Rogerian Essay

Board Diversity and Corporate Social Responsibility

Maretno Harjoto • Indrarini Laksmana •

Robert Lee

Received: 5 April 2014 / Accepted: 22 August 2014 / Published online: 29 August 2014

� Springer Science+Business Media Dordrecht 2014

Abstract This study examines the impact of board

diversity on firms’ corporate social responsibility (CSR)

performance. Using seven different measures of board

diversity across 1,489 U.S. firms from 1999 to 2011, the

study finds that board diversity is positively associated with

CSR performance. Board diversity is associated with a

greater number of areas in which CSR is strong and a fewer

number of areas in which CSR is a concern. These findings

support the stakeholder theory and are consistent with the

view that board diversity enhances firms’ ability to satisfy

the needs of their broader groups of stakeholders. We find

that gender, tenure, and expertise diversities seem to be the

driving factors of firms’ CSR activities. Furthermore, we

find that board diversity significantly increases CSR per-

formance by increasing CSR strengths and reducing CSR

concerns for firms producing consumer-oriented products

and firms operating in more competitive industries. Our

results remain robust using different measures of CSR

performance, different estimation methods, and different

samples.

Keywords Diversity � Corporate social responsibility � Board of Directors � Stakeholders

JEL Classifications M14 � G34 � G39

Introduction

Recently, diversity in corporate boardrooms of publicly

traded corporations around the world has become a press-

ing issue. Several developed countries, such as the United

States and the European Union countries, now require

corporations to improve their board diversity practices and

the disclosure of these practices. 1 In the U.S., the SEC

adopted a new set of rules mandating publicly traded

companies to disclose whether and how board diversity is

considered in the selection process of director nominees

(SEC Release 33-9089 issued on December 16, 2009).

While these rules recognize the importance of board

diversity, there is limited evidence on the influence of

diversely comprised boards on management decision

making. 2 In the present study, we examine the impact of

diverse boards on management decisions to engage in

socially responsible activities.

Introducing the idea of stakeholder management, Free-

man (1984) argues that corporate managers are required to

satisfy the need of all groups who have a stake in the

business (i.e., stakeholders) to maximize firm value (Free-

man et al. 2004). More specifically, Jensen (2001, 2002)

indicates that firms need to build relationships with various

stakeholder groups in order to maximize shareholder value.

M. Harjoto (&) � R. Lee Graziadio School of Business and Management, Pepperdine

University, Malibu, USA

e-mail: [email protected]

R. Lee

e-mail: [email protected]

I. Laksmana

College of Business Administration, Kent State University, Kent,

USA

e-mail: [email protected]

1 See http://www.sec.gov/rules/final/2009/33-9089.pdf and http://

www.eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2012:

0614:FIN:en:PDF. 2 Prior studies on board diversity have focused on gender diversity

and its association with firm performance (e.g., Adams and Ferreira

2009) and board monitoring functions such as overseeing the financial

reporting process (e.g., Srinidhi et al. 2011; Abbott et al. 2012).

123

J Bus Ethics (2015) 132:641–660

DOI 10.1007/s10551-014-2343-0

Stakeholders groups include, but not limited to, share-

holders, creditors, employees, customers, and local com-

munities. The stakeholder theory by Cornell and Shapiro

(1987) suggests that firms have contracts with their stake-

holders and that firm value depends on the firms’ ability to

fulfill these contracts. 3 Firms could suffer both monetary

and reputational losses from failing to align management’s

interests with those of their stakeholders. Effective stake-

holder management is a critical requirement for firm suc-

cess. Therefore, boards of directors, as representatives of

shareholders, play an important role in overseeing the cre-

ation and execution of management’s plans to balance the

interests of multiple stakeholders.

We examine the effectiveness of diverse boards in

overseeing management’s performance on stakeholder

management. Specifically, we investigate the relationship

between board diversity and corporate social responsibility

(CSR) performance. Following prior research (e.g., Hillman

and Keim 2001; Benson and Davidson 2010; Benson et al.

2011), we use CSR performance as a proxy for management

performance in balancing the interest of multiple stake-

holders. Management performance on CSR is the outcome

of its decisions to satisfy the need of various groups of

stakeholders. Prior studies documenting a positive rela-

tionship between CSR and corporate governance have

focused on external monitoring, such as institutional own-

ership and analyst coverage, and internal monitoring mea-

sured using board independence (Francoeur et al. 2008;

Harjoto and Jo 2011; Jo and Harjoto 2011). These studies,

however, have not examined board diversity which could

potentially provide more insights on management’s deci-

sion to invest in CSR projects. Given that group dynamics

and decision making vary depending on the background of

the individuals serving on corporate boards, a diverse group

of directors brings a different knowledge base, sets of

experiences, and perspectives on society to group decision

making. As a result, diversity increases the board’s ability

to recognize the needs and interests of different groups of

stakeholders as reflected on CSR performance.

We measure board diversity in seven dimensions: gen-

der, race, age, outside directorship, tenure, power, and

expertise. We measure CSR performance based on Kinder,

Lyndenberg, and Domini (KLD) scores on the strengths

and concerns of firms’ social responsibility performance in

six areas: community, employee, environment, product,

human rights, and corporate governance. Our study is the

first study that directly examines the impact of board

diversity on firms’ CSR activities with comprehensive

measures of board diversity and CSR performance. Our

study also examines whether the business environment in

which firms operate determines the effectiveness of diverse

boards in overseeing CSR performance. As different

environments require different levels of stakeholder man-

agement, we classify firms into consumer and industrial

product subsamples and into high and low competition

product market subsamples. Prior studies indicate that

firms in consumer product industries and high competition

industries have greater need to invest in CSR activities in

order to differentiate their products from those of their

competitors (Baron et al. 2011; Fisman et al. 2005).

Using a sample of 9,001 observations across 1,489 U.S.

firms from 1999 to 2011, we find that board diversity posi-

tively influences firms’ CSR performance. We find that board

diversityis associatedwith a greater numberof areasin which

CSR is strong and a fewer number of areas in which CSR is a

concern, consistent with the view that diverse boards play an

important role in managing mutual relationships with multi-

ple stakeholders. Our additional analysis reveals that our

measure of board diversity is positively related to the CSR

components in the community, environment, product, and

corporate governance areas. However, we find that board

diversity is not associated with CSR components in the

employee and human right areas. 4 Examining the impact of

each diversity component, we find that gender, tenure, and

expertise diversities are positively associated with the overall

CSR performance. More specifically, our results suggest that

gender is associated with the overall CSR score by increasing

CSR strengths and reducing CSR concerns, while tenure and

expertise increase the overall CSR score only by reducing

CSR concerns. Our results are robust when using different

measures of CSR performance, different subsamples, and

different estimation methods.

Our industry analysis reveals that diverse boards are more

effective in overseeing CSR performance when firms operate

in industries with greater need for stakeholder management

(i.e., firms in consumer product markets and firms in highly

competitive markets). Our results suggest that board diver-

sity increases CSR performance for firms operating in con-

sumer product industries and for firms in more competitive

markets indicated by lower Herfindahl–Hirschman Index

(HHI) and higher advertising expenditure ratio (ADVR). The

stakeholder management theory suggests that firms utilize

3 Firms have both explicit and implicit contracts with their

stakeholder. Explicit contracts refer to formal contractual agreements

between firms and their stakeholders, such as investment contracts

with shareholders, loan contracts with creditors, and wage contracts

with employees. Implicit contracts refer to promises to stakeholders

that are either too vague or too costly to specify in writing. For

examples, firms may have implicit contracts to provide customers

with quality products and services, to maintain safe workplace for

employees, and to protect the environment for local communities and

government.

4 One potential explanation for the results is that social pressures

(e.g., laws protecting human rights and employees and movements by

independent organizations, such as Greenpeace) may have repre-

sented the rights of employees.

642 M. Harjoto et al.

123

CSR as a strategic tool to differentiate themselves from their

competitors (Freeman 1984; Fisman et al. 2005; Baron 2009;

Baron et al. 2011). Our results support this notion by indi-

cating that diverse boards are more effective in influencing

CSR performance when firms have greater need to differ-

entiate themselves from their competitors.

Our study contributes to the growing literature on both

CSR and board diversity. First, our study contributes to the

greater understanding of the potential value of board

diversity. Board diversity literature has been considered

inconclusive (Forbes and Milliken 1999) and has struggled

to ‘‘provide clear answers to the basic question of what

kinds of directors make the most effective board’’ (Johnson

et al. 2013, p. 246). We provide evidence that board

diversity influences the level of CSR performance, sug-

gesting that diverse boards have influence in management

decisions to balance the interests of multiple stakeholders.

Firms have not only an economic responsibility to be

profitable, but also other responsibilities such as a legal

responsibility to follow laws, and an ethical responsibility

to bring corporate behavior that is consistent with norms

and social ethics (Carroll 1979; Sethi 1975). Our study

shows that diverse boards provide a more effective moni-

toring of CSR performance, fulfilling firms’ moral com-

mitment, as well as legal and ethical responsibilities, to

serve the interests of multiple stakeholders. Further, we

provide insights on how different dimensions of diversity

impact the strengths and weaknesses of CSR performance,

as well as examine the effectiveness of board diversity in

different environments that require different levels of

stakeholder management. Second, our study provides sup-

port for the recent regulatory requirements to improve board

diversity in the United States and the European Union

countries. Specifically, our results provide implications for

evaluating director candidates and highlight the importance

of having directors from different backgrounds to oversee

management’s performance on various CSR areas.

The rest of the paper is organized in the following

structure. In the next section, we discuss the existing lit-

erature examining the role of board diversity and CSR and

develop our hypotheses. In the following section, we dis-

cuss our data and sample statistics. Then, we report and

discuss our main analyses and the additional robustness

checks. Finally, we conclude with summarizing the main

findings and providing the implications of our study.

Literature Review and Hypothesis

Prior Research on Board Diversity

While the importance of board diversity is widely recog-

nized, empirical evidence on the benefits of board diversity

is inconclusive. Studies examining how board diversity

affects the performance of U.S. firms document positive,

negative, or insignificant results. Within this stream of

literature, some studies have documented that diversity in

corporate boards is positively related to financial perfor-

mance (Erhardt et al. 2003; Carter et al. 2003). Erhardt

et al. (2003) find that ethnic and gender representation on

boards is positively associated with financial performance

ratios, such as firm return on investment and return on

assets. Carter et al. (2003) show that the proportion of

women or minorities on boards is positively associated

with firm value, measured with Tobin’s Q. However, other

studies find a negative relationship between diversity and

firm performance. Adams and Ferreira (2009), for example,

find a negative association between gender diversity and

firm performance, measured with Tobin’s Q and return on

assets. Finally, there are a number of studies finding an

insignificant relationship between board diversity and firm

performance (Francoeur et al. 2008; Miller and Carmen

Triana 2009; Carter et al. 2010).

The existing literature provides limited evidence on the

relationship between board diversity and effective board

governance. Prior research on board diversity has focused

on gender diversity and has documented that the presence

of female directors could improve corporate governance

(e.g., Huse et al. 2009; Adam and Ferreira 2009; Abbott

et al. 2012). Adam and Ferreira (2009) find that female

directors have better attendance records and are more

involved with committees that require intense monitoring

(e.g., audit, nominating, and corporate governance com-

mittees) than male directors. Abbott et al. (2012) demon-

strate that the presence of female board members is

associated with a lower likelihood of financial restatement.

Forbes and Milliken (1999) develop a model of board

processes showing the impact of board diversity on its

effectiveness. They conclude that board diversity can have

conflicting effects on board decisions. Diversity can not

only enhance, but also reduce the board effectiveness in

performing its monitoring duties and making cohesive

decisions.

Stakeholder Management and CSR

There are two seemingly contradictory approaches for

maximizing firm value (i.e., shareholder vs. stakeholder

maximization views). Proponents of the shareholder theory

believe that managers have a primary duty to maximize

shareholder returns. In contrast, proponents of the stake-

holder theory believe that managers have duties to balance

the interests of shareholders against the interests of other

stakeholder groups.

Freeman (1984) introduces the ideas of stakeholder

management that corporate managers are required to

Board Diversity and CSR 643

123

satisfy the need of all groups who have a stake in the

business (i.e., stakeholders) to maximize firm value

(Freeman et al. 2004). Freeman (1984) defines stakeholders

as any groups or individuals who can affect or are affected

by the achievement of an organization’s purpose. Stake-

holder groups include, but not limited to, shareholders,

creditors, consumers, employees, and local communities.

Cornell and Shapiro (1987) suggest that firms have both

explicit and implicit contracts with their stakeholders and

that the value of these contracts determines the firm value.

Jensen (2001, 2002) proposes the enlightened value

maximization theory to reconcile the two competing the-

ories of shareholder versus stakeholder value maximiza-

tion. Under the enlightened value maximization theory,

firms should satisfy the needs of their stakeholders until the

marginal cost of doing it exceeds the marginal benefit to

their shareholders. Benson and Davidson (2010) provide

empirical evidence to support the enlightened value max-

imization theory. They find that performance regarding

stakeholder management (measured using CSR perfor-

mance) is positively associated with firm value, but is not

associated with CEO compensation. In a separate analysis,

they find an endogenous relationship between CEO com-

pensation and firm value, suggesting that managers are

compensated to maximize shareholder value, but managers

optimize their relationships with other stakeholders to

achieve the shareholder maximization goal.

Prior research has used CSR performance to measure

performance on stakeholder management (e.g., Hillman

and Keim 2001; Benson and Davidson 2010; Benson et al.

2011). CSR includes four areas of responsibilities: (1) the

economic responsibility to be profitable; (2) the legal

responsibility to obey the laws of society; (3) the ethical

responsibility to do what is right, just, and fair; and (4) the

philanthropic responsibility to provide resources for vari-

ous kinds of social, educational, recreational, or cultural

purposes (Carroll 1979, 1999). Consistent with this defi-

nition of CSR, Sethi (1975) indicates that the three stages

of corporate responsibilities are to respond to market forces

and legal requirements, to bring corporate behavior that is

consistent with norms and social ethics, and to respond to

social pressures.

Prior CSR research provides several theories that could

explain firms’ motivations for embracing CSR (Garriga and

Mele 2004). The instrumental theory views CSR as a

means for wealth creation. Motivated by self-interest, firms

engage in socially responsible activities and use these

activities as strategic tools to enhance profit and maximize

shareholder value (Matten and Crane 2005; Garriga and

Mele 2004). Other theories, such as integrative and ethical

theories, suggest that firms engage in socially responsible

activities because they have a normative (moral) commit-

ment to serve multiple stakeholders (Evan and Freeman

1988; Berman et al. 1999; Garriga and Mele 2004; Matten

and Crane 2005). The concept of stakeholder management

under Jensen’s (2001) enlightened value maximization

theory is consistent with the instrumental theory of CSR.

Firm management should build mutual relationships with

their various stakeholders through various CSR activities

and use CSR as a strategic approach for maximizing firm

value (Freeman et al. 2004).

In recent years, the growing public interest in CSR is

consistent with the view that corporations need to satisfy

the need of various stakeholder groups. The increasing

number of firms engaging in social responsible activities

provides evidence for the growing importance of non-

investor stakeholders. Building mutual relationships with

these stakeholders is essential to compete in today’s busi-

ness environment. Corporations could no longer ignore

these stakeholders, therefore, CSR has become as a critical

component to build a competitive advantage in business

(Jensen 2001, 2002; Fisman et al. 2005; Baron 2009).

Prior studies have generally found that there are eco-

nomic benefits associated with firms participating in CSR

activities. The benefits are lower cost of equity capital, cost

of debt, and systematic risk. Dhaliwal et al. (2011) and El

Ghoul et al. (2011) find that CSR disclosure and CSR

intensity reduce the cost of equity capital. Goss and Rob-

erts (2011) find that CSR reduces firms’ borrowing cost.

Oikonomou et al. (2012) find that CSR is negatively but

weakly related to systematic firm risk and that corporate

social irresponsibility is positively and strongly related to

financial risk.

Several studies find a positive relationship between CSR

and several corporate governance mechanisms (Francoeur

et al. 2008; Harjoto and Jo 2011; Jo and Harjoto 2011).

These studies measure corporate governance using both

external monitoring mechanisms (e.g., institutional own-

ership and analysts following) and internal monitoring

mechanisms (i.e., independent boards). Within this rich

stream of research, there are only a few studies that

examine the relationship between board diversity and CSR.

These studies, however, focus only on gender diversity.

Wang and Coffey (1992, 1998), for example, find that the

proportion of female and ethnic minority board members is

positively associated with a firms’ charitable contributions.

Williams (2003) documents a similar finding that higher

proportion of female directors increases firms’ charitable

giving. Finally, Bear et al. (2010) find that board gender

diversity is positively associated with CSR strengths,

measuring positive actions toward various groups of

stakeholders.

Our study differs from the previous studies examining

the relationship between board diversity and CSR in sev-

eral ways. First, our study defines board diversity beyond

gender and uses seven dimensions of board diversity

644 M. Harjoto et al.

123

(gender, race, age, outside directorship, tenure, power, and

expertise). Studies that focus on gender diversity only

could potentially underestimate the impact diversity has in

boardrooms. We examine stakeholder management by

CSR strengths and CSR concerns, as well as the overall

CSR performance (net strengths and concerns), while prior

studies focus on only CSR strengths. Effective board

monitoring of CSR performance should not only increase

CSR strengths, but also decrease CSR concerns. We argue

that directors with diverse backgrounds (beyond gender)

bring their unique perspectives to the board and increase

the boards’ ability to recognize the needs and interests of

various stakeholder groups, facilitating more in-depth dis-

cussion on managers’ CSR performance as the outcome of

stakeholder management.

Hypotheses

Boards of directors serve two main roles, as advisors of

management by providing strategic and operating direc-

tions and as monitors of management by overseeing man-

agement performance and reducing agency costs (Larcker

and Tayan 2013). As the business community recognizes

the importance of stakeholder management in maximizing

shareholder values, corporate boards play an important role

in providing directions on CSR issues and monitoring

management’s CSR performance.

Work group diversity literature has found both positive

and negative effects of diversity on group performance

(Jackson et al. 2003; Ilgen et al. 2005; Knippenberg and

Schippers 2007). On one hand, board diversity introduces a

wide range of knowledge and skills that foster different

perspectives, resulting in more comprehensive board

decisions. Westphal and Milton (2000), for example,

indicate that minority directors make important contribu-

tions to board decision making by providing unique per-

spectives that could challenge the conventional wisdom of

majority directors.

Greater board diversity could increase firms’ ability to

recognize the needs and interests of different groups of

stakeholders, to identify the best strategies that would align

the different interests, and to manage potential conflicts

among stakeholders. Since CSR performance measures

firms’ ability to satisfy the need of their various stakeholder

groups, firms with a diverse board will have broader per-

spectives and knowledge base to make decisions on social

responsible issues, suggesting a positive relationship

between board diversity and CSR.

While board diversity could create positive effects on

board performance by introducing a wide range of

knowledge and skills that foster different perspectives, we

also acknowledge the negative effects of diversity. Board

diversity can generate more diverse options, create more

conflicts, and lengthen the decision making process. As

such, board diversity could lead to more challenges in

reaching board consensus, resulting in ineffective moni-

toring of management performance. However, the work

group diversity literature has examined two components of

diversity, surface level and deep level diversity. Surface

level diversity refers to observable attributes, such as

gender, ethnicity, and age. Harrison et al. (1998) find that if

surface level diversity creates a negative effect, time will

moderate this effect because over a period of time, team

members will become more knowledgeable about one

another and bypass any surface level differences. There-

fore, we argue that the positive effects of diversity will

outweigh the negative effects after directors serving on the

board work together for a period of time. Any delays in

reaching board consensus on CSR issues are likely to

weaken, if any, the positive relationship between board

diversity and CSR performance, but are unlikely to result

in a negative association between diversity and CSR

performance.

We present our first hypothesis in an alternative form as

follows

Hypothesis 1 Ceteris paribus, diversity in corporate

boards is positively associated with CSR performance.

Prior research has shown that the level of CSR inten-

sity and the impact of CSR on firm value depend on the

nature of the firm’s business environment. Fisman et al.

(2005) show that firms operating in more competitive

product markets utilizes CSR activities as a signal to

differentiate themselves from their competitors. These

firms have higher CSR performance than those in less

competitive product markets. Fisman et al. (2005) further

find a stronger link between CSR performance and prof-

itability for firms in more competitive markets than those

in less competitive markets. Consistent with Fisman et al.

(2005), Baron et al. (2011) find that the association

between CSR on firm value depends on whether firms

operate in consumer or industrial product markets. 5 Like

firms in competitive markets, firms in consumer product

markets would have a greater need to invest in CSR

activities, especially those related to product, community,

and environment. Investment in CSR projects is more

beneficial for firms operating in the consumer product

markets than those in the industrial product markets as the

former has greater need to differentiate their products

from their competitors.

Benson et al. (2011) examine the association between

internal corporate governance mechanisms (i.e., board size

5 Consumer-oriented firms are firms whose products most likely

consumed directly by end consumers, while the industrial firms are

firms whose products consumed by other firms.

Board Diversity and CSR 645

123

and independence) and excessive spending on CSR activ-

ities. They find that firms with more effective boards (i.e.,

smaller and more independent boards) are unlikely to have

excessive spending on CSR activities, suggesting a sub-

optimal stakeholder management. Furthermore, Benson

et al. (2011) document that the effectiveness of board

governance in monitoring managers’ performance regard-

ing stakeholder management varies by industry. They show

that corporate boards are more effective in overseeing the

stakeholder management of firms in consumer product

markets than those in industrial product markets.

Taken together, the preceding discussion suggests that

the effectiveness of diverse boards in supervising manag-

ers’ CSR performance varies depending on firms’ business

environment. Diverse boards will provide more effective

monitoring of CSR performance when stakeholder man-

agement is more crucial for the firms’ long-term survival.

Since firms in consumer product markets and more com-

petitive markets would have a greater need to differentiate

their firm and products by engaging in CSR activities than

those in industrial product markets and less competitive

markets, our second set of hypotheses in an alternative

form is presented as follows.

Hypothesis 2a Ceteris paribus, the positive association

between diverse boards and CSR performance is stronger

for firms in consumer product markets than for firms in

industrial product markets.

Hypothesis 2b Ceteris paribus, the positive association

between diverse boards and CSR performance is stronger

for firms operating in more competitive than less compet-

itive markets.

Data and Sample Statistics

Sample Construction

The sample for this study utilizes the RiskMetrics Directors

database from 1998 to 2011 to construct seven diversity

indices: gender, race, age, outside directorship, tenure,

power, and expertise. 6 RiskMetrics Directors database is

commonly used in empirical research on board character-

istics and board diversity (Srinidhi et al. 2011; Carter et al.

2003, 2010). We use the MSCI ESG Stats (formerly known

as Kinder, Lyndenberg, and Domini or KLD Stats) that

provides assessment data on the strengths and concerns on

various areas of corporate social performance for compa-

nies listed in the database from 1991 to 2011. MSCI ESG

Stats is a common database used in recent CSR studies

(e.g., Kim et al. 2012; El Ghoul et al. 2011; Goss and

Roberts 2011; Baron et al. 2011; Harjoto and Jo 2011). We

merge the RiskMetrics Directors database with the KLD

database, resulting in 13,257 observations (firm-years)

from 1998 to 2011.

We gather financial data from Compustat and stock

market data from the Center for Research in Securities

Prices (CRSP). After merging the data with Compustat and

CRSP and deleting observations with missing values, we

have 10,955 observations. Since we use a 1-year lag on the

diversity and CSR measures to account for serial correla-

tions, our final sample consists of 9,001 observations across

1,489 firms from 1999 to 2011.

Constructing Diversity and CSR Measures

We construct seven diversity indices. Each diversity index

is constructed using Blau’s index of heterogeneity, calcu-

lated as 1 - RPi2, where P is the proportion of individuals (directors) in a category and i is the number of categories

(Blau 1977). GENDER is the index of heterogeneity for

gender with two categories: male and female. RACE is the

index of heterogeneity for race with five categories: Asian,

Black, Caucasian, Hispanic, and Native American. AGE is

the index of heterogeneity for director age with five cate-

gories: less than 40-years old, 40 to 49, 50 to 59, 60–69,

and 70-years old and older. OUTDIR is the index of het-

erogeneity for director experience, classified based on the

number of other directorship positions that each director

currently holds. We use five categories: 0, 1, 2, 3, and 4 and

more other positions. TENURE is the index of heteroge-

neity for director tenure (length of service), measured using

the number of terms served on the current board. On

average, a director term consists of 3 years. TENURE is

based on six categories: 1 (less than 3 years), 2, 3, 4, 5, and

more than 5 terms (more than 15 years). AFTER CEO is

the index of heterogeneity for director power, measured

using two categories whether the director was appointed

before or after the current CEO appointment. EXPERTISE

is the index of heterogeneity for director expertise, classi-

fied using directors’ type of services and employment

categories. There are five areas of director expertise:

financial, consulting, legal, management, and other exper-

tise (e.g., research, technology, medical, etc.). 7

6 We do not use the RiskMetrics data from 1996 to 1997 due to

missing data on gender, race, director tenure, and other directorship

positions.

7 We acknowledge that our approach for measuring expertise

diversity assumes that each director has only one area of expertise,

although many directors may possess expertise in more than one area.

646 M. Harjoto et al.

123

A heterogeneity (diversity) index takes on values

between zero and one. An index has a value of zero when

there is only one category within a diversity dimension

(e.g., only female directors serve on a board), suggesting

that the group is perfectly homogeneous. An index value

closer to one suggests a more heterogeneous group. The

maximum values of the diversity indexes are less than one

and vary with the number of categories within each

dimension and the degree of representation in each cate-

gory. For example, an index with four (ten) categories has a

maximum value of 0.75 (0.90) when there is equal repre-

sentation in each category. 8 Since the diversity indexes

have different ranges, we standardize each index to have

the same value ranging between zero and one by dividing

the calculated index with the maximum index value within

each industry for each year. We use the Fama–French 48

industry classification. We sum the seven standardized

indices to construct our overall diversity measure (DIV).

MSCI ESG (KLD) uses qualitative data from surveys,

financial statements, media reports, regulatory filings, and

other sources to capture a firm’s CSR activity in seven

different categories (i.e., community, corporate gover-

nance, diversity, employee relations, environment, human

rights, and product characteristics). Within each category,

KLD sets several criteria for determining CSR strength

(CSR concern) scores and uses a binary rating (i.e., one

(zero) for meeting (not meeting) the criteria). For example,

if a firm meets the criteria in one CSR strength (concern)

item in the ‘‘community’’ category, it will receive one

point. Our measure of CSR strengths (CSRSTR) is the sum

of the scores on KLD strengths across six different cate-

gories (i.e., community, employee, environment, product,

human rights, and corporate governance). 9 We exclude the

KLD diversity category to avoid regressing our diversity

measures from RiskMetrics on the same diversity measures

from the KLD diversity category. 10

Similarly, we use the

sum of the scores on KLD concerns across six categories to

measure CSR concerns (CSRCON). This approach is

consistent with the existing CSR studies (e.g., Kim et al.

2012; El Ghoul et al. 2011; Waddock and Graves 1997).

We calculate the overall CSR measure (CSR) by taking

CSRSTR minus CSRCON. CSR performance increases

with greater value of CSRSTR and lower value of CSR-

CON. We do not include the KLD exclusionary criteria

(gambling, tobacco, alcohol, military contracting, and

nuclear power) in our CSR measures since these criteria do

not represent management discretionary activities (Kim

et al. 2012). Appendix A provides the variable definitions

for both diversity and CSR measures.

Control Variables

We run several regressions of CSR measures on our

diversity measure (DIV) and a set of control variables that

have been found significantly affecting firms’ CSR inten-

sity on the existing literature. Based on McWilliams and

Siegel (2001), we control for firm size (ASSET and

SALES), level of diversification (CAPXR), and research

and development (RNDR) that are expected to be posi-

tively correlated with firms’ CSR activities. Campbell

(2007) argues that firms’ CSR is positively related to firms’

financial performance (ROA) and is negatively related with

firms’ risk (LEV and TOTRISK). Waddock and Graves

(1997) and Hilman and Keim (2001) also find a positive

relation between financial performance (ROA) and social

performance (CSR). Fisman et al. (2005) argue that firms

operating in more competitive market measured by a low

Herfindhal–Hirschman Index (HHI) and a high advertising

ratio (ADVR) tend to conduct higher CSR activities as

product differentiation strategies. Dhaliwal et al. (2011)

indicate that there is a positive relationship between CSR

and the percentage of institutional ownership (PCTINSTI).

Harjoto and Jo (2011) find that CSR is positively related to

the percentage of independent board (PCTINDEP), insti-

tutional ownership (PCTINSTI), and analyst followings

(LOGANAL). Ioannou and Serafeim (2014) also find that

firms with higher CSR activities tend to receive more

favorable analyst recommendations.

Sample Statistics

Table 1 presents the descriptive statistics for our sample.

Our sample firms have an average CSR concern score

(CSRCON) of 2.122 and an average CSR strength score

(CSRSTR) of 1.425. The average overall CSR score

(CSRSTR minus CSRCON) is -0.697 as there are more

concerns than strengths. The average board is more diverse

in directors’ tenure, age, outside directorship, and exper-

tise, but is more homogeneous in gender, race, and power

(AFTERCEO). The mean of the overall diversity measure

(DIV) is 4.559 and is evenly distributed between 4 and 5

with a range between 1.777 and 7.

The average firm in our sample has an ASSET value

(i.e., natural log of total assets) of 8.295 or approximately

$4 billion, has a return on asset (ROA) of 5 percent, and a

financial leverage (LEV) of 20.1 percent of total assets.

8 The maximum value of a diversity index with four categories is

0.75 (=1 - (0.25 2 ? 0.25

2 ? 0.25

2 ? 0.25

2 ).

9 Detail explanations of KLD criteria can be found in existing studies

(El Ghoul et al. 2011; Goss and Roberts 2011; Jo and Harjoto 2011). 10

KLD diversity criterion consists of components that are similar to

board diversity measures from RiskMetrics, e.g., the representation of

women and minorities on corporate boards.

Board Diversity and CSR 647

123

The means of the average firm’s advertising expense

(ADVR), capital expenditure (CAPXR), and research and

development expense (RNDR) are 1, 6.7, and 3.8 % of net

sales, respectively. The average firm is 29-years old, has an

average volatility of daily stock return (TOTRISK) of

2.5 %, and is followed by about seven analysts (i.e., the

natural log of the number of analysts following (LOG-

ANAL) is 1.867). On average, institutional ownership

(PCTINSTI) represents 75.8 % of the firm’s ownership.

The percentage of independent directors (PCTINDEP) on

the average board is 77.6 %. The average board has about 8

independent outside (non-executive) directors (DIREC-

TOR). The average annual net sales growth (SALEGRW)

is 9.1 %. The average firm has a Tobin Q of 1.874,

suggesting that its market value is higher than their book

value. During our sample period, the average annual stock

return (RET) for our sample firms is 12 % and the average

value-weighted stock market return (VWRET) is 4 %. We

find that the average percentage of woman and ethnic

minority employees (INDPCT) is 54.2 %.

Table 2 displays the distribution of our sample across

the Fama–French 48 industry classifications (Fama and

French 1997). Business services, utility, computer chips,

retail, and banks represent the top five industries, which are

over 34 % of our sample. We conduct a sensitivity analysis

by excluding utility, banks, and other financial services

industries and the result is discussed under the ‘‘Robustness

Tests’’ section.

Table 1 Descriptive statistics

Variable Obs. Mean Std. dev. 10 percentile 25 percentile 50 percentile 75 percentile 90 Percentile

CSR 9,001 -0.697 2.344 -3 -2 -1 0 2

CSRSTR 9,001 1.425 2.107 0 0 1 2 4

CSRCON 9,001 2.122 2.239 0 1 1 3 5

DIV 9,001 4.559 0.749 3.596 4.064 4.572 5.084 5.496

GENDER 9,001 0.466 0.311 0 0.307 0.484 0.694 0.871

RACE 9,001 0.547 0.295 0 0.332 0.584 0.781 0.918

AGE 9,001 0.781 0.153 0.584 0.692 0.805 0.889 0.958

OUTDIR 9,001 0.748 0.219 0.44 0.650 0.806 0.907 0.969

TENURE 9,001 0.831 0.173 0.632 0.786 0.879 0.938 0.979

AFTERCEO 9,001 0.481 0.390 0 0 0.490 0.889 0.988

EXPERT 9,001 0.706 0.240 0.401 0.627 0.759 0.863 0.943

ASSET 9,001 8.295 1.614 6.341 7.121 8.143 9.352 10.42

SALES 9,001 7.931 1.464 6.137 6.888 7.820 8.903 9.881

ROA 9,001 0.050 0.082 -0.01 0.018 0.050 0.088 0.129

LEV 9,001 0.201 0.161 0 0.064 0.186 0.305 0.411

ADVR 9,001 0.010 0.025 0 0 0 0.010 0.033

CAPXR 9,001 0.067 0.122 0.006 0.018 0.034 0.066 0.145

RNDR 9,001 0.038 0.109 0 0 0 0.031 0.132

HHI 9,001 0.056 0.064 0.022 0.030 0.045 0.057 0.088

FIRMAGE 9,001 29.088 20.292 8 13 24 39 60.8

TOTRISK 9,001 0.025 0.012 0.013 0.017 0.022 0.030 0.04

PCTINSTI 9,001 0.758 0.181 0.523 0.653 0.786 0.893 0.977

LOGANAL 9,001 1.867 0.668 0.965 1.447 1.946 2.351 2.674

PCTINDEP 9,001 0.776 0.138 0.571 0.7 0.8 0.889 0.917

SALEGRW 9,001 0.091 0.250 -0.11 -0.005 0.074 0.159 0.289

DIRECTOR 9,001 7.461 2.360 5 6 7 9 10

DT 9,001 0.361 0.335 0.024 0.079 0.248 0.586 1

TOBINQ 9,001 1.874 1.201 1.022 1.158 1.492 2.132 3.129

RET 9,001 0.120 0.427 -0.33 -0.119 0.091 0.297 0.552

VWRET 9,001 0.040 0.417 -0.59 -0.314 0.176 0.365 0.619

INDPCT 9,001 0.542 0.097 0.485 0.491 0.494 0.597 0.663

648 M. Harjoto et al.

123

Table 3 provides the correlations of the CSR and

diversity measures. We find that the overall diversity

measure (DIV) is positively correlated with CSR,

CSRSTR, and CSRCON. 11

We also find that gender and

tenure diversity are positively correlated with all CSR

measures. We observe that age diversity is negatively

correlated with CSR strengths and CSR concerns, while

outside directorship (experience) diversity (OUTDIR) is

positively correlated with CSR strengths and CSR con-

cerns. Director power diversity (AFTERCEO) is positively

correlated with the overall CSR measure and negatively

correlated with CSR concerns. We find that board expertise

diversity (EXPERT) is positively correlated with the

overall CSR and CSR concerns. In short, we find signifi-

cant correlations between the diversity measures and CSR

measures. Additionally, we do not find strong correlations

among our seven diversity measures.

Results and Analysis

We examine the impact of board diversity on CSR using

the multivariate regression analysis and controlling for

other factors that have been found significantly affecting

CSR in prior research (Baron et al. 2011; Harjoto and Jo

2011; Barnea and Rubin 2010). Appendix B provides the

definitions and expected signs of the control variables.

Since CSR intensity tends to remain unchanged over time,

there is a potential serial correlation between the current

period CSR and the previous period CSR. We include the

lag effect of CSR to control for the potential serial

correlation. 12

Ordinary Least Square Regression

Table 4 reports the ordinary least square (OLS) regression

results. We find a serial correlation between the current

CSR and the previous period CSR. The coefficients of the

lag effect of the CSR measures are statistically significant

and close to one. In the first three columns of Table 4, we

Table 2 Sample distribution across 48 industries

Industries Obs. Percent Cumulative

Agriculture 14 0.16 0.16

Food 206 2.29 2.44

Soda 18 0.2 2.64

Beer 40 0.44 3.09

Smoke 16 0.18 3.27

Toys 65 0.72 3.99

Entertain 45 0.5 4.49

Books 104 1.16 5.64

Household 178 1.98 7.62

Clothes 125 1.39 9.01

Health 105 1.17 10.18

Med eq 235 2.61 12.79

Drugs 314 3.49 16.28

Chemicals 304 3.38 19.65

Rubber 68 0.76 20.41

Textiles 19 0.21 20.62

Build Mat 162 1.8 22.42

Construct 136 1.51 23.93

Steel 134 1.49 25.42

Fab prod 1 0.01 25.43

Machine 398 4.42 29.85

Elec eq 99 1.1 30.95

Miscellan 42 0.47 31.42

Autos 151 1.68 33.1

Aero 95 1.06 34.15

Ships 15 0.17 34.32

Guns 32 0.36 34.67

Gold 15 0.17 34.84

Mines 44 0.49 35.33

Coal 24 0.27 35.6

Energy 357 3.97 39.56

Utility 655 7.28 46.84

Telecom 134 1.49 48.33

Per Svc 80 0.89 49.22

Bus Svc 789 8.77 57.98

Computer 252 2.8 60.78

Chips 580 6.44 67.23

Lab eq 207 2.3 69.53

Paper 160 1.78 71.3

Boxes 53 0.59 71.89

Transport 234 2.6 74.49

Wholesale 289 3.21 77.7

Retail 567 6.3 84

Meals 162 1.8 85.8

Banks 498 5.53 91.33

Insurance 443 4.92 96.26

Real estate 11 0.12 96.38

Other fin 326 3.62 100

Total 9,001 100

11 The positive correlation between DIV and both CSRSTR and

CSRCON is consistent with Kotchen and Moon (2012) that indicate

firms with higher CSR concerns tend to have higher CSR strengths to

address the concerns. Since CSRSTR and CSRCON are positively

related and DIV is positively related to CSRSTR, then DIV is also

positively related to CSRCON. We address this endogeneity and

causality issue by using instrumental variable approach in our

‘‘Robustness Tests’’ section. 12

We conduct Dickey–Fuller (Dickey and Fuller 1979) and Phillips–

Perron (Phillips and Perron 1988) unit root tests for CSR measures

and find that our CSR measures have a unit root. Both tests fail to

reject the null hypothesis of having a unit root (i.e., p values are greater

than 5 %). Therefore, we include the lagged CSR in our regressions to

control for the non-stationary nature of the CSR measures.

Board Diversity and CSR 649

123

examine the impact of the overall board diversity measure

(DIV) on the overall CSR (CSR), CSR strengths

(CSRSTR), and CSR concerns (CSRCON). We find that

DIV is positively associated with the overall CSR and CSR

strengths and is negatively associated with CSR concerns.

Overall, our results suggest that board diversity increases

CSR strengths and reduces CSR concerns, consistent with

the view that board diversity increases firms’ ability to

recognize and serve different stakeholder groups, as well as

to prevent and address conflicts with their broader stake-

holders. These results support Hypothesis 1.

In the last three columns of Table 4, we examine the

impact of each diversity measure on CSR. We find that

gender diversity increases the overall CSR by increasing

CSR strengths and reducing CSR concerns. We find that

race, tenure, and expertise diversities increase the overall

CSR by reducing the CSR concerns. The magnitude of the

slope coefficients indicates that race, tenure, and expertise

diversity measures have higher impact on reducing CSR

concerns than increasing CSR strengths. Overall, our

results suggest that the different dimensions of diversity

play a more important role in reducing CSR concerns than

increasing CSR strengths.

We find that the impacts of the control variables are

generally consistent with the findings in existing studies.

Total assets (ASSET), net sales (SALES), and return on

asset (ROA) are positively associated with CSR because

larger and more profitable firms have more resources

available to engage in CSR activities. We find that firms

with higher advertising ratio (ADVR) tend to have higher

CSR performance, consistent with the findings of Fisman

et al. (2005) and Siegel and Vitaliano (2007). We show that

firms with higher capital expenditure ratio (CAPXR) have

higher overall CSR and CSR strengths, and lower CSR

concerns. We also find that firms with higher volatility

stock returns (TOTRISK) have higher CSR concerns, and

therefore, lower overall CSR.

Consistent with Gillan et al. (2010), we find that insti-

tutional ownership (PCTINSTI) reduces both CSR

strengths and concerns, and therefore, has an insignificant

impact on the overall CSR. This finding is also consistent

with Harjoto and Jo (2011) showing that institutional

investors adjust their ownership based on their view of

whether the managers are over or under invested in the

level of CSR activities. The number of analyst following is

associated with the overall CSR and CSR strengths, con-

sistent with the existing studies (e.g., Dhaliwal et al. 2011;

Ioannou and Serafeim 2014; Jo and Harjoto 2011; Harjoto

and Jo 2011). Finally, we find that the presence of inde-

pendent outside directors increases CSR strengths.

Two-Stage Least Square Regression

Existing studies have shown that board diversity is

endogenous (Gul et al. 2011). We conduct the Durbin-Wu-

Hausman and the instrumental variable approach to test for

the endogeneity of board diversity (Davidson and MacK-

innon 1993). Our results (not tabulated) indicate that board

diversity (DIV) is endogenous. We conduct the two-stage

least square (2SLS) method to account for the potential

endogeneity of board diversity. In the first stage, we

examine factors affecting the board diversity measures

using the variables in Gul et al. 2011 and Srinidhi et al.

2011. Gul et al. (2011) and Srinidhi et al. (2011) used a

predictor model of firms having a gender diverse board.

More diverse boards are predicted for firms that are larger,

older, more profitable, more visible, and more scrutinized

by stakeholders, and have greater need for diverse per-

spectives. Following these studies, the independent vari-

ables in our first-stage regression are total assets,

Table 3 Correlation coefficients

No. Variables 1 2 3 4 5 6 7 8 9 10

1 CSR 1

2 CSRSTR 0.50* 1

3 CSRCON -0.58* 0.42* 1

4 DIV 0.04* 0.18* 0.13* 1

5 GENDER 0.05* 0.25* 0.18* 0.38* 1

6 RACE 0.02 -0.01 -0.03 0.41* 0.02 1

7 AGE 0.01 -0.06* -0.07* 0.28* -0.004 0.01 1

8 OUTDIR -0.06 0.22* 0.27* 0.39* 0.17* 0.07* -0.08* 1

9 TENURE 0.06* 0.11* 0.04* 0.38* 0.07* -0.02 0.02 0.04* 1

10 AFTERCEO 0.06* -0.01 -0.08* 0.49* -0.05* 0.01 0.06* -0.07* 0.04* 1

11 EXPERT 0.02* 0.03 0.009* 0.40* 0.01 -0.05* 0.03 -0.10* 0.01 0.12*

* Statistically significant at 1 % level or less

650 M. Harjoto et al.

123

accounting performance (ROA), market performance (To-

bin’s Q, firm’s stock returns, market returns, total risk),

firm’s age, sales growth, number of directors, total diver-

sification measure from Palepu (1985), and percentage of

employees who were women and ethnic minorities in the

firm’s industry.

Then, in the second stage, we examine the impact of

board diversity on CSR activities. We use the same control

variables as those in the OLS regressions. We include the

lag of board diversity (LAGDIV) to control for a potential

serial correlation between the current period diversity and

the previous period diversity. Table 5 presents both the first

and second stages of 2SLS estimates. Consistent with the

OLS results, we find that board diversity (DIV) increases

the overall CSR by increasing CSR strengths and reducing

CSR concerns, supporting Hypothesis 1.

Based on the first-stage regression results, we find that

the lag of board diversity significantly affects the current

period diversity (DIV), suggesting the presence of a serial

correlation between the current and previous period of

Table 4 Ordinary least square regressions

CSR CSRSTR CSRCON CSR CSRSTR CSRCON

LAGCSR 0.8610 (93.46)*** 0.8587 (93.71)***

LAGCSRSTR 0.9194

(122.74)***

0.9183

(123.35)***

LAGCSRCON 0.7788 (69.41)*** 0.7788 (69.29)***

DIV 0.0885 (4.69)*** 0.0266 (2.22)** -0.0593

(4.36)***

GENDER 0.1819 (4.27)*** 0.0912 (3.24)*** -0.0671 (2.18)**

RACE 0.1016 (2.21)** -0.0035 (0.12) -0.0861 (2.29)**

AGE -0.0712 (0.79) -0.0146 (0.25) 0.0255 (0.39)

OUTDIR 0.0297 (0.50) -0.0230 (0.59) -0.0487 (1.10)

TENURE 0.1281 (1.70)* 0.0101 (0.19) -0.1338 (2.49)**

AFTERCEO 0.0516 (1.52) 0.0220 (0.99) -0.0319 (1.30)

EXPERT 0.1652 (2.42)** 0.0676 (1.54) -0.1012 (2.07)**

ASSET 0.0651 (3.17)*** 0.0669 (4.28)*** 0.0620 (3.20)*** 0.0673 (3.29)*** 0.0691 (4.43)*** 0.0623 (3.18)***

SALES 0.0198 (0.86) 0.1012 (6.39)*** 0.1401 (7.12)*** 0.0143 (0.62) 0.0988 (6.21)*** 0.1405 (7.02)***

ROA 0.6311 (3.59)*** 0.2055 (1.94)* -0.3930

(2.74)***

0.6417 (3.64)*** 0.2138 (2.00)** -0.3921

(2.72)***

LEV -0.1066 (1.25) -0.0533 (0.89) 0.0092 (0.13) -0.1150 (1.35) -0.0528 (0.88) 0.0098 (0.14)

ADVR 2.5954 (4.41)*** 2.1292 (4.76)*** 0.0084 (0.02) 2.5611 (4.35)*** 2.1273 (4.81)*** -0.0002 (0.00)

CAPXR 0.3134 (2.38)** 0.1618 (2.19)** -0.2452 (2.17)** 0.3309 (2.52)** 0.1676 (2.25)** -0.2480 (2.21)**

RNDR 0.3190 (1.25) 0.2456 (1.62) 0.0167 (0.19) 0.3322 (1.28) 0.2532 (1.66)* 0.0174 (0.19)

HHI -1.1243 (0.61) 0.6277 (0.50) 0.6297 (0.48) -0.0973 (0.05) 0.5939 (0.48) 0.5922 (0.45)

FIRMAGE 0.0007 (0.90) 0.0004 (0.68) 0.0011 (1.61) 0.0004 (0.44) 0.0003 (0.57) 0.0013 (1.92)*

TOTRISK -2.8727 (2.07)** -0.3747 (0.46) 3.2716 (2.88)*** -2.7233 (1.95)* -0.2394 (0.29) 3.2161 (2.82)***

PCTINSTI -0.0420 (0.43) -0.1372 (2.17)** -0.1675 (2.33)** -0.0329 (0.34) -0.1350 (2.13)** -0.1714 (2.38)**

LOGANAL 0.0707 (2.71)*** 0.0486 (3.02)*** -0.0303 (1.61) 0.0706 (2.71)*** 0.0503 (3.12)*** -0.0293 (1.55)

PCTINDEP 0.0617 (0.66) 0.1192 (2.06)** 0.1335 (1.67)* 0.0627 (0.63) 0.1256 (2.03)** 0.1224 (1.50)

Constant -1.3037

(5.90)***

-1.3429 (5.09)*** 0.1151 (0.20) -1.8103

(3.70)***

-1.2864 (4.58)*** 0.1265 (0.21)

R 2

0.7150 0.8424 0.8195 0.7154 0.8425 0.8196

Dickey–Fuller 0.9997 0.9999 0.8391 0.9997 0.9999 0.8391

Phillips–

Perron

0.1828 0.1989 0.1344 0.1828 0.1989 0.1344

Observations 9,001 9,001 9,001 9,001 9,001 9,001

# Firms 1,489 1,489 1,489 1,489 1,489 1,489

All regressions include the Fama–French 48 industries and year fixed effects and all standard errors are clustered based on two dimensions of

firm and year clustering. Robust absolute values of t-statistics are in parentheses. The p values from the Dickey–Fuller and Phillips–Perron unit

root tests are reported

*, **, and *** indicate statistically significant at 10, 5, and 1 %, respectively

Board Diversity and CSR 651

123

board diversity. The signs of the other control variables on

the overall diversity measure are consistent with those of

Gul et al. (2011) and Srinidhi et al. (2011). Sales growth

(SALEGRW) and the number of independent outside

directors (DIRECTOR) are positively associated with

board diversity. Similarly, the percentage of women and

ethnic minority employees (INDPCT) is positively asso-

ciated with board diversity.

The impacts of the control variables in the second-stage

regressions are generally consistent with the results in

Table 4 with two exceptions. Unlike the OLS results, we

find significant and negative coefficients of the analyst

following (LOGANAL) and the percentage of independent

directors (PCTINDEP) in the CSRCON regression. These

results suggest that when firms have more analysts fol-

lowing the firm and more independent board members, the

firm will be associated with a lower level of CSR concerns.

Table 6 presents the first-stage regressions of the 2SLS

examining the determinants of each diversity component.

We find that the lag effect of each diversity component is

positive and highly significant, indicating the presence of a

serial correlation between the current and previous period

diversity measures. We also find that the signs of the

control variables are consistent with those in Gul et al.

(2011) and Srinidhi et al. (2011).

Table 7 reports the results of the second-stage regres-

sions examining the impact of each diversity measure on

CSR activities. Consistent with the OLS results, we find

that gender diversity is positively associated with CSR

activities, increasing CSR strengths and reducing CSR

concerns. We also find that tenure and expertise diversities

increase the overall CSR by reducing CSR concerns.

However, unlike the OLS results, we do not find that race

diversity decreases CSR concerns.

Table 5 Two-stage least square (2SLS) regressions

First stage Second stage First stage Second stage First stage Second stage

DIV CSR DIV CSRSTR DIV CSRCON

LAGCSR 0.8604 (127.08)***

LAGCSRSTR 0.9190 (156.52)***

LAGCSRCON 0.8035 (103.18)***

DIV 0.0836 (3.03)*** 0.0432 (2.34)** -0.2391 (9.67)***

LAGDIV 0.6998 (97.73)*** 0.6998 (97.73)*** 0.6998 (97.73)***

ASSET 0.0312 (6.86)*** 0.0665 (2.41)** 0.0312 (6.86)*** 0.0670 (3.61)*** 0.0312 (6.86)*** 0.0550 (2.20)**

SALES 0.0195 (0.68) 0.0995 (5.22)*** 0.1212 (4.68)***

ROA 0.0788 (1.06) 0.6350 (3.33)*** 0.0788 (1.06) 0.2063 (1.62) 0.0788 (1.06) -0.4364 (2.55)**

LEV -0.1124 (1.13) -0.0568 (0.86) -0.0126 (0.14)

ADVR 2.5662 (4.09)*** 2.1332 (5.08)*** -0.6686 (1.19)

CAPXR 0.3142 (2.14)** 0.1633 (1.66)* -0.2507 (1.90)*

RNDR 0.3278 (2.11)** 0.2413 (2.32)** 0.1574 (1.13)

HHI -0.0948 (0.06) 0.6172 (0.58) 2.5267 (1.77)*

FIRMAGE -0.0000 (0.11) 0.0007 (0.81) -0.0000 (0.11) 0.0003 (0.56) -0.0000 (0.11) -0.0005 (0.61)

TOTRISK 0.4580 (0.74) -2.8871 (1.72)* 0.4580 (0.74) -0.3602 (0.32) 0.4580 (0.74) 4.2581 (2.83)***

PCTINSTI -0.0375 (0.43) -0.1397 (2.39)** -0.2522 (3.23)***

LOGANAL 0.0692 (2.43)** 0.0481 (2.53)** -0.0584 (2.29)**

PCTINDEP 0.0621 (0.58) 0.1143 (1.59) -0.2740 (2.84)***

SALEGRW 0.0462 (2.19)** 0.0462 (2.19)** 0.0462 (2.19)**

DIRECTOR 0.0181 (6.75)*** 0.0181 (6.75)*** 0.0181 (6.75)***

DT -0.0213 (1.13) -0.0213 (1.13) -0.0213 (1.13)

TOBINQ 0.0042 (0.78) 0.0042 (0.78) 0.0042 (0.78)

RET 0.0010 (0.07) 0.0010 (0.07) 0.0010 (0.07)

VWRET -0.0261 (0.62) -0.0261 (0.62) -0.0261 (0.62)

INDPCT 0.4731 (2.83)*** 0.4731 (2.83)*** 0.4731 (2.83)***

Constant 0.8540 (5.53)*** -1.8938 (4.05)*** 0.8540 (5.53)*** -1.4030 (4.48)*** 0.8540 (5.53)*** 1.3660 (3.25)***

R 2

0.6155 0.7150 0.6155 0.8423 0.6155 0.7617

Observations 9,001 9,001 9,001 9,001 9,001 9,001

# Firms 1,489 1,489 1,489 1,489 1,489 1,489

*, **, and *** Statistically significant at 10, 5, and 1 %, respectively. Robust absolute values of t-statistics are in parentheses

652 M. Harjoto et al.

123

Regressions on CSR Components

The scores on CSR strengths and CSR concerns are com-

puted across six different social responsibility areas:

community, employee, environment, product, human

rights, and corporate governance. We run separate regres-

sions for the CSR components on the overall board

diversity (DIV). Each CSR component score is measured

as the difference between the strength score and the con-

cern score in each area. Table 8 reports the results. We find

that DIV is positively associated with the CSR components

in the community, environment, product, and corporate

governance areas. However, we find that DIV does not

affect the CSR components related to employee and human

rights.

Industry Subsamples and Analyses

To test Hypothesis 2a and 2b, we divide our sample into

subsamples. First, following Baron et al. (2011), we clas-

sify our sample firms into consumer and industrial subs-

amples. We examine the impact of board diversity on CSR

performance separately for firms in consumer and indus-

trial subsamples. Second, following Fisman et al. (2005),

Table 6 First-stage regressions of diversity components

GENDER RACE AGE OUTDIR TENURE AFTER CEO EXPERT

LAGGENDER 0.8041

(135.87)***

LAGRACE 0.5937

(69.29)***

LAGAGE 0.6770

(86.36)***

LAGOUTDIR 0.7168

(106.11)***

LAGTENURE 0.6956

(112.12)***

LAGAFTERCEO 0.7552

(111.61)***

LAGEXPERT 0.5117

(60.82)***

ROA -0.0376 (1.49) 0.0252 (0.71) 0.0054 (0.31) 0.0100 (0.50) 0.0123 (0.73) 0.0503 (1.29) 0.0094 (0.70)

ASSET 0.0056

(3.63)***

0.0066

(3.06)***

-0.0010

(0.94)

0.0108

(8.62)***

0.0005 (0.53) 0.0009 (0.37) 0.0045

(5.57)***

FIRMAGE 0.0001 (0.88) 0.00001 (0.11) 0.0002

(2.92)***

0.0002

(2.58)***

0.0002 (2.42)** -0.0002 (1.03) 0.0001 (1.63)

SALEGRW 0.0038 (0.52) 0.0126 (1.25) 0.0050 (1.01) -0.0012 (0.20) -0.0072 (1.51) 0.0271 (2.44)** 0.0042 (1.09)

DIRECTOR 0.0061

(6.63)***

0.0030

(2.37)**

0.0016

(2.55)**

0.0074

(10.16)***

0.0042

(6.84)***

0.0004 (0.26) 0.0058

(11.88)***

DT -0.0010 (0.15) 0.0005 (0.05) 0.0024 (0.54) 0.0003 (0.07) -0.0088

(2.06)**

-0.0191

(1.92)*

-0.0011 (0.31)

TOTRISK -0.4654

(2.20)**

-0.6013

(2.03)**

0.0298 (0.20) -0.3252

(1.94)*

0.1324 (0.94) 0.1564 (0.48) -0.3035

(2.71)***

TOBINQ 0.0014 (0.78) 0.0013 (0.50) 0.0012 (0.96) 0.0004 (0.29) 0.0028 (2.36)** -0.0013 (0.45) -0.0013 (1.37)

RET 0.0030 (0.64) 0.0097 (1.50) -0.0003

(0.08)

0.0043 (1.18) -0.0039 (1.26) -0.0069 (0.96) -0.0014 (0.59)

VWRET -0.0069 (0.48) 0.0029 (0.15) 0.0026 (0.26) -0.0014 (0.12) 0.0075 (0.78) -0.0360 (1.62) 0.0046 (0.61)

INDPCT 0.0356 (0.63) -0.0057

(0.07)

0.0241 (0.61) 0.1169

(2.61)***

0.0437 (1.16) 0.1624 (1.85)* 0.0138 (0.46)

Constant 0.0429 (0.83) 0.2045

(2.82)***

0.3183

(8.64)***

0.0391 (0.96) 0.2592

(7.45)***

-0.0153 (0.19) 0.0650

(2.37)**

R 2

0.7417 0.4397 0.4851 0.6754 0.6319 0.6083 0.7577

Observations 9,001 9,001 9,001 9,001 9,001 9,001 9,001

# Firms 1,489 1,489 1,489 1,489 1,489 1,489 1,489

Robust absolute values of t-statistics are in parentheses

*, **, and *** Statistically significant at 10, 5, and 1 %, respectively

Board Diversity and CSR 653

123

we form two sets of subsamples for firms in high compe-

tition industries and low competition industries. Firms in

high competition product markets have a low Herfindahl–

Hirschman Index (HHI) and a high ratio of advertising

expenditure to net sales (ADVR). Therefore, we examine

the relationship between diversity and CSR for firms below

the median HHI (i.e., high competition industries) and

above the median HHI (i.e., low competition industries).

We also examine the impact of diversity on CSR for above

and below median advertising ratio subsamples. 13

Panel A of Table 9 presents the regression results of the

impact of board diversity on CSR for consumer and

industrial subsamples, high HHI and low HHI subsamples,

and high ADVR and low ADVR subsamples. The results of

the impact of diversity on CSR for consumer versus

industrial subsamples and high competitive versus low

competitive subsamples are reported in panel A of Table 9.

We find strong evidence that board diversity significantly

increases CSR for only firms in consumer product markets

and firms in more competitive markets, measured by low

HHI and high advertising ratio. The results suggest that

diverse board provides more effective advisory and moni-

toring roles to differentiate the firms from their competitors

by intensifying CSR activities when firms operate in con-

sumer product markets and more competitive markets.

We further examine the impact of board diversity on

CSR strengths and CSR concerns for these subsamples.

Panel B of Table 9 indicates that board diversity increases

CSR strengths and reduces CSR concerns for firms with

consumer-oriented products and those operating in more

competitive markets. In contrast, our untabulated results

indicate that board diversity does not affect CSR strengths

and concerns for firms with industrial-oriented products

and those operating in less competitive markets. These

findings provide support for Hypothesis 2a and 2b that

board diversity plays a greater role in overseeing manag-

ers’ CSR performance when firms operate in an environ-

ment with greater need for stakeholder management.

Using the full sample, we conduct regressions with a

dummy variable for firms with consumer-oriented products

Table 7 Second-stage regressions of CSR measures

Robust absolute values of t-

statistics are in parentheses

*, **, and *** Statistically

significant at 10, 5, and 1 %,

respectively

CSR CSRSTR CSRCON

LAGCSR 0.8573 (125.53)***

LAGCSRSTR 0.9175 (154.99)***

LAGCSRCON 0.7780 (117.49)***

GENDER 0.2516 (4.24)*** 0.1130 (2.84)*** -0.1057 (2.36)**

RACE -0.0566 (0.68) 0.0064 (0.12) 0.0673 (1.07)

AGE -0.1728 (1.28) -0.0084 (0.09) 0.1084 (1.06)

OUTDIR 0.0461 (0.47) 0.0206 (0.32) -0.0197 (0.27)

TENURE 0.2563 (2.40)** 0.1074 (1.51) -0.1595 (1.97)**

AFTERCEO 0.0549 (1.18) 0.0161 (0.52) -0.0462 (1.30)

EXPERT 0.1696 (2.26)** 0.0366 (0.38) -0.1057 (1.86)*

ASSET 0.0685 (2.47)** 0.0681 (3.64)*** 0.0601 (2.82)***

SALES 0.0105 (0.36) 0.0969 (5.03)*** 0.1414 (6.39)***

ROA 0.6644 (3.48)*** 0.2132 (1.67)* -0.4111 (2.83)***

LEV -0.1106 (1.11) -0.0567 (0.85) 0.0011 (0.01)

ADVR 2.5946 (4.11)*** 2.1292 (5.04)*** -0.0338 (0.07)

CAPXR 0.3332 (2.25)** 0.1665 (1.69)* -0.2488 (2.21)**

RNDR 0.3433 (2.20)** 0.2450 (2.35)** 0.0003 (0.00)

HHI -0.2057 (0.13) 0.5621 (0.53) 0.6692 (0.55)

FIRMAGE -0.0001 (0.17) 0.0000 (0.08) 0.0015 (2.25)**

TOTRISK -2.4647 (1.46) -0.1991 (0.18) 3.0350 (2.37)**

PCTINSTI -0.0301 (0.34) -0.1363 (2.33)** -0.1750 (2.64)***

LOGANAL 0.0688 (2.40)** 0.0484 (2.53)** -0.0290 (1.33)

PCTINDEP 0.0434 (0.37) 0.0984 (1.19) 0.1206 (1.36)

Constant -1.7221 (3.50)*** -1.3655 (4.10)*** -0.0281 (0.08)

R 2

0.7148 0.8424 0.8192

Observations 9,001 9,001 9,001

# Firms 1,489 1,489 1,489

13 We only examine the impact of diversity on CSR for firms with

non-zero advertising expenditure. We divide firms with non-zero

advertising expenditure into above and below median advertising

expenditure ratio.

654 M. Harjoto et al.

123

and a dummy variable for firms that operate in more

competitive market (low HHI or high ADVR) and we

interact these dummy variables with our diversity measure

(DIV). Our untabulated results are consistent with our

findings that board diversity plays more significant role in

overseeing managers’ CSR performance when firms oper-

ate in consumer product markets and in more competitive

markets.

Robustness Tests

We conduct several robustness tests. First, we examine

whether our results hold using different measures of CSR.

Since diversity measures are constructed from board

characteristics, we exclude the corporate governance cat-

egory from our CSR measures to avoid the spurious cor-

relation between the CSR corporate governance category

and the board diversity measures. We find that our results

remain unchanged when we exclude the corporate gover-

nance category from the CSR measures.

We also test our results by using an alternative dataset

for CSR activities, the Bloomberg Environmental, Social,

and Governance (ESG) data collected from the Bloomberg

terminal. While our sample size is significantly reduced to

2,368 observations across 673 firms during 2006–2011, we

find that the positive impact of diversity on CSR (envi-

ronment and social or environment, social and governance)

remains statistically significant.

Second, we examine whether our results hold using a

different sample. Since our sample is dominated by five

industries: business services, utility, computer chips, retail,

and banks, we exclude these five industries from our

sample and re-estimate our regression analyses. Our sam-

ple size decreases to 5,912 observations across 975 firms.

We find that the impact of diversity on the overall CSR and

CSR concerns remains robust, while the impact of diversity

Table 8 Regressions of the overall board diversity on CSR components

COM EMP ENV PRO HUM CGOV

LAGCOM 0.8011 (72.12)***

LAGEMP 0.7772 (86.01)***

LAGENV 0.8766 (104.17)***

LAGPRO 0.7961 (89.67)***

LAGHUM 0.7430 (41.15)***

LAGCGOV 0.6610 (57.91)***

DIV 0.0197 (3.35)*** 0.0068 (0.75) 0.0213 (2.91)*** 0.0199 (3.32)*** 0.0047 (1.58) 0.0215 (2.71)***

ASSET 0.0165 (2.34)** 0.0192 (1.76)* 0.0248 (2.81)*** -0.0061 (0.84) -0.0025 (0.79) -0.0013 (0.13)

SALES 0.0195 (2.83)*** -0.0172 (1.50) 0.0308 (3.24)*** -0.0314 (4.45)*** -0.0042 (1.26) -0.0058 (0.55)

ROA 0.0555 (1.21) 0.5217 (5.66)*** 0.0560 (0.86) 0.0092 (0.16) 0.0082 (0.30) 0.1004 (1.31)

LEV -0.0110 -0.1113 -0.0090 0.0289 -0.0018 -0.0448

(0.41) (2.36)** (0.28) (1.02) (0.15) (1.20)

ADVR 0.7740 (3.67)*** 0.9340 (3.17)*** 0.6123 (2.77)*** -0.3161 (1.85)* 0.0179 (0.21) 0.7050 (2.70)***

CAPXR 0.0833 (2.06)** 0.0408 (0.64) 0.1810 (2.65)*** -0.0221 (0.62) 0.0651 (2.90)*** 0.0192 (0.37)

RNDR 0.0687 (1.48) 0.2492 (2.20)** 0.0689 (0.99) -0.0123 (0.29) -0.0121 (0.90) 0.0012 (0.02)

HHI -0.4128 (0.82) 0.7338 (1.18) -0.7277 (1.30) -0.8557 (1.19) 0.0506 (0.14) -0.2490 (0.31)

FIRMAGE -0.0009 (3.08)*** 0.0001 (0.13) 0.0004 (1.08) 0.0002 (0.54) -0.0003 (2.42)** 0.0017 (4.50)***

TOTRISK -0.6381 (1.37) 1.0951 (1.57) -0.9183 (1.98)** -0.8756 (1.94)* -0.1047 (0.49) -1.8827 (3.25)***

PCTINSTI -0.0591 (2.09)** -0.0313 (0.76) -0.0118 (0.38) 0.0258 (0.81) 0.0111 (1.06) -0.0478 (1.22)

LOGANAL 0.0109 (1.48) 0.0269 (2.21)** 0.0285 (2.83)*** 0.0128 (1.60) -0.0027 (0.77) -0.0176 (1.54)

PCTINDEP 0.0323 (1.18) -0.0666 (1.37) 0.1324 (3.88)*** -0.0586 (1.75)* -0.0066 (0.43) -0.0233 (0.56)

Constant -0.2988 (4.42)*** -0.0374 (0.36) -0.7895 (10.51)*** 0.2851 (3.94)*** 0.0432 (1.24) -0.1003 (1.04)

R 2

0.6920 0.6557 0.7489 0.7247 0.6211 0.4745

Observations 9,001 9,001 9,001 9,001 9,001 9,001

# Firms 1,489 1,489 1,489 1,489 1,489 1,489

Robust absolute values of t-statistics with both firm and year clustering are in parentheses. All regressions include the Fama–French 48 industries

and year fixed effects and all standard errors are clustered based on two dimensions of firm and year clustering

*, **, and *** Statistically significant at 10, 5, and 1 %, respectively

Board Diversity and CSR 655

123

on CSR strength becomes statistically insignificant with the

exclusion of these five industries.

Third, we examine whether our results hold using dif-

ferent estimation methods. Since corporate decisions on

board diversity and CSR activities can be jointly deter-

mined, we include the CSR measures as the independent

variables in the diversity equations (first stage) and include

the diversity measures in the CSR equation (second stage)

and re-estimate our two-stage least square (2SLS). We find

that our conclusions remain unchanged. Furthermore, we

conduct a reverse causality test by regressing DIV on CSR,

lagged CSR, and both CSR and lagged CSR. Our untabu-

lated results indicate that CSR and lagged CSR do not

significantly affect board diversity. Therefore, we believe

that our results are not driven by a reverse causality

mechanism.

Although we have used the lagged CSR and lagged

diversity measures to address the potential problems of

serial correlations, simultaneity, and reverse causality, it is

possible that our estimations suffer from correlated, omit-

ted variables that affect both CSR performance and board

diversity. To address this issue, we conduct the instru-

mental variable (IV) estimation method. Following Cai

et al. (2011), we estimate the industry median CSR based

on the Fama–French 48 industries. We use this industry

median CSR as an instrumental variable for our CSR

measures from the KLD data. We also use the state voting

records as an instrumental variable for CSR (Goss and

Roberts 2011; Rubin 2008) and the percentage of woman

and ethnic minority employees as an instrumental variable

for board diversity (Gul et al. 2011; Srinidhi et al. 2011). 14

We find that our results remain robust.

Adams and Ferreira (2009) suggest that the fixed effect

panel data regression analysis addresses the concern that

omitted corporate culture or any other time-invariant

Table 9 The impact of board diversity on CSR components: industry subsamples

Panel A: the impact of board diversity on CSR

Consumer Industrial Low HHI High HHI High ADVR Low ADVR

CSR CSR CSR CSR CSR CSR

LAGCSR 0.8589 (89.36)*** 0.8522 (26.21)*** 0.8623 (60.71)*** 0.8607 (71.58)*** 0.8430 (41.20)*** 0.8604 (44.72)***

DIV 0.1141 (3.42)*** -0.0126 (0.11) 0.1703 (3.98)*** 0.0311 (0.65) 0.2011 (2.42)** 0.0336 (0.51)

Constant -1.4525 (5.89)*** -0.8217 (1.27) -2.6353 (5.41)*** -1.1803 (3.60)*** -1.3931 (2.55)** -1.2500 (3.00)***

Control Variables Yes Yes Yes Yes Yes Yes

R 2

0.7157 0.7151 0.7075 0.7240 0.7242 0.7302

Observations 3,444 5,557 4,500 4,501 1,771 1,771

# Firms 574 915 898 848 360 417

Panel B: The impact of board diversity on CSR strengths and concerns

Consumer Consumer Low HHI Low HHI High ADVR High ADVR

CSRSTR CSRCON CSRSTR CSRCON CSRSTR CSRCON

LAGCSRSTR 0.9125 (71.43)*** 0.9128 (74.15)*** 0.9026 (64.40)***

LAGCSRCON 0.7838 (64.68)*** 0.7722 (47.49)*** 0.7074 (20.97)***

DIV 0.0671 (1.90)* -0.0933 (3.88)*** 0.0435 (1.71)* -0.1226 (3.75)*** 0.1106 (1.83)* -0.0909

(1.67)*

Constant -1.4390 (6.85)*** -0.9195 (4.43)*** -1.7862 (6.53)*** -0.0465 (0.12) -1.5442 (4.09)*** -1.4763 (3.43)***

Control Variables Yes Yes Yes Yes Yes Yes

R 2

0.8286 0.8214 0.8394 0.7795 0.8693 0.7946

Observations 3,444 3,444 4,500 4,500 1,771 1,771

i# Firms 574 574 898 898 360 360

Robust absolute values of t-statistics are in parentheses. All regressions include the control variables and Fama–French 48 industries and year fixed effects

and all standard errors are clustered based on two dimensions of firm and year clustering. In Panel B, we report only the results for firms in consumer

product markets and firms in highly competitive industries. We run the regression analysis, but do not report the results, for firms in industrial product

markets and firms in low competition markets DIV is not associated with CSRSTR and CSRCON for these subsamples (i.e., Industrial, High HHI, and

High Ads)

*, **, and *** Statistically significant at 10, 5, and 1 %, respectively

14 Goss and Roberts (2011) and Rubin (2008) find that firms with

high CSR rankings tend to be located in the states that vote for

Democratic in presidential elections and those with low CSR ratings

tend to be located in the states that vote for Republican. To capture

the impact of regional differences in political views on firms’ attitudes

toward conducting CSR, we include a measure of Republican strength

in each state as calculated by the Brookings Institute.

656 M. Harjoto et al.

123

unobservable firm characteristics could affect board

diversity. We run the fixed effect panel data regression and

find that board diversity (DIV) is positively associated with

the overall CSR and is negatively associated with CSR

concerns.

We conduct regressions with the same control variables

for both first stage and second stage models. Our results

(not tabulated) are consistent with the reported results.

Then, we run a separate regression excluding DIRECTOR

and INDPCT since they are highly correlated with CSR

and board diversity measure (DIV) from our first-stage

regression and re-estimate our 2SLS. We also exclude the

independent variables that are in both CSR and DIV

equations (ASSET, ROA, FIRMAGE, and TOTRISK)

from both first- and second-stage regressions and re-esti-

mate our 2SLS. The results from both analyses are con-

sistent with our reported results. Therefore, we believe our

results are not driven by the spurious correlations of the

control variables.

Finally, we conduct size analyses using the subsamples

of large and small firms (based on total assets or net sales).

Using the full sample, we define large firms as firms with

total assets (net sales) above the median total assets (net

sales) and small firms as firms with total assets (net sales)

at and below the median total assets (net sales). Our results

(not tabulated) indicate that there is no size effect and our

reported results remain robust.

Conclusions

Board diversity and CSR have become two pressing issues

for publicly held corporations. Regulators are urging

companies to improve diversity in boardrooms, and con-

temporaneously, firm stakeholders and the public are

demanding companies to be more socially responsible. Our

study examines the relationship between board diversity

and firm qualitative assessments on socially responsible

initiatives and activities. We argue that greater board

diversity could increase firms’ ability to manage the need

and interests of different groups of stakeholders. We

measure board diversity in seven dimensions: gender, race,

age, outside directors, tenure, power, and expertise. We

measure CSR based on Kinder, Lyndenberg, and Domini

(KLD) scores on the strengths and concerns of firms’ social

responsibility performance in six areas: community,

employee, environment, product, human rights, and cor-

porate governance.

We find that the overall board diversity measure is

positively associated with CSR strengths and negatively

associated with CSR concerns, supporting the stakeholder

theory and consistent with the view that more diverse

boards are more effective in monitoring social responsi-

bility performance than less diverse boards. More specifi-

cally, our analysis reveals that the overall measure of board

diversity is positively associated with CSR components in

the community, environment, product, and corporate gov-

ernance areas. Examining the impact of each diversity

component, we find that gender diversity increases CSR

strengths and reduces CSR concerns, while both tenure and

expertise diversities reduce CSR concerns.

We expect that the impact of diverse boards on CSR

activities is stronger for firms with greater need for stake-

holder management. Our analysis suggests that diverse

boards increase CSR performance by increasing CSR

strengths and reducing CSR concerns for firms with con-

sumer-oriented products and those operating in more

competitive markets. The results suggest that diverse

boards play a more significant role in stakeholder man-

agement in firms operating in an environment that requires

high intensity of stakeholder management.

Our study contributes to the greater understanding of the

role of board diversity in overseeing management perfor-

mance. Specifically, we examine the effectiveness of

diverse boards in supervising managers’ CSR performance.

Our study supports the calls for greater board diversity

from regulators in the U.S. and European countries. Future

studies could examine the effect of board diversity on other

areas of management performance. Finally, our study has

important implications for the director selection process as

our results highlight the importance of considering the

diverse background of individuals nominated for board

positions. Future studies could provide more insights on the

selection (nomination) process of directors. More specifi-

cally, future studies could investigate corporate events

triggering the increased level of board diversity and the

change in certain board diversity components following

such events. In addition, future studies could examine the

differences in the director selection process for firms in

consumer versus industrial product markets.

Acknowledgements We are grateful for the helpful comments and suggestions of two anonymous referees. Harjoto acknowledges Julian

Virtue Professorship endowment and Rothschild awards for financial

support and release time for this research. Lee acknowledges Julian

Virtue Professorship endowment for financial support and release

time for this research.

Appendix 1

See Appendix in Table 10.

Board Diversity and CSR 657

123

Appendix 2

See Appendix in Table 11.

Table 10 Definitions of dependent variables and variables of interest

Variables Expected

signs on

CSR

Definitions

CSR The net of CSR strengths minus CSR

concerns scores across six different

CSR categories: community,

employee, environment, product,

human rights, and corporate

governance

CSRSTR The score on CSR strengths across six

different CSR categories:

community, employee, environment,

product, human rights, and corporate

governance.

CSRCON The score on CSR concerns across six

different CSR categories:

community, employee, environment,

product, human rights, and corporate

governance

DIV ? The sum of seven different board

heterogeneity indexes: GENDER,

RACE, AGE, OUTDIR, TENURE,

AFTER CEO, and EXPERTISE.

Each of these seven board

heterogeneity indexes is calculated

based on Blau’s index of

heterogeneity (calculated as 1 -

RPi2, where P is the proportion of individuals (directors) in a category

and i is the number of categories)

GENDER ? Index of heterogeneity for board

gender with two categories: male

and female, standardized between

zero and one

RACE ? Index of heterogeneity for board race

with five categories: Asian, Black,

Caucasian, Hispanic, and Native

American. The index is standardized

between zero and one

AGE ? Index of heterogeneity for board age

with five categories: 40 and younger,

40–49, 50–59, 60–69, 70-years old

and older. The index is standardized

between zero and one

OUTDIR ? Index of heterogeneity for director

experience, measured using the

number of other directorship

positions. Five categories include 0,

1, 2, 3, and 4 and more positions.

The index is standardized between

zero and one

TENURE ? Index of heterogeneity for director

tenure, measured using the number

of terms served on the board. On

average, a director term consists of

3 years. Six categories include 1

(i.e., less than 3 years), 2, 3, 4, 5, and

more than 5 (i.e., more than

15 years). The index is standardized

between zero and one

Table 10 continued

Variables Expected

signs on

CSR

Definitions

AFTERCEO ? Index of heterogeneity for director

power with two categories based on

whether a director is selected to

serve on the board before or after the

current CEO took office. The index

is standardized between zero and

one

EXPERT ? Index of heterogeneity for director

expertise across five categories:

financial, consulting, legal,

management (executives), and

others. The index is standardized

between zero and one

Table 11 Control variables definitions

Variables Expected

signs on

CSR

Expected

signs on

DIV

Definitions

ASSET ? ? Natural log of total assets

(total assets in $ million)

SALES ? Natural log of net sales (net

sales in $ million)

ROA ? ? Income before extraordinary

items divided by total

assets

LEV - Total debt divided by total

assets

ADVR ? Advertising expense divided

by net sales

CAPXR ? Capital expenditure divided

by net sales

RNDR ? Research and development

expense divided by net

sales

HHI - Herfindahl–Hirschman index is calculated from the sum

of squared of each firm’s

net sales (market share)

within each industry. HHI

represents the intensity of

market competition.

FIRMAGE ? ? Number of years since the

firm was first listed on

CRSP database

TOTRISK - - Standard deviation of daily

stock return in 1 year

658 M. Harjoto et al.

123

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Table 11 continued

Variables Expected

signs on

CSR

Expected

signs on

DIV

Definitions

PCTINSTI - Institutional ownership

shareholdings divided by

total shares outstanding

LOGANAL ? Natural log of the mean of

the number of analyst

followings

PCTINDEP ? Number of independent

outside directors divided by

total number of directors

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SALEGRW ? Net sales growth within

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DIRECTOR ? Number of independent

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directors

DT - Total diversification as

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sales of the firm

TOBINQ ? Tobin’s Q ratio calculated as

the book value of assets

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by the book value of assets

RET ? Annual stock return during

the year

VWRET ? Value-weighted market

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year

INDPCT ? Percentage of employees

who were women and

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industry categories as

reported by the Bureau of

Labor and Statistics.

Available at http://www.

bls.gov/cps/tables.htm. We

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to match our sample period

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