Mitigating Effects of Gender Diverse Boards in Companies Managed

by Overconfident CEOs∗

Suman Banerjee†

Ron Masulis‡

Arun Upadhyay§

This version: July 31, 2018

Abstract

Little research exists on matching CEO types with board composition. We examine whethergender-diverse boards help mitigate the negative effects of overconfident CEOs. We find strongerperformance in firms with overconfident CEOs and female independent directors. Exogenousdepartures of female independent directors trigger negative market reactions at firms with over-confident CEOs. We observe that female directors have different viewpoints, approaches and skillswhich can improve boardroom decision-making. Further, we find the benefits of gender-diversityis concentrated at firms with non-independent boards. Our results suggest that simple boardchanges are as effective in improving CEO behavior as more intrusive board regulation.

JEL Classification Code: G23, G32, G34

Keyword: Gender-diverse board, Female directors, Directors’ death, Firm performance, Inde-pendent board, Overconfident CEOs, Over-investment, SOX, SOX compliant firms

∗Suman Banerjee gratefully acknowledge SER Grant from the University of Wyoming. We would like to thank theparticipants at the Conference on Empirical Legal Studies (CELS) 2017 and particularly our discussant Brian JeffreyBroughman for many insightful comments. We would also to like to thank the participants at the Stevens’ Institute ofTechnology Seminar, the University of Wyoming Seminar, and the Indian Finance Conference 2017, Stefano Bonini,Xin Chang, Nan Hu, David Hirshleifer, Mark Humphery-Jenner, Angie Low, Vikram Nanda, Tom Noe, and StevenXiao for helpful comments. Usual disclaimer applies.

†Stevens Institute of Technology. Tel: (201) 216-3689. Email: sbanerj2@stevens.edu‡University of New South Wales, Australia. Tel: (612) 9385-5860. Email: ron.masulis@unsw.edu.au§Florida International University. Tel: (775) 682-9167. Email: arun.upadhyay@fiu.edu

Mitigating Effects of Gender Diverse Boards in Companies Managed

by Overconfident CEOs

This version: July 31, 2018

Abstract

Little research exists on matching CEO types with board composition. We examine whethergender-diverse boards help mitigate the negative effects of overconfident CEOs. We find strongerperformance in firms with overconfident CEOs and female independent directors. Exogenousdepartures of female independent directors trigger negative market reactions at firms with over-confident CEOs. We observe that female directors have different viewpoints, approaches and skillswhich can improve boardroom decision-making. Further, we find the benefits of gender-diversityis concentrated at firms with non-independent boards. Our results suggest that simple boardchanges are as effective in improving CEO behavior as more intrusive board regulation.

JEL Classification Code: G23, G32, G34

Keyword: Gender-diverse board, Female directors, Directors’ death, Firm performance, Inde-pendent board, Overconfident CEOs, Over-investment, SOX, SOX compliant firms

1 Introduction

“Diversity: the art of thinking independently together.” – Malcolm Forbes

We ask whether corporate boardroom diversity can help to moderate the actions of overconfident

CEOs: preserving the benefits of their overconfidence, while mitigating its negative aspects.1 The

extant literature has shown that exogenously-mandated governance-improving regulation like the

Sarbanes Oxley Act (SOX) of 2002 helps to bring new perspectives and greater scrutiny to the inside

the corporate boardroom, and thus, mitigates the extent to which overconfident CEOs hold sway

over insider-dominated boards (see e.g., Banerjee et al., 2015). This leads to significant improvement

in operating efficiency and consequently, firm value. But, there is substantial evidence suggesting

that blanket regulations like SOX can impose significant additional costs on many companies (see

e.g., Ahmed, McAnally, Rasmussen, and Weaver, 2010; Bedard and Graham, 2011; Hollis, Collins,

Kinney, and Lafond, 2008; Iliev, 2010; Leuz, Triantis, and Yue Wang, 2008; Wintoki, 2007). Hence,

in this study, we ask whether simpler governance-improving mechanisms like board independence

and diversity, rather than blanket regulation, can help to restrain the negative aspects and harness

the positive attributes of CEO overconfidence.

The double-edged nature of confidence is evident from the prior literature. Confidence is crucial

for success in many domains, including business (see e.g., Johnson and Fowler, 2011; Puri and

Robinson, 2007). Not surprisingly, CEOs tend to be more optimistic and less risk-averse than the

general population (Graham, Harvey, and Puri, 2013). For instance, overconfidence can be a desirable

trait in managers when there are valuable, but risky investment opportunities available in developing

new technologies or products (see e.g., Hirshleifer, Low, and Teoh, 2012; Galasso and Simcoe, 2011;

Simsek, Heavy, and Veiga, 2010). The downside is that overconfidence can lead to faulty assessments

of investment value and risk, resulting in suboptimal investment decisions (see e.g., Dittrich, Guth,

and Maciejovsky, 2005). Indeed, Ben-David et al. (2013) indicate that overconfident CEOs often

mis-estimate the risk-return relationship of a firm?s investments.

Along similar lines, the prior literature on board structure shows that in order for a board to

be effective, a good fit is needed between key characteristics of the board and the firm (see e.g.,

Raheja, 2005; Coles, Daniel, and Naveen, 2008; Duchin, Matsusaka, and Ozbas, 2010; Bhagat and

1As documented in the prior literature, overconfident CEOs invests aggressively and expose their firms to excessiverisk (see e.g., Ben-David, Graham, and Harvey, 2013; Banerjee, Humphery-Jenner, and Nanda, 2015; Malmendier andTate, 2008). Johnson and Fowler (2011) argue that overconfidence and the investment and risk-taking associated withit, can create the (potentially false) overconfident signal of profitability, which itself can deter competitors and improvethe company’s competitive position.

1

Black, 1999; Kim, Mauldin, and Patro, 2014). An effective board is one that offers a skillset which

meets a particular firm’s monitoring and advising needs.2 It is often difficult to tease out the factors

that make one board effective and another equally talented board, highly ineffectual. Interestingly,

gender diversity is one corporate board characteristic often touted as a critical ingredient for a

successful board. Regulators and foundation supported think-tanks have long pushed for greater

representation of females on corporate boards (see e.g., WorldBank, 2012; Eastman and Rallis, 2016).

Some researchers have posited that gender diverse boards might benefit companies financially because

diversity encourages greater creativity and better decision-making (see e.g., Hong and Page, 2004).

While others have suggested that diverse boards indicate a better utilization of the available director

talent pool (see e.g., Hunt, Layton, and Prince, 2015). Rating agencies like S&P, Moody’s and large

pension and investment funds, such as CalPERS and PAX World, use the extent of gender diversity

as one of their investment criteria (see e.g., Dhir, 2015). The social psychology literature argues that

often it only takes “one person with distinct viewpoint” to get things rolling in organizations (see

e.g., Phillips, Liljenquist, and Neale, 2008).3

Whether gender diversity can lead to higher firm value is also a hotly debated topic, with aca-

demic studies presenting mixed empirical evidence. For example, Adams and Ferreira (2009) find

that controlling for endogeneity, board gender diversity can actually hurt a firm. Matsa and Miller

(2013) study the 2006 exogenous policy shock in Norway that required substantially higher female

representation on corporate boards and find a large value loss for previously non-complaint firms.

Ahern and Dittmar (2012) also study the impact of this statute and find that such mandated board

diversity leads to potentially less capable corporate boards. On the other hand, Kim and Starks

(2016) show that a gender diverse board has greater advisory effectiveness, as measured by the het-

erogeneity of functional expertise, and is associated with higher firm value. Further, Eckbo, Nygaard,

and Thorburn (2017) analyze quota-induced board changes on shareholder announcement returns,

long-run stock and accounting performance and fail to reject the hypothesis of a zero valuation ef-

fect. We find that almost all existing studies on board diversity examine matching of firm-types with

director-types (see e.g., Fich, 2005; Linck, Netter, and Yang, 2008b), but no one to our knowledge

has examined whether matching CEO-types and director-types improves shareholder wealth. Thus,

2Prior studies have documented evidence indicating how directors with specific skills, expertise or professionalexperience (e.g. banker, venture capitalists, ex-politician, and lawyers) bring value to firms that have a need for thosespecific skills.

3 In Norway since 2006, all publicly listed firms are required to reserve 40% of board seats for females. The EuropeanUnion is planning to introduce similar regulation that will apply to all the countries in the EU. In 2009, the securitiesexchange commission (SEC) in the U.S. mandated new disclosure rules requiring listed firms to disclose whether theyconsider diversity when recruiting new directors.

2

whether gender diversity is generically valuable for corporate boards or whether it should be reserved

for certain types of managers is an open question (see e.g., Feldman and Arnold, 1983).4

We know from the existing literature that overconfident CEOs are more likely to undertake

undertake hubris motivated takeovers (see e.g., Roll, 1986; Hayward and Hambrick, 1997; Malmendier

and Tate, 2008), increased personal and corporate risk taking (see e.g., Cain and McKeon, 2013;

Banerjee et al., 2015), and to spend more resources internally (see e.g., Malmendier and Tate, 2005;

Banerjee et al., 2015).5 These troubles can be compounded by a permissive board that exhibits group

think and inadequate oversight. Perhaps the most important link in the virtuous cycle of effective

team dynamics is the capacity to challenge one another’s assumptions and beliefs (retain individual

thinking) without creating an environment contaminated by distrust and animosity. Further, the

existing literature argue that gender diversity helps to improve trust among board members that

leads to greater sharing of pertinent information among them. As this spirited give-and-take becomes

the boardroom norm, board members learn to adjust their own interpretations in response to new

arguments and information and learn to value the viewpoints of each other (see e.g., Dhir, 2015; Gul,

Srinidhi, and Ng, 2011; Srinidhi, Gul, and Tsui, 2011). Therefore, we expect the gender-diverse board

to more openly question corporate policies that appear to be driven more by a CEO’s behavioral

biases than by clear economic opportunities, thereby pushing the firm’s strategies closer to more

profitable outcomes and often towards industry trends.

Obviously, gender diversity cannot be a panacea for all that can be wrong with corporate boards.

At times, it can also lead to reduced board effectiveness by raising boardroom divisiveness and by

constraining or slowing a board’s responses to economic changes (see e.g., Garlappi, Giammarino,

and Lazrak, 2017). Disadvantages of gender diverse boards includes more prolonged decision-making,

less initial director bonding, and additional conflicts due to more diverse perspectives (see e.g.,

Mankins, 2004; Donaldson, Malenko, and Piacentino, 2017). With non-overconfident CEOs at the

helm, these positive and negative impacts of gender diverse boards are more likely to be offsetting

at the margin. This board outcome appears consistent with the mixed empirical results documented

in the prior literature (see e.g., Adams and Ferreira, 2009; Ahern and Dittmar, 2012; Matsa and

Miller, 2013; Eckbo et al., 2017). We argue that pairing a gender diverse board with overconfident

CEOs tilts the aggregate net impact of gender diverse board towards positive outcomes, because

4The conceptual rationale for the improved effectiveness of boards that diversity yields is based on Harrison andKlein (2007), who argue that diversity is inherently a multilevel construct and has multiple influence.

5In the case of Enron, for instance, it is claimed that overconfidence may have rendered CEOs slow to recognizetheir mistakes and quick to engage in risky behavior in their attempt to cover up these mistakes as per O’Connor(2003).

3

with an overconfident CEO, a more independent thinking board that provides strong oversight is

much more important. Consequently, we posit that gender-diverse boards help counterbalance some

of the undesirable tendencies of overconfident CEOs documented in the prior behavioral finance

literature (see e.g., Banerjee, Humphery-Jenner, Nanda, and Thiam, Forthcoming; Banerjee et al.,

2015; Malmendier and Tate, 2005, 2008).

We document several important findings. We find that prior to having a female director on the

board, firms with overconfident CEOs tend to employ more capital, measured by greater capital

expenditures (CAPX), greater investment in property, plant and equipment (PP&E), higher selling

and general administrative (SG&A) expenses and more acquisitions, relative to other matched firms

in the industry without overconfident CEOs. However, after controlling for firm and year fixed effects

along with various other firm and CEO characteristics, we find that firms with overconfident CEOs

and gender diverse board actually employ a significantly lower quantity of capital in terms of CAPX,

PP&E and SG&A expenses, which bring these ratios closer to industry norms.

We next address how overconfident CEOs influence a firm’s exposure to measures of total risk,

systematic risk, and firm-specific risk. We conjecture that overconfident CEOs are likely to under-

estimate the risk associated with their investments; and thus, are more likely to engage in excess

risk-taking (see e.g., Ben-David et al., 2013; Banerjee et al., 2015; Niu, 2010). Our results, after con-

trolling for firm and year fixed effects along with various other firm and CEO characteristics, indicate

that firms with overconfident CEOs and a gender diverse board expose their firms to significantly

lower levels of total volatility, systematic and firm-specific risk.

An important follow-up question that we analyze is whether this reduction in investments and

risk exposure actually benefits shareholders (see e.g., Banerjee et al., 2015; Jo and Harjoto, 2011). We

specifically test whether gender diverse boards result in curbing what previously was value-creating

tendencies of overconfident CEOs. We use several measures of firm performance: both market-based

and accounting-based measures, namely Tobin’s Q and Earnings Before Interest & Tax (EBIT) scaled

by total assets.6 Our results are quite clear, despite the reduction in investment expenditures and

risk-taking, overconfident CEOs continue to create more shareholder value in firms with a gender

diverse board and following the initial appointment of a female director. The results are similar

whether we use an indicator for relatively high CEO overconfidence levels or a continuous measure

of CEO overconfidence.

Next, we investigate whether this positive effect of the gender-diverse board comes from a certain

6Additionally, we also use operating cash flow (OCF) to measure operating performance because it is less susceptibleto earnings management.

4

class of female director or from any female director. For this purpose, we examine the affiliation of

female directors to analyze if this positive valuation effect varies by a female director’s affiliation.

We find that the mitigating effect on overconfident CEOs is significant only for boards which have a

female independent director. We conjecture that these female independent directors are less likely to

be influenced by CEOs and are less likely to develop back channels to the CEOs compared to executive

directors or affiliated (henceforth, gray) directors, who have a financial or a familial connections to

the firm or the CEO.

Further, we consider whether higher demand for female independent directors relative to existing

supply can lead to a situation where female directors serve only on the boards of “high quality”

firms. To address concerns about such a self-selection effect, we reexamine the effects of gender

diverse boards on firms managed by overconfident CEOs by looking at the appointment of new

female independent directors and the associated changes in Tobin’s Q across the pre-appointment to

post-appointment period. To obtain a clean measure of the effect of a female independent director

appointment, we exclude cases where new male director appointments occur at the same time. We

find a significant positive effect of female director appointments in overconfident-CEO managed firms,

but we observe no such value-enhancing effects in firms without overconfident CEOs. Lastly, as an

alternative approach, we investigate the “marginal effect” of a female independent director where

we identify firms that do not have a female director in the prior year and re-run our analysis. We

find that the strongest mitigating effect on overconfident CEOs occurs in those firms that appoint a

female to the board for the first time.

As documented in Hermalin and Weisbach (1998, 2003), the board of directors is an endogenously

determined institution. Specifically, the authors provide theoretical and empirical evidence that poor

performance leads to changes in board composition.7 To further address this endogeneity concern, we

looked at a subsample of “sudden departures” of female independent directors where we can exactly

identify the reason for their departure and then restrict our analysis to departures due to purely

exogenous factors (like sudden death, mandatory retirement age, etc.) We find that overconfident-

CEO managed firms witness a significant loss in value when a board losses its gender diversity for

exogenous reasons. 8

Next, we turn our attention to the impacts of exogenous governance-improving events. With the

7In the cross-section, the potentially beneficial effect of independent directors might, therefore, be overshadowed bypoor historic performance. Thus, making it difficult to identify any causal relationship between board composition andperformance.

8Further, we also analyze whether we observe similar mitigating effects when a firm with gender diverse board inplace appoints a new CEO who is overconfident. We find positive effects.

5

passage of SOX and associated exchange listing rule changes, we have an event that, for many firms,

is arguably represents an exogenous improvement in governance, disclosure, and monitoring (see e.g.

Coates, 2007; Engel, Hayes, and Wang, 2007; Linck, Netter, and Wintoki, 2012). Although, SOX has

a significant dark-side (see e.g., Ahmed et al., 2010; Hollis et al., 2008; Iliev, 2010; Leuz et al., 2008;

Wintoki, 2007), one of the positive consequences of SOX, as documented in the literature, is that

SOX helps to restrain some of the negative qualities of overconfident CEOs (see e.g., Banerjee et al.,

2015). We find that the mitigating effect of gender diverse boards at firms with overconfident CEOs

is concentrated in the pre-SOX period. We fail to find any significant effects of gender-diverse boards

on overconfident CEOs after the passage of SOX. These results suggest that the disciplining effect

of female independent directors is a “substitute” governance mechanism to the effects of SOX. In

the post-SOX and new exchange listing rules period when boards generally become independent and

directors are subject to much more personal liabilities, overconfident CEOs appear to be effectively

disciplined by their boards (see e.g., Banerjee et al., 2015).

An obvious question is “what is the beneficial effect of a gender-diverse board on firms led by

overconfident CEOs that had SOX-like governance mechanism in place prior to the passage of SOX?”

To address this question, we compare the impact of a gender-diverse board on firms that previously

complied with major provisions of SOX prior to its passage, compared to firms that were non-

compliant. We find that the mitigating effects of a gender-diverse board on overconfident CEOs are

only associated with firms non-compliant with major provisions of SOX prior to its passage. Thus,

gender diversity appears to be a substitute for the major provisions of SOX.

Other governance mechanisms such as high insider ownership or institutional ownership (McCa-

hery, Sautner, and Starks, 2016), or the presence of a fully independent nominating committee (Guo

and Masulis, 2015) could also affect board governance quality and hence, could act as a substitute

for a gender diverse board. With the exception of a fully independent nominating committee, we

find that high insider ownership does not weaken the mitigating effect of board gender diversity

on overconfident CEOs. We believe that the effect of a non-independent nominating committee –

the committee responsible for hiring and firing of officers and directors – might be selectively hiring

“female independent directors” in a way that vaguely satisfies the regulatory definition, but violates

the “true spirit” of director independence due to social dependence or a weak director skillset.

Similar to Malmendier and Tate (2005) and Banerjee et al. (2015), we construct measures of

overconfidence based on a CEO’s decision to voluntarily expose herself to additional firm-specific

risk by retaining vested, deep-in-the-money options.9 Following the existing literature, we argue

9Often CEOs receive large option grants as well as restricted stocks as compensation. In most cases, they are

6

that a CEO is overconfident if she retains exercisable options that are in-the-money.10 We measure

CEO overconfidence by examining the value of the CEO’s exercisable, but not-yet-exercised options.

This decision reflects the CEO’s willingness to keep more of her personal wealth tied up in the

company without any tangible evidence of positive private information.11 We set Holder67 equal

to one if a CEO fails to exercise her vested options with at least five years remaining life despite a

67% or more increase in stock price relative to the grant date strike price for any two years out of

a consecutive three-year window. The results reported below are robust to variation in the value of

the threshold.12 We apply these measures to a panel dataset of options and stock holdings of CEOs

taken from Execucomp between 1992 and 2011.

We undertake several robustness tests to further mitigate econometric concerns. We control

for various firm, CEO, and governance characteristics, and include firm or industry and year fixed

effects in our statistical analysis. Given that our results are also associated with strongly exogenous

events – like exogenously induced departures of female independent directors, the passage of SOX

and the associated changes in the listing rules, and support from the aforementioned falsification

tests, we conclude that endogeneity (particularly reverse causality) is unlikely to drive our results.

For example, we conduct falsification tests to show that, for the most part, the board changes around

the passage of SOX are concentrated in companies previously non-compliant with SOX. Similarly, we

also conduct robustness tests using alternative measures of CEO overconfidence and we find that our

earlier findings continue to hold when we use a press-based measure of overconfidence; or a measure

based on the value of the CEO’s vested-but-unexercised options scaled by her total compensation.

As a further falsification test, we use appointments of male independent directors in lieu of

female independent directors and find that our earlier value-enhancing benefits of female independent

director appointment do not hold for the appointment of male independent directors. Lastly, we use

county-level supply of female independent directors as an instrument to predict a female independent

director on the board. Then, we use the “Predicted Female Independent Director Indicator” and

“Predicted Female Independent Director Ratio” to analyze the effect of female independent board

prohibited from trading their options/stock for at least some pre-specified period of time (known as the vesting period);nor can they short-sell company stock to hedge this risk exposure. At the same time, a CEO’s human capital is closelylinked to the firm’s performance. Thus, this potentially serious under-diversification should prompt any unbiased CEOto exercise her options and/or sell her stock at the earliest opportunity, given a sufficiently high stock price (deep-in-the-money). See, for example, Lambert, Larcker, and Verrecchia (1991), Meulbroek (2001), Hall and Murphy (2000)and Hall and Murphy (2002) for more detailed discussions.

10One possible explanation is based on private information, but these firms typically underperform market implyingthat the easy outside options viable to these CEOs is more valuable and hence, their beliefs are “perceived” in nature.

11As confirmed in Malmendier and Tate (2008, pg. 36), the return from holding these options is poor, inconsistentwith an inside information explanation for not cashing-out.

12This is analogous to the measure of overconfidence used in (Malmendier and Tate, 2005, 2008), which is basedupon proprietary data to which we do not have access.

7

members on performance of firms managed by overconfident CEOs. We find that the earlier firm

value-enhancing outcomes associated with female directors continue to hold.

Our study contributes to two important branches of the financial economics literature: one

is on managerial overconfidence and board gender diversity. Consistent with the prior literature,

we confirm that CEO overconfidence can lead to risky capital expenditures and consequently, the

destruction of shareholder value. We find evidence that a gender-diverse board is associated with

a significant reduction in shareholder value-destruction at the hands of overconfident CEOs. Our

results provide support for matching important CEO characteristics with key board characteristics.

Specifically, our study provides novel evidence on the benefits of board gender diversity, particularly

that of independent female directors, through its moderating influence on CEO behavior.

Although our findings may not extrapolate to other proposed or enacted types of broad gover-

nance changes, it appears that appointments of women to corporate boards as independent directors

acts as effective restraint on excessive CEO risk taking tendencies and this produces shareholder

value-enhancing benefits (and potentially social welfare gains).13 The message of this study is un-

equivocal: managerial overconfidence can be regulated, monitored and positively channeled by imple-

menting a simple governance improving mechanism, namely by introducing gender diversity among

a firm’s independent directors. How best to harness CEO overconfidence remains an open question

of substantial importance. While our results are suggestive of a less intrusive approach to improving

board decision making, we do not claim to offer a definitive answer to the question of how best to

design regulations that helps maximize the benefits net of the costs of managerial overconfidence.

2 Hypotheses

Overconfident CEOs, by definition, value investments more positively than non-overconfident CEOs

do, i.e., assign a greater perceived expected value to their investments. Thus, this type of CEO

bias can induce risky over-investment. For example, hubris is one potential driver of over-bidding in

takeovers (see e.g., Roll, 1986; Hayward and Hambrick, 1997). Malmendier and Tate (2008) argue

that overconfident CEOs are more likely to undertake hubristic takeovers. By similar reasoning,

overconfident CEOs are also likely to spend more resources internally (i.e. in terms of CAPX and

PP&E growth). Similarly, prior studies show that overconfident CEOs tend to overinvest on internal

13Such evidence is consistent with prior literature that suggests that board effectiveness prevents insiders fromexpropriating from minority shareholders (as in Duarte, Kong, Young, and Siegel (2014)), and is associated withimprovements in disclosure and governance (see e.g. Arping and Sautner (2013); Ashbaugh-Sakife, Collins, Kinney,and Lafond (2009))).

8

general administrative expenditures (see e.g., Malmendier and Tate, 2005; Chen, Gores, and Nasev,

2013). Because these overconfident CEOs over-estimate the expected value of their investments,

and under-estimate the associated downside risk, overconfident CEOs are more likely to increase

corporate risk relative to nonoverconfident CEOs (see e.g., Banerjee et al., 2015).

Although, there is dearth of female directors in corporate boardrooms, prior literature documents

that female and male directors differ systematically in their core values and risk attitudes (see e.g.,

Adams and Funk, 2012; Huffington, 2003; Kirk and Gwin, 2009).14 There are studies in social

psychology literature that argue that it only takes is one person with distinct viewpoint to trigger

discussion (see e.g., Phillips et al., 2008). Phillips et al. (2008) demonstrate that the mere presence

of a socially distinct new (female independent) member and the social concerns their presence raises

among existing board members can motivate behavior that creates cognitive gains. These results are

robust to controlling for differences in observable characteristics. In particular, prior studies find that

female directors are more concerned about performance, but less power-seeking than male directors

(see e.g., Dhir, 2015). In the McKinsey 2008 survey of 800 business leaders titled “Gender Matters 2,”

many board members observed that female directors are “more likely than their male counterparts to

explore in depth the issues at hand” by asking more probing questions, leading to more robust board

deliberations. Also, as indicated in this survey, most female directors appeared to be uninterested

in presenting a facade of knowledge and were loath to make decisions they did not fully understand.

Other board members observed that female directors tended to have a different style of engagement,

seeking the opinions of others and trying to engage the entire board in discussions.

Turning to the effects of overconfident CEOs, there is evidence suggesting that they can in certain

circumstances impose significant costs on the companies they manage. For example, overconfident

CEOs are expected to overinvest and to assume more risk than is optimal from a shareholder’s

perspective, and they are less likely to learn from past mistakes when doing so (Chen, Crossland,

and Luo, 2014). We hypothesize that more robust board member deliberations due to gender diversity

lead to stronger governance in companies, which can curtail these excesses of overconfident CEOs.15

The above analysis gives rise to the following hypotheses:

Hypothesis 1. (a) Gender-diverse board reduces the impact of CEO overconfidence on the amount

of corporate spending on capital expenditures, investments in property plant and equipment, selling

and general administrative expenses, and on acquisitions.

14Xu (2017) finds that female executives are promoted less frequently than their male peers.15This is all the more so in light of prior evidence that overconfident CEOs are more likely to be dismissed than

other CEOs in boards dominated by independent directors (see e.g., Campbell, Gallmeyer, Johnson, Rutherford, andStanley, 2011).

9

(b) Gender-diverse board creates an environment inside the boardroom that helps to moderate over-

confident CEO’s tendency to take excessive systematic as well as unsystematic risk.

Prior evidence suggests that post-SOX superior financial performance in firms led by overconfident

CEOs in terms of stronger sales and asset growth and higher returns on equity are attainable (see e.g.,

Banerjee et al., 2015). More efficient risk management policies post-SOX is also widely documented.

There is evidence that female executives have a similarly positive effect on firm performance and risk-

taking in firms operating within the Chinese automotive industry (see e.g., Horak and Cui, 2017).

To the extent that a gender-diverse board reduces excessive risk taking and wasteful expenditures by

overconfident CEOs, we expect there to be a positive impact on their firms’ operating performance

and firm valuation. This yields the following prediction:

Hypothesis 2. (a) Gender-diverse boards encourage the positive effects of overconfident CEOs on

firm-value.

(b) Gender-diverse boards positively affect operating performance in firms managed by overconfident

CEOs.

Next, we follow the literature to analyze effects of female director affiliation. We expect the

mitigating effects of gender-diverse board to be stronger if board gender diversity is due to female

independent directors, rather than female executive directors or gray directors, who have beneficial

affiliations with the firm and are less independent of the CEO.

Hypothesis 3. Gender-diverse board with at least one female independent director positively affects

the values of firms managed by overconfident CEOs. Board gender-diversity due to a female executive

director or female gray director provides no such positive effect on firm value.

We use “appointment” of fresh independent directors to better identify the relationship between

gender diversity and performance of firms managed by overconfident CEOs in a difference-and-

difference framework. We develop two related, but distinct hypotheses. We also examine appoint-

ments of female independent directors in firms that lacked a female director on their board and are

led by overconfident CEOs and we expect to find a significant increases in these firms’ Tobin’s Q

between the pre-appointment and post-appointment periods.

Hypothesis 4. (a) Appointment of female independent directors to a board with or without female

directors, and led by overconfident CEOs increases a firm’s Tobin’s Q from the pre-appointment to

post-appointment period.

10

(b) The appointment effect is stronger in companies without a sitting female independent board mem-

ber.

To avoid questions of endogeneity, we examine female independent directors departures that are

due to exogenous causes. If the positive effects that we previously document are driven by the

presence of female independent directors on the boards of firms managed by overconfident CEOs,

then we expect to see a negative effect of a female independent director departures while the firm

continues to be managed by an overconfident CEO.

Hypothesis 5. Departure of the only female independent director on the board for exogenous reasons

such as death, mandatory board retirement age significantly decreases Tobin’s Q between pre-departure

to post-departure periods at firms led by overconfident CEOs.

Next we investigate a substitute mechanism to improve governance standards. To the extent

that SOX and the associated exchange listing rules changes strengthens board independence and

expertise and helps to reduce excess risk taking and wasteful expenditures by overconfident CEOs

(see e.g., Banerjee et al., 2015), then we expect to observe a reduced effect of gender diverse boards

on the performance of firms managed by overconfident CEOs. We predict, therefore:

Hypothesis 6. After the passage of a comprehensive governance-improving mechanism such as

SOX, we expect a decline in the mitigating effects of gender-diverse boards on the performance of

firms managed by overconfident CEOs. Likewise, firms that voluntarily adopted SOX like governance-

improving mechanisms prior to the passage of SOX should experience little additional benefits from

having a gender-diverse board to restrain overconfident CEOs, even in the pre-SOX period.

3 Data

We use a sample of Execucomp firms covering the period 1998 through 2011. Following studies by

Banerjee et al. (2015); Hirshleifer et al. (2012); Malmendier and Tate (2005, 2008), we exclude

utilities and financial services firms. Data on board characteristics i.e., board structure, director

relationships with the firm, and beneficial stock-holdings and voting rights, are taken from Risk-

Metrics and proxy statements. We use COMPUSTAT for accounting and financial data, and the

COMPUSTAT industrial segment files for segment data. For CEO compensation related data, we

use Execucomp. Institutional ownership data comes from Thomson Financials 13f filing database.

11

3.1 Key variables

We measure gender diversity in several standard ways. We use an indicator variable for the presence

of any female director(s) on a firm’s board in a given year. We also use the ratio of the number

of female directors to board size, the ratio of the number of female independent directors to board

size and an indicator variable for the presence of one or more female independent directors. To

assess whether the main effects of gender diversity vary by director affiliation, we use two additional

indicator variables for one or more board members who are female affiliated (gray) directors and

female executive directors respectively. Affiliated directors have a business or familial relationship

with the firm or its senior executives. Executive directors are firm employees.

Our second key variable is CEO overconfidence. We employ several alternative measures of

CEO overconfidence. Following existing literature (Banerjee et al., 2015; Hirshleifer et al., 2012;

Malmendier and Tate, 2005, 2008), we primarily measure CEO overconfidence by examining the

value of her unexercised, but exercisable in-the-money options. For this purpose, we start with the

value-per-vested option. We then divide this variable by the company’s stock price at the end of the

relevant fiscal year (as reported in COMPUSTAT). We use this continuous variable as a measure of

CEO overconfidence. From this ratio, we also create an indicator variable, Holder67, which takes a

value of 1 if the continuous variable has a value above 0.67. For robustness, we use other alternative

measures of this indicator variable using as cut-offs the ratio’s median and the 3rd quartile across

our sample firms and sample period. In addition, we use a press-based measure of overconfidence.

We follow a similar approach to Hirshleifer et al. (2012) and Banerjee et al. (2015) and hand collect

data on how a CEO is described by the press during 2000-2006 period.16

3.2 Dependent variables

First, we examine whether gender diverse boards affect how over-confident CEOs make investment

decisions. For this purpose, we examine the capital investments of a firm headed by an overconfident

CEOs. Capital investment is the dollar amount that a firm invests in capital assets scaled by book

value of assets. Next, we examine selling and general administrative expenses (SG&A), property,

plant and equipment (PP&E) and acquisitions of firms headed by overconfident CEOs. We also

16We only label those CEOs as overconfident based on “News” when the positive (or favorable to overconfidence)news exceeds the negative (unfavorable to overconfidence) news, and then use the ratio of positive news to total newsas the measure of CEO overconfidence:

Press-based OC measure =Positive News

Total News|Positive News > Negative News

12

examine a firm’s risk taking policies. For this purpose, we use total risk measured by standard

deviation of monthly returns over the prior 60 months. We also use the stock’s beta and residual

standard deviation (MSE) as alternative risk measures.

To examine the performance effects of gender diverse boards on firms led by overconfident CEOs

we primarily use Tobin’s Q as our measure of firm performance, which is common in the literature

(see e.g., Yermack, 1996; Coles et al., 2008). We use a commonly employed approximation of Tobin’s

Q, defined as the market value of total assets scaled by book value of total assets. The market value

of total assets is approximated by the market value of equity plus the book value of debt. Specifically

we measure Tobin’s Q as:

Tobin’s Q =Market Value of Equity + Book Value of Debt

Book Value of Total Assets(1)

We use end of the next year’s Tobin’s Q ratio in all our performance regressions (see e.g., Lewellen

and Badrinath, 1997; Coles et al., 2008; Masulis and Mobbs, 2011, 2014).

3.3 Control variables

Following prior studies, we use a number of control variables with strong explanatory power for firm

investment and operating decisions. Firm specific measures include annual sales, lagged profitability,

lagged Tobin’s Q, insider holdings, financial leverage, R&D intensity, diversification and company age.

CEO related controls include total compensation, age, tenure and gender. We also include market

related controls such as contemporaneous return volatility, and stock return. Board structure related

controls include board independence and size, and institutional ownership. Executive directors are

defined as current employees of the firm. Affiliated (or Gray) directors are outside directors who have

business ties to the firm, e.g., and retired employees, legal counsel, investment bankers, consultants

or commercial bankers or they have familial ties to the senior executives of the firm. In contrast,

independent directors are outside directors who have no such relationship with the firm or its senior

executives. Following Yermack (1996), we use the natural log of number of directors on the board

to measure board size.17 Following Coles et al. (2008), we use the natural log of a firm’s sales as a

measure of firm size and R&D investment scaled by book value of total assets as a measure of growth

opportunities. Firm profitability is measured by ROA.18 We measure leverage as the ratio of book

value of long term debt to total assets.

17We also use board size without the log transformation and find similar results.18In unreported results, we use the natural log of book value assets, the natural log of capital and the natural log of

market capitalization to measure firm size, finding our results are robust to these alternatives.

13

Insider ownership is the proportion of common stock held by a firm’s officers and directors.

Institutional ownership is the proportion of common stock held by institutional shareholders. Di-

versification is measured by the number of operating segments that a firm has (see e.g., Yermack,

1996). Firm age is the natural log of the number of years that a firm has been in the CRSP database.

Intangible assets is the ratio of intangible assets to book value of total assets. CEO age is the natu-

ral log of CEO age taken from ExecuComp. For firm specific risk, we use the standard deviation of

monthly stock returns estimated over the previous 60 months (see e.g., Coles et al., 2008). Following

Brickley, Coles, and Jarrell (1997) and Linck, Netter, and Yang (2008a), we measure CEO tenure as

the number of years that a CEO has spent in his/her current position.

3.4 Univariate Analysis

We begin our analysis with a review of how board gender diversity has changed over our sample

period. We present the annual distribution of female directors in Table 1. The ratio of female

directors to board size grew from 7.55% in 1998 to almost 13% in 2011.19 This represents a 72% gain

over our sample period. Another interesting statistic in Table 1 is the growth of female independent

directors as a proportion of all independent directors. The ratio of female independent directors in

our sample rose from 10.66% in 1998 to 14.68% in 2011. That represents nearly a 38% growth rate.

Because of this recent growth, it is important to understand how the presence of female directors

may affect the behavior of boards and CEOs.

Insert Table 1

In Table 2 we show how board gender diversity changed from the pre-SOX period to the post-

SOX period. It is interesting to note that although post-SOX listing rule changes did not require

appointing female directors, nevertheless in order to meet the 100% independence requirement of

audit, compensation and nomination committees, many companies chose to increase female repre-

sentation. This change appears to be significantly higher among firms without an independent board.

For example, we find for an average firm lacking board independence, the number of female directors

was 0.591 and the number of independent female directors was 0.337 just prior to the passage of

SOX (1996-2001). But over the post-SOX period (2002-2011), these two figures increased to 0.806

and 0.589 respectively. This represents an increase of 36.38% in the number of female directors and

19The number of directors in year 2006 is larger than the number in 2005 and 2007. This is because RiskMetricschanged the coverage of firms in 2007 and also because it started using a different firm identification system (for adetailed description of these changes please see Coles et al., 2014). We follow Coles et al. (2014) to merge data from1998-2006 period with data from 2007-2011.

14

an almost 75% increase in the number of female independent directors. Compared with the increases

in female independent directors, the ratio of all independent directors increased by only 30.86%.

We also see an increase of almost 18% in the number of female independent directors in firms with

independent boards, although the increase in the level of board independence in these firms was only

6.29%.

Insert Table 2

Table 3 presents some descriptive statistics for the variables used in this study. The average firm

has approximately 10% of their board comprised of female directors and about 66% of firm-years

have at least one female director. On the other hand, only 2.2% of firm-years in our sample has a

female CEO. Approximately 9% of firms in our sample have an overconfident CEO as measured by

exercisable option holdings that are in-the-money by at least 67%. Following the extant literature,

we choose 67% as a proxy for deep-in-the-money options such that the CEO’s “option delta” is close

to her “stock delta,” which is 1.

Insert Table 3

Since univariate analysis does not control for various other firm characteristics such as firm

size, we cannot use these correlations to draw any meaningful inferences about relationships to firm

outcomes. Therefore, in the next section we examine the associations between gender diversity, CEO

overconfidence and other corporate outcomes in a multivariate setting that controls for other major

firms, board and CEO characteristics.20

4 Analysis

We begin by evaluating our first hypothesis using a difference-in-difference approach. We use two

explanatory variables: Female Director Indicator and Female Director Ratio. In Tables 4-7, we

examine boards with gender diversity, regardless of the type of female director on the board. In

Table 8, we differentiate by female directors affiliation and examine there separate effects. Then in

Tables 9-14, we focus our analysis on the gender diversity of boards with one or more independent

female directors. To control for unobservable firm specific factors that are time-invariant (e.g. firm

culture), we add firm fixed effects in all the models. Similarly, to control for the influence of aggregate

20Table OA6 in Online Appendix 1 presents pairwise correlations for some key variables used in this study. Inour sample, board gender diversity is negative correlated with the overconfident CEO. Board gender diversity is alsonegatively correlated with Tobin’s Q. But there is a positive correlation between Tobin’s Q and the presence of anoverconfident CEO, which is similar to Hirshleifer et al. (2012).

15

trends, which have nothing to do with these causal relationships, we add year fixed effects in all the

models.

4.1 Does the presence of female board member(s) restrain overconfident CEOs’

over-investment tendencies?

First, we test whether a gender-diverse board limits the tendencies of overconfident CEOs to over-

invest in various types of firm assets. As explained earlier, we examine four specific investment

strategies pursued by firms managed by overconfident CEOs. These strategies include capital ex-

penditure intensity (CAPX/Assets) (see e.g., Banerjee et al., 2015; Malmendier and Tate, 2005),

tangible investment intensity in property plant & equipment (PP&E/Assets) (see e.g., Banerjee

et al., 2015), selling & general administrative expenses ratios (SG&A/Assets) as a measure of major

non-production cost (see e.g., Banerjee et al., 2015; Chen et al., 2013), and acquisition activity (see

e.g., Banerjee et al., 2015; Malmendier and Tate, 2005).21 Over-investment in these strategies can

be wasteful and we hypothesize that gender diverse boards are likely to restrain overconfident CEOs

from over-investing in these investment categories.

We initially test for a moderating effect on CEO over-investment behavior by examining the

relationship between female directors, CEO-confidence, and CAPX intensity. Next, we examine

PP&E-intensity following Banerjee et al. (2015), who argue that overconfident CEOs often over-

spend on physical assets. The logic behind this investigation is that overconfident CEOs tend to

have overly positive views about future investment-prospects, so they are more likely to want to build

PP&E to meet this perceived future demand. In addition, we examine the effect of gender-diverse

board on SG&A following Chen, Gores, and Nasev (2013). They argue that overconfident CEOs

tend to overspend on the SG&A account, given their excessively positive views about the potential

future demand for their products. Lastly, we examine acquisition activities of overconfident CEOs.

Malmendier and Tate (2005, 2008) argue that overconfident CEOs frequently engage in acquisitions

and that these acquisitions are often value destroying. However, there is some evidence that firms

with board gender diversity (see e.g., Levi, Li, and Zhang, 2010) lower the level of acquisition activity.

Therefore, we examine whether board gender diversity leads to lower acquisition activity in firms

managed by overconfident CEOs. We estimate the model using firm fixed effects to control for time

invariant unobservable firm characteristics, where we cluster standard errors by firm to account for

21SG&A includes all the costs not directly tied to making a product or performing a service. That is, SG&A includesthe costs to sell and deliver products or services, in addition to the costs to manage the company.

16

potential firm level dependence in the error term.

Investmenti,t+1 = α+ β1 Female Director Indicator/Ratioi,t + β2 Confidencei,t

+ β3 Female Director Indicator/Ratioi,t × Confidencei,t + θXi,t + φt + λj(i) + εi,t

(2)

where the dependent variable Investmenti,t+1 sequentially represents CAPX/Assetsi,t+1, PP&E/Salesi,t+1,

SG&A/Salesi,t+1 and Acquisition Activityi,t+1 in the analysis to follow. Our two key explanatory

variables are Female Director Indicator and Female Director Ratio. Similarly, X represents a set of

CEO and firm control variables. We consider three sets of control variables: firm related controls,

CEO related controls, and board and market related controls. Following Banerjee et al. (2015), Hir-

shleifer et al. (2012) and Malmendier and Tate (2005) we use same sets of variables as controls in

all our baseline regression models. Similarly, φt, and λj(i) stands for year, and firm fixed effects

respectively.

Results from this analysis are presented in Table 4. The first two columns of Table 4 present

results for CAPX-intensity, the next two columns present results for PP&E-intensity followed by

SG&A-intensity and the last two columns cover acquisition activity.22 Columns 1, 3, 5 and 7 of

Table 4 present results for the Female Director Indicator as our measure of board gender diversity.

Columns 2, 4, 6 and 8 of Table 4 present results for the Female Director Ratio as our measure of

board gender diversity. As expected, the coefficient on CEO Holder67 is positive and significant at

the 5% level in Columns 1 through 8. This is consistent with the prior studies and indicates that

overconfident CEOs tend to over-invest in CAPX, PP&E, SG&A and Acquisitions. In contrast, the

coefficients associated with the interaction terms between CEO overconfidence and board gender

diversity are negative and significant across all eight models reported in Table 4. For example, for

the dependent variable CAPX-intensity, the coefficient on Female Director Indicator × CEO Holder

67 is -0.018 with a t-stat of -2.289 and for Female Director Ratio × CEO Holder67, it is -0.087

with a t-statistic of -2.397. These results indicate that the presence of female directors on the board

helps to mitigate an overconfident CEO’s tendency to overinvest in CAPX. These results support

our hypothesis that gender diverse boards are more likely to question optimistic projections made

by an overconfident CEO and reduce a firm’s investment in CAPX.

Like CAPX, we find that overconfident CEOs tend to overinvest in PP&E, but gender diverse

22All the regressions include an intercept, and firm and year fixed effects, although these coefficients are not tabulatedfor brevity.

17

boards are likely to question this overconfident investment strategy and subsequently, are likely

to reduce the over-investment in PP&E. To test this hypothesis, we estimate Equation (2) using

PP&E/Sales as the dependent variable. Like the previous analysis, we use two alternative measures

of board gender-diversity. The results from this analysis are presented in Columns 3 and 4 of Table

4. We find a positive coefficient on the overconfident CEO indicator, and a negative coefficient on

the interaction term of an overconfident CEO and board gender diversity as predicted.

Similarly, we find that overconfident CEOs tend to overinvest in SG&A. We present estimates

based on 1-year lead SG&A/Sales as the dependent variable in Columns 5 and 6 of Table 4. The

coefficient on CEO Holder67 is positive and significant at the 5% level in both regression models.

Likewise, the interaction terms of a gender-diverse board and an overconfident CEO are negative and

significant in both models. In Column 5, the coefficient on the interaction term is a negative -0.017

and significant at the 5% level. These results indicate that in firms without a gender diverse board,

but with overconfident CEO, there is overspending on SG&A, while in firms with gender diverse

boards this overspending appears more constrained and is closer to the industry level.

Finally, we examine acquisition activity of overconfident CEOs with a gender diverse board. The

results from this analysis are presented in Columns 7 and 8 of Table 4. We find that overconfident

CEOs tend to be very active in the takeover market. However, gender diverse boards tend to mitigate

this over-acquisitive tendency of overconfident CEOs. This is evident in the negative and significant

coefficient on both gender diversity variables, i.e. Female Director Indicator (Coefficient -0.082 with

t-stats 2.542) as well as Female Director Ratio (Coefficient -0.413 with t-stats 2.626). The negative

effects of board gender diversity appears to be dominant since both interaction terms Female Director

Indicator × CEO Holder67 in Column 7 and Female Director Ratio × CEO Holder67 in Column

8 are negative and significant and greater than the coefficient on the overconfident CEO indicator.

These last results indicate that board gender diversity also reduces investments in acquisitions by

overconfident CEOs, which can enhance firm value by utilizing a firm’s cash flow more efficiently.

4.2 Does the Presence of Female Directors Reduce Overconfident CEOs’ Exces-

sive Risk-taking Tendencies?

Regardless of whether there is over-investment by a firm, CEO over-confidence can also lead to high

firm risk exposure, measured by both systematic (or market) risk and unsystematic (or firm-specific)

risk. Thus, we ask whether gender-diverse boards help to mitigate the effects of CEO overconfidence

on a firm’s risk exposure. Since overconfident CEOs tend to overestimate the internal expected rates

18

of returns of investment projects, they are also likely to underestimate the risk levels associated with

these projects. Thus, firms led by such CEOs can take on excessive (or sub-optimal) amounts of

risk. We argue that presence of female director(s) with alternative viewpoints and skill sets lead to a

boardroom environment where overconfident CEOs are more constrained in choosing the firm’s risk

level. More specifically, the presence of female directors can encourage boards to assess firm risk-

taking activities in a more critical manner. For example, prior studies find that female directors are

less overconfident, more risk averse and are less acquisition oriented than their male counterparts (see

e.g., Adams and Funk, 2012; Levi et al., 2010; Huang and Kisgen, 2012; Levi, Li, and Zhang, 2014).

Hence, we conjecture that gender-diverse boards help to mitigate excessive risk taking tendencies of

overconfident CEOs.

We expect that the reduction in over-investment will be associated with a reduction in excessive

risk taking (Hypothesis 1b). We examine total risk measured by the stock raw return variance and

then decompose total risk into its two components: systematic/market risk (measured by beta) and

idiosyncratic/firm-specific risk (see e.g., Banerjee et al., 2015; Low, 2009).23 The statistical model

has the following form:

Riski, t+1 = α+ β1 Female Director Indicator/Ratioi,t + β2 Confidencei,t

+ β3 Female Director Indicator/Ratioi,t × Confidencei,t + θXi,t + φt + λj(i) + εi,t (3)

where Riski, t+1 is alternatively measured by Volatilityi,t+1, Betai,t+1, and MSEi,t+1.

The results for total risk (volatility), market risk exposure (beta) and idiosyncratic risk (MSE)

are reported in Columns 1 - 4, Columns 5 - 8, and Columns 9 - 12 of Table 5, respectively. We

find that the coefficients associated with our primary measure of CEO overconfidence, namely CEO

Holder67 are positive and highly significant in all these models. Consistent with prior studies, these

results indicate that overconfident CEOs expose their firms to relatively more risk. However, in firms

with overconfident CEOs, we find that a gender diverse board tends to reduce a firm’s level of risk

exposure considerably. This is reflected in the negative and significant coefficients of the interaction

terms across all the models. For example, the coefficients associated with Female Director Indicator

× CEO Holder 67 is -3.41 (t-statistic: 2.296) in Column 1, where risk is measured by stock return

volatility; -0.001 (t-statistic: 2.310) in Column 5 where risk is measured by (MSE ) employing a

23We estimate beta by running a single-index model over the course of the year using daily data. The proxy foridiosyncratic risk is the mean squared error (MSE) from that single-index-model. Some studies (see e.g., Banerjeeet al., 2015) use natural log when examining Return Variance and MSE in order to adjust for nonlinearities. We findqualitatively similar results using natural logs.

19

one factor market model and -0.064 (t-statistic: 1.722) in Column 9 where where risk is measured

by Beta. Similar interaction coefficients are obtained for the alternative interaction term, Female

Director Ratio × CEO Holder67, in all three firm risk exposure models. Overall, these results

support our conjecture that gender diverse boards significantly reduce risk exposure in firms led by

overconfident CEOs.

4.3 Gender Diverse Boards, Overconfident CEOs and Corporate Performance

Our analysis so far has restricted itself to documenting the mitigating effects of a gender-diverse

board on overconfident CEOs with respect to a firm’s investment level (as well as its growth rate of

investment) and its risk exposure. Thus, a question that naturally arises is: does a gender-diverse

board help overconfident CEOs improve the quality of their investments?

Hence, we test the overarching hypothesis that a gender-diverse board causes overconfident CEOs

to make better quality investments, leading to better firm performance. We use three conventional

measures of firm performance for this purpose: First, we use end of next year Tobin’s Q as market

based measure of long term firm performance. Second, we use Earnings Before Interest & Taxes

(EBIT) scaled by total assets, a standard accounting based measure of operating performance. Lastly,

in an unreported table, we examine the Operating Cash Flows (OCF) scaled by total assets, which is

a measure of operating performance that is less susceptible to earning management since it excludes

accruals. We next discuss our research design and regression results.

4.3.1 Is Gender-Diverse Board Associated with Value-increases in Overconfident CEOs’

Companies?

We expect that gender-diverse boards encourage overconfident CEOs to create more long term cor-

porate value (Hypothesis 2). We use Tobin’s Q as our primary measure of long term firm value

(as per Gompers, Ishii, and Metrick (2003); Bebchuk, Cohen, and Ferrell (2009)). We examine the

impact of gender-diverse boards and CEO overconfidence on firm-value by constructing a firm-year

panel of all companies, except utilities and financial services, in the COMPUSTAT database that

have the requisite data. We estimate these models with firm and year fixed effects.24 Standard errors

are clustered by firm. The model has the following specification where firm performance is based on

24The results are robust to controlling for industry fixed effects.

20

Tobin’s Q:

Tobin’s Qi, t+1 = α+ β1 Female Director Indicator/Ratioi,t + β2 CEO Holder67i,t + β3

Female Director Indicator/Ratioi,t × CEO Holder67i,t + θXi,t + φt + λj(i) + εi,t.

(4)

We present results for Tobin’s Q in Table 6. We expect to find a positive coefficient on the

interaction term of an overconfident CEO and board gender diversity. In Columns (1) through

(4) we use Female Director Indicator as a measure of board gender diversity and in Columns (5)

though (8) we use Female Director Ratio as an alternative measure of board gender diversity. As

expected, we find that overconfident CEOs have either no effects or negative effects in firms without

a gender diverse board. This is reflected in the insignificant (Columns 1 and 2) coefficients on CEO

Holder67. But coefficients associated with the interaction term are positive and significant in all

eight models. The coefficient associated with Female Director Indicator × CEO Holder67 is positive

and significant at the 1% level in the first four columns. Similarly, the coefficients associated with the

interaction term Female Director Ratio × CEO Holder67 are positive and significant in the last four

columns. These results indicate that the monitoring by gender diverse boards leads overconfident

CEOs to channel their investment and risk taking strategies towards improving shareholder wealth.

For example, from the results presented in Column 1, we see that the net effect of overconfident

CEOs on Tobin’s Q is 0.131 (0.227-0.096). Economically, the estimates from Column 5 indicate

that one standard deviation (9.5%) increase (the addition of one female director) to a firm led by

overconfident CEO adds 4.6% to a firm’s market value. We also derive the economic significance

of our results: In Column 5, the coefficient on CEO Holder67 is -0.049 and the coefficient on the

interaction term Female Director Ratio × CEO Holder67 is 0.985. The mean of Tobin’s Q in our

sample is 1.935. Therefore, the overall effect of a 10% increase in the female director ratio for the

average firm managed by overconfident CEO is equal to (0.985 − 0.049) × 0.0951.935 = 0.0459 or 4.6%

increase in Tobin’s Q.

Next, we use other measures of CEO overconfidence to analyze the effects of gender-diverse boards

on long term corporate value. The other measures of CEO overconfidence includes a continuous

measure of CEO overconfidence, the top half of the continuous measure (CEO ConfidenceTop50 )

and the top quartile of the continuous measure (CEO Confidence Top25 ). We present results for

Tobin’s Q and the alternative measures of CEO overconfidence in Table 6. We expect to find a

positive coefficient on the interaction term of an overconfident CEO and board gender diversity and

21

the empirical results support this hypothesis. We observed that the coefficients of the interaction

terms Female Director Ratio × CEO Confidence, Female Director Ratio × CEO ConfidenceTop25,

and Female Director Ratio × CEO ConfidenceTop50 are positive and significant at the 1% level.

In Table 6, we find that the coefficients associated with the female director indicator/ratio are

either statistically insignificant or negative and significant, which suggests that female directors are

not adding value in firms managed by nonoverconfident CEOs, which is consistent with findings of

Adams and Ferreira (2009). Also, we find that the sum of the coefficients of CEO Holder67 and the

interaction term FID Indicator × CEO Holder67 in Columns 1, 2 and 4 are positive and significant

at the 1% level.

4.3.2 Does the Presence of Female Director Associated with Increase in Operating

Performance in Overconfident CEOs’ Companies?

We also expect that gender-diverse boards encourage overconfident CEOs to improve operating

performance. We measure operating performance by a firm’s return on assets (EBIT/Assets)i, t+1

following Powell and Stark (2005) and by operating cash flow, (OCF/Assets)i, t+1 (following Lee,

Ingram, and Howard, 2010). We examine the impact of gender-diverse boards and CEO overconfi-

dence on operating performance by constructing a firm-year panel of all companies except utilities

and financial services in the COMPUSTAT database that have the necessary data. The models are

of the following form:

Operating Performancei, t+1 = α+ β1 Female Director Indicator/Ratioi,t + β2 CEO Holder67i,t + β3

Female Director Indicator/Ratioi,t × CEO Holder67i,t + θXi,t + φt + λj(i) + εi,t

(5)

where Operating Performancei, t+1 stands for EBIT/Assetsi, t+1 or OCF/Assetsi, t+1.

Like Tobin’s Q, we obtain similar results for a firm’s operating performance. Table 7 presents

results based on end of next year firm operating performance as the dependent variable. Like Table

6, we continue to find a positive effect of female directors on the operating performance of firms led

by an overconfident CEO, although female directors in firms without overconfident CEOs have no

such effect. We also examine operating cash flow scaled by total assets as an alternative measure of

operating performance. Operating cash flows are free from earnings management concerns related

to use of accruals. In untabulated results, similar to the findings for operating profitability reported

in Table 7, we observe that the interaction terms Female Director Ratio × CEO Holder67 and

22

Female Director Indicator × CEO Holder67 are positive and significant at the 5% level when we use

operating cash flow (OCF) as the dependent variable. Also in Table 7, we find that the coefficients

associated with the female director indicator/ratio are statistically insignificant, again indicating

that gender diversity is primarily beneficial in firms headed by overconfident CEOs.

4.4 Female Directors’ Affiliation, Overconfident CEOs and Firm Performance

In the previous sections, we find that board gender diversity reduces overinvestment tendencies

and risk exposures caused by overconfident CEOs. An important question that naturally arises

is whether this effect comes from a certain type of female director or from any type of female

director. To analyze this question, we examine the affiliation of female directors to see if this effect is

fundamentally influenced by the type of director affiliation. We expect the effect to be stronger for

female independent directors as they are less likely to be influenced by the CEO compared to female

executive directors or other affiliated outside directors, who have a business or familial affiliation

with the firm or its senior executives.

We identify female directors who are financially and familially unconnected to the CEO and have

no other financial relationships with the firm except for serving as a Female Independent Director

(FID). We place female executive directors in a separate category (Female Executive Director). Then,

we create a third category of female affiliated directors who could be suppliers, bankers, lawyers,

consultants etc. that provide services or products to the firm (Female Gray Director). First, we

create an indicator variable for each of these three categories of female directors. Alternatively, we

employ the ratio of the number of female directors in each of these categories scaled by board size

as the key explanatory variable.

We re-estimate our prior models with Tobin’s Q as dependent variable along with these three

types of female directors as explanatory variables (both indicator and ratio) and present the results in

Table 8. Of the six regression estimates reported on Table 8, only two interaction terms associated

with female independent directors (in Columns 1 and 4) are positive and significant. All other

interaction terms associated with female affiliated and female executive director are insignificant.

These results confirm our conjecture that the positive effects of board gender diversity in firms led

by overconfident CEOs is primarily due to female independent directors, who tend to be less strongly

influenced by CEO. In Table 8, we find that the sum of the CEO overconfidence coefficients of CEO

Holder67 and the interaction term FID Indicator × CEO Holder67 in Column 1 is positive and

significant at the 1% level, which suggests that overconfident CEOs create shareholder value when

23

female independent directors are present.

4.5 Appointment, Departure of Female Independent Directors, Overconfident

CEOs and Firm Performance: Difference-In-Difference analysis

Although we find substantial evidence that gender diverse boards affect corporate performance pos-

itively if a firm is led by an overconfident CEO, these results can be affected by various endogeneity

concerns. For example, one can argue that since there is such a large demand for female directors

after the passage of Sarbenes-Oxley Act 2000, they can self-select to serve on the boards of higher

quality firms that also exhibit other strong governance mechanisms or a strong performance based

culture, which is not captured by our current models. Hence, we examine female directors appoint-

ments and departures in period t. We also looked at the appointment of overconfident CEOs in firms

that previously did not have an overconfident CEO, but did have a gender-diverse board. Given our

results from Section 4.4 , we focus on only two variants of our main explanatory variable, formally

Female Independent Director Indicator and Female Independent Director Ratio for the remainder of

our analysis.

4.5.1 Appointment of Female Independent Directors, Overconfident CEOs and Firm

Performance

First, we re-examine the effects of gender diverse boards in firms that are led by overconfident CEOs

by examining the appointments of female directors on changes in Tobin’s Q from the pre-appointment

to the post-appointment period; i.e., we use the following dependent variable: ∆Qi(t − 1, t + 1) =

Tobin’s Qi,t+1 − Tobin’s Qi,t−1. We create an indicator variable: FID Appointment Indicator. This

indicator is one if there is at least one female independent director appointed to the company’s board

in period t, and is zero otherwise. In order to obtain a sharper test, we drop sample firms that also

appoint a new male independent director in the same period t. The model takes of the following

form:

∆Qi(t− 1, t+ 1) = α+ β1 FID Appointment Indicatori,t + β2 CEO Holder67i,t + β3

FID Appointment Indicatori,t × CEO Holder67i,t + θXi,t + φt + λj(i) + εi,t.

(6)

We present the results from this analysis in Column 1 of Table 9.25 Consistent with our earlier

25We test for the trend of common assumptions and find no violation of this assumption in this analysis.

24

findings, we find a positive market reaction to female director appointments in firms managed by

overconfident CEOs. The coefficient on CEO Holder67 is negative and significant at 1% level consis-

tent with overconfident CEOs destroying shareholder value. The coefficient on the interaction term

FID Appointment Indicator × CEO Holder67 is positive and statistically significant, indicating that

adding a gender diverse board is beneficial. This evidence also indicates that our firm performance

results are unlikely to be driven by endogenous relationships.

Since a gender diverse board helps to restrain excessive investment and risk-taking strategies of

overconfident CEOs, we expect to find the largest effect in those firms that appoint a new female

independent director in the current period and have no female independent directors in the prior

year. To test this hypothesis, we identify firms in our sample that lack such a director in prior year,

but then appoint a female independent director sometime in our sample period. We re-estimate our

difference-in-difference analysis using this sub-sample of firms, which has 2,055 firm-year observations.

The resulting estimates are presented in Columns 9 through 12 of Table 9. As expected, we find a

negative and significant coefficient on the CEO overconfidence measures (e.g. CEO Holder67 ), while

the coefficient on the interaction terms of FID Appointment Indicator and the CEO overconfidence

measures are positive and significant. For example, the sum of the coefficients of CEO Holder67

and the interaction term FID Appointment Indicator × CEO Holder67 is positive and insignifi-

cant in Column 1, while it is positive and significant at the 5% or 10% level in Columns 5 and 9,

which suggests that a gender diverse board significantly mitigates the value-destroying effects of an

overconfident CEO.

If gender diverse boards discipline overconfident CEOs and channel investment strategies in a

more positive direction that selects value enhancing projects, then we should observe a positive effect

in firms with a gender diverse board that appoint an overconfident CEO for the first time. We expect

to see a non-negative effect for such firms, but no effects for firms that have a gender diverse board

and are managed by a non-overconfident CEO. We present the results of this analysis in Table 10.

We find that gender diverse boards are beneficial when they appoint an overconfident CEO. The

coefficient on the interaction term FID Indicator × Overconfident CEO Appointment is positive and

significant at the 10% level (coefficient: 0.577*, t-statistic: 1.882). Interestingly, the coefficient on

FID Indicator itself is insignificant.

25

4.5.2 Departure of Female Independent Directors, Overconfident CEOs and Firm Per-

formance: Exogenous and Non-exogenous Departures

To further address these endogeneity concerns, we also examine whether the departure of female

independent directors at overconfident CEO led firms hurts its performance. If the positive effects

that we documented before are driven by the presence of female directors on boards of overconfident

CEO led firms, then we should expect to find a negative effect on the departure of female independent

directors if the firm continues to have an overconfident CEO. It is of course possible that female

director departures occur due to reasons that are endogenous to firm performance. For example,

female independent directors might start leaving a firm that is about to perform poorly. In that

case, the negative effect that we interpret to be due to departure of female independent directors

may not be a “results of the departure” itself, but instead, a reverse causality effect of directors

reacting to negative proprietary information about the firm.

To avoid such endogeneity concerns, we identify cases where a female independent director de-

parture occurs due to death, critical illness, term limits or the retirement policies of the firm. We

obtain this data from Audit Analytics for the period of 2001-2011. We find 94 departures of fe-

male independent directors initially from Audit Analytics, but after merging these cases with our

sample, we are left with 57 firm-year observations. We exclude those firms that also experience

a male independent director departure alongside a female independent director departure to avoid

any conflation of the reasons for the performance change. We use the change in Tobin’s Q from

pre-departure to post-departure years as the dependent variable. We re-estimate our base model of

firm performance including this FID Departure Indicator and its interaction with our three measures

of CEO overconfidence: namely CEO Confidence, CEO ConfidenceTop50 and CEO Holder67 as our

main explanatory variable. The model specification has the following form:

∆Q(t− 1, t+ 1) = α+ β(1) FID Departure Indicatori,t + β(2) CEO Holder67/Confidence/ConfidenceTop50i,t

+ β(3) FID Departure Indicatori,t × CEO Holder67/Confidence/ConfidenceTop50i,t

+ θ xi,t + φt + εi,t. (7)

To further sharpen our test, we only consider those departures that leave the board non-gender

diverse.

We present the results of estimating Equation (7) in Table 11. Consistent with our primary

hypothesis, we find that firms led by overconfident CEOs experience a negative change in their per-

26

formance when a FID departs for exogenous reasons, regardless of which of the three measures of

CEO overconfidence we use. We find a negative and significant coefficients on the interaction terms

FID Departure Indicator × CEO Overconfidence and FID Departure Indicator × CEO Holder67.26

On the other hand, the coefficient on the FID Departure Indicator itself is insignificant in both sets

of regressions. Also, we find that the sum of the coefficients of CEO Holder67 and the interac-

tion term FID Departure Indicator × CEO Holder67 is negative and significant at the 1% level in

Columns 2, 3 and 5, and negative and insignificant in Column 6. These results again are generally

consistent with our main hypothesis that gender-diverse board are primarily helpful in disciplining

overconfident CEOs and more specifically in channeling their investments and risk taking strategies

in more productive directions that create shareholder value.

4.6 SOX, Demand for Female Independent Directors, Overconfident CEOs and

Corporate Performance

In Table 2, we observe an increase in female directors in the post-SOX period, especially in female

independent directors. Banerjee et al. (2015) find that SOX also exhibits a restraining effect on

overconfident CEOs, similar to the effect of female independent directors. In this section, we ex-

amine whether the post-SOX restraint on CEO behavior that Banerjee et al. (2015) documented is

actually driven by those firms that hired female independent directors. On the other hand, if other

independent directors hired in post-SOX period have a similar restraining effect on overconfident

CEOs, then we should expect a reduced (or negligible) impact of female independent directors in the

post-SOX period. To examine these questions, we divide our sample into pre- and post-SOX periods

where the pre-SOX period is defined as pre-2002 and then we separately estimate Equation (4) for

the two sub-periods.

We present these sub-period results in Table 12. We estimate this equation under four alternative

measures of CEO overconfidence: CEO Holder67, CEO Confidence, CEO ConfidenceTop50 and

CEO ConfidenceTop25. We use both the FID Indicator and FID Ratio as measures of gender

diversity. We find that the positive effects of female independent directors in overconfident CEO led

firms are primarily concentrated in the pre-SOX period. In Columns 1 through 8, the interaction

terms of the FID Indicator (Ratio) with all four alternative measures of CEO overconfidence are

26With CEO Holder67 measure we may have a small sample issue; hence, we use multiple measures of CEO overconfi-dence to tease out concern. Also to increase the departure sample size, we test our hypothesis using female independentdirector departures – for known and unknown reasons – at firms led by overconfident CEOs. We find somewhat weakerresult, but there is a negative and significant coefficient on the interaction term FID Departure Indicator × CEOConfidence and on interaction term Female director departure indicator × ConfidenceTop50.

27

positive and significant at the 1% level. We do not find any significant differential effects of board

gender diversity on overconfident CEO led firms in the post-SOX period. These results indicate

that the disciplining effects of female independent directors is only present in firms where other

directors are less likely to be acting as strong monitors/advisors, which is concentrated in the pre-

SOX period. In the post-SOX period when most boards are independent, overconfident CEOs

are more likely to be effectively monitored and disciplined by these independent directors. This

is consistent with the findings of Banerjee et al. (2015). The post-SOX listing rule changes also

require the board’s nominating committee to be composed of 100% independent directors and as a

consequence, subsequent independent director appointments by these boards are likely to be truly

independent, rather than only appearing to be independent.

4.6.1 Compliance with SOX, board gender diversity, overconfident CEOs and Corpo-

rate Performance

In the analysis of board gender diversity in the post-SOX period, we find that its restraining effects

are only significant in the pre-SOX period, when boards are generally not providing the necessary

level of monitoring of overconfident CEOs. Not surprising, the effect of board gender diversity

on overconfident CEOs behavior is no longer apparent in the post-SOX period when boards are

independent.

To more directly test the conjecture that regulatory changes around SOX replaced the benefits of

board gender diversity on overconfident CEO led firms, we assess how female independent directors

affect the behavior of overconfident CEOs prior to the passage of SOX in firms compliant with

the board independence requirements. The SOX regulations along with the associated post-SOX

exchange listing rules forced publicly listed companies to have a majority of independent directors

as well as fully independent audit, nominating and compensation committees. Using these four

criteria, we identify firms compliant with these board regulations at the end of year 2001 along with

non-compliant firms. We then analyze whether the effects of board gender diversity varied by board

compliance status in both the pre-SOX and post-SOX periods.

The results of this analysis are presented in Table 13. As expected, we find that the interaction

term FID Indicator × CEO Holder67 is positive and significant in only one of the four sub-samples,

namely the sub-sample of non-compliant firms in the pre-SOX period. The coefficient estimates of

this interaction term in the other three subsamples are all insignificant, which was also expected.

Also, the coefficients on the FID Indicator is insignificant across all the models. These results indicate

28

that the post-SOX listing rule requirements of an independent board and fully independent major

board committees appear to replace the moderating effects of board gender diversity in firms with

overconfident CEOs. As a consequence, these firms did not enjoy any incremental valuation benefits

from being compliant with SOX related listing requirements.

4.7 Female Independent Directors, Overconfident CEOs and Corporate Perfor-

mance: Effects of Other Governance Mechanisms

Some studies document evidence that other governance mechanisms such as insider ownership, and

the presence of independent nominating committees can impact board monitoring effectiveness. We

examine whether the presence of these mechanisms weakens the effects of board gender diversity on

firms with overconfident CEOs in Table 14. We find that high insider ownership does not weaken the

positive effect of board gender diversity. However, at firms led by overconfident CEOs and lacking

a fully independent nominating committee, the positive effect of board gender diversity on firm

performance disappears. We conjecture that this is because non-independent nominating committees

often select outside female directors who are not truly independent. Overall, these results indicate

that the positive effects of board gender diversity on overconfident CEOs are not fully explained

by the other corporate governance mechanisms, particularly when female independent directors are

truly independent.

5 Robustness Tests

We take several additional steps to assess alternative explanations for our findings and to mitigate

econometric concerns about the robustness of our analysis.

5.1 2SLS Instrumental Variable Estimation

Although we present a range of empirical evidence to support our hypothesis that board gender di-

versity disciplines overconfident CEOs and that this drives firm investment and risk-taking strategies

that help create shareholder wealth, it is still be possible for these relations to be driven by reverse

causality. For instance, one can argue that due to paucity of female independent directors and the

rising demand for independent directors, these directors can easily self-select to sit on the boards

of highly valuable and prestigious firms and these firms are highly valuable due to the innovative

efforts of their overconfident CEOs (see e.g., Hirshleifer et al., 2012). To address this concern, we

use a 2SLS (IV) approach and present the resulting estimates in Table 15.

29

For the 2SLS estimation, instruments are needed that are strongly correlated with the presence of

female directors with corporate experience, but uncorrelated with firm performance metrics except

through the presence of such female directors. As our instrument, we employ the proportion of firms

with female independent directors among all the firms headquartered in the same county as the firm

in question, but excluding the firm in question. This variable is designed to capture the local supply

of female independent directors among peer firms, but it is unlikely to have a measurable impact

on the performance of the firm in question, except through the change in its board composition.27

Thus, the county-based instrument appears to be suitable IV since the available supply of female

independent directors at other local peer firms should affect the board composition at the firm in

question, but it is unlikely to impact the performance of a firm directly, but only through its board

composition.

The first stage results from OLS estimation using the female independent director indicator and

ratio as the dependent variable are reported in Columns 1 and 2 of Table 15. These estimates show

that the instrumental variable has a significant positive association with the FID Indicator and the

FID Ratio respectively. The predicted values of the FID Indicator and the FID Ratio estimated from

the first stage equations are then included as explanatory variables in the second stage regressions.

The second stage estimates are reported in Columns 3 and 4 of Table 15. They indicate that the

interaction terms of CEO Holder67 with the predicted values of the FID Indicator and FID Ratio

are both positively associated with Tobin’s Q, and are significant at the 5% level. These findings are

inconsistent with reverse causality being the cause of our main results.

6 Additional Robustness Test

6.1 Press-Based Measure of CEO Overconfidence

Our results are also robust to using a media or press-based measure of CEO overconfidence. Prior

studies have used press-based measures of overconfidence, usually based on a comparison of the

number of articles that report a CEO as being overconfident with those that report the CEO as

being non-overconfident (see e.g. Hirshleifer et al., 2012; Shu, Yeh, Chiang, and Hung, 2013). We

follow a similar method and construct a News Ratio measure, which is equal to the number of articles

that report the CEO as overconfident divided by the total number of articles collected, provide that

the number of articles reporting the CEO as overconfident is strictly greater than the number of

27See, for example, Balsam, Puthenpurackal, and Upadhyay (2016) who examine board leadership choices and findthat the predicted board leadership choice, which is based on peer leadership choices, positively affects firm performance.

30

articles that report the CEO as non-overconfident. We obtain news articles by conducting “Factiva”

keyword searches (as in Hirshleifer et al., 2012) of articles in the New York Times, US Today, Business

Week, and Wall Street Journal.28 We have this data for the years 2000, 2004, 2006. We estimate the

statistical model over the years 2000-2006. We interpolate the data for the intervening years where we

have no news-articles data. We report the results of this subsample in Table OA1, which is presented

in the Online Appendix 1. For brevity, we do not tabulate all these results. The important outcome

is that these results are qualitatively similar to the main results reported earlier, and indicate that

our findings are robust to this alternative measure of CEO overconfidence.

6.2 Options Relative to CEO Compensation

A concern with some option-based overconfidence measures is that they do not capture whether the

vested options are economically important to the CEO. One way to address this concern is to divide

the value of a CEO’s options by the CEO’s salary. We construct this measure by taking the natural

log of one plus the ratio of the total value of vested, but unexercised options, scaled by the CEO’s

annual total compensation (Execucomp: tdc1). The reported results are in Table OA1 of the Online

Appendix 1 and they are qualitatively similar to those found in the main models.

6.3 Male Independent Directors and Overconfident CEOs

We conduct placebo tests to examine the impact of having a Male Independent Director in firms

with overconfident CEOs. We re-estimate the base models by replacing the Female Independent

Director Indicator by an analogous Male Independent Director Indicator. We then undertake the

same tests on our full sample of firms after excluding firms with female directors in the boardroom

(in order to ensure that any ineffectiveness in male independent directors is not due to the presence

of female directors). The results indicate that combination of a Male Independent Director and

an overconfident CEO is not associated with a reduction in firm investment or risk taking, nor is

it associated with improvements in firm value, acquisition performance, earnings, or dividends. In

other words, the female-independent-director effect observed in firms with overconfident CEOs is

not mirrored in a similar male-independent-director effect. We report these results in Table OA3

presented in the Online Appendix 1.

28We search for positive words like “overconfident” or “overconfidence,” “optimistic,” or “optimism,” or “aggressive,”and search for negative words like “reliable”, “cautious”, “conservative”, “practical”, “frugal”, or “steady.” We carefullyhand-check that these terms are generally used to describe the CEO in question and separate out newspaper articlesdescribing the CEO of interest as “not confident” or “not optimistic.”

31

6.4 Residual CEO Overconfidence

The Black-Scholes value of options are closely correlated with stock returns. Thus, managers with

private information about a stock’s future return are likely to hold on to their in-the-money exercis-

able stock options. Such CEOs will be wrongly labelled as overconfident according to the Malmendier

and Tate (2005) classification, when in fact these CEOs are really using their private information

to time the market. To differentiate between “perceived” private information and “true” private

information, we create a “residual” confidence measure (CEO Confidence Residual), which is defined

as the residual from a regression of the CEO Confidence variable onto future stock returns from year

t+ 1. This CEO Confidence Residual represents the portion of the CEO Confidence measure that is

not a mere reflection of future stock performance. The results of this test are reported in Table OA4

of the Online Appendix 1. The estimates based on this residual CEO overconfidence measure are

consistent with the evidence from our main models. Given these results, we conclude that a CEO’s

private information about a firm’s future stock performance is unlikely to drive our results.

6.5 Controlling for New CEOs

We find that our results are also robust to excluding firms that experience recent CEO turnovers.

For this purpose, we restrict ourselves to a sub-sample of firms where the firm’s CEO remains in

office for at least 4 years. Thus, the results of re-estimating Equation (4) for this subsample of firms

can not merely reflect a mechanical change in overconfidence due to the turnover of the CEO. These

findings are reported in Table OA5 of the Online Appendix 1 and are qualitatively similar to those

reported in our main models.

6.6 Controlling for Entrenchment

The results are also robust to controlling for managerial entrenchment. Prior literature indicates

that managerial entrenchment, as proxied by having a preponderance of anti-takeover provisions, can

insulate managers from the market for corporate control and enable managers to make self-interested

or unprofitable empire building investments (see e.g. Bebchuk et al. (2009); Gompers et al. (2003);

Harford, Humphery-Jenner, and Powell (2012); Masulis, Wang, and Xie (2007)). However, other

empirical studies suggest an endogenous link between CEO entrenchment and firm performance

(Core, Guay, and Rusticus (2006); Lehn, Patro, and Zhao (2007); O’Connor and Rafferty (2012)).

To address this endogeneity concern, we require data on managerial entrenchment (from IRRC/Risk

Metrics), which significantly reduces our sample size. In robustness tests, we examine models that

32

includes a control for the average entrenchment index (E-index) for six key anti-takeover provisions

proposed by Bebchuk et al. (2009) for other firms headquartered in the same state or alternatively

by the firm’s actual E-index. We examine state-average E-index level on the grounds that the

degree of entrenchment depends on the statutory takeover protections provided in a firm’s state-of-

incorporation. We note that the prior literature suggests that a race-to-the-bottom occurred earlier

in terms of these state-level takeover provisions and particularly with respect to state business com-

bination statutes (see e.g., McCahery and Vermeulen, 2005). However, our results are qualitatively

robust to controlling for a CEO’s entrenchment level and are left untabulated for brevity.

6.7 Robustness to CEO Age and Gender

Another possibility is that there is a significant relationship between CEO age and firm risk taking

(see e.g., Kim (2013)). To explore this possibility, we include a control for CEO age. We also

find that our results are qualitatively robust to splitting the sample based on median CEO age,

suggesting that CEO age per se does not drive our findings.29 These findings (unreported) are also

robust to controlling for CEO-gender, which Levi, Li, and Zhang (2010) finds is correlated with

overconfident-CEO behavior, such as the tendency to undertake acquisitions.

6.8 Variation in Time and Industry Effects

In all our main results, we include firm and year fixed effects and standard errors are clustered at

the firm level. However, our results are robust to including (i) industry fixed effects in place of firm

fixed effects (based on 3-digit SIC-levels or higher), (ii) to excluding industry and year fixed effects

entirely, and (iii) to clustering standard errors by industry or year, rather than by firm. The results

are also robust to using either the NAICS 3-digit industries or the Hoberg and Phillips (2010) industry

classifications in place of the 3-digit SIC industries. We also obtain qualitatively similar results if we

cluster by year, industry, or double cluster by industry and year so as to capture differential industry

trends. Moreover, our results are qualitatively similar if we omit the Tech-Crash years of 2000 and

2001, or if we remove all the high-tech firms from the sample.30 Likewise, the results are robust to

omitting the global financial crisis years and the post-crisis years (2007 onward). Another concern

is that the purported effect of SOX can be affected by the corporate board’s or its shareholders’

29Our primary results are also robust to excluding firms that only recently became public.30Specifically, we define the high-tech firms, following Loughran and Ritter (2002), as those whose industries are

in computer hardware (SIC: 3571, 3572, 3575, 3577, and 3578), communication equipment (SIC: 3661, 3663, 3669),electronics (SIC: 3671, 3672, 3674, 3675, 3677, 3678, 3679), and navigation (SIC: 3812), measuring (SIC: 3823, 3825,3826, 3827, and 3829), medical (SIC 3841 and 3845), telecommunications equipment (SIC: 4812, 4813), communicationservices (SIC: 4899), software (SIC: 7371, 7372, 7373, 7374, 7375,7378 and 7379).

33

response to the back-dating scandals which occurred within our sample period. These backdating

scandals tend to occur in firms with a higher proportion of inside directors according to Veld and

Wu (2014). We address this concern by using the Corporate Library to identify firms with any

reported backdating (see e.g., Lie (2005) and then include an indicator for these firms as a control

in our baseline regressions. Our results (unreported) are robust to including this control and to

alternatively excluding these back-dating firms from the sample.

7 Conclusion

Two highly contentious issues in the corporate governance literature are the effects of CEO overcon-

fidence and whether gender-diverse boards offer any tangible governance benefits. Prior literature

documents that CEO overconfidence can entail both benefits and costs. The benefits of CEO over-

confidence include more rapid innovations and higher product market shares (see e.g., Hirshleifer

et al., 2012; Galasso and Simcoe, 2011; Simsek et al., 2010). But CEO overconfidence also has a

dark side. It is associated with over-investment and with high and potentially excessive risk-taking

(see e.g., Malmendier and Tate, 2008, 2005). We believe that the diverse perspectives of directors of

different genders enable boards to become better monitors and advisors, which in turn, has a positive

impact on the governance of public corporations and on firm performance and valuation.

We hypothesize that improving boardroom gender diversity can help to restrain overconfident

CEOs. Further, the presence of female directors positively moderates the impact of CEO overcon-

fidence on various types of firm investment decisions and leads to improved firm value, earnings

and operating performance. To address endogeneity concerns, we study female director departures

due to exogenous causes such as death, illness and mandatory retirement age. We find that such

departures have negative market reactions and adverse effects on the performance of firms led by

overconfident CEOs, especially when these departures result in the loss of a gender diverse board.

We also document the positive effects of female director appointments on the performance of firms

led by overconfident CEOs, although it must be recognized that these appointments are not exoge-

nously determined.31 Further, we find that in the post-SOX period, the beneficial effects of female

board members are no longer significant, suggesting that governance benefits of SOX and the re-

lated exchange listing rule changes yield similar outcomes to having gender-diverse boards. Likewise,

when firms are compliant with these SOX related board characteristics before the passage of SOX,

there is no incremental effects of gender diverse boards. Importantly, the beneficial aspects of female

31This is similar in spirit to the Jensen and Meckling (1976) argument.

34

directors appear primarily to be attributable to female directors who are independent of the CEO.

Overall, the major findings of this study suggest that the presence of female directors, and especially

female independent directors, improves corporate governance standards and helps to mitigate the

potentially harmful aspects of CEO overconfidence, but importantly it does not appear to undercut

the positive aspects of having overconfident CEOs.

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40

Data Appendix 1 Variable Definitions

1. Board independence: Ratio of independent outside directors to board size. Source: RiskMetrics

2. Beta: The firm’s beta as estimated using a single index model using daily stock returns overthe course of the year with an CRSP equally weighted market index. Source: CRSP

3. CAPEX/Sales: The firm’s capital expenditures scaled by its sales. Source: COMPUSTAT

4. CEO Bonus/Salary: Bonus/Salary for a CEO. Source: ExecuComp

5. CEO Holder67: =1 if CEO Overconfidence ≥ 0.67, zero otherwise. Source: ExecuComp,COMPUSTAT

6. CEO Overconfidence: Ratio of value of all unexercised exercisable options (Execucomp: optunex exer est val) by the number of options (Execucomp: opt unex exer num), scaled by theprice at the end of the fiscal year as reported in (COMPUSTAT: prcc f)

7. CEO Overconfidence Top50= 1 if CEO overconfidence is greater than the sample median, zerootherwise. Source: ExecuComp, COMPUSTAT

8. CEO Overconfidence Top25= 1 if CEO overconfidence is greater than the 3rd quartile value ofthe sample, zero otherwise. Source: ExecuComp, COMPUSTAT

9. Co-opted Board: = 1, if the number of board members appointed during current CEO resignexceeds 50% (a variant uses 40% as well). Source: RiskMetrics

10. County ratio of firms with female independent director: The proportion of number of firmswith at least one female independent director (except sample firm) to number of all firms inthe county of the sample firms, computed yearly. Source: ExecuComp, COMPUSTAT, Proxystatements

11. Diversification: Number of operating segments. Source: COMPUSTAT

12. EBIT/Assets: Operating income divided by total assets. Source: COMPUSTAT

13. Female CEO indicator: Indicator variable that takes a value of 1 if firm’s CEO is female in agiven year, zero otherwise. Source: ExecuComp

14. Female Director Indicator: =1 if a board has at least one female director, zero otherwise.Source: RiskMetrics

15. Female Director Ratio: Ratio of number of female directors to board size. Source: RiskMetrics

16. Female Executive Director Indicator: =1 if a firms has at least one employee female director,zero otherwise. Source: RiskMetrics

17. Female Executive Director Ratio: = Ratio of number of female executive directors to boardsize Source: RiskMetrics

18. Female Gray Director Indicator: = 1 if a firms has at least one affiliated/gray female director,zero otherwise. Source: RiskMetrics

19. Female Gray Director Ratio: = Ratio of number of female gray directors to board size Source:RiskMetrics

41

20. Female Independent Female Director Indicator: = 1 if a firms has at least one independentfemale director, zero otherwise. Source: RiskMetrics

21. Female Independent Director Ratio: = Ratio of number of independent female directors toboard size. Source: RiskMetrics

22. Firm size: Natural log of sales. Source: COMPUSTAT

23. Insider ownership: Percentage of outstanding shares held by the directors and officers, excludingthe CEO. Source: RiskMetrics

24. Institutional ownership: Percentage of outstanding shares held by institutional investors. Source:Thomson Financial

25. Intangible Assets: Intangibles/Assets. Source: COMPUSTAT

26. Ln(CEO Age): Natural log of # of CEO Age. Source: ExecuComp

27. Ln(CEO tenure): Natural Log of # of years served by a CEO in current position. Source:ExecuComp

28. Ln(Firm age): Natural log of number of years that a firm has been in CRSP. Source: CRSP

29. Leverage: Long term debt/total assets. Source: COMPUSTAT

30. Ln(Boardsize): Natural log of Board Size which is # of directors on board. Source: RiskMetrics

31. MSE: The mean squared error from the estimation of the single index model (above) over thecourse of that year. Source: CRSP

32. Operating cash flow: Net Operating Cash Flow/Assets (Compustat)

33. PP&E/sales: Ratio of gross PP&E to sales. Source: COMPUSTAT

34. R&D intensity: R&D expense divided by total assets. Source: COMPUSTAT

35. SG&A/Sales: Ratio of SG&A expenses to annual sales. Source: COMPUSTAT

36. SOX = 1 if the observation occurs in 2002 or later and equals zero otherwise.

37. SOX-Compliant=1 if a firm meets independence requirements by year 2002 (board indepen-dence¿51%; fully independent audit and nominating committees), zero otherwise.

38. Stock volatility: Standard deviation of monthly stock return for the prior 60 months. Source:CRSP

39. Stock return: 1-Year holding period return. Source: CRSP

40. Tobin’s Q: Ratio of (market value of equity + book value of debt) to book value of assets.Source: COMPUSTAT

42

Table 1: Year-wise Distribution of Female Directors and Independent Female Directors

This table documents year-wise distribution of Female Directors, new appointment of Female Directors and Female IndependentDirectors. The Data Appendix 1 contains more extensive variable definitions.

Directors Directors Ratio Female Directors Independent Directors Directors Director Ratio

1998 806 10,515 7.67% 110 770 6587 7.32%1999 956 10,800 8.85% 135 902 6837 8.35%2000 793 8,873 8.94% 85 749 5422 8.44%2001 889 8,998 9.88% 110 836 6005 9.29%2002 981 10,011 9.80% 137 942 6779 9.41%2003 1081 10,485 10.31% 142 1051 7368 10.02%2004 1166 10,777 10.82% 197 1167 7781 10.83%2005 1187 10,619 11.18% 163 1097 7699 10.33%2006 1021 9,066 11.26% 113 936 5782 10.32%2007 1011 8,646 11.69% 175 912 6616 10.55%2008 1197 9,670 12.38% 183 1012 7501 10.47%2009 1277 10,247 12.46% 141 1205 8042 11.76%2010 1359 10,728 12.67% 143 1279 8541 11.92%2011 1358 10,292 13.19% 157 1284 8279 12.48%

Total 15,082 139,727 10.79% 1,991 14,142 99,239 10.12%

Table 2: Women Directors Distribution in the Pre-SOX and Post-SOX Period

This table documents year-wise distribution of Female Directors, Female Independent Directors and Independent Directors inthe pre-SOX and the post-SOX periods. The Data Appendix 1 contains more extensive variable definitions.

Pre-SOX Post-SOX Change

Non-Compliant

Compliant Non-Compliant

Compliant Non-Compliant

Compliant

[1] [2] [3] [4] [5] [6]

Average Board Size 9.180 9.750 8.966 9.391 -2.33% -3.68%Independent Board and Overconfident CEO 0.400 0.686 0.583 0.742 45.75% 8.16%No. of Female Directors 0.591 0.981 0.806 1.147 36.38% 16.92%No. of Female Independent Directors 0.337 0.903 0.589 1.064 74.78% 17.83%Female Independent Director Ratio 0.037 0.093 0.062 0.108 68.89% 16.61%Female Independence Director Ratio and OverconfidentCEO

0.045 0.069 0.057 0.098 26.67% 42.03%

43

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Tab

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s,SG

&A

/Sale

sand

Acquis

itiv

eness

.Female

Direc

torIn

dicato

ris

one

ifth

ere

isat

least

one

fem

ale

dir

ecto

rin

the

com

pany’s

board

inp

eri

od

t,and

0oth

erw

ise.Female

Direc

torRatio

isa

rati

oof

fem

ale

mem

bers

toth

eto

tal

size

of

the

board

.T

he

Data

App

endix

1conta

ins

more

exte

nsi

ve

vari

able

defi

nit

ions.

All

models

are

OL

Sm

odels

that

inclu

de

firm

and

year

fixed

eff

ects

,and

use

standard

err

ors

clu

stere

dby

firm

.T

he

signifi

cance

levels

at

the

1%

,5%

,and

10%

are

denote

dby

***,

**

and

*,

resp

ecti

vely

.

Dep

endent

Vari

able

Lead

CA

PX

/Sale

sLead

PPE/Sale

sLead

SG

A/Sale

sA

quisitiv

eness

Model

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

Fem

ale

Dir

ecto

rIn

dic

ato

r-0

.004

-0.0

06

0.0

16

-0.0

82**

(-1.2

77)

(-0.8

23)

(1.1

17)

(-2.5

42)

Fem

ale

Dir

ecto

rIn

dic

ato

rx

CE

OH

old

er6

7-0

.018**

-0.0

23**

-0.0

17**

-0.1

87***

(-2.2

89)

(-2.2

08)

(-2.0

37)

(-2.6

89)

Fem

ale

Dir

ecto

rR

ati

o-0

.004

0.0

07

0.0

40

-0.4

13***

(-0.3

55)

(0.2

42)

(0.6

49)

(-2.6

26)

Fem

ale

Dir

ecto

rR

ati

ox

CE

OH

old

er6

7-0

.087**

-0.1

04**

-0.0

71*

-1.1

20**

(-2.3

97)

(-2.3

03)

(-1.7

27)

(-2.5

11)

Ln[B

oard

Siz

e]

0.0

08

0.0

06

0.0

06

0.0

06

-0.0

08

-0.0

02

-0.0

32

-0.0

78

(1.4

38)

(1.1

32)

(0.4

65)

(0.4

28)

(-0.8

68)

(-0.3

16)

(-0.5

02)

(-1.2

45)

Board

Indep

endence

0.0

04

0.0

04

-0.0

19

-0.0

21

-0.0

03

-0.0

01

-0.0

01

0.0

01

(0.6

55)

(0.5

22)

(-1.2

70)

(-1.4

15)

(-0.2

80)

(-0.0

98)

(-0.0

09)

(0.0

17)

CEO

Related

Controls

CE

OH

old

er6

70.0

19***

0.0

16***

0.0

17**

0.0

18**

0.0

19**

0.0

16**

0.3

01***

0.2

78***

(2.8

40)

(2.9

43)

(1.9

90)

(2.2

18)

(2.5

76)

(2.4

65)

(5.6

22)

(5.5

40)

Ln[C

EO

Tenure

]0.0

02*

0.0

02*

0.0

04

0.0

04

0.0

02

0.0

02

0.0

21

0.0

20

(1.9

21)

(1.9

53)

(1.4

85)

(1.5

79)

(0.6

30)

(0.6

38)

(1.5

49)

(1.4

46)

Ln[C

EO

Age]

0.0

03

0.0

02

-0.0

09

-0.0

10

0.0

12

0.0

12

0.0

79

0.0

74

(0.1

72)

(0.1

18)

(-0.4

01)

(-0.4

46)

(0.5

95)

(0.6

05)

(0.7

49)

(0.7

03)

CE

OB

onus/

Sala

ryR

ati

o0.0

01

0.0

01

-0.0

00

-0.0

00

0.0

04

0.0

04

0.0

47***

0.0

45***

(1.1

29)

(1.0

71)

(-0.0

24)

(-0.0

34)

(1.2

78)

(1.2

66)

(4.3

47)

(4.1

76)

CE

OG

ender

Indic

ato

r0.0

02

0.0

02

0.0

07

0.0

06

-0.0

07

-0.0

01

-0.1

57

-0.1

27

(0.4

96)

(0.4

22)

(0.8

52)

(0.6

82)

(-0.4

07)

(-0.0

56)

(-1.3

76)

(-1.1

07)

Firm

Related

Controls

R&

D/A

ssets

-0.0

83

-0.0

83

-0.1

99*

-0.2

94**

0.1

83

0.1

88

0.5

71*

0.6

19*

(-1.4

55)

(-1.4

52)

(-1.7

17)

(-2.5

62)

(0.3

70)

(0.3

76)

(1.8

11)

(1.9

60)

Inta

ngib

les/

Ass

ets

0.0

04

0.0

05

-0.1

02***

-0.0

75***

0.0

19

0.0

17

0.6

05***

0.6

17***

(0.5

06)

(0.5

06)

(-4.4

58)

(-3.6

35)

(0.5

91)

(0.5

07)

(8.1

37)

(8.3

06)

Siz

e-0

.003

-0.0

03

0.0

28***

0.0

18*

-0.0

48***

-0.0

47***

0.1

40***

0.1

42***

(-0.6

39)

(-0.6

57)

(3.4

81)

(1.9

05)

(-6.3

03)

(-6.3

91)

(11.7

64)

(11.8

55)

Age

-0.0

05

-0.0

06

-0.0

14

-0.0

14

-0.0

06

-0.0

06

-0.0

19

-0.0

20

(-1.1

98)

(-1.3

03)

(-1.4

32)

(-1.4

46)

(-1.0

49)

(-0.9

82)

(-1.0

90)

(-1.1

31)

Levera

ge

-0.0

70***

-0.0

70***

-0.0

70***

-0.0

66***

-0.0

25

-0.0

25

-0.1

40

-0.1

30

(-3.6

69)

(-3.6

61)

(-3.7

18)

(-3.5

86)

(-1.1

31)

(-1.1

56)

(-1.5

54)

(-1.4

38)

Div

ers

ificati

on

0.0

00

0.0

00

-0.0

01

-0.0

01

0.0

01**

0.0

01**

0.0

08**

0.0

09**

(0.7

87)

(0.7

84)

(-1.6

06)

(-1.5

03)

(2.4

95)

(2.5

60)

(2.4

21)

(2.5

00)

Insi

der

%O

wners

hip

-0.0

07

-0.0

07

0.0

40

0.0

38

0.0

04

0.0

04

-0.1

71

-0.1

70

(-1.0

06)

(-0.9

45)

(1.5

75)

(1.4

86)

(0.3

55)

(0.3

36)

(-0.9

84)

(-0.9

79)

EB

IT/A

ssets

0.0

62**

0.0

62**

0.1

02**

0.0

81*

0.0

01

0.0

02

0.2

07

0.2

18

(2.2

07)

(2.2

23)

(2.4

41)

(1.7

17)

(0.0

20)

(0.0

26)

(1.1

92)

(1.2

55)

PP

E/Sale

s0.4

64***

0.4

76***

(11.2

74)

(11.5

64)

CA

PX

/Sale

s0.4

30***

0.4

31***

(8.1

83)

(8.1

71)

SG

A/Sale

s0.8

57***

0.8

57***

(22.9

72)

(22.8

68)

Mark

etRelated

Controls

Inst

ituti

onal

%O

wners

hip

-0.0

05

-0.0

05

0.0

03

0.0

04

0.0

43

0.0

44

-0.0

41

-0.0

57

(-0.6

98)

(-0.7

50)

(0.1

53)

(0.2

15)

(1.0

96)

(1.0

90)

(-0.4

68)

(-0.6

51)

Sto

ck

Retu

rnV

ola

tility

0.0

00

0.0

00

0.0

01

0.0

01

-0.0

00

-0.0

00

0.0

02

0.0

02

(0.8

00)

(0.7

86)

(1.6

20)

(1.5

07)

(-0.0

84)

(-0.1

07)

(1.0

94)

(1.1

57)

Sto

ck

Retu

rn0.0

00***

0.0

00***

-0.0

00***

-0.0

00***

0.0

00

0.0

00

-0.0

00

-0.0

00

(3.2

63)

(3.2

74)

(-6.3

93)

(-6.3

05)

(0.3

76)

(0.3

72)

(-0.8

00)

(-0.7

17)

Inte

rcept,

Fir

m&

Year

Fix

ed

Eff

ects

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No.

of

Obse

rvati

ons

10,9

00

10,9

00

10,9

30

10,9

30

9,9

24

9,9

24

4,1

19

4,1

19

Adju

sted

R2

0.6

946

0.6

938

0.8

979

0.8

971

0.8

565

0.8

565

0.0

545

0.0

543

45

Tab

le5:

Fem

ale

Dir

ecto

rs,

Ove

r-co

nfi

den

tC

EO

san

dth

eF

irm

’sR

isk-t

akin

gS

trate

gie

s

This

table

conta

ins

models

that

analy

ze

the

rela

tionsh

ipb

etw

een

fem

ale

dir

ecto

rs,

overc

onfi

dent

CE

Os

and

the

app

oin

ting

firm

’sfu

ture

risk

takin

gst

rate

gie

s.Female

Direc

torIn

dicato

ris

one

ifth

ere

isat

least

one

fem

ale

dir

ecto

rin

the

com

pany’s

board

;and

zero

oth

erw

ise.Female

Direc

torRatio

isa

rati

oof

fem

ale

board

mem

bers

toth

eto

tal

size

of

the

board

.W

euse

mult

iple

measu

res

of

CE

Ooverc

onfi

dence.

We

als

ocontr

ol

for

lagged

Sto

ck

Retu

rnV

ola

tility

,M

SE

and

Beta

resp

ecti

vely

.O

ther

CE

O,

Fir

mand

Mark

et

rela

ted

contr

ol

vari

able

sas

list

ed

inT

able

4in

clu

ded

but

not

rep

ort

ed

for

bre

vit

y.

The

Data

App

endix

1conta

ins

more

exte

nsi

ve

vari

able

defi

nit

ions.

All

models

are

OL

Sm

odels

that

inclu

de

firm

and

year

fixed

eff

ects

,and

use

standard

err

ors

clu

stere

dby

firm

.T

he

signifi

cance

levels

at

the

1%

,5%

,and

10%

are

denote

dby

***,

**

and

*,

resp

ecti

vely

.

Vola

tility

t+

1M

SEt+

1B

eta

t+

1

Model

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

[12]

Panel

A

a.

Fem

ale

Dir

ecto

rIn

dic

ato

r0.0

29

0.2

75**

0.1

81

0.1

55

-0.0

00

0.0

00

-0.0

00

-0.0

00

-0.0

01

0.0

24

0.0

14

0.0

05

(0.2

94)

(2.3

28)

(1.5

71)

(1.4

92)

(-0.3

17)

(0.6

67)

(-0.3

74)

(-0.0

07)

(-0.0

28)

(1.0

29)

(0.6

60)

(0.2

56)

b.

CE

OH

old

er6

70.7

74***

0.0

02***

0.2

09***

(6.0

65)

(5.1

74)

(6.8

67)

c.

CE

OC

onfi

dence

1.0

95***

0.0

02***

0.2

79***

(5.2

41)

(2.7

14)

(6.4

40)

d.

CE

OC

onfi

denceT

op50

0.4

00***

0.0

00

0.0

90***

(4.0

45)

(1.2

53)

(4.2

84)

e.

CE

OC

onfi

denceT

op25

0.5

42***

0.0

01***

0.1

41***

(4.5

46)

(3.9

10)

(6.0

00)

ax

b-0

.341**

-0.0

01**

-0.0

64*

(-2.2

96)

(-2.3

10)

(-1.7

22)

ax

c-0

.713***

-0.0

02**

-0.1

17**

(-3.0

46)

(-2.1

04)

(-2.4

54)

ax

d-0

.248**

-0.0

00

-0.0

52**

(-2.2

57)

(-1.3

12)

(-2.2

91)

ax

e-0

.310**

-0.0

01*

-0.0

57**

(-2.3

70)

(-1.8

31)

(-2.1

22)

Panel

B

k.

Fem

ale

Dir

ecto

rR

ati

o-0

.048

1.1

64*

0.7

41

0.4

30

0.0

00

0.0

00

0.0

01

-0.0

00

0.0

49

0.1

48

0.0

79

0.0

21

(-0.0

96)

(1.8

79)

(1.3

03)

(0.7

97)

(0.1

36)

(0.0

25)

(0.3

47)

(-0.0

07)

(0.5

53)

(1.4

22)

(0.8

01)

(0.2

28)

l.C

EO

Hold

er6

70.7

74***

(6.0

65)

m.

CE

OC

onfi

dence

0.8

59***

0.0

01**

0.2

79***

(4.8

48)

(2.2

17)

(7.4

60)

n.

CE

OC

onfi

denceT

op50

0.3

00***

0.0

00

0.0

86***

(3.6

37)

(0.6

29)

(5.2

02)

o.

CE

OC

onfi

denceT

op25

0.5

01***

0.0

01***

0.1

45***

(5.0

68)

(4.3

00)

(7.4

70)

kx

l-1

.571**

-0.0

07***

-0.4

02**

(-2.0

25)

(-2.5

91)

(-2.0

89)

kx

m-4

.290***

-0.0

08**

-0.8

43***

(-3.6

49)

(-2.0

24)

(-3.5

79)

kx

n-1

.556***

-0.0

01

-0.3

45***

(-2.9

99)

(-0.7

67)

(-3.4

43)

kx

o-1

.608***

-0.0

05**

-0.4

05***

(-2.5

93)

(-2.1

60)

(-3.0

61)

Oth

er

CE

OC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Oth

er

Board

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mR

ela

ted

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Mark

et

Rela

ted

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Inte

rcept

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mF

ixed

Eff

ect

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Year

Fix

ed

Eff

ect

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No.

of

Obse

rvati

ons

10,2

50

10,2

50

10,2

50

10,2

50

9,3

54

9,3

54

9,3

54

9,3

54

10,9

89

10,9

89

10,9

89

10,9

89

Adju

sted

R2

0.8

892

0.8

898

0.8

897

0.8

798

0.6

215

0.6

215

0.6

211

0.6

213

0.4

501

0.4

606

0.4

595

0.4

607

46

Tab

le6:

Fem

ale

Dir

ecto

rs,

Ove

rcon

fid

ent

CE

Oan

dF

irm

’sM

arket

Per

form

an

ce

Th

ista

ble

conta

ins

mod

els

that

an

aly

zeth

ere

lati

on

ship

bet

wee

nfe

male

dir

ecto

rs,

over

confi

den

tC

EO

san

dth

eap

poin

tin

gfi

rm’s

mark

etp

erfo

rman

ce.

Th

ed

epen

den

tvari

ab

leis

on

e-p

erio

dle

ad

Tob

in’s

Q.Fem

ale

DirectorIn

dicator

ison

eif

ther

eis

at

least

on

efe

male

dir

ecto

rin

the

com

pany’s

board

;ze

rooth

erw

ise.

Fem

ale

DirectorRatio

isa

rati

oof

fem

ale

dir

ecto

rsto

the

board

size

.O

ther

CE

O,

Fir

man

dM

ark

etre

late

dco

ntr

ol

vari

ab

les

as

list

edin

Tab

le4

incl

ud

edb

ut

not

rep

ort

edfo

rb

revit

y.T

he

Data

Ap

pen

dix

1co

nta

ins

more

exte

nsi

ve

vari

ab

led

efin

itio

ns.

All

mod

els

are

OL

Sm

od

els

that

incl

ud

efi

rman

dyea

rfi

xed

effec

ts,

an

du

sest

an

dard

erro

rscl

ust

ered

by

firm

.T

he

sign

ifica

nce

level

sat

the

1%

,5%

,an

d10%

are

den

ote

dby

***,

**

an

d*,

resp

ecti

vel

y.

Tob

in’s

Qt+

1

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

a:

Fem

ale

Dir

ecto

rIn

dic

ato

r0.0

16

-0.0

62*

-0.0

42

-0.0

32

(0.7

41)

(-1.8

56)

(-1.5

19)

(-1.2

16)

b:

CE

OH

old

er67

-0.0

96

-0.0

49

(-1.6

22)

(-0.9

54)

c:C

EO

Con

fid

ence

-0.1

13

-0.0

09

(-1.5

43)

(-0.1

61)

d:

CE

OC

on

fid

ence

Top

50

-0.0

45

-0.0

01

(-1.4

87)

(-0.0

47)

e:C

EO

Con

fid

ence

Top

25

-0.0

52

0.0

01

(-1.4

37)

-0.0

36

a×

b0.2

27***

(3.1

14)

a×

c0.4

02***

(5.1

49)

a×

d0.1

38***

(4.2

12)

a×

e0.1

96***

(4.6

64)

f:F

emale

Dir

ecto

rR

ati

o-0

.055

-0.5

75***

-0.4

08***

-0.3

74***

(-0.4

60)

(-4.0

49)

(-3.0

90)

(-3.0

98)

f×

b0.9

85**

(2.5

67)

f×

c1.5

91***

(4.7

59)

f×

d0.4

87***

(3.7

08)

f×

e0.8

43***

(4.7

67)

Oth

erC

EO

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Oth

erB

oard

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mR

elate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Mark

etR

elate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Inte

rcep

t,F

irm

&Y

ear

Fix

edE

ffec

tY

esY

esY

esY

esY

esY

esY

esY

es

No.

of

Ob

serv

ati

on

s11,0

66

10,9

14

10,9

14

10,9

14

11,0

69

10,9

14

10,9

14

10,9

14

Ad

just

edR

20.5

240

0.5

184

0.5

232

0.5

783

0.5

221

0.5

757

0.5

712

0.5

806

47

Tab

le7:

Fem

ale

dir

ecto

rs,

Ove

rcon

fid

ent

CE

Oan

dF

irm

’sO

per

atin

gP

erfo

rman

ce

Th

ista

ble

conta

ins

mod

els

that

an

aly

zeth

ere

lati

on

ship

bet

wee

nfe

male

dir

ecto

rs,

over

con

fid

ent

CE

Os

an

dth

eap

poin

tin

gfi

rm’s

op

erati

ng

per

form

an

ce.

Th

ed

epen

den

tvari

ab

leis

on

e-p

erio

dle

ad

EB

IT/A

sset

s.Fem

ale

DirectorIn

dicator

ison

eif

ther

eis

at

least

on

efe

male

dir

ecto

rin

the

com

pany’s

board

;an

dze

rooth

erw

ise.

Fem

ale

DirectorRatio

isa

rati

oof

fem

ale

board

mem

ber

sto

the

tota

lsi

zeof

the

board

.O

ther

CE

O,

Fir

man

dM

ark

etre

late

dco

ntr

ol

vari

ab

les

as

list

edin

Tab

le4

incl

ud

edb

ut

not

rep

ort

edfo

rb

revit

y.T

he

Data

Ap

pen

dix

1co

nta

ins

more

exte

nsi

ve

vari

ab

led

efin

itio

ns.

All

mod

els

are

OL

Sm

od

els

that

incl

ud

efi

rman

dyea

rfi

xed

effec

ts,

an

du

sest

an

dard

erro

rscl

ust

ered

by

firm

.T

he

signifi

can

cele

vel

sat

the

1%

,5%

,an

d10%

are

den

ote

dby

***,

**

an

d*,

resp

ecti

vel

y.

(EB

IT/A

sset

s)t+

1

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

a:

Fem

ale

Dir

ecto

rIn

dic

ato

r0.0

01

-0.0

00

0.0

02

0.0

01

(0.3

63)

(-0.1

34)

-0.6

81

(0.4

79)

b:

CE

OH

old

er67

-0.0

08*

-0.0

06

(-1.6

92)

(-1.4

48)

c:C

EO

Con

fid

ence

0.0

05

0.0

06

(0.8

74)

(1.5

66)

d:

CE

OC

on

fid

ence

Top

50

0.0

03

0.0

02

(1.1

14)

(1.6

32)

e:C

EO

Con

fid

ence

Top

25

-0.0

00

0.0

02

(-0.0

22)

(0.7

88)

ax

b0.0

17***

(2.8

40)

ax

c0.0

16**

(2.5

32)

ax

d0.0

05**

(1.9

75)

ax

e0.0

10***

(3.0

03)

f:F

emale

Dir

ecto

rR

ati

o0.0

02

-0.0

07

0.0

02

0.0

01

(0.1

58)

(-0.4

61)

(0.1

31)

(0.0

64)

fx

b0.0

87***

(3.0

43)

fx

c0.0

75***

(2.6

43)

fx

d0.0

24**

(1.9

67)

fx

e0.0

51***

(3.1

75)

Oth

erC

EO

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Oth

erB

oard

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mR

elate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Mark

etR

elate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Inte

rcep

t,F

irm

&Y

ear

Fix

edE

ffec

tY

esY

esY

esY

esY

esY

esY

esY

es

No.

of

Ob

serv

ati

on

s11,0

66

11,0

66

11,0

66

11,0

66

11,0

66

11,0

66

11,0

66

11,0

66

Ad

just

edR

20.5

240

0.5

184

0.5

232

0.5

783

0.5

221

0.5

757

0.5

712

0.5

806

48

Tab

le8:

Fem

ale

Dir

ecto

rs’

Affi

liat

ion

,O

verc

onfi

den

tC

EO

and

Fir

m’s

Mark

etP

erfo

rman

ce

Th

ista

ble

conta

ins

mod

els

that

an

aly

zeth

ere

lati

on

ship

bet

wee

nfe

male

dir

ecto

rs’

pri

or

affi

liati

on

,over

con

fid

ent

CE

Oan

dth

eap

poin

tin

gfi

rm’s

mark

etp

erfo

rman

ce.

Th

ed

epen

den

tvari

ab

leis

on

e-p

erio

dle

ad

Tob

in’s

Q.Fem

ale

Indepen

den

tDirectorIn

dicator

ison

eif

ther

eis

at

least

on

efe

male

ind

epen

den

td

irec

tor

on

the

com

pany’s

board

;ze

rooth

erw

ise.

Fem

ale

GrayDirectorIn

dicator

ison

eif

ther

eis

at

least

on

efe

male

dir

ecto

rin

the

com

pany’s

board

whose

affi

liati

on

isu

ncl

ear;

zero

oth

erw

ise.

Fem

ale

Execu

tive

DirectorIn

dicator

ison

eif

ther

eis

at

least

on

efe

male

dir

ecto

ron

the

com

pany’s

board

wh

ois

als

oth

efi

rm’s

exec

uti

ve;

an

dze

rooth

erw

ise.

We

als

ou

sealt

ern

ati

ve

mea

sure

of

board

gen

der

div

ersi

ty,

nam

elyFem

ale

Indepen

den

t/Gray/Execu

tive

DirectorRatios.

Oth

erC

EO

,F

irm

an

dM

ark

etre

late

dco

ntr

ol

vari

ab

les

as

list

edin

Tab

le4

incl

ud

edb

ut

not

rep

ort

edfo

rb

revit

y.T

he

Data

Ap

pen

dix

1co

nta

ins

more

exte

nsi

ve

vari

ab

led

efin

itio

ns.

All

mod

els

are

OL

Sm

od

els

that

incl

ud

efi

rman

dyea

rfi

xed

effec

ts,

an

du

sest

an

dard

erro

rscl

ust

ered

by

firm

.T

he

sign

ifica

nce

level

sat

the

1%

,5%

,an

d10%

are

den

ote

dby

***,

**

an

d*,

resp

ecti

vel

y.

Dep

end

ent

Vari

ab

leT

ob

in’s

Qt+

1

Model

[1]

[2]

[3]

[4]

[5]

[6]

Fem

ale

Ind

epen

den

tD

irec

tor

Ind

icato

r0.0

18

(0.8

97)

Fem

ale

Ind

epen

den

tD

irec

tor

Ind

icato

r×

CE

OH

old

er67

0.2

61***

(3.6

57)

Fem

ale

Gra

yD

irec

tor

Ind

icato

r-0

.012

(-0.4

19)

Fem

ale

Gra

yD

irec

tor

Ind

icato

r×

CE

OH

old

er67

0.1

67

(1.3

14)

Fem

ale

Exec

uti

ve

Dir

ecto

rIn

dic

ato

r-0

.024

(-0.5

69)

Fem

ale

Exec

uti

ve

Dir

ecto

rIn

dic

ato

r×

CE

OH

old

er67

-0.2

30

(-1.2

20)

Fem

ale

Ind

epen

den

tD

irec

tor

Rati

o-0

.099

(-0.8

28)

Fem

ale

Ind

epen

den

tD

irec

tor

Rati

o×

CE

OH

old

er67

1.1

63***

(2.8

47)

Fem

ale

Gra

yD

irec

tor

Rati

o-0

.026

(-0.0

89)

Fem

ale

Gra

yD

irec

tor

Rati

o×

CE

OH

old

er67

1.2

58

(0.8

44)

Fem

ale

Exec

uti

ve

Dir

ecto

rR

ati

o0.1

34

(0.2

83)

Fem

ale

Exec

uti

ve

Dir

ecto

rR

ati

o×

CE

OH

old

er67

-1.4

19

(-0.8

15)

Oth

erC

EO

Rel

ate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Oth

erB

oard

Rel

ate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mR

elate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Mark

etR

elate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Inte

rcep

t,F

irm

&Y

ear

Fix

edE

ffec

tY

esY

esY

esY

esY

esY

es

No.

of

Ob

serv

ati

on

s11,0

66

11,0

32

11,0

54

11,0

66

11,0

66

11,0

66

Ad

just

edR

20.5

204

0.5

219

0.5

272

0.5

187

0.5

221

0.5

222

49

Tab

le9:

Eff

ect

ofA

pp

ointm

ent

ofF

emal

eIn

dep

end

ent

Dir

ecto

rson

Ch

ange

ofP

erfo

rman

ceof

Fir

ms

Managed

by

Ove

rconfi

den

tC

EO

s

This

table

conta

ins

diff

ere

nce-i

n-d

iffere

nce

analy

sis

of

the

eff

ect

of

app

oin

ting

afe

male

indep

endent

dir

ecto

ras

board

mem

ber

of

an

overc

onfi

dent

CE

Ole

dfi

rmon

the

change

inm

ark

et

perf

orm

ance

of

the

firm

betw

een

peri

od

t−

1and

peri

od

t+

1–

i.e.,

∆Q

(t−

1,t+

1)

=T

obin

’sQ

t+

1−

Tobin

’sQ

t−

1.

We

consi

der

thre

esu

bsa

mple

of

firm

s:O

ur

firs

tsu

bsa

mple

consi

sts

of

all

firm

s,i.e.,

firm

swithorwithout

any

fem

ale

dir

ecto

r(s)

sitt

ing

on

board

inp

eri

od

t−

1.

Our

second

subsa

mple

consi

sts

of

firm

swithout

any

fem

ale

dir

ecto

rsi

ttin

gon

board

inp

eri

od

t−

1.

Our

thir

dsu

bsa

mple

consi

sts

of

firm

sw

here

no

fem

ale

serv

ed

on

their

board

anyti

me

befo

reth

eapp

oin

tment

of

afe

male

as

dir

ecto

rin

peri

od

t.Appoin

tmentofFemale

IndependentDirec

tor(F

ID)In

dicato

ris

one

ifat

least

one

fem

ale

indep

endent

dir

ecto

rand

no

male

dir

ecto

ris

app

oin

ted

toth

ecom

pany’s

board

inp

eri

od

t;it

iszero

oth

erw

ise.

Oth

er

CE

O,

Fir

mand

Mark

et

rela

ted

contr

ol

vari

able

sas

list

ed

inT

able

4in

clu

ded

but

not

rep

ort

ed

for

bre

vit

y.

The

Data

App

endix

1conta

ins

more

exte

nsi

ve

vari

able

defi

-nit

ions.

All

models

are

OL

Sm

odels

that

inclu

de

firm

/in

dust

ryand

year

fixed

eff

ects

,and

use

standard

err

ors

clu

stere

dby

firm

.T

he

signifi

cance

levels

at

the

1%

,5%

,and

10%

are

denote

dby

***,**

and

*,re

specti

vely

.

Wit

hor

Wit

hout

Fem

ale

Dir

ecto

rin

Peri

od

t-1

Wit

hout

Fem

ale

Dir

ecto

rin

Peri

od

t-1

Wit

hout

Fem

ale

Dir

ecto

runti

lP

eri

od

t-1

(Fir

stti

me)

Dep

endent

Vari

able

∆Q

(t−

1,t

+1)

∆Q

(t−

1,t

+1)

∆Q

(t−

1,t

+1)

Model

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

[12]

a:

App

oin

tment

of

Fem

ale

IDIn

dic

ato

r-0

.016

-0.0

87**

-0.0

62**

-0.0

51**

-0.0

01

-0.1

30**

-0.0

92**

-0.0

51

0.0

48

-0.1

56

-0.0

87

-0.0

31

(-0.4

67)

(-2.5

59)

(-2.2

76)

(-1.9

88)

(-0.0

16)

(-2.4

10)

(-2.1

56)

(-1.3

61)

(0.8

12)

(-1.6

20)

(-1.0

78)

(-0.3

97)

b:

CE

OH

old

er6

7-0

.213***

-0.2

69***

-0.1

90***

(-3.2

78)

(-2.8

24)

(-3.8

78)

c:

CE

OC

onfi

dence

-0.5

56***

-0.6

24***

-0.6

38***

(-8.4

03)

(-7.2

49)

(-4.2

70)

d:

CE

OC

onfi

denceT

op50

-0.1

90***

-0.2

23***

-0.2

35***

(-8.1

73)

(-7.0

31)

(-4.2

15)

e:

CE

OC

onfi

denceT

op25

-0.1

99***

-0.2

33***

-0.2

54***

(-6.5

32)

(-5.6

50)

(-3.2

93)

ax

b0.4

59*

0.7

75**

0.8

03**

(1.8

91)

(1.9

86)

(2.4

62)

ax

c0.2

36*

0.4

73**

0.7

37**

(1.8

67)

(2.3

97)

(2.2

92)

ax

d0.0

88*

0.1

95***

0.2

77*

(1.7

81)

(2.5

88)

(1.9

25)

ax

e0.1

28*

0.1

97*

0.3

01*

(1.8

33)

(1.9

07)

(1.6

77)

Oth

er

CE

OR

ela

ted

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Oth

er

Board

Rela

ted

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mR

ela

ted

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Mark

et

Rela

ted

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Inte

rcept

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mF

ixed

Eff

ect

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Year

Fix

ed

Eff

ect

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No.

of

Obse

rvati

ons

10,5

42

10,5

42

10,5

42

10,5

42

5,7

19

5,7

19

5,7

19

5,7

19

2,0

55

2,0

55

2,0

55

2,0

55

Adju

sted

R2

0.1

726

0.1

059

0.1

032

0.1

021

0.1

380

0.1

226

0.1

197

0.1

320

0.1

650

0.1

320

0.1

292

0.1

308

50

Table 10: Effect of Appointing of an Overconfident CEO on the Performance of Firm with GenderDiverse Board

This table contains difference-in-difference analysis of the effect of appointing an overconfident CEO in a firmwith existing gender diverse board on the change in market performance of the firm between period t− 1 andperiod t+ 1 – i.e., ∆Qi(t− 1, t+ 1) = Tobin’s Qi,t+1 −Tobin’s Qi,t−1. We consider a subsample of firms thatappoint a new CEO who is previously categorized as “overconfident.” Appointment of Overconfident CEOIndicator is one if a firm appoints new CEO with identifiable Holder67 = 1 in period t, and zero otherwise.Other CEO, Firm and Market related control variables as listed in Table 4 included but not reported forbrevity. The Data Appendix 1 contains more extensive variable definitions. All models are OLS models thatinclude firm and year fixed effects, and use standard errors clustered by firm. The significance levels at the1%, 5%, and 10% are denoted by ***, ** and *, respectively.

∆Qi(t− 1, t+ 1)

Female Independent Director Indicator 0.008(0.169)

Female Independent Director Ratio -0.247(-0.901)

Female Independent Director Indicator × Appointment of Overconfident CEO 0.577*(1.882)

Female Independent Director Ratio × Appointment of Overconfident CEO 1.717*(1.913)

Appointment of Overconfident CEO -0.795*** -0.557*(-2.654) (-1.654)

Other CEO Related Controls Yes YesOther Board Related Controls Yes YesFirm Related Controls Yes YesMarket Related Controls Yes Yes

Intercept Yes YesYear Fixed Effects Yes YesFirm Fixed Effects Yes Yes

Number of Observations 5,063 5,063Adjusted R-Sqd. 0.1592 0.1698

51

Table 11: Effect of Female Director’s Departure Due to Known Exogenous and Unknown Reasonson Firm Performance

This table contains difference-in-difference analysis of the effect of departure a female director as board member of an over-confident CEO led firm on the change in market performance of the firm between period t − 1 and period t + 1 – i.e.,∆Q(t − 1, t + 1) = Tobin’s Qt+1 − Tobin’s Qt−1. Female Independent Director (ID) Departure Indicator takes a value of oneif a firm loses at least one female independent director, zero otherwise. To get a clean test, we only consider those cases where there isno male director’s departure alongside a female independent director’s departure. We carefully classify departure reasons: ExogenousReason (departures due to death, critical illness and mandatory retirement age) and Any Departure (no clear departure reason wasstated plus exogenous reasons). Other CEO, Firm and Market related control variables as listed in Table 4 included but not reportedfor brevity. The Data Appendix 1 contains more extensive variable definitions. All models are OLS models that include firm and yearfixed effects, and use standard errors clustered by firm. The significance levels at the 1%, 5%, and 10% are denoted by ***, ** and *,respectively.

∆Q(t− 1, t + 1)

Departure Due to Any DepartureExogenous Reasons (Exogenous + Unknown)

Model [1] [2] [3] [4] [5] [6]

Female ID Departure Indicator 0.117 0.065 0.003 0.111* 0.064 0.055(0.701) (0.503) (0.025) (1.897) (1.383) (1.307)

Female ID Departure Indicator × CEO Confidence -0.696** -0.475*(-1.992) (-1.831)

Female ID Departure Indicator × CEO ConfidenceTop50 -0.366** -0.161*(-2.154) (-1.675)

Female ID Departure Indicator × CEO Holder67 -0.379***

-0.369

(-2.953) (-1.248)

Confidence -0.412***

-0.295***

(-4.600) (-3.067)ConfidenceTop50 -

0.158***-

0.130***(-5.256) (-4.069)

CEO Holder67 -0.070 -0.081(-1.254) (-1.188)

Other CEO Related Controls Yes Yes Yes Yes Yes YesOther Board Related Controls Yes Yes Yes Yes Yes YesFirm Related Controls Yes Yes Yes Yes Yes YesMarket Related Controls Yes Yes Yes Yes Yes Yes

Intercept Yes Yes Yes Yes Yes YesFirm Fixed Effect Yes Yes Yes Yes Yes YesYear Fixed Effect Yes Yes Yes Yes Yes Yes

No. of Observation 5,118 5,118 5,118 5,118 5,118 5,118Adjusted R2 0.1729 0.1709 0.1724 0.1441 0.1436 0.1457

52

Tab

le12

:F

emal

eIn

dep

end

ent

Dir

ecto

rs,

CE

OO

verc

onfi

den

cean

dth

eE

ffec

tson

Fir

m’s

Mark

etV

alu

ati

on

inth

eP

re-S

OX

an

dth

eP

ost-

SO

XP

erio

ds

This

table

conta

ins

models

that

analy

ze

the

rela

tionsh

ipb

etw

een

fem

ale

indep

endent

dir

ecto

rsand

the

app

oin

ting

firm

’sm

ark

et

perf

orm

ance

inth

epre

-SO

Xand

the

post

-SO

Xp

eri

ods.

SO

XIn

dic

ato

ris

one

ifyear

is2002

or

aft

er,

and

zero

oth

erw

ise.

The

dep

endent

vari

able

isone-p

eri

od

lead

Tobin

’sQ

.Female

Indicato

rDirec

torIn

dicato

ris

one

ifa

firm

has

at

least

one

fem

ale

dir

ecto

r;zero

oth

erw

ise.

Female

Independent

Direc

torRatio

isth

era

tio

of

fem

ale

mem

bers

toth

eto

tal

board

size.

Oth

er

CE

O,

Fir

mand

Mark

et

rela

ted

contr

ol

vari

able

sas

list

ed

inT

able

4in

clu

ded

but

not

rep

ort

ed

for

bre

vit

y.

The

Data

App

endix

1conta

ins

more

exte

nsi

ve

vari

able

defi

nit

ions.

All

models

are

OL

Sm

odels

that

inclu

de

firm

and

year

fixed

eff

ects

,and

use

standard

err

ors

clu

stere

dby

firm

.T

he

signifi

cance

levels

at

the

1%

,5%

,and

10%

are

denote

dby

***,

**

and

*,

resp

ecti

vely

.

Dep

endent

Vari

able

Tobin

’sQ

t+

1

Sub-S

am

ple

sP

re-S

OX

Post

-SO

X

Model

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

[15]

[16]

a:

Fem

ale

IDR

ati

o-0

.315

-0.7

07

-0.2

91

-0.2

71

0.0

78

-0.1

02

-0.0

54

-0.0

97

(-0.7

94)

(-1.5

09)

(-0.6

82)

(-0.6

45)

(0.6

53)

(-0.6

82)

(-0.3

92)

(-0.7

49)

b:

Fem

ale

IDIn

dic

ato

r0.0

39

-0.0

89

-0.0

20

-0.0

16

0.0

57***

-0.0

09

0.0

13

0.0

30

(1.0

87)

(-1.3

58)

(-0.3

48)

(-0.2

83)

(2.7

51)

(-0.2

87)

(0.4

57)

(1.1

87)

c:

CE

OH

old

er6

7-0

.266**

-0.2

42***

0.0

12

-0.0

21

(-2.4

02)

(-2.9

35)

(0.2

19)

(-0.3

84)

d:

CE

OC

onfi

dence

-0.3

89***

-0.4

35***

0.0

53

0.0

08

(-2.6

60)

(-2.7

73)

(0.8

57)

(0.1

20)

e:

CE

OC

onfi

denceT

op50

-0.1

32**

-0.1

45**

0.0

08

-0.0

04

(-2.4

84)

(-2.4

42)

(0.3

50)

(-0.1

35)

f:C

EO

Confi

denceT

op25

-0.2

25***

-0.2

48***

0.0

29

0.0

36

(-3.3

77)

(-3.3

90)

(0.9

55)

(1.0

25)

a×

c3.3

96***

-0.0

79

(3.2

94)

(-0.1

88)

a×

d3.8

82***

0.2

82

(3.7

66)

(0.7

80)

a×

e1.3

65***

0.0

43

(3.3

41)

(0.2

89)

a×

f2.3

72***

0.3

19

(4.2

57)

(1.6

12)

b×

c0.3

74***

0.0

48

(3.5

18)

(0.6

66)

b×

d0.6

01***

0.1

20

(3.7

30)

(1.6

09)

b×

e0.2

08***

0.0

26

(3.1

00)

(0.8

40)

b×

f0.3

46***

0.0

67

(3.9

03)

(1.5

75)

Oth

er

CE

OC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Oth

er

Board

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mR

ela

ted

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Mark

et

Rela

ted

Contr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Inte

rcept

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mF

ixed

Eff

ect

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Year

Fix

ed

Eff

ect

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No.

of

Obse

rvati

ons

3,5

80

3,5

80

3,5

80

3,5

80

3,5

80

3,5

80

3,5

80

3,5

80

7,4

86

7,4

86

7,4

86

7,4

86

7,4

86

7,4

86

7,4

86

7,4

86

Adju

sted

R2

0.1

159

0.1

493

0.1

441

0.1

424

0.1

387

0.1

487

0.1

424

0.1

430

0.4

507

0.4

939

0.4

974

0.4

936

0.4

500

0.4

938

0.4

982

0.4

959

53

Table 13: Effect of SOX Compliance, Female Independent Directors on Firm’s Performance

This table presents analysis of the effect of a female independent director on market performance ofSOX-compliant and SOX-non-compliant firms. The dependent variable is one-period lead Tobin’s Q. Westudy a sub-sample between 1998 to 2005. Female Independent Director Indicator is one if a firm has atleast one female independent director; zero otherwise. “Compliant firms” are those that were compliantwith the three major SOX provisions: full board independence, complete audit committee independence,complete nominating committee independence prior to the passage of SOX Act 2002. “Non-compliant firms”are defined based on non-compliance with anyone of the three major SOX provisions mentioned above priorto the passage of SOX Act 2002. Other CEO, Firm and Market related control variables as listed in Table 4included but not reported for brevity. The Data Appendix 1 contains more extensive variable definitions. Allmodels are OLS models that include firm and year fixed effects, and use standard errors clustered by firm.The significance levels at the 1%, 5%, and 10% are denoted by ***, ** and *, respectively.

Dependent Variable Tobin’s Qt+1

Sub-Sample 1 Compliant Non-compliant

Sub-Sample 2 Pre-SOX Post-SOX Pre-SOX Post-SOX

Model [1] [2] [3] [4]

Female Independent Director Indicator 0.057 -0.016 0.008 -0.045(0.858) (-0.345) (0.050) (-0.602)

Female Independent Director Indicator x CEO Holder67 0.173 0.089 0.530** 0.032(0.876) (0.948) (2.282) (0.168)

CEO Holder67 -0.029 -0.054 -0.325** 0.019(-0.174) (-0.693) (-2.076) (0.150)

Tobin’s Qt -0.061 0.181*** -0.270*** 0.221***(-0.818) (3.662) (-4.374) (3.574)

Other CEO Related Controls Yes Yes Yes YesOther Board Related Controls Yes Yes Yes YesFirm Related Controls Yes Yes Yes YesMarket Related Controls Yes Yes Yes Yes

Intercept Yes Yes Yes YesFirm Fixed Effect Yes Yes Yes YesYear Fixed Effect Yes Yes Yes Yes

No. of Observations 823 1,853 1,602 3,699Adjusted R2 0.0400 0.4520 0.0480 0.6904

54

Tab

le14

:F

emal

eD

irec

tor,

Ove

rcon

fid

ent

CE

Oan

dth

eE

ffec

tsof

Oth

erG

over

nan

ceM

ech

an

ism

on

Fir

mP

erfo

rman

ce

Th

ista

ble

conta

ins

mod

els

that

an

aly

zeth

ere

lati

on

ship

bet

wee

nfe

male

ind

epen

den

td

irec

tors

an

dm

ark

etp

erfo

rman

cefo

rsu

b-s

am

ple

sso

rted

on

vari

ou

sgover

nan

cech

ara

cter

isti

cs.

Th

ed

epen

den

tvari

ab

leis

on

e-p

erio

dle

ad

Tob

in’s

Q.

Ind

epen

den

tF

emale

Dir

ecto

rIn

dic

ato

ris

on

eif

ther

eis

at

least

on

efe

male

ind

epen

den

td

irec

tor

inth

eco

mp

any’s

board

;ze

rooth

erw

ise.

Oth

erC

EO

,F

irm

an

dM

ark

etre

late

dco

ntr

ol

vari

ab

les

as

list

edin

Table

4in

clu

ded

bu

tn

ot

rep

ort

edfo

rb

revit

y.T

he

Data

Ap

pen

dix

1co

nta

ins

more

exte

nsi

ve

vari

ab

led

efin

itio

ns.

All

mod

els

are

OL

Sm

od

els

that

incl

ud

efirm

an

dyea

rfi

xed

effec

ts,

an

du

sest

an

dard

erro

rscl

ust

ered

by

firm

.T

he

sign

ifica

nce

level

sat

the

1%

,5%

,and

10%

are

den

ote

dby

***,

**

an

d*,

resp

ecti

vel

y.

Dep

end

ent

Vari

ab

leT

ob

in’s

Qt+

1

Su

b-S

am

ple

Hig

hL

ow

Ind

epen

den

tN

ot

Ind

epen

den

tC

o-o

pte

dN

ot

Co-o

pte

dH

igh

Insi

der

Low

Insi

der

Inst

itu

tion

al

Inst

itu

tion

al

Nom

inati

on

Nom

inati

on

Board

sB

oard

sO

wn

ersh

ipO

wn

ersh

ipO

wn

ersh

ipO

wn

ersh

ipC

om

mit

tee

Com

mit

tee

Model

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

Fem

ale

IDIn

dic

ato

r0.0

55

0.0

11

-0.0

18

0.0

55

0.0

29

0.0

30

0.0

30

0.0

65

(1.6

12)

(0.3

46)

(-0.6

16)

(1.5

65)

(1.2

12)

(0.5

66)

(1.2

65)

(1.0

12)

Fem

ale

IDIn

dic

ato

r×

CE

OH

old

er67

0.2

90***

0.3

56***

0.2

94***

0.3

11***

0.1

50*

0.8

16***

0.3

31***

0.0

43

(2.6

03)

(3.1

61)

(3.2

59)

(2.5

97)

(1.9

34)

(4.5

44)

(3.8

92)

(0.3

10)

CE

OH

old

er67

-0.2

56**

-0.2

26**

-0.2

42***

-0.0

06

-0.0

67

-0.4

67***

-0.0

27

-0.0

05

(-2.1

03)

(-2.0

76)

(-2.9

35)

(-0.0

74)

(-1.0

82)

(-3.2

98)

(-0.4

52)

(-0.0

84)

Oth

erC

EO

Rel

ate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Oth

erB

oard

Rel

ate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

mR

elate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Mark

etR

elate

dC

ontr

ols

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Inte

rcep

tY

esY

esY

esY

esY

esY

esY

esY

esF

irm

Fix

edE

ffec

tY

esY

esY

esY

esY

esY

esY

esY

esY

ear

Fix

edE

ffec

tY

esY

esY

esY

esY

esY

esY

esY

es

No.

of

Ob

serv

ati

on

s5,0

72

5,2

12

5,8

42

5,2

24

8,6

40

2,4

26

8,0

20

2,2

64

Ad

just

edR

20.4

758

0.4

701

0.4

319

0.5

392

0.5

196

0.4

608

0.4

744

0.2

280

55

Table 15: Addressing Endogeneity Issue with Spatial Instrument Variable

This table contains models that use county-level availability of female directors to predict Female Independent Director (FID)Indicator and Female Independent Director (FID) Ratio. Next, we use the Predicted Female Independent Director Indicator andPredicted Female Independent Director Ratio to analyze the effect of female board members on firm performance. The dependentvariable is one-period lead Tobin’s Q. The Data Appendix 1 contains more extensive variable definitions. All models are OLSmodels that include firm and year fixed effects, and use standard errors clustered by firm. The significance levels at the 1%, 5%,and 10% are denoted by ***, ** and *, respectively.

FID Indicator FID Ratio (Tobin’s Q)t+1

Ratio of firms with FID in a county 1.515*** 0.036***(7.066) (5.460)

Predicted FID Indicator 0.099(0.872)

Predicted FID Indicator × CEO Holder67 0.190*(1.760)

Predicted FID Ratio 0.461(0.670)

Predicted FID Ratio × CEO Holder67 1.437*(1.832)

CEO Holder67 -0.168** -0.197**(-2.048) (-2.247)

Ln(Board size) 3.270*** 0.045*** -0.115** -0.057(12.185) (5.684) (-2.234) (-1.219)

Board Independence 4.180*** 0.087*** -0.102 -0.052(13.083) (8.483) (-1.528) (-0.678)

CEO Tenure -0.167*** -0.005*** -0.002 -0.003(-3.545) (-3.304) (-0.277) (-0.364)

CEO Age -0.306 0.001 -0.005 -0.017(-0.748) (0.085) (-0.081) (-0.305)

Female CEO 0.286 0.130*** -0.054 -0.124(0.956) (12.740) (-1.441) (-1.280)

Salary/Bonus 0.021 -0.001 0.012 0.014*(0.489) (-0.699) (1.620) (1.874)

Firm size 0.440*** 0.016*** -0.018** -0.015(9.396) (9.933) (-2.188) (-1.220)

Firm Age 0.134* 0.001 -0.006 -0.003(1.835) (0.326) (-0.649) (-0.332)

Stock Return -0.001* -0.000 -0.001*** -0.001***(-1.842) (-1.056) (-4.940) (-5.052)

Leverage -0.134 0.017* 0.041 0.022(-0.443) (1.672) (0.845) (0.453)

Diversification 0.009 -0.000 -0.005*** -0.005***(0.564) (-0.192) (-3.173) (-3.340)

Stock Volatility -0.018* -0.000 -0.003*** -0.003***(-1.946) (-1.178) (-3.040) (-3.133)

R&D Intensity 1.356 0.006 1.410*** 1.413***(1.163) (0.138) (5.483) (5.486)

Intangibles -0.285 -0.013 -0.143*** -0.132***(-0.917) (-1.179) (-3.663) (-3.332)

Insider Ownership (0.409) -0.010 0.073 0.072(-1.231) (-0.645) (1.272) (1.300)

Institutional Ownership 0.193 -0.006 -0.116** -0.086*(0.614) (-0.557) (-2.249) (-1.796)

Lagged Tobin’s Q 0.056 0.002 0.767*** 0.768***(1.281) (1.241) (55.707) (55.700)

Lagged (EBIT/Assets) 0.241 -0.000 0.505*** 0.502***(0.425) (-0.002) (3.849) (3.825)

Intercept Yes Yes Yes YesFirm Fixed Effect Yes Yes Yes YesYear Fixed Effect Yes Yes Yes Yes

No. of Observations 10,133 9,892 10,133 9,892Adjusted R2 0.3396 0.3349 0.7372 0.7343

56

Online Appendix 1 Online Appendix

This online appendix reports additional results, including additional robustness tests. The relevanttables are as follows.

• Table OA1 reports models that use a ‘press-based’ measure of CEO overconfidence.

• Table OA2 contains propensity score-based matching models.

• Table OA3 contains analysis based on male independent directors.

• Table OA4 reports models that use a ‘residual’ measure of CEO overconfidence.

• Table OA5 reports results for CEOs with at least 4 years of tenure, which we estimate usingOLS.

• Table OA6 reports the correlation coefficient between all variables used in the study.

1

Table OA1: Robustness test – Press-based Measure of CEO Overconfidence, AggregateCompensation-based Measure of CEO Overconfidence, Female Director and Firm Performance

This table contains models that analyze the relationship between female director, news-based measure ofCEO overconfidence, aggregate compensation-based measure of CEO overconfidence and the appointingfirm’s performance. The dependent variable is one-period lead Tobin’s Q. Female Independent DirectorIndicator is one if there is at least one female independent director in the company’s board in period t, andzero otherwise. Female Independent Director Ratio is a ratio of female independent members to the total sizeof the board. FID is the abbreviation for Female Independent Director and Comp-based is the abbreviationfor Compensation-based. Other CEO, Firm and Market related control variables as listed in Table 4 includedbut not reported for brevity. The Data Appendix 1 contains more extensive variable definitions. All modelsare OLS models that include firm and year fixed effects, and use standard errors clustered by firm. Thesignificance levels at the 1%, 5%, and 10% are denoted by ***, ** and *, respectively.

Tobin’s Qt+1

Model [1] [2] [3] [4]

Female Independent Director Indicator -0.007

-0.028

(-0.351)

(-1.080)

FID Indicator × Press-based CEO Overconfidence 0.253**(3.040)

Female Independent Director Ratio 0.002 -0.191

(0.021) (-1.446)

FID Ratio × Press-based CEO Overconfidence 1.208**(2.300)

Press-based CEO Overconfidence -0.008*

-0.012*

(-1.827)

(-1.882)

FID Indicator × Comp-based CEO Overconfidence 0.066***(2.821)

FID Ratio × Comp-based CEO Overconfidence 0.241**(1.982)

Compensation-based CEO Overconfidence -0.025

-0.008

(-1.133)

(-0.381)

Other CEO Related Controls Yes Yes Yes YesOther Board Related Controls Yes Yes Yes YesFirm Related Controls Yes Yes Yes YesMarket Related Controls Yes Yes Yes Yes

2

Intercept Yes Yes Yes YesYear Fixed Effects Yes Yes Yes YesFirm Fixed Effects Yes Yes Yes Yes

No. of Observations 5,0095,00911,993 11,993Adjusted R2 0.75840.75830.5571 0.5554

3

Table OA2: Matched Sample: Female Directors, Overconfident CEOs and Firm’s Performance

This table contains models that analyze the effect of CEO Holder67 measure, female director andmarket performance on a pre-matched sample. We match firms led by overconfident CEOs withfirms led by non-overconfident CEOs by “size” and “book-to-market” and “industry classification.”All models are OLS models that include firm and year fixed effects, and use standard errors clusteredby firm. The significance levels at the 1%, 5%, and 10% are denoted by ***, ** and *, respectively.

Tobin’s Qt+1

Female Independent Director Indicator 0.022(0.215)

FID Indicator × CEO Holder67 0.371***(2.985)

Female Independent Director Ratio -0.161(-0.305)

FID Ratio × CEO Holder67 1.486**(2.331)

CEO Holder67 -0.075 -0.010(-0.661) (-0.100)

Other CEO Related Controls Yes YesOther Board Related Controls Yes YesFirm Related Controls Yes YesMarket Related Controls Yes Yes

Intercept Yes YesFirm Fixed Effects Yes YesYear Fixed Effects Yes Yes

Number of Observations 2,026 2,026Adjusted R-Sqd. 0.2701 0.2625

4

Table OA3: Independent Boards, Male Independent Directors, Overconfident CEOs and Firm’sPerformance

This table contains models that analyze whether an independent board and/or male independent directors have the sameeffect on the appointing firm’s performance, when the appointing firm is lead by overconfident CEO. The dependent variable isone-period lead Tobin’s Q. Female Independent Director Ratio is the ratio of female members to the total board size. OtherCEO, Firm and Market related control variables as listed in Table 4 included but not reported for brevity. The Data Appendix1 contains more extensive variable definitions. All models are OLS models that include firm and year fixed effects, and usestandard errors clustered by firm. The significance levels at the 1%, 5%, and 10% are denoted by ***, ** and *, respectively.

Dependent Variable Tobin’s Qt+1

Model [1] [2] [3]

Independent Board -0.001 -0.004 -0.073(-0.020) (-0.029) (-0.334)

Independent Board × CEO Holder67 0.055(0.282)

Male Independent Director Ratio 0.031 0.014(0.265) (0.200)

Male Independent Director Ratio × CEO Holder67 -0.241 -0.078(-1.194) (-0.363)

Female Independent Director Ratio -0.048(-0.362)

Female Independent Director Ratio × CEO Holder67 0.950**(2.327)

CEO Holder67 0.005 0.179 0.001(0.035) (1.435) (0.009)

Other CEO Related Controls Yes Yes YesOther Board Related Controls Yes Yes YesFirm Related Controls Yes Yes YesMarket Related Controls Yes Yes Yes

Intercept and Year Dummies Yes Yes YesFirm Fixed Effects Yes Yes Yes

No. of Observations 11,033 11,033 11,033Adjusted R2 0.5236 0.5231 0.5192

Table OA4: Female Directors, Residual Overconfidence Measure and Firm’s Performance

This table contains models that analyze the stock return adjusted Holder67 measure, female directorand market performance. All models are OLS models that include firm and year fixed effects, anduse standard errors clustered by firm. The significance levels at the 1%, 5%, and 10% are denotedby ***, ** and *, respectively.

Tobin’s Qt+1

Female Independent Director Indicator 0.029(1.140)

FID Indicator × Residual CEO Holder67 0.304***(3.994)

5

Female Independent Director Ratio -0.041(-1.110)

FID Ratio × Residual CEO Holder67 1.435***(3.910)

Residual CEO Holder67 0.133 0.141(1.583) (1.610)

Other CEO Related Controls Yes YesOther Board Related Controls Yes YesFirm Related Controls Yes YesMarket Related Controls Yes Yes

Intercept Yes YesFirm Fixed Effects Yes YesYear Fixed Effects Yes Yes

No. of Observation 11066 11066Adj.R2 0.5298 0.5280

6

Table OA5: Female Directors, Overconfident Long-Tenured CEOs and Firm’s Performance

This table presents results from a sub-sample of firms that have CEOs with at least 4-year tenure.All models are OLS models that include firm and year fixed effects, and use standard errors clusteredby firm. The significance levels at the 1%, 5%, and 10% are denoted by ***, ** and *, respectively.

Dependent Variable: Tobin’s Qt+1

Female Director Ratio -0.022(-0.113)

Female Director Ratio × CEO Holder67 0.933***(2.734)

Female Independent Director Ratio -0.117(-0.615)

Female Independent Director Ratio × CEO Holder67 1.208**(2.300)

CEO Holder67 -0.023 -0.029(-0.401) (-0.446)

Other CEO Related Controls Yes YesOther Board Related Controls Yes YesFirm Related Controls Yes YesMarket CEO Related Controls Yes Yes

Intercept Yes YesFirm Fixed Effect Yes YesYear Fixed Effect Yes Yes

No. of Observations 7104 7104Adj. R-Sqd. 0.3778 0.4606

7

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