of response by these firms is that the
cost of adding a female director is prohibitive. In untabulated results, we find that Director Pay
averages $141,199 for these firms, which exceeds the $100,000 penalty for noncompliance.
We also examine the 136 firms that added at least one female director (conditional on Gap
> 0). In contrast to what was observed following Norway’s gender quota (Ahern and Dittmar,
2012; Eckbo et al., 2019), we find that more firms choose to expand the board rather than replace
male directors. In particular, 81 firms (60%) expand the board to accommodate new female
director(s) while 55 firms (40%) replace male directors. Firms that chose to expand the board have
significantly lower board size than those that replace directors (7.07 compared to 8.09), suggesting
that increasing board size is costly, particularly for those that already have a large board.
30
Finally, we compare California firms to the control firms described in Section 6.3. For each
California firm, we match to a non-California firm by industry, pre-SB 826 Gap, and closest in
sales. We search for proxy statements for these firms and find data for 258 unique firms. Firms
outside of California experience an increase in number of female directors and percent of female
directors following SB 826, though the magnitudes (0.21 and 2.3%, respectively) are lower than
in California firms. In Panel C, we conduct multivariate analyses on the pooled sample of
California and control firms. In columns 1 and 2, the dependent variables are the change in the
number and percentage of female directors from pre- to post-SB 826. The coefficient on CA Firm
is positive and statistically significant at the 5% level in both columns, indicating that the increase
in female directors is not due to a general trend of increasing female board representation in all
firms. In columns 3 and 4, the dependent variables are the change in Gap and board size. The
change in Gap is significantly more negative for California firms, suggesting that these firms are
responding to SB 826. The change in board size is not significantly different, which could be
driven by some California firms expanding the board while others replace directors.
Overall, Table 10 provides evidence that firms respond to SB 826 by adding women to
their boards and that many firms prefer to expand the board to do so. However, we caution that
this evidence is preliminary, as not all firms have filed proxy statements for 2019 and firms have
until the end of the 2019 calendar year to comply.
7.3. Considering the Legality of SB 826
Our results suggest that the signing of SB 826 negatively impacted the stock prices of firms
headquartered in California and that the impact was more negative for firms with larger Gap. The
evidence in Table 10 further suggests that many firms are complying with the law by adding
women to their boards, despite legal challenges. Even if the current lawsuit is successful in
31
reducing financial penalties, firms in California will likely face public pressure to meet the legal
requirements of the mandate (which would remain in place).
While legal scholars argue that SB 826 may only apply to firms both headquartered and
incorporated in California, in Table 8 we find no differential market reaction between firms
incorporated in California and elsewhere. One interpretation of the result in Table 8 is that the
market believes the law will be upheld for all public firms headquartered in California, regardless
of state of incorporation. Even if SB 826 is on shaky legal ground, affected firms may be reluctant
to directly challenge the law if doing so will result in public backlash. Given the uncertain legal
environment, the experiment may also not be sharply identified. However, uncertainty about the
legality of the law would only attenuate our results.
Another interpretation of Table 8 is that, regardless of whether the law is struck down, it
signals stronger demand for gender equality on corporate boards. Recently, institutional investors
BlackRock and State Street Advisors have publicly advocated for their portfolio companies to
increase gender diversity (Krouse, 2018). However, this interpretation does not explain why
returns are more negative for California firms with larger Gap, which is calculated based on the
specific requirements of SB 826. Further, it does not explain why we find significantly stronger
results for California firms than non-California firms in tests of abnormal returns and changes in
board composition, since firms in all states would be pressured by these institutions.
Given our results, the most likely explanation is that firms are choosing to respond to the
law either because it will be upheld in court or because public pressure motivates them to meet the
mandate’s requirements even if the financial penalties are reduced.
32
8. Conclusion
We examine the impact of California’s board gender diversity mandate (SB 826) on the
602 publicly traded firms headquartered in the state. These firms experience a large negative stock
market reaction at the signing of the law. This reaction is more pronounced for firms that are
required to add more female directors and for California firms compared to control firms in other
states. The results are robust to different methodologies and do not appear to be related to other
laws passed in conjunction with SB 826.
The negative stock price reaction does not mean that adding female directors reduces firm
value, but can be interpreted as the law imposing a constrained optimization on board composition.
We find that firms which can more easily adjust board structure, such as firms in industries with a
greater supply of female candidates and firms that can more easily replace existing directors or
more easily attract female directors, are less negatively affected by the mandate. These findings
suggest that male and female directors are largely interchangeable for some firms.
We also examine the direct costs of compliance and changes in board composition
following SB 826. The costs of board expansion are negligible for the largest firms but substantial
for the smallest. For many firms, the costs of expansion outweigh the 2019 penalties for non-
compliance. Following SB 826, firms significantly increase the number and percent of female
directors. These changes are greater for California firms than control firms, and thus are not driven
by a general trend of increasing gender diversity. Sixty percent of firms expand board size to
accommodate new female directors. Board size in these firms is lower compared to the firms that
replace male directors, which is consistent with boards facing significant costs of expansion.
Overall, our paper sheds new light on gender diversity in the corporate board room and on the
effects of mandatory board gender quotas on firms.
33
Future research can investigate the impact of legal challenges to California SB 826 as well
the impact of board gender quotas in other states that may pass similar legislation. In addition,
research can examine changes in firm policies after women are added to the board as a result of
gender quotas.
34
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Appendix A: The Replace vs. Expand Decision
In Appendix Table 1, the columns under the “Assume Replace” heading assume that the
pre-SB 826 board size remains fixed and male directors will be replaced with female directors if
needed. Gap% can be as high as 50% for firms that have no female representation (i.e., half of the
board will need to be replaced by female directors by 2021).
Firms can also increase board size to satisfy the requirements of SB 826. We calculate the
number of additional female directors needed to comply assuming board expansion (Expand) in
the “Assume Expand” columns of Appendix Table 1. For four or five member boards, increasing
board size to satisfy SB 826 may trigger further increases in the number of female directors needed.
For example, if a board has four members, the law requires at least one female director by the end
of both 2019 and 2021. For boards with zero female directors, Gap is 1 and Gap% is 25% (1/4).
If the firm adds a female director and retains all existing male directors, board size will expand to
five. A five-member board, however, requires two female directors by 2021. Adding a second
female director increases the board size to six, which necessitates adding a third female director
and expanding the board to seven members. Adding three directors to comply with the mandate is
an increase of 75% of the original board size (Expand% = 3/4 = 75%), which is strikingly different
from the numbers obtained under the assumption of replacement. Thus, a firm with a four-member
board and no female representation can either (1) replace one male director with a female director
or (2) retain all existing members and add three additional female directors by expanding to a
seven-member board. Appendix Table 1 outlies a similar scenario for five member boards that
have no female directors. A six member (or greater) all-male board must add three female directors
by 2021. Firms can accomplish this by replacing male directors, expanding the board, or a
combination of the two options.
39
Appendix Table 1: Board Structure and SB 826 Mandates
This table shows the 2019 and 2021 gender requirements of SB 826 for firms, conditional on board size. In the Assume Replace columns we
report the effect on boards conditional on existing directors being replaced by female candidates. In the Assume Expand columns we report
the effect on boards conditional on the firm expanding board size to accommodate female directors. Gap is defined as the difference between
the mandated number of female directors the board must have by 2021 and the pre-SB 826 number of female directors. Gap% is Gap divided
by pre-SB 826 board size. Expand is the number of female directors that must be added to the board by 2021 assuming that no current board
members are replaced. Expand% is Expand divided by the pre-SB 826 board size.
SB 826 Requirements
Assume Replace
Assume Expand
Pre- SB
826
Board
Size
Female
Directors
Required
Female
Directors
2019
Required
Female
Directors
2021
Female
Directors
Added
(Gap)
% Female
Directors
Added
(Gap%)
Board
Size
2021
Female
Directors
Added
(Expand)
% Female
Directors
Added
(Expand%)
Board
Size
2021
4
1
1
1
25%
4
3
75%
7
0
0
0
0%
4
0
0%
4
5
1
2
2
40%
5
3
60%
8
0
1
1
20%
5
2
40%
7
0
0
0
0%
5
0
0%
5
6 or more
1
3
3
50%
6
3
50%
9
0
2
2
33%
6
2
33%
8
0
1
1
17%
6
1
17%
7
0
0
0
0%
6
0
0%
6
40
Appendix B: Variable Definitions
Variable Name
Construction
Abnormal Return
Market model adjusted stock return on October 1, 2018, the first trading day
after the Governor signed SB 826
Gap
The difference between the mandated number of female directors the board
must have by 2021 and the pre-SB 826 number of female directors
Gap%
Gap divided by pre-SB 826 board size
Add Female Director 2019
Dummy that takes a value of one if the pre-SB 826 board has zero female
directors and zero otherwise
Add Female Director 2021
Dummy that takes a value of one if Gap is positive and zero otherwise
Female Directors
Pre-SB 826 number of female directors
Expand
The number of female directors that must be added to the board by 2021
assuming that no directors are replaced
Expand(%)
Expand divided by pre-SB 826 board size
Total Assets
Compustat item AT
Sales
Compustat item SALE
ROA
Compustat items NI/AT
Leverage
Compustat items (DLC+DLTT)/AT
Cash to Assets
Compustat items CHE/AT
Cash Flow Volatility
Standard deviation of (IB+DP)/AT over the past ten years (minimum 3
years). If missing, we replace with industry median volatility.
Board Size
Pre-SB 826 number of directors on the firm’s board
Market Value
Stock price multiplied by shares outstanding, measured on April 17, 2018,
which predates the first hearing on SB 826 in the California Senate
Director Pay
Median compensation received by independent directors
Director Pay Expand
Director Pay multiplied by Expand. Represents increase in compensation to
directors if the board expands
Zero Female CEOs
Dummy that equals one if the firm’s industry has zero female CEOs over the
past five years and zero otherwise
High Industry Female Directors
Dummy that equals one if the number of female directors in an industry
divided by the number of firms in an industry is above the sample median
and zero otherwise
Firm Age
The number of fiscal years that the firm appears in Compustat, based on the
first fiscal year with non-missing stock price data
Number of VC Directors
The number of venture capitalist directors on the board. We match directors
employed by VC and/or PE firms with the VC/PE investors listed in SDC at
the time of the IPO; we consider these directors to be VC directors. Since
SDC often lists “undisclosed firms”
as VC investors, we also identify
directors as VC directors if they (1) are employed by a VC/PE firm, (2) were
a director before the IPO, and (3) are associated with an entity that has or had
a substantial investment in the firm.
Female VC Backed
Dummy that equals 1 if a firm has venture capital or private equity backing
from a fund with a female presence at its IPO. Female presence is identified
when a female holds the position of CEO, president, managing partner,
managing director, general partner, partner, or founder/cofounder
Young Female VC Backed
Dummy that equals 1 for young firms with venture capital or private equity
backing from a fund with a female presence at its IPO. Young is defined
based on sample median or lowest tercile.
41
Table 1: Summary Statistics and Univariate Tests
This table reports the summary statistics for the 602 firms headquartered in California that are affected by SB 826. Variables are
defined in Appendix B. Panel A shows the distribution of the key variables used in the analysis. Panel B reports the market model
Abnormal Return for the sample of all firms and according to the pre-SB 826 number of female directors and the number of female
directors that must be added by 2021 (Gap), respectively. Column (3) shows the difference in means between firms with 1+ female
directors and firms with zero female directors, as well as the difference in means between firms with Gap of one, two, three and firms
with Gap of zero. Tests for differences in means are based on t-tests. Columns (5) (8) show other tests of whether the mean abnormal
return for the given sub-sample of firms is different from zero and are based on a t-test, Kolari and Pynnonen (2010) (KP), Corrado
(1989) (C), and Corrado and Zivney (1992) (CZ), using Kaspereit’s (2018) command. ***, **, and * indicate statistical significance
at the 1%, 5%, and 10% levels, respectively.
Panel A: Summary Statistics
N
Mean
SD
p25
Median
p75
Board Size
602
7.81
2.03
6.00
8.00
9.00
Female Directors
602
1.22
1.09
0.00
1.00
2.00
Gap
602
1.68
0.91
1.00
2.00
2.00
Gap% (%)
602
23.60
14.26
12.50
25.00
33.33
Market Value ($mill)
602
8,790
30,811
177
834
3,007
Total Assets ($mill)
602
5,523
18,223
100
482
2,338
Sales ($mill)
602
2,352
7,606
36
249
1,081
ROA (%)
602
-16.76
39.69
-23.88
-0.39
3.93
Leverage
602
0.22
0.27
0.00
0.14
0.33
Cash to Assets
602
0.36
0.30
0.08
0.27
0.59
Cash Flow Volatility
602
0.37
1.28
0.03
0.09
0.23
Director Pay ($)
600
181,999.30
107,787.20
100,166.50
172,818.00
252,865.00
Female VC Backed
268
0.14
0.35
0
0
0
Num. VC Directors
268
0.77
1.09
0
0
1
Panel B: Abnormal Return Univariate Analysis
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Difference
Tests of Mean=0
No. firms
Mean
in Means
Median
t-test
KP
CZ
All Firms
602
-1.17%
n/a
-1.05%
***
***
***
Pre-SB 826 Number of Female Directors
0
171
-1.29%
n/a
-1.01%
***
**
**
1+
431
-1.12%
0.17%
-1.17%
***
***
***
Gap
0
71
-0.49%
n/a
-0.58%
**
**
**
1
167
-1.06%
-0.57%
-0.86%
***
**
**
2
249
-1.22%
-0.73%**
-1.36%
***
***
***
3
115
-1.64%
-1.15%***
-1.45%
***
***
**
42
Table 2: Portfolio Returns
This table reports stock return analysis based on daily portfolios, following the methodology in Eckbo, Nygaard, and Thorburn
(2019). The dependent variable is the daily equal weighted excess return. The portfolio includes only firms with at least 100
non-missing return observations in the estimation period and a return observation on an event date. The estimation period starts
252 days before the event date and excludes any earlier event dates. The key independent variables in Panel A columns 1, 2,
3, and 4 are dummies indicating the date that SB 826 was signed by the Governor (October 1, 2018), Passed the Assembly
(August 29, 2018), Passed the Senate (May 31, 2018), and was Introduced into the Senate (January 3, 2018), respectively.
Panel B reports the excess returns surrounding the event date (October 1, 2018) while Panel C provides excess returns for the
sub-samples of firms conditional on whether they need to add female directors by 2019 and 2021. In Panel D, the sample in
columns 1, 2, 3, and 4 includes firms with Gap equal to zero, one, two, and three, respectively. The key independent variable
in Panels C and D is a dummy indicating the date that SB 826 was signed by the Governor. For brevity, we do not report the
coefficients on Excess Value Weighted Return or the Constant in Panels B, C, and D. T-statistics are reported in parentheses.
***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels, respectively.
Daily Mean Excess Return
Panel A: Key dates in legislative process
(1)
(2)
(3)
(4)
Signed by Governor (Oct 1, 2018)
-0.011**
(-2.458)
Passed Assembly (Aug 29, 2018)
0.002
(0.518)
Passed Senate (May 31, 2018)
0.007
(1.559)
Introduced in Senate (Jan 3, 2018)
0.001
(0.223)
Excess Value Weighted Return
0.962***
0.975***
0.975***
1.315***
(26.649)
(27.622)
(28.509)
(25.429)
Constant
-0.000
0.000
0.000
0.003***
(-0.630)
(0.158)
(0.429)
(5.767)
Number of observations
250
251
252
253
Number of firms in portfolio
602
602
602
602
R-squared
0.74
0.75
0.77
0.72
Panel B: Alternate dates around October 1, 2018
(1)
(2)
(3)
(4)
September 28, 2018 (t=-1)
0.001
(0.208)
October 2, 2018 (t=+1)
-0.010**
(-2.043)
CAR (0,+1)
-0.010***
(-3.177)
CAR (-1,+1)
-0.007**
(-2.444)
Number of observations
250
250
250
250
Number of firms in portfolio
602
602
602
602
R-squared
0.74
0.75
0.75
0.74
continued…
43
Table 2, continued
Daily Mean Excess Return
Panel C: Sub-sample by Add Female Director Dummies
(1)
(2)
(3)
(4)
Add Female
Director 2019 = 0
Add Female
Director 2019 = 1
Add Female
Director 2021= 0
Add Female
Director 2021= 1
Signed by Governor (Oct 1, 2018)
-0.011**
-0.013**
-0.005
-0.012**
(-2.446)
(-2.015)
(-1.169)
(-2.477)
Number of observations
250
250
250
250
Number of firms in portfolio
431
171
71
531
R-squared
0.77
0.56
0.76
0.72
Panel D: Sub-sample by Gap
(1)
(2)
(3)
(4)
Gap = 0
Gap = 1
Gap = 2
Gap = 3
Signed by Governor (Oct 1, 2018)
-0.005
-0.010**
-0.012**
-0.016**
(-1.169)
(-2.014)
(-2.246)
(-2.455)
Number of observations
250
250
250
250
Number of firms in portfolio
71
167
250
114
R-squared
0.76
0.75
0.68
0.56
44
Table 3 Firm Value and the SB 826 Mandate
This table reports the results of ordinary least squares regressions on the sample of 602 California based firms
affected by SB 826. The dependent variable is Abnormal Return, which is the market model adjusted stock return
on October 1, 2018. Add Female Director 2019 is a dummy that takes a value of one if the board has zero female
directors. Add Female Director 2021 is a dummy that takes a value of one if Gap is positive and zero otherwise.
Gap is the difference between the mandated number of female directors the board must have in 2021 and the pre-
SB 826 number of female directors. Gap% is Gap divided by the pre-SB 826 board size. All other variables are
defined in Appendix B. Each regression includes industry (two-digit SIC code) fixed effects. T-statistics, reported
in parentheses, are based on standard errors clustered at the industry level. ***, **, and * indicate statistical
significance at the 1%, 5%, and 10% levels, respectively.
Abnormal Return
(1)
(2)
(3)
(4)
Add Female Director 2019
-0.005
(-1.145)
Add Female Director 2021
-0.010***
(-4.474)
Gap
-0.005***
(-3.044)
Gap%
-0.027**
(-2.068)
Board Size
0.000
0.000
0.000
-0.000
(0.389)
(0.389)
(0.526)
(-0.355)
Market Value
-0.002**
-0.002**
-0.002***
-0.002***
(-2.289)
(-2.442)
(-2.989)
(-2.714)
ROA
-0.000
-0.000
0.000
-0.000
(-0.142)
(-0.092)
(0.071)
(-0.035)
Cash to Assets
-0.003
-0.003
-0.002
-0.003
(-0.671)
(-0.671)
(-0.464)
(-0.611)
Leverage
0.003
0.003
0.004
0.003
(0.705)
(0.636)
(0.723)
(0.695)
Cash Flow Volatility
-0.001*
-0.001*
-0.001**
-0.001**
(-1.951)
(-1.999)
(-2.572)
(-2.177)
Constant
0.020***
0.029***
0.032***
0.031***
(4.707)
(5.463)
(5.088)
(3.941)
Industry FE
Yes
Yes
Yes
Yes
Observations
602
602
602
602
R-squared
0.08
0.08
0.09
0.08
45
Table 4: California Firms versus Control Firms
This table reports the results of ordinary least squares regressions on the sample of California and non-California
firms. The dependent variable is Abnormal Return, which is the market model adjusted stock return on October 1,
2018. Panel A includes non-California control firms headquartered in states less likely to be sympathetic to
California political ideals, as proxied by Presidential election results over the past five elections. These states
include AK, AL, AR, AZ, CO, FL, GA, IA, ID, IN, KS, KY, LA, ME, MI, MO, MS, MT, NC, ND, NE, NH, NM,
NV, OH, OK, PA, SC, SD, TN, TX, UT, VA, WI, and WV, respectively. Panel B includes up to three control firms
matched to each California firm by pre-SB 826 board structure, industry, and closest in size. CA Firm is a dummy
that takes the value of one for California headquartered firms. Add Female Director 2019 is a dummy that takes a
value of one if the board has zero female directors. Add Female Director 2021 is a dummy that takes a value of one
if Gap is positive and zero otherwise. Gap is the difference between the mandated number of female directors the
board must have in 2021 and the pre-SB 826 number of female directors. Gap% is Gap divided by the pre-SB 826
board size. Controls (not reported for brevity) include Board Size, Market Value, ROA, Cash to Assets, Leverage,
and Cash Flow Volatility. Each regression includes industry (two-digit SIC code) fixed effects. T-statistics, reported
in parentheses, are based on standard errors clustered at the industry level. ***, **, and * indicate statistical
significance at the 1%, 5%, and 10% levels, respectively.
Abnormal Return
Panel A: Pooled sample
(1)
(2)
(3)
(4)
Add Female Director 2019
0.001
(0.686)
Add Female Director 2019 x CA Firm
-0.006*
(-1.904)
Add Female Director 2021
0.001
(0.937)
Add Female Director 2021 x CA Firm
-0.007**
(-2.496)
Gap
-0.000
(-0.520)
Gap x CA Firm
-0.003***
(-2.962)
Gap%
-0.002
(-0.467)
Gap% x CA Firm
-0.014*
(-1.777)
CA Firm
-0.000
0.004*
0.004**
0.002
(-0.250)
(1.874)
(2.176)
(0.926)
Controls
Yes
Yes
Yes
Yes
Industry FE
Yes
Yes
Yes
Yes
Observations
1,742
1,742
1,742
1,742
R-squared
0.17
0.17
0.17
0.17
continued…
46
Table 4, continued
Abnormal Return
Panel B: Matched sample
(1)
(2)
(3)
(4)
Add Female Director 2019
0.005*
(1.759)
Add Female Director 2019 x CA Firm
-0.010***
(-3.621)
Add Female Director 2021
0.003
(0.954)
Add Female Director 2021 x CA Firm
-0.010**
(-2.347)
Gap
0.001
(0.804)
Gap x CA Firm
-0.005***
(-3.287)
Gap%
0.011
(1.003)
Gap% x CA Firm
-0.027***
(-3.088)
CA Firm
0.002
0.008**
0.008***
0.006***
(1.603)
(2.335)
(3.706)
(3.068)
Controls
Yes
Yes
Yes
Yes
Industry FE
Yes
Yes
Yes
Yes
Observations
1,658
1,658
1,658
1,658
R-squared
0.13
0.12
0.13
0.12
47
Table 5: Labor supply tests
This table reports the results of ordinary least squares regressions on the sample of 602 California based firms
affected by SB 826. The dependent variable is Abnormal Return, which is the market model adjusted stock return
on October 1, 2018. Gap is the difference between the mandated number of female directors the board must have
in 2021 and the pre-SB 826 number of female directors. Zero Female CEOs is a dummy that equals 1 if the firm’s
industry has zero female CEOs over the past five years. High Industry Female Directors is a dummy variable equal
to 1 if the number of female directors divided by the number of firms in the industry is above the sample median.
Controls (not reported for brevity) include Board Size, Market Value, ROA, Cash to Assets, Leverage, and Cash
Flow Volatility. Each regression includes industry (two-digit SIC code) fixed effects. T-statistics, reported in
parentheses, are bas
ed on standard errors clustered at the industry level. ***, **, and * indicate statistical
significance at the 1%, 5%, and 10% levels, respectively.
Abnormal Return
(1)
(2)
(3)
(4)
Gap
-0.004***
-0.004**
-0.003
-0.003
(-2.736)
(-2.560)
(-1.524)
(-1.303)
Zero Female CEOs (NAICS)
0.026**
(2.429)
Gap x Zero Female CEOs (NAICS)
-0.017**
(-2.355)
Zero Female CEOs (FF48)
0.019*
(1.777)
Gap x Zero Female CEOs (FF48)
-0.006**
(-2.243)
High Industry Female Directors (NAICS)
0.009*
(1.841)
Gap x High Industry Female Directors (NAICS)
-0.004**
(-2.122)
High Industry Female Directors (FF48)
0.007
(1.281)
Gap x High Industry Female Directors (FF48)
-0.004*
(-1.737)
Controls
Yes
Yes
Yes
Yes
Industry Fixed Effects
Yes
Yes
Yes
Yes
Observations
582
594
592
589
R-squared
0.09
0.09
0.09
0.09
48
Table 6: Ease of Replacement
This table reports ordinary least squares regressions on the sample of 602 California based firms affected by SB 826.
The dependent variable is Abnormal Return, which is the market model adjusted stock return on October 1, 2018. In
column 1, we restrict our analysis to a subsample of California firms that are ten years old or younger for which we
hand collect data from proxy statements on the presence of male directors associated with VC firms. All variables are
defined in Appendix B. Controls (not included for brevity) include Board Size, Market Value, ROA, Cash to Assets,
Leverage, and Cash Flow Volatility. Each regression includes industry (two-digit SIC code) fixed effects. The last two
rows give predicted values from the regression where all variables are set to their means and the dummy varies from
zero to one. T-statistics, reported in parentheses, are based on standard errors clustered at the industry level. ***, **,
and * indicate statistical significance at the 1%, 5%, and 10% levels, respectively.
Abnormal Return
(1)
(2)
(3)
(4)
Dummy if Male VC Directors >= Gap
0.005**
(2.725)
Dummy if “No Committee” Directors >= Gap
0.005*
(1.808)
Dummy if Directors Age 72+ >= Gap
0.007**
(2.213)
Dummy if Directors Age 75+ >= Gap
0.010***
(3.831)
Controls
Yes
Yes
Yes
Yes
Industry FE
Yes
Yes
Yes
Yes
Observations
268
601
602
602
R-squared
0.19
0.08
0.08
0.09
Predicted Abnormal Return
Dummy=0
-1.45%
-1.34%
-1.46%
-1.46%
Dummy=1
-0.96%
-0.79%
-0.79%
-0.49%
49
Table 7: Firm Age and Venture Capital (VC) Representation
This table examines the impact of firm age and venture capital backing on the market reaction to SB 826. Columns 1 and 2
divide the sample of California based firms affected by SB 826 into below versus above median firm age (13 or below versus
14 or above, respectively). Column 3 uses the entire sample of California based firms affected by SB 826 while Columns 4
and 5 use a subsample of California firms that are ten years old or younger. The dependent variable is Abnormal Return,
which is the market model adjusted stock return on October 1, 2018. Gap is the difference between the mandated number of
female directors the board must have in 2021 and the pre-SB 826 number of female directors. Young Female VC Backed is
an indicator set equal to 1 for young firms that are backed by VC funds with a female presence. In Column 4 (5), we define
young based on the median (lowest tercile) of firm age in the sub-sample of firms with VC data. Other variables are defined
in Appendix B. Controls (not included for brevity) include Board Size, Market Value, ROA, Cash to Assets, Leverage, and
Cash Flow Volatility. Each regression includes industry (two-digit SIC code) fixed effects. T-statistics, reported in
parentheses, are based on standard errors clustered at the industry level. ***, **, and * indicate statistical significance at the
1%, 5%, and 10% levels, respectively
Firm Age
Below Median
Firm Age
Above Median
(1)
(2)
(3)
(4)
(5)
Gap
-0.006***
-0.002
-0.004***
-0.006**
-0.005***
(-3.843)
(-0.867)
(-2.360)
(-2.692)
(-3.291)
Firm Age Below Median
0.001
(0.193)
Gap x Firm Age Below Median
-0.002
(-1.333)
Young Female VC Backed (Below Median)
-0.011
(-1.162)
Gap x Young Female VC Backed (Below Median)
0.008*
(1.778)
Young Female VC Backed (Below Tercile)
-0.014*
(-1.969)
Gap x Young Female VC Backed (Below Tercile)
0.016***
(3.527)
Controls
Yes
Yes
Yes
Yes
Yes
Industry FE
Yes
Yes
Yes
Yes
Yes
Observations
311
291
602
268
268
R-squared
0.18
0.09
0.09
0.21
0.21
50
Table 8: Additional Tests
This table reports robustness tests using ordinary least squares regressions on the sample of 602 California based firms
affected by SB 826. The dependent variable is Abnormal Return, which is the market model adjusted stock return on
October 1, 2018. Gap is the difference between the mandated number of female directors the board must have in 2021 and
the pre-SB 826 number of female directors. Telecom is a dummy that equals 1 for firms in the telecom industry (SIC 48)
or listed on the website of USTelecom. MeToo Firm Dummy is an indicator that equals 1 if the firm has an employee faced
with a #MeToo accusation. Multiple Female Executives is a dummy equal to 1 for firms with two or more women among
the highest paid executives. High Tech is a dummy variable that identifies firms in high tech industries based on four-digit
SIC codes as in Loughran and Ritter (2004). STEM is a dummy variable that identifies firms in STEM industries based on
NAICS codes as in Adams and Kirchmaier (2016). Column 6 excludes firms in the financial or utility industries.
Incorporated in CA is a dummy variable that equals 1 for firms that are incorporated in California. Controls (not reported
for brevity) include Board Size, Market Value, ROA, Cash to Assets, Leverage, and Cash Flow Volatility. Regressions
include industry (two-digit SIC code) fixed effects where noted. T-statistics, reported in parentheses, are based on standard
errors clustered at the industry level. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels,
respectively.
Abnormal Return
(1)
(2)
(3)
(4)
(5)
(6)
(7)
Gap
-0.005***
-0.005***
-0.005***
-0.005***
-0.010**
-0.005***
-0.005***
(-3.081)
(-2.987)
(-3.064)
(-3.214)
(-2.546)
(-2.948)
(-2.871)
Telecom
-0.002
(-0.558)
MeToo Firm Dummy
0.023*
(1.747)
Gap x MeToo Firm Dummy
0.001
(0.076)
Multiple Female Executives
-0.007**
(-2.519)
High Tech
-0.004
(-1.061)
Gap x High Tech
0.003
(0.897)
STEM
-0.005
(-0.938)
Gap x STEM
0.006
(1.525)
Incorporated in CA
-0.001
(-0.264)
Gap x Incorporated in CA
-0.001
(-0.405)
Controls
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Industry Fixed Effects
No
Yes
Yes
No
No
Yes
Yes
Observations
602
602
600
602
602
493
602
51
Table 9: Direct costs of SB 826
This table shows director compensation for the sample of 602 California based firms affected by SB 826. Statistics are reported within deciles of Market Value.
Director Pay is the median compensation received by independent directors. Expand is the number of female directors that must be added to the board by 2021
assuming that no directors are replaced. Director Pay Expand is a firm level variable that is equal to Director Pay multiplied by Expand.
Director Pay
($)
%mkt
%sales
%assets
Expand
Director Pay Expand
($)
%mkt
%sales
%assets
mkt10
N
mean
mean
mean
mean
mean
mean
mean
mean
mean
Smallest
61
$77,829
0.34%
8.53%
0.46%
2.30
$176,101
0.76%
13.17%
0.93%
2
60
$109,198
0.14%
8.36%
0.28%
2.38
$256,615
0.33%
16.06%
0.64%
3
60
$116,041
0.07%
2.78%
0.16%
2.25
$264,815
0.15%
5.07%
0.31%
4
59
$128,263
0.04%
2.99%
0.12%
2.28
$292,852
0.10%
5.63%
0.28%
5
60
$170,328
0.03%
1.89%
0.10%
2.07
$346,718
0.06%
3.01%
0.20%
6
60
$178,883
0.02%
1.78%
0.03%
1.72
$289,348
0.03%
3.10%
0.05%
7
60
$208,767
0.01%
0.21%
0.04%
1.58
$335,050
0.02%
0.43%
0.07%
8
60
$236,551
0.01%
0.29%
0.03%
1.43
$356,109
0.01%
0.38%
0.05%
9
60
$268,840
0.00%
0.03%
0.01%
1.50
$402,098
0.01%
0.05%
0.03%
Largest
60
$326,133
0.00%
0.01%
0.00%
0.68
$220,681
0.00%
0.01%
0.00%
52
Table 10: Board Changes Around SB 826
This table shows changes in board characteristics pre- and post- SB 826 for firms with proxy statements available
from January through July 2019. Panel A reports pre- and post-SB 826 board characteristics for 488 California
firms as well as changes and t-statistics. Panel B reports the frequency distribution of number of female directors
for 488 California firms in the pre- and post-SB 826 periods. Panel C shows multivariate results for California and
non-California control firms. For each California firm, we match to a non-California firm by industry, pre-SB 826
Gap, and closest in sales. We search for proxy statements for these firms and find data for 258 unique firms. Each
regression includes industry (two-digit SIC code) fixed effects. T-statistics, reported in parentheses, are based on
standard errors clustered at the industry level. ***, **, and * indicate statistical significance at the 1%, 5%, and
10% levels, respectively.
Panel A: Mean Board Characteristics for California firms
N
Mean
Pre-SB 826
Mean
Post-SB 826
t-statistic
Total Board Size
488
7.89
8.06
3.86***
Num. Female Directors
488
1.26
1.55
10.92***
Pct. Female Directors
488
15.0%
18.5%
10.37***
Pct. Independent Directors
488
79.3%
79.9%
1.86*
Gap
488
1.67
1.40
-10.69***
Gap%
488
23.3%
19.4%
-10.17***
Panel B: Frequency Distribution
N
Pct.
N
Pct.
Pre-SB 826
Post-SB 826
Number of Female Directors
0
129
26.4%
70
14.3%
1
182
37.3%
194
39.8%
2
124
25.4%
141
28.9%
3+
53
10.9%
83
17.0%
continued…
53
Table 10, continued
Panel C: Multivariate analysis
Change in
Num. Female Directors
Change in
Pct. Female Directors
Change in
Gap
Change in
Board Size
(1)
(2)
(3)
(4)
CA Firm
0.081**
0.009**
-0.068**
0.076
(2.390)
(2.494)
(-2.109)
(1.055)
Board Size
-0.000
0.000
-0.011*
-0.157***
(-0.048)
(0.220)
(-1.711)
(-3.459)
Num. Female Directors
-0.231***
-0.028***
0.208***
-0.061
(-6.392)
(-8.003)
(8.066)
(-1.186)
Market Value
0.081***
0.007***
-0.055***
0.157***
(5.435)
(4.580)
(-4.107)
(4.179)
ROA
-0.094
-0.015
0.107
-0.065
(-1.162)
(-1.368)
(1.344)
(-0.706)
Cash to Assets
0.091
0.012
-0.083
-0.080
(0.750)
(0.759)
(-0.975)
(-0.272)
Leverage
0.036
0.000
-0.048
0.115
(0.381)
(0.012)
(-0.542)
(0.789)
Cash Flow Volatility
-0.016***
-0.004***
0.048***
0.055*
(-3.931)
(-9.524)
(3.479)
(1.738)
Constant
-0.137
0.001
-0.255***
-0.410
(-1.412)
(0.147)
(-3.391)
(-1.289)
Industry FE
Yes
Yes
Yes
Yes
Observations
746
746
746
746
R-squared
0.18
0.19
0.18
0.14
54
Figure 1. Daily Search Interest for Bills Also Considered at the Time of the Signing of SB 826. This figure
reports the daily search interest from Google Trends during August through October 2018. Per Google, numbers
represent search interest relative to the highest point on the chart for the U.S. over the time period. A value of 100 is
the peak popularity for the term. A value of 50 means that the term is half as popular. A score of 0 means there was
not enough data for this term. Search interest scores for AB 1870 are not included since they equal 0 throughout the
entire range.
55
Figure 2. Median Director Pay by Deciles of Market Value. This figure shows mean Director Pay (in dollars),
which is defined as the median compensation paid to independent directors, and mean Director Pay scaled by market
value (in percent) by deciles of market value.
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