OKAFOR-DISSERTATION-2015

ESSAYS ON EXECUTIVE COMPENSATION, CORPORATE SOCIAL
RESPONSIBILITY, AND FIRM PERFORMANCE
A Dissertation
by
COLLINS EMEKA OKAFOR
Submitted to Texas A&M International University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
August 2015
Major Subject:
International Business Administration
Essays on Executive Compensation, Corporate Social Responsibility, and Firm Performance
Copyright 2015 COLLINS EMEKA OKAFOR
ESSAYS ON EXECUTIVE COMPENSATION, CORPORATE SOCIAL
RESPONSIBILTY, AND FIRM PERFORMANCE
A Dissertation
by
COLLINS EMEKA OKAFOR
Submitted to Texas A&M International University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Approved as to style and content by:
Chair of Committee,
Committee Members,
Head of Department,
Dr. Steve Sears
Dr. Anand Jha
Dr. George Clarke
Dr. Siddhart Shankar
Dr. Jorge Brusa
August 2015
Major Subject:
International Business Administration
DEDICATION
I dedicate this work to my Rock and Shield, Jesus Christ. I also extend
profound gratitude to my lovely wife and wonderful kids for their unconditional love, support
and encouragement.
v
ABSTRACT
Essays on Executive Compensation, Corporate Social Responsibility, and Firm Performance
(August 2015)
Collins Emeka Okafor, B.B.A., Stetson University; MBA., M.Sc., MPacc., Texas A&M
International University
Chair of Committee: Dr. Steve Sears
Using a large sample of 1301 US firms for the period of 1993 to 2013, the associations
between Corporate Social Responsibility (CSR), Executive Compensation, and Firm
Performance are revisited. This study contributes to the literature on executive compensation
structure, CSR, and firm performance, by examining the moderating effect of the Golden
Parachute (GP) on these associations. The findings in essay1 suggest that there exists an inverse
relationship between current (long-term) compensation and firms’ CSR performance. While the
direct association between the GP and CSR is negative, the test for a moderating effect reveals
that the GP and long-term compensation jointly and positively increase firms’ CSR performance.
This is consistent with the expectation that executives with a GP clause seek to maximize their
long-term wealth by approving of mostly value-enhancing CSR projects that positively enhance
firm financial performance. Furthermore, the results in this essay also suggest that female
executives are more likely than their male counterparts to promote CSR engagements. Older
executives are less willing to engage in CSR even with the GP clause, and current compensation
increases CSR concerns at a greater magnitude than long-term compensation.
vi
The findings in essay 2 suggest that the association between CSR and firm performance,
ROA, is positive. The test to examine the moderating effect of the GP produced empirical
evidence to suggest that the GP amplifies the positive association between CSR and ROA. That
is, CEOs that have the GP clause in their executive compensation contract, to a greater extent,
engage in more value-enhancing CSR projects than their counterparts who do not have the GP
clause. The results in this essay also suggest that CEOs with a GP clause do not especially invest
in external CSR projects like they do in internal CSR projects. That is, CEOs that are endowed
with a GP clause project a preferential inclination towards internal CSR projects. Lastly, this
essay provided empirical evidence that lends credence to the argument that the uncertainty
surrounding the financial payoffs CSR investments could actually increase the volatility of the
firms’ earnings.
vii
ACKNOWLEDGEMENTS
I would like extend a profound gratitude to my highly esteemed committee members Dr.
Sears, Dr. Shankar, Dr. Jha, and Dr. Clarke. I am exceptionally grateful for their valuable help
and support throughout this research. Especially, I would like to thank my chair, Dr. Sears, for
his expert pedagogic guidance. His professional approach and highly detailed supervision was
very instrumental in helping me navigate through the challenges encountered during this
research. He is indeed a true scholar that cares a lot about his students.
All the members of my dissertation committee were extremely resourceful in providing
me with highly valuable insights and guidance throughout this research process. Their thorough
readings and thoughtful comments over the course of this research contributed significantly to
the final product of my dissertation. To this, I am forever grateful for their dedication and
guidance.
Thanks also go to my friends and colleagues and the department faculty and staff for
making my time at Texas A&M International University a great experience. Finally, thanks to
my mother and father for their encouragement and to my wife and children for their patience and
love.
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TABLE OF CONTENTS
Page
ABSTRACT……………………………………………………………………………….v
ACKNOWLEDGEMENTS .............................................................................................. vii
TABLE OF CONTENTS ................................................................................................. viii
LIST OF TABLES ............................................................................................................. xi
CHAPTER
I
Introduction: Campaign for Corporate Social Responsibility ...........................1
Antecedents and Recent CSR Proliferation ...............................................1
What is the Value of CSR for firms? ...........................................................2
Why do Firms Pursue CSR? ........................................................................3
The Role of the Golden Parachute ...............................................................8
Dissertation Focus and Contribution .........................................................11
Essay One...................................................................................................13
Essay Two ..................................................................................................14
Summary and Implications of this Dissertation .........................................15
II
Executive Compensation and Corporate Social Responsibility: The Effect
of the Golden Parachute ...................................................................................18
Introduction ................................................................................................18
Literature Review.......................................................................................22
Hypotheses Development ..........................................................................26
Methodology ..............................................................................................35
Main Dependent Variable ..........................................................................37
ix
Main Independent Variable........................................................................38
Control Variables .......................................................................................39
Results and Analysis ..................................................................................40
Endogeniety, Selection Bias, and Reverse Causality.................................50
Disaggregated Measures of CSR ...............................................................53
Conclusion .................................................................................................84
III
Executive Compensation, CSR, and Firm Performance: The Effectuating
Capacity of the Golden Parachute....................................................................86
Introduction ................................................................................................86
Motives Behind CSR Engagements ...........................................................90
CSR, Executive Compensation and Firm Performance .............................93
CSR and Information Asymmetry .............................................................96
Research Design and Hypothesis Development .........................................98
Data Sample .............................................................................................109
Result and Analysis..................................................................................113
Endogeneity Tests ....................................................................................126
Summary and Conclusion ........................................................................130
IV
Summary, Conclusion, and Future Research .................................................135
Essay 1 .....................................................................................................137
Essay 2 .....................................................................................................138
Conclusion and Future Research .............................................................140
REFERENCES ................................................................................................................142
x
APPENDICES
A
Selected Literatures on the Association between CSR and Firm Performance ...156
B
Essay 1 Variables Descriptions............................................................................158
C
Essay 2 Variables Descriptions............................................................................159
D
List of CSR Qualitative Measures .......................................................................160
E
CSR Theories and Definitions .............................................................................161
VITA………… ................................................................................................................162
xi
LIST OF TABLES
Page
Table 2.1: Summary Statistics – Essay 1 ...........................................................................40
Table 2.2: Pairwise Correlation Matrix of All Variables – Essay 1 ..................................42
Table 2.3: Association between Executive Compensation and CSR_NET .......................43
Table 2.4: Association between Executive Compensation and CSRST ............................47
Table 2.5: Association between Executive Compensation and CSRCN ...........................49
Table 2.6: Endogeneity, Selection Bias, and Reverse Causality .......................................51
Table 2.7: Association between Executive Compensation and PROD_NET ....................54
Table 2.8: Association between Executive Compensation and PRODST .........................56
Table 2.9: Association between Executive Compensation and PRODCN ........................57
Table 2.10: Association between Executive Compensation and DIV_NET .....................60
Table 2.11: Association between Executive Compensation and DIVST ..........................62
Table 2.12: Association between Executive Compensation and DIVCN..........................63
Table 2.13: Association between Executive Compensation and ER_NET .......................65
Table 2.14: Association between Executive Compensation and EMPST .........................68
Table 2.15: Association between Executive Compensation and EMPCN ........................69
Table 2.16: Association between Executive Compensation and COMM_NET ................71
Table 2.17: Association between Executive Compensation and COMMST .....................74
Table 2.18: Association between Executive Compensation and COMMCN ....................75
Table 2.19: Association between Executive Compensation and ENV_NET ....................78
Table 2.20: Association between Executive Compensation and EVNST .........................80
xii
LIST OF TABLES
Page
Table 2.21: Association between Executive Compensation and EVNCN ........................82
Table 3.1: Pay-For-Performance Sensitivity ...................................................................104
Table 3.2: Summary Statistics - Essay 2 ..........................................................................114
Table 3.3: Essay 2- Pairwise Correlation Matrix of All Variables ..................................115
Table 3.4: Association between CSR_NET and ROA.....................................................116
Table 3.5: Association between CSRST and ROA..........................................................119
Table 3.6: Association between CSRCN and ROA .........................................................120
Table 3.7: Association between Internal & External CSR Net score and ROA ..............122
Table 3.8: Association between Internal & External CSR Strengths score and ROA.....125
Table 3.9: Association between Internal & External CSR Concerns score and ROA.....126
Table 3.10: Association between CSR_NET and Firm Risk ...........................................128
Table 3.11: Test for Endogeneity.....................................................................................131
1
CHAPTER 1
INTRODUCTION: CAMPAIGN FOR CORPORATE SOCIAL RESPONSIBILITY
1.1
Antecedents and Recent CSR Proliferation
The debate on the roles of corporations in society is ongoing in academia, among
practitioners, and other interested stakeholders. The discussion on corporate rights and
responsibilities continues to persist. Recent corporate accounting scandals of the pre and post
millennia1, increase in environmental pollution cases,2 coupled with the recent financial crisis of
2007, continue to fuel this debate. Gaining increasing speed and attention is the consensus by
different facets of society that corporations have responsibilities toward all stakeholders thus
should be held accountable for their activities and actions that affect all stakeholders (Gössling
2003).
There are divergent views on whether the corporate managers’ duty should focus solely on
maximizing shareholders’ wealth or should all stakeholders’ interests be incorporated in this
duty. Overtime, the latter view has gained prominence and increasing acceptance in both the
public and corporate domains. Marom (2006) posits that firms have been encouraged to
incorporate socially responsible practices in their business operations for both moral and
practical business incentives. Gössling and Vocht (2007) also suggest that business organizations
are expected and obligated to be accountable to the environment and society from which they
extract profit. They argue that the mission of a corporation should be to achieve reasonable
__________
This dissertation follows the format in the Journal of Financial and Quantitative Analysis
1
See: The 10 Worst Accounting Scandals of All Time. (2013, February 7).
2
See: Jowit, J. (2010, February 18).
2
between profit pursuits and societal welfare.
This dissertation is the format in the Journal of Financial and Quantitative Analysis
A firm’s reputation and public image is a critical factor that calls for strategic measures to
ensure positive stakeholders’ view and overall public perception of the firm. Stakeholders’
perceptions can greatly impact the performance and long-term sustainability of the firm (Berman
et al. 1999; Hart 1995a; Russo and Fouts 1997). In pursuit of wealth, more than before, firms are
now expected to incorporate polices that protect, respect and further the interest of the
stakeholders and environment. A measure that captures this societal expectation is Corporate
Social Responsibility (CSR). Frooman (1997) defines CSR as “an action by a firm, which the
firm chooses to take, that substantially affects an identifiable societal stakeholder’s welfare.’’
This encompasses the economic, legal, ethical, and discretionary expectations of the society
(Carroll 1979). Jo and Harjoto (2011) define CSR as how a firm conducts its business operations
to generate an overall positive impact on the society as regards to serving people, community,
and environment, in a manner that exceeds the legal requirement.
1.2
What is the Value of CSR for firms?
Research on how CSR is associated with firm performance is mixed. Some studies show
that CSR is positively associated with firm performance. That is, the greater the firm’s
investment in CSR, the higher the firm’s performance (Barnett and Salomon 2006; Eccles,
Ioannou and Serafeim 2012; Graves and Waddock 1999; Preston and O’bannon 1997; Ruf et al.
2001). Some find negative association (Boyle, Higgins and Rhee 1997; Brammer, Jackson and
Matten 2012; Krueger 2013; Moore 2001; Shane and Spicer 1983; Wright and Ferris 1997).
Others find no association (Aupperle, Carroll and Hatfield 1985; Bauer, Koedijk and Otten 2005;
Guerard Jr 1997)
3
In matching socially responsible mutual funds to conventional funds in the late 1990s,
Bello (2005) finds no significant difference in long-run investment performance or portfolio
diversification between the two groups. These conflicting findings in literature can present a
challenge for firms when evaluating the potential benefit and incentive of pursuing CSR
engagements. Thus, requiring a more assiduous deliberation by corporate executives when
deciding on how or whether resources should be allocated to CSR projects. Despite the
conflicting empirical findings on CSR value-enhancing potential, firms continue to engage in
CSR projects thus inciting a question, for better understanding, as to why do firms indulge in
CSR? Related to this is the question as to how do firms decide on how much resources to devote
to CSR investments? The conflicting findings in some selected studies on the relationship
between CSR and firm performance is tabulated in appendix A.
1.3
Why do Firms Pursue CSR?
In order to better understand the motivations behind firms’ engagements in CSR, studies
that have focused on investigating the association between CSR and CEO compensation have
produced mixed results. In these studies, two opposite arguments have been put forward: (1) the
conflict-resolution theory and, (2) the over-investment hypothesis. The former suggests that
firms use CSR as a tool to maintain good relationships with other stakeholders such as the
employees, suppliers, customers, and the society at large. This theory predicts a negative
association between CSR engagement and CEO compensation. That is, the more a company
engages in CSR, the lower the CEO’s compensation. Consistent with this idea, Cai, Jo and Pan
(2011) find that the lag of CSR adversely affects both CEO’s total compensation and cash
compensation. The results of their analysis shows that an interquartile increase in CSR is
followed by a 4.35% and 2.78% decrease in CEO’s total and cash compensation, respectively.
4
In contrast, the over-investment hypothesis predicts that CSR is used as a tool by CEOs
to enhance their personal goals, image/reputation building, and increased compensation. The key
argument is that greater involvement in CSR will bring visibility to the CEO and improve her/his
chances of building her/his own career. A good reputation can increase the value of the CEO in
the market for corporate labor thus giving him/her a bargaining leverage to negotiate his/her
compensation even higher. This argument predicts a positive association between CEO
compensation and CSR. Consistent with this idea, and, in contrast to Cai, Jo and Pan (2011) ,
Mahoney and Thorn (2006) using lagged CSR data, find a positive relationship between CSR
and CEO compensation. In particular, Mahoney and Thorn (2006) findings support prior studies
that suggest that executive compensation can be an effective tool in aligning executives’ welfare
with that of the “common good” (Bebchuk, Fried and Walker 2002; Zalewski 2003).
Consistent with the overinvestment hypothesis, Barnea and Rubin (2010) find
supporting empirical evidence to suggest that top managers propensity to overinvest is motivated
by a desire to obtain private benefits at the expense of the shareholders. The authors further
narrates that as the overinvesting manager’s reputation begins to improve as a good social
citizen, with time, he or she starts developing overconfidence. A behavior that has been argued in
theoretical literature and proven in empirical studies to cause managers to make valuedestroying investments (Goel and Thakor 2008; Malmendier and Tate 2005). In such case, a
manager that has a proclivity to overinvest for personal gains would constitute a risk to the
shareholders. If there is no efficient system in place to closely monitor the manager, especially
when he or she is insulated from takeovers, the self-serving manager might resort to reckless
self-aggrandizement and self-enrichment to the detriment of the shareholders (Bertrand and
Mullainathan 2003).
5
For the purpose of this research study, it is imperative to note that the relative context of
the term ‘self-serving’ as employed in this research study defines a managerial behavior that is
opportunistic, self-interest, and selfish. This behavior is usually manifested and executed for
private gains at the detriment of the shareholders’ interest. Self-serving, as defined in this
context, could weaken the expected fiduciary duty entrusted upon the manager (agent) by the
shareholders (principals). Managers are expected to comply with the duty of care when engaging
and making business decisions that affect the financial wellbeing and economic interest of the
shareholders. A good manager is one that strives to achieve a balance between personal interest
and shareholders’ interest. A self-serving manager is more concerned in maximizing the former.
Top managers (CEOs) are arguably the most visible employees of the firm. As influential
leaders, the responsibility of consciously promulgating and re-emphasizing the corporate ethical
and social responsibility culture throughout the firm largely rest on their shoulders (Waldman et
al. 2006). Indeed, the success of CSR campaign could greatly depend on the willingness of
corporate managers to engage and promote social responsibilities. Theoretically, the use of CSR
projects in a firm could be grossly limited if the manager is not attuned and receptive to the idea.
Invariably, the manager play an important role in a firm’s CSR engagement, making them
valuable drivers of CSR in corporate settings (Godos-Díez, Fernández-Gago and MartínezCampillo 2011). Argument has been put forward that, occasionally, the manager should be
willing to sacrifice some corporate financial goals, interest and needs in favor of socially
responsible investments (Hunt, Kiecker and Chonko 1990; Quazi 2003; Swanson 2008; Wood,
Chonko and Hunt 1986).
Corporate executives cautiously desire to reduce their compensation and employment
risk by avoiding risky investments with high uncertain payoffs. This might encourage managers
6
to pursue and engage in business activities that reduces the firm’s risk below its relative optimal
level; a risk averseness that might negatively affect the firm’s profit potential (Amihud and Lev
1981; Jensen and Meckling 1976). Managers are expected to meet an earnings target, which can
be quarterly, semi-annually, or annually. In attempt to protect themselves from personal risk
exposures, managers can become reluctant in engaging in projects with high uncertain payoffs
that could negatively affect their ability to meet an earnings target, hence an undesirable
evaluation outcome - an outcome that could result to a reduced compensation or even loss of
employment.
The link between CSR and firm performance remains hazy. Empirical evidence has
produced mixed findings, thus escalating the uncertainty of probable payoffs (Bansal 2005;
Sharma 2000). This uncertainty could increase the manager’s compensation and employment
risk exposure. For instance, a firm’s equipment is functioning efficiently to generate expected
productivity. The manager chooses to invest in new technologically enhanced equipment that
would help reduce or eliminate the firm’s pollution emission. If this initiative succeeds, the firm
benefits from an increased positive reputation. If the initiative fails by causing product quality
problems or other types of unforeseen costs, the manager bears the negative consequences and is
held accountable. The above narrative is an example of a CSR engagement that could increase
the manager’s compensation and employment risk.
From a practical perspective, investors and creditors can always mitigate their risk
exposure through portfolio diversification. In contrast, firms’ executives do not have that option
of diversifying their employment and sources of compensation. Without this, executives are
faced with a risk exposure which they may seek to mitigate. Some of the mitigating channels that
could dampen the exposure of executive’s employment risk include: stock option grants,
7
retirement packages, and golden parachutes. These long-term compensation arrangements can
partially shield the executives from employment risk exposure. The lack of full immunity from
this risk exposure could compel some executives to look elsewhere for additional protection.
In order to mitigate such risk exposure, and further encourage managers to pursue CSR
projects, it is reasonable for firms to strategically insulate managers from certain exposures,
especially if their actions are geared towards a common good like CSR projects. It is therefore
important to examine the effects that a Golden Parachute (GP), a mechanism that insulates
managers from risk of job termination, has on CSR decisions by top managers. Graham, Harvey
and Puri (2013) provide empirical evidence that CEO traits such as risk-aversion and time
preference are related to their compensation. By mitigating the CEO’s risk exposure, a
conscientious CEO might be willing (incentivized) to engage in more value-enhancing CSR
projects without much concern of a probable negative effect on his or her compensation. The
reverse might be the case if the CEO is unconscientious. In this case, the provision of a GP might
provide insulation for the CEO to further pursue his self-interest at the detriment of the interest
of investing and non-investing stakeholders.
Falaschetti (2002) postulates that the GP enhances firm’s efficiency by increasing the
credibility with which owners can commit against opportunism. The incentive hypothesis
suggests that a compensation arrangement like a GP alleviates managerial concern about meeting
short-term profit goals (Narayanan 1985; Stein 1988; Stein 1989). Therefore, by mitigating the
short-term concerns of executives, having a GP could encourage and provide flexibility for
executives to pursue investments that maximize shareholder’s wealth in the long-run. Drawing
from this argument, CSRs have the potential to increase firm value thus improving the
shareholders’ wealth, mostly in the long-run. It could be that the provision of a GP might
8
encourage CEOs to pursue CSR projects, depending on if the CEO is self-interest driven or firminterest driven. A self-interest driven CEO will take actions that benefits his/her private interest,
even if the action is to the detriment of the shareholders. A firm-interest CEO would make
decisions and take those actions that are in the best interest of the firm.
Establishing and maintaining a good reputation could help make an executive attractive
and highly sought after by other firms in the market for corporate labor. By building upon a good
reputation, executives could be rest assured that employment options are steadily available,
especially in the event of a job lost. The executive’s ability to help drive the firm’s financial
performance upwards is also a critical component of the executive’s personal reputation
building.
An executive that steadily helps the firm produce good financial performance for the
shareholders is expected to be highly solicited by other firms. Executives can only ride the wave
of financial performance for as long the firm continues to replicate or exceed the financial
success achieved. But what happens if the firm stops producing exceptional financial
performance? What if the firm is struggling to stay afloat? During periods of ‘not so well’
financial performance, executives could also seek to protect themselves against probable
backlash, a move that could be self-interest driven to the detriment of the shareholders.
1.4
The Role of the Golden Parachute
The controversy surrounding the GP is well documented in the literature. Critics and detractors
of GP frown-upon its advocacy and question its legitimacy. They argue that a GP is only linked
to a change of control of the firm and is executed even when the CEO is terminated due to bad
performance (Ling 2012). It has been argued that the execution of the GP places a hefty cost
burden on the paying firm and directly depletes funds available for business operations (Bebchuk
9
and Fried 2004). Some studies find empirical evidence that seems to suggest that entrenched
managers introduce GP contracts in order to stall or hamper the disciplinary effect of corporate
takeovers (Dann and DeAngelo 1983; Dann and DeAngelo 1988; DeAngelo and DeAngelo
1989; Gompers, Ishii and Metrick 2003; Singh and Harianto 1989; Subramaniam and Daley
2000; Wade, O'Reilly III and Chandratat 1990). In contrast, Machlin, Choe and Miles (1993)
find evidence to suggest that GPs increase the probability of a takeover.
Proponents of the GP argue that it is a necessary competitive recruiting tool for attracting
and retaining talented executives (Frydman and Saks 2010; Rau and Xu 2013; Rosen 1981;
Terviö 2008). Some argue that an antitakeover provision like GP is aimed to align the manager’s
interest with that of the shareholders, thus maximizing firm value, mostly in the event of a
takeover (Baron 1983; Comment and Schwert 1995; Harris 1990; Lambert and Larcker 1985;
Machlin, Choe and Miles 1993; Singh and Harianto 1989; Stein 1988). Jensen (1988) posit that
an efficient and effective implementation of GP can help reduce the conflict of interest between
the shareholders and the managers.
CSR engagements such as improved employee relations, good environmental policy, and
product quality may result in high employee morale, increased productivity, and improved firm
reputation. Consequently, these intangible and tangible benefits could drive the firm value
upwards. This increase in firms’ value reduces the chances of the firm being a target for hostile
takeover. In the event of a takeover, the shareholders should expect to receive a high premium.
Theoretically, a common method of measuring intangible asset is by calculating the firm’s
Tobin’s Q. It has been argued that market-to-book ratio is strongly correlated with Tobin’s Q
(Villalonga 2004).
10
With the presence of a GP, a manager that promotes CSR investments could increase
shareholders’ value in the long run, even while in pursuit of self-interest goals. A manager would
rather maximize his pay in the event of a takeover. In a tender offer, the value-added produced
by CSR should give the executive an advantageous bargaining leverage, thus leading to higher
negotiated premium paid. Which should also maximize the shareholders wealth should the firm
be taken over. Poison pills, GPs, Shark repellents, control shares laws and business combination
laws are forms of antitakeover mechanisms.3 Comment and Schwert (1995) argue that the
presence of an antitakeover mechanism increases the bargaining position of the target firm.
The manager of a firm can play a critical role in initiating and increasing the presence of
CSR projects. Thus, the endorsement by the manager is crucially vital to the acceptance and
practice of CSR in a corporate setting (Hemingway and Maclagan 2004; Quazi 2003; Swanson
2008). For the shareholders, the increase in shareholder value is the core motivation behind their
willingness to invest. Thus, the incentive to pursue CSR investment is expected to stem from a
commercial business imperative. That said, it is safe to assume that shareholders would support
CSR campaign if it increases the firm value.
The uncertainty surrounding the payoffs of CSR investments, as documented in existing
studies, might result to reluctance and decrease in a firm’s willingness to engage in such projects.
Getting the shareholders’ approval might not necessarily be an easy task for the manager. In
promoting CSR, managers should be willing to assume the risk of possible undesirable
outcomes. If the project succeeds, the manager gets rewarded. If it fails, he/she bears the full
3
Poison Pills, Shark Repellent, control shares laws, and business combinations laws – are strategies used to protect
the firm against hostile takeovers. By utilizing shareholders’ right plans, these antitakeover measures provide
procedures, mechanics and key drafting language to fend-off hostile takeovers.
11
consequence. Given this risk exposure, a mechanism like GP should mitigate this risk and reduce
a probable principal-agent conflict by protecting the manager from possible negative
consequences that might arise from ‘doing good’. Thus, the provision of a GP should amplify the
positive association between CSR and firm performance, and mitigate a negative association.
1.5
Dissertation Focus and Contribution
This section discusses the focus and contribution of this research study.
1.5.1 Executive Compensation Structure and CSR
In this study, the association between the structure of CEO compensation package, firm
CSR engagements, and firm performance are examined. In particular, the effect of the GP on
these relationships is closely examined. Investigating the association between the mechanics of
compensation and CSR is important because it may shed light on why results in the literature
have been conflicting. Possibly, it could be that the method of CEO compensation, rather than
the amount, has an effect on CSR. Often, CSR means that firms forgo short-term profits (Kane
2002) for long term gains. Therefore, if the CEO compensation package is structured in a manner
that steers/incentivizes the executive to focus on the long term value of the firm, it may
encourage an increase in value-enhancing CSR projects.
1.5.2 The Importance of a CEO’s Age and Gender
How close the CEO is to retiring might dictate the moderating effect of the GP on the
association between executive compensation and CSR. Coughlan and Schmidt (1985) assert that
the probability of observing a change in a firm’s executive is one turnover in every two cases
when the CEO age is 64 or above, and for younger executives the probability of managerial
turnover is less than one out of every eleven cases. Conyon and Florou (2002) assert that firms
cutback on capital expenditures as the CEO become older.
12
Similarly, the effect of GP on CSR could differ based on whether the firm’s CEO is a
male or female. Male CEOs might be willing to take more risk, and be more aggressive in using
GP for personal gain. It could also be that that the presence of a GP might compel female
executives to be more willing to entertain projects with more uncertain payoffs. Martin,
Nishikawa and Williams (2009) present empirical findings that support the view that the market
perceives female CEOs to be relatively risk-averse. There are empirical evidence to suggest that
men are more risk tolerant than their female counterparts (Barsky et al. 1997), women are more
risk averse than men when it has to do with risk-sensitive financial decision-making (Sapienza,
Zingales and Maestripieri 2009), and female executives are more benevolent but less power
oriented than their male counterparts (Adams and Funk 2012).
1.5.3 Importance of the GP as a measure of CEO Compensation
Similar studies on executive compensation, CSR, and firm performance have mainly
focused on finding a direct relationship. This present study differs from prior studies by
examining an indirect association. That is, we empirically test for the channels through which
CSR could affect firm performance. But first, in essay 1, we examine to see if the provision of
the GP influences managerial decisions on CSR. The unique attribute of the GP that makes it
executable only upon the termination of employment should produce an interesting result that
extends the findings in prior literatures on similar topic.
In most instances, CSR investments are naturally designed to positively yield benefits in
the long run, if any. Firms could benefit by including long-term contingent compensation in the
executive’s pay arrangements in other to focus the CEOs efforts on optimizing the longer term
goals of the firm. Brickley, Bhagat and Lease (1985) find evidence to suggest a positive market
reaction upon the announcement of a long-term managerial compensation packages. Some
13
studies that examined the relationship between CSR and long-term CEO compensation find
positive associations ((Mahapatra 1984; Mahoney and Thorne 2005).
This dissertation extends the literature of CEO compensation, CSR, and firm
performance in the following ways: First, I focus on a special kind of the CEO compensation
mechanism—the golden parachute (GP). This is a severance package arrangement that is
executed in the event that the executive is terminated of her job or forced out of the company. It
is expected that the GP would reduce the corporate managers’ personal losses should corporate
control be transferred to another management team. Thus, a GP may encourage CEO risk taking
- a behavior that could either increase or decrease the firm value.
Second, this study will examine the effect of the presence of a GP on the relationship
between CSR and firm performance. It is predicted that the presence of a GP would amplify the
association between a firm’s CSR engagements and firm performance, positively if CSR
investments are value-enhancing for the firm. It should also be acknowledged that there could be
a negative effect of GP on the relationship between CSR and firm performance if overinvestment
is the case. In all, the GP should illuminate the picture on the relationship between CSR and firm
performance.
1.6
Essay One
The commercial imperative is not the only driver of CSR engagements in a firm. The
significance of the corporate manager’s role in driving CSR initiatives is critical to its outcome.
The personal values of the manager could significantly influence managerial decision on CSR.
The degree of adoption and implementation of CSR by firms is arguably dependent on the
managers’ willingness to occasionally sacrifice corporate objectives, interest, and needs in favor
of pursuing socially responsible investments (Godos-Díez, Fernández-Gago and Martínez-
14
Campillo 2011; Hemingway and Maclagan 2004; Hunt, Kiecker and Chonko 1990; Wood,
Chonko and Hunt 1986). Therefore, the manager’s personal profile is a critical element in
understanding the permeation of socially responsible initiatives and other ethical business
decisions in a corporate setting (Singhapakdi et al. 2008; Waldman et al. 2006). Thus, it is
important to examine any possible motivating triggers or impediments to a CEO’s willingness to
allocate resources and effort toward CSR engagements.
In Essay One, I examine the association between golden parachutes and corporate social
responsibility. Specifically, I explore the effect and association between CSR and a unique
compensation arrangement, the golden parachute; which mitigates the CEO’s employment and
compensation risk. This essay examines whether or not the willingness of the CEO to pursue
socially responsible projects is affected by the presence of a GP. CSR investments are projects
whose benefits and costs are not typically in time alignment; payoffs are also uncertain.
Specifically, this essay attempts to answer the following questions: (1) Does a GP provide
incentive for managers to pursue increased CSR engagements? (2) Is the association between the
GP and CSR affected by the CEO’s age? (3) Is the association between the GP and CSR affected
by the CEO’s gender?
1.7
Essay Two
The second essay will attempt to contribute to the strand of studies that have examined
the association between CSR and firm performance, CSR and executive compensation, and
executive compensation and firm performance. This essay will extend prior studies by examining
how the presence of a golden parachute, a unique type of compensation, impacts the relationship
between CSR and firm performance. This essay will also analyze the impact of golden parachute
on the relationship between CSR and firm risk.
15
Specifically, this essay will provide insights to the following questions: (1) Is the
association between CSR and financial performance affected by whether the CEO has a GP or
not? (2) Does the provision of a GP encourage (discourage) managerial overinvestment in CSR
projects and what impact does this have on firm performance? (3) What types of CSR projects
have the most positive (negative) impact on firm performance and what effect does the provision
a GP have on the firm’s preference in these CSR projects? (4) What impact does the provision of
a GP have on the relationship between CSR, firm risk, and firm performance?
1.8
Summary and Implications of this Dissertation
This section summarizes the purpose of this research study and discusses the findings and
their implications
1.8.1 Essay 1
The association between executive compensation and CSR is explored. This essay
extends previous research on similar topic by examining the moderating effect of the golden
parachute. Given that the largest portion of the GP payments usually come from the accelerated
payments of unvested stock options and other stock units, I argue that CEOs with the GP clause
would behave differently towards CSR from those CEOs without it. If CSR projects are value
enhancing, then the CEO with a GP would promote CSR engagements for as long as it increases
firm financial performance.
Using a large sample of 1301 unique US firms from 1993 to 2013, the findings suggest
that there exists an inverse relationship between current (long-term) compensation and firms’
CSR engagements. While the direct association between the golden parachute and CSR is also
negative, the test for a moderating effect reveals that the GP and long-term compensation jointly
and positively increase firms’ CSR performance. This is consistent with the expectation that
16
executives with a GP clause would desire to maximize their long-term wealth by approving only
value-enhancing CSR projects that positively enhance firm financial performance. Furthermore,
the results also suggest that female executives are more likely than their male counterparts to
promote CSR engagements. Older executives are less willing to engage in CSR even with the GP
clause.
The result of the analysis on the relationship between CF and CSRST alludes to the
possibility that, from previous experience, firms are not convinced that CSR engagements always
increase financial performance. It could be that an overinvestment in CSR erodes the benefits to
the firm, hence the need to reduce investments in CSR strengths to avoid overinvestment. The
findings are robust to model specification, endogeneity and selection bias issues, and sufficient
control variables.
1.8.2 Essay 2
In this essay the association between CSR and firm performance is explored. Previous
studies on similar topic have produced mixed and conflicting findings. Some studies show that
CSR is positively associated with firm performance. That is, the greater the firm’s investment in
CSR, the higher the firm’s performance (Barnett and Salomon 2006; Eccles, Ioannou and
Serafeim 2012; Graves and Waddock 1999; Preston and O’bannon 1997; Ruf et al. 2001). Some
find negative association (Boyle, Higgins and Rhee 1997; Brammer, Jackson and Matten 2012;
Krueger 2013; Moore 2001; Shane and Spicer 1983; Wright and Ferris 1997). Others find no
association (Aupperle, Carroll and Hatfield 1985; Bauer, Koedijk and Otten 2005; Guerard Jr
1997).
The findings in this essay suggest that the association between CSR and firm
performance, ROA, is positive. The test to examine the moderating effect of the GP produced
17
empirical evidence to suggest the GP amplifies the positive association between CSR and ROA.
That is, CEOs that have the GP clause in their executive compensation contract engage in more
value-enhancing CSR projects than their counterparts that do not have the GP clause. This result
supports the hypotheses 1a and 1b which states which predicts a positive association between
CSR and firm performance, and a positive effect of the GP on this association.
The empirical findings in this study support the conflict resolution theory which posits
that top managers could use CSR as effective tool to develop good relations with the employees,
good environmental policy, and good product quality. This could result in high employee morale,
increased productivity, and improved firm reputation. Consequently, these intangible and
tangible benefits could drive the value of the firm upwards, increasing profitability.
The findings in this essay also lend credence to the argument that the uncertainty
surrounding the CSR payoffs could indeed pose a risk to the firm. To empirically test this, I
examined the association between CSR net score and firms’ risk. Risk is defined as the standard
deviation of firms’ earnings scaled to the average total assets. The regression results produced a
positive statistically significant relationship. This finding supports the argument that the
uncertainty surrounding payoffs in the CSR investments could increase the volatility of the
firms’ earnings.
18
CHAPTER 2
EXECUTIVE COMPENSATION AND CORPORATE SOCIAL RESPONSIBILITY: THE
EFFECT OF THE GOLDEN PARACHUTE
1.
Introduction
The literature on executive compensation structures and firm performance has produced a
litany of interesting discussions and debates. An enduring consensus amongst scholars is the
notion that managers (agent) are not inherently unselfish by nature and thus are not innately
faithful stewards to the owners (principal).4 In aligning the interest of the manager with that of
the shareholders, arguments emanating from the quarters of the proponents of incentive based
compensation structures suggest that the mechanics rather than the amount of executive
compensation is most effective in achieving the desired outcome (Acharya, Myers and Rajan
2011; Jensen and Murphy 1990b; Mehran 1995). That is, long-term equity-based compensation
structures rather than cash compensation provide better alignment of the manager and
stakeholders’ interests. It incentivizes the manager to pursue projects that maximizes firm value
in the long-term.
4
See: Blanchard, O. J., F. Lopez-de-Silanes, and A. Shleifer. "What do firms do with cash windfalls?" Journal of Financial
Economics 36 (1994), 337-360.; Jensen, M. C. "Agency costs of free cash flow, corporate finance, and takeovers." The American
economic review (1986), 323-329.; Jensen, M. C. "The Modern Industrial Revolution, Exit, and the Failure of Internal Control
Systems." The Journal of Finance 48 (1993), 831-880.; Morck, R., A. Shleifer, and R. W. Vishny. "Do managerial objectives
drive bad acquisitions?" Ibid.45 (1990), 31-48.; Shleifer, A., and R. W. Vishny. "A survey of corporate governance." The journal
of finance 52 (1997), 737-783.; —. "Management entrenchment: The case of manager-specific investments." Journal of financial
economics 25 (1989), 123-139.
19
The stakeholder theory posits that the purpose of the firm is to create as much value for
its stakeholders as possible. It hinges on the premise that if a firm is to achieve success and
sustainability over time, the interest of the shareholders, employees, suppliers, community, and
environment must be aligned and moving in the same direction. The onus rest upon the shoulders
of the manager to creatively and innovatively identify measures to ensure that these interests are
in alignment rather than resorting to inefficacious strategies of trading-off the interests of the
stakeholders against each other. Thus, the long-term viability and success of the firm is a product
of a continuous conscious effort by the firm’s executives to incorporate the interest of the
stakeholders in its business operations.
The concept of Corporate Social Responsibility (CSR) is grounded in the stakeholder
theory. It has been defined as the actions which a firm chooses to take that substantially
enhances the wellbeing of its stakeholders (Frooman 1997). This encompasses the economic,
legal, ethical, and discretionary expectations of the society (Carroll 1979). Jo and Harjoto (2011)
define CSR as how a firm conducts its business operations to generate an overall positive impact
on the society as regards to serving people, community, and environment, in a manner that
exceeds the legal requirement.
In this study, the efficacy of the structure of executive compensation in encouraging the
corporate manager to promote socially responsible actions that affect the stakeholders is
examined. In particular, the effect of the presence of a special type of executive contractual
clause, golden parachute (GP),5 on managerial behavior regarding CSR is closely examined.
5
The Golden Parachute (GP) refers to the benefit received by a CEO either in the event that a firm is acquired, employment is
terminated, or the CEO remains with the firm through a recessionary cycle Bebchuk, A. Cohen, and C. C. Wang. "Golden
Parachutes and the Wealth of Shareholders." Journal of Corporate Finance 25 (2014a), 140-154, Fich, E. M., A. L. Tran, and R.
A. Walkling. "On the importance of golden parachutes." Journal of Financial and Quantitative Analysis 48 (2013), 1717-1753,
20
Corporate policies that are geared towards promoting social responsibility invariably incorporate
the interests of the stakeholders in its business operations, and are generally long-term focused.
That is, socially responsible firms are occasionally willing to sacrifice short-term profit in favor
of socially responsible actions and long-term prosperity (Hunt, Kiecker and Chonko 1990; Quazi
2003; Swanson 2008; Wood, Chonko and Hunt 1986).
If a firm’s engagements in CSR have the capacity to enhance firm value and produce
sustainable profitability in the longer-term, then it behooves the owners (principal) to use longterm executive compensation structures to incentivize the manager (agent) to engage in CSR
projects. The board of directors, to whom the manager is directly accountable to, is endowed
with a governing capacity to steer the executive’s decision-making towards objectives that
promote the common good of the stakeholders; which ultimately increases firm value and
shareholders’ wealth in the long run.
Previous studies that have explored the association between executive compensation and
CSR focus on the following proxies for compensation: cash compensation (salary and bonus)
and stock options grants. The former is related to short-term compensation, while the latter is
related to long-term compensation. This present study advance these proxies used in prior studies
by introducing the presence of a golden parachute. This study contributes to the existing
literature by examining the effect of the unique nature of a GP on the association between
executive compensation and CSR. Unlike the other forms of executive compensation proxies
which do not necessarily and incontrovertibly guarantee payments to the executives, the GP
Lambert, R. A., and D. F. Larcker. "Golden parachutes, executive decision-making, and shareholder wealth." Journal of
Accounting and Economics 7 (1985), 179-203..
21
guarantees the executive of all payments and entitlements stipulated in the contractual clause,
even in the event of an involuntary job loss.
One of the major contributions of this study to existing literature is that I capture the
relative importance of the GP on the two categorical elements that comprises the executive
composition package: short-term & long-term compensation. That is, I argue that the value of the
compensation package to the executive is proportionately dependent on the insured size of the
long-term compensation (stock options & other long-term incentives) relative to the cash
compensation (salary & bonus), vice-versa. In general, corporate managers desire to maximize
their wealth. If the insured size of the long-term compensation is significantly greater than the
cash compensation, it might induce the executive to favor managerial decisions that are focused
on maximizing long-term value. Kelly and Alam (2008) assert that the landscape of corporate
environment is rapidly changing as firms now seek long-term financial prosperity rather than
short-term profitability.
Value enhancing CSR policies are usually long-term oriented. Therefore, to steer the
executive towards promoting socially responsible projects, the value of the long-term portion of
the executive compensation must be greater than that of the short-term. This should firmly align
the interest of the manager (executive wealth maximization) with that of the shareholders
(shareholders value maximization).
Following previous literature that have examined the associations between executive
compensation and CSR, I adopt three measures of CSR, namely: Net CSR (total strength minus
total concerns), Total CSR Strengths, and Total CSR Concerns (Mahoney and Thorn 2006;
McGuire, Dow and Argheyd 2003). To further extend this methodology, I also run regressions
22
using the different qualitative measures of CSR, respectively. These qualitative social measures
are: Community, Environment, Product, Employee Relations, and Diversity.
The findings suggest that there exist an inverse relationship between current (long-term)
compensation and firms’ CSR performance. While the direct association between the golden
parachute and CSR is also negative, the test for a moderating effect reveals that the GP and longterm compensation jointly and positively increase firms’ CSR performance. This is consistent
with the expectation that executives with a GP clause would desire to maximize their long-term
wealth by approving only value-enhancing CSR projects that positively enhance firm financial
performance. Furthermore, our results also suggest that female executives are more likely than
their male counterparts to promote CSR engagements. Older executives are less willing to
engage in CSR even with the GP clause. Our findings are robust to model specification,
endogeneity and selection bias issues, and sufficient control variables.
The rest of this paper is organized as follows: literature review, hypothesis development,
data & methodology, result & analysis, and summary & conclusion.
2. Literature Review
This sections discusses some of the related literatures on CSR, Golden Parachutes and
Firm Performance
2.1 CSR
The importance and benefits of CSR to a society is arguably vast. To the firm, the
benefits of a positive reputation could be economically rewarding to its shareholders and
valuably beneficial to the welfare of the other stakeholders. When firms are socially responsible,
the benefits extend to the investing and non-investing stakeholders, natural environment, and the
23
society at large. Tsoutsoura (2004) posits that the risk of negative rare events is less likely when
firms are socially responsible.
The importance of CSR cannot be ignored or overemphasized. Samuelson (1971)
acknowledged the increasing indispensability of CSR engagements by corporations when he
posited that “a large corporation these days not only may engage in social responsibility, it had
damn well better try to do so.” Progressively, CSR is becoming a commercial imperative as
firms understand the vital importance of corporate image building and image rebranding. Maron
(2006) posits that corporations have been encouraged to move toward socially responsible
behavior for both moral and practical business incentives. Gossling and Vocht (2007) also
suggest that business organizations are expected and obligated to be accountable to the
environment and society from which they extract profit. The mission of corporations should be
to achieve a reasonable balance between profit pursuits and society building.
2.1.1 CSR and Firm Performance
The value of CSR to a firm and the reason why firms engage in CSR remains a puzzle.
Tsoutsoura (2004) assert that in many cases, the timing of cost and benefits of CSR can be out
of alignment. The costs are immediate while the benefits usually realized later. The empirical
findings in studies that have examined the relationship between CSR and firm performance have
produced mixed and conflicting results. Some find positive association (Barnett and Salomon
2006; Graves and Waddock 1999; Preston 1978; Preston and O’bannon 1997; Ruf et al. 2001),
negative association (Cronqvist et al. 2009; Friedman 2007; Pagano and Volpin 2005; Surroca
and Tribó 2008; Vance 1975), while some find no association (Aupperle, Carroll and Hatfield
1985; Guerard Jr 1997; McWilliams and Siegel 2000; Moore 2001). With these conflicting
24
findings there is need to apply caution and judicious prudence in examining, for better
understanding, the true motives behind firms’ pursuit of CSR.
2.1.2 Why Firms Invest in CSR
Similar to the stakeholder theory of CSR, the conflict-resolution hypotheses suggests that
firms use CSR as tool to maintain good relationship with stakeholders such as employees and the
society at large. The theory predicts a positive association between CSR and firm performance
and negative association between CSR and executive compensation. That is, when the CSR
engagement of the firm goes up the executive compensation goes down thus indicating an
inverse relationship. Turban and Greening (1997) argue that firms that have significant CSR
commitment usually have a competitive advantage and ability to attract and retain highly
talented quality employees.
A prudent executive with a GP clause should be willing to sacrifice some short-term
personal wealth for the firm’s long-term prosperity. When the firm is prosperous in the longerterm, the executive long-term wealth is also maximized. Even in the event of an involuntary job
loss, the value of the stock options and other long-term benefits stipulated in the GP contract is
maximized. The guarantee that all payment will be made should further encourage a
conscientious CEO to promote managerial decisions that enhances the long-term value of the
firm.
It is expected that firms that invest resources towards CSR projects, e.g., improving the
working conditions and labor practices, should record increased employee productivity and
constant improvement of product quality. Studies have found a positive association between
CSR practices and employee morale, resulting in increased productivity (Collier and Esteban
2007; Moskowitz 1972; Stanwick and Stanwick 1998). CSR could positively affect firm value in
25
multiple ways. It could enhance the firm’s reputation and reduce the frequency of investors
explicit claims (McGuire, Alison and Schneeweis 1988), reduce the cost of capital (El Ghoul et
al. 2011) undesirable debt ratio (Bae, Kang and Wang 2011), and increase in
customers(investors) willingness to pay premium prices for socially responsible firms products,
given that good reputation is usually considered as a signal for product quality (Fombrun and
Shanley 1990).
Drawing from the overinvestment hypothesis, argument has been put forward to suggest
that CSR is a vice employed by CEOs to enhance their private gains and further their personal
goals. They burnish their reputations as responsible stewards of industry and good global
citizens at the detriment of the shareholders’ interest (Barnea and Rubin 2010). The key
argument is that greater involvement in CSR will bring visibility to the CEO and improve her/his
chances of building his/her own career. This argument predicts a positive association between
CEO compensation and CSR. Consistent with this idea and in contrast to Cai, Jo and Pan
(2011), Mahoney and Thorn (2006) find a positive association CSR and CEO compensation. An
improved CEO reputation should attract suitors in the market for corporate labor. The executive
might use this increased personal worth and popularity to negotiate a higher compensation from
the firm.
2.2
Golden Parachutes
The controversy surrounding firms’ use of golden parachutes abound. In some quarters,
detractors of this contractual clause in the executive compensation package argue that its
legitimacy is questionable as it is only linked to a change of control and not necessarily a tool to
reward performance (Ling 2012). The underlining attribute of the golden parachute that makes it
executable even in the event of an involuntary job termination due bad performance further
26
exasperates the critics of this type of contractual clause. Past and recent experience shows that
the payment of golden parachute places a hefty cost on the firm (Bebchuk and Fried 2004)
Proponents of the golden parachute argue that it is a necessary competitive recruiting tool
for attracting and retaining talented executives (Frydman and Saks 2010; Rau and Xu 2013;
Rosen 1981; Terviö 2008). Some argue that an antitakeover provision like GP is aimed to align
the manager’s interest with that of the shareholders, thus maximizing firm value, mostly in the
event of a takeover (Baron 1983; Comment and Schwert 1995; Harris 1990; Lambert and
Larcker 1985; Machlin, Choe and Miles 1993; Singh and Harianto 1989; Stein 1988). Jensen
(1988) posit that an efficient and effective implementation of GP can help reduce the conflict of
interest between the shareholders and the managers.
When corporate managers are excessively focused on maximizing their short-term
wealth, they might do so at the detriment of the shareholders long-term value. That is, a desire to
maximize short-term compensation (salary and bonus) by all means could compel the manager to
overinvest in CSR for private gains. Even if doing so jeopardizes the shareholders’ interests. As
the overinvestment hypothesis suggests, by enhancing his reputation as responsible stewards of
industry and good global citizen, the manager is able to build his image and command higher
value (compensation) in the market for corporate labor. With this the manager could negotiate a
higher compensation with the current employer (firm).
3. Hypotheses Development
Scholars have extensively engaged in the explication and investigation of the golden
parachute in an effort to shed more light on the inclusion of this contractual clause in executive
compensation package(Bebchuk, Cohen and Wang 2014b; Brusa, Lee and Shook 2009; Fich,
Tran and Walkling 2013; Jenter and Lewellen 2011; Mansi, Nguyen and Wald 2013). This
27
present study subscribes to the reasoning put forward by the proponents of the golden parachute.
This motivation is anchored on the presumption that executives would want to maximize their
wealth. That is, given that the largest portion of the golden parachute comes from the accelerated
payment of unvested stock options and other stock units,6 it is to the best interest of the executive
to maximize stock price in the long-term; which should positively maximize the premium when
the stock options is exercised. This is based on an assumption that engagements in CSR projects
are positively associated with increase in the stock price, and ultimately the firm value.
In the designing and implementation of corporate objectives (which incorporates the
interest of all stakeholders), the firm (owners) could adopt control mechanisms that fosters
actions that promote socially responsible behaviors and also rewards the executive for promoting
such (Bebchuk, Fried and Walker 2002; Jensen and Murphy 1990a; Lambert and Larcker 1985).
The caveat to this is that the control mechanism should encourage managerial decisions only to
the extent that it increases the shareholders’ value. In the context of this research study,
argument is put forward that the golden parachute should fulfil this purpose. The value of
manager’s golden parachute is maximized when the stock value is maximized.
The golden parachute provides the managers with protection against employment and
compensation risk. Given this insulation, the manager could be more willing to pursue
investments with uncertain immediate payoffs, especially if the socially responsible action is a
common good that aligns the interests of the different stakeholders. It is important to note that
CSR investments are good for the firm only to the extent that it is positively associated with
6
According to Bloomberg, often, the largest portion of severance comes from accelerated payment of unvested stock options and
other stock units that would otherwise not be eligible for a payout – http://www.bloomberg.com/news/2013-06-06/goldenparachutes
28
shareholders’ value. Given this, to rightfully use the insulation of the golden parachute to the
best interest of the shareholders, the manager should invest in CSR projects to the extent that it
positively impacts firm performance.
3.1.1 Current Compensation - Salary and Bonus
In the executive compensation package, salary is the fixed component. Argument has
been put forward in literature to suggest that higher executive salaries are attributable to
managerial hubris (Bliss and Rosen 2001; Brown and Sarma 2007; Datta, Iskandar‐Datta and
Raman 2001). That is, as executive salary rises managerial attention is less focused on
stakeholders’ interest (Berman et al. 1999), and thus managers are less inclined to make
decisions that promotes the interest of the society, especially if such action does not have an
imminent positive effect on the fixed nature of the salary(Mahoney and Thorn 2006).
A distinct characteristic of a ‘bonus’ as a form payment to executives is that it focuses the
manager’s attention on short-term events that increases the payment received. Given that
executive bonus payments are contingent upon short-term financial performance targets, this
could inadvertently infringe upon the firm’s long-term potentials (Healy 1985; Holthausen,
Larcker and Sloan 1995; Lewellen, Loderer and Martin 1987; Stata and Maidique 1980). An
excessive use of bonus to reward executives promotes short-term orientations focused on
meeting and exceeding short-term earnings targets. This could be detrimental to promoting and
achieving corporate goals that are long-term orientated like value-enhancing CSR engagements.
The short-term orientation of current compensation induces the manager to aggressively
seek to maximize their short-term wealth. This could unintendedly produce an undesirable
outcome for the firm. A short-term focused manager, compelled by the strong desire to maximize
short-term personal wealth, may sacrifice long-term shareholders’ value for short-term personal
29
wealth enhancement. A managerial decision could actually increase firm financial performance
in the short-term but be detrimental to shareholders’ long-term value.
Therefore, for the association between current compensation (salary and bonus) and CSR
I put forward the following hypotheses:
H1a:
If the overinvestment (conflict-resolution) hypothesis is true, the association
between current compensation and CSR_NET is positive (negative). The
provision of a GP should jointly have a negative (negative) impact on this
association.
H1b:
If the overinvestment (conflict-resolution) hypothesis is true the association
between current compensation and CSR Strengths is positive (negative). The
provision of a GP should jointly have a negative (positive) impact on this
association
H1c: In the absence of a GP, the association between current compensation and CSR
Concerns is positive. The provision of a GP should mitigate this relationship
3.1.2 Long-term Compensation - Stock Options and other long-term incentives
Long-term equity-based compensation structures rather than cash compensation provide
better alignment of the manager’s interest with that of the stakeholders’. It incentivizes the
manager to pursue projects that maximizes firm value in the long-term. Argument has been put
forward suggesting that stock options are the most typical form of long-term incentive
compensation that are contingent upon the value of stock in the future(Mahoney and Thorn 2006;
Mahoney and Thorne 2005; Murphy and Zabojnik 2004). The logic behind the use of stock
options to align the interest of the manager with that of the shareholders’ is hinged on the
maximization of stock value. That is, by focusing the executive efforts and channeling
managerial decision making towards increasing future stock price, the shareholders’ value
increases and the executive’s wealth also increases.
30
When a firm invests in CSR projects that enhances the wellbeing of the stakeholders, in
the long-term, the capital market will recognize this value and thus this should result in both the
appreciation of the stock price and the maximization of executive gains. The caveat to this is that
if the executive is unexpectedly fired it could automatically terminate the unvested stock option
granted. The golden parachute eliminates this concern for the executives. Usually, the
stipulations in the executive compensation clause guarantees the executive accelerated payments
of all stock options in the event that employment is discontinued.
In order to capture the effect of the amount of stock options in the total executive
compensation, I subtract the total current compensation (Salary plus Bonus)7 from the total
executive compensation. This should account for the long-term executive compensation portion
of the total compensation. Stock options makeup for the largest part of the executive long-term
compensation Thus, I put forward the following hypotheses:
7
H2a:
In the absence of a GP, the association between executive long-term
compensation (i.e.., stock options, long-term Incentive Payouts etc.) and CSR-Net
is negative. The provision of a GP should mitigate this relationship.
H2b:
There is a positive association between executive long-term compensation (i.e..,
stock options, long-term Incentive Payouts etc.) and CSR-Strengths. When
probable likelihood of overinvestment (conflict-resolution) is observed, the
provision of a GP should mitigate this relationship.
H2c:
There is a negative association between executive long-term compensation (i.e..,
stock options, long-term Incentive Payouts etc.) and CSR-Concerns. The presence
of a GP should further strengthen this relationship.
Execucomp database defines Total current compensation as: Salary plus Bonus. Total compensation is the sum of
current and long-term executive compensation. It is calculated as: Salary + Bonus + Other Annual + Total Value of
Restricted Stock Granted + Total Value of Stock Options Granted (using Black-Scholes) + Long-Term Incentive
Payouts + Other Total.
31
𝐶𝑆𝑅𝑖𝑡 = 𝛼𝑖𝑡 + 𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + ∑𝑛𝛽=1 𝛼𝑋𝑖𝑡 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
(2.1)
Equation (1) represents the hypothesized relationships between CSR, Current and Longterm compensation, and the moderating effect of the GP. Where CSR represents the three
measures of social responsibility: CSR-Net, CSR-Strengths, and CSR-Concerns, respectively.
CCP2 is the one-year lag of current compensation. LCP2 is the one-year lag of long-term
compensation. GP is an indicator variable that is equal to 1 if the firm’s CEO has golden
parachutes and 0 otherwise, X is the set of control variables, and ε is the error term. The unit of
analysis is firm-year; i represent a firm, and t represent the year of the observation. The control
variables will be largely based on (Cai, Jo and Pan 2011). These controls variables include: firm
size (LogSales), Debt ratio, firm age (RETE), capital expenditure (CAPEX), and cash flow.
These variables are defined in Appendix B.
3.1.3
Does a CEO’s age play a role?
For older executives, their shorter time horizon might reduce the incentive to pursue
investments that might negatively impact their earnings targets in the short run, thus reducing
their compensation. In related evidence, Adams and Ferreira (2009) find that chief executive
officer turnover is more sensitive to stock performance in the short-run. Coughlan and Schmidt
(1985) posit that the probability of observing a change in a firm’s executive is one turnover in
every two cases when the CEO age is 64 or above, and for younger executives the probability of
managerial turnover is less than one out of every eleven cases. Conyon and Florou (2002) assert
that firms cutback on capital expenditures as the CEO become older. This evidence suggests that
older executives are more short term oriented. That is, they are more focused on how their
decisions affect their immediate wealth, given that that long-term objectives might not be
practical for them as their employment risk is higher.
32
I argue that the sensitivity of older CEOs to earnings targets is high, thus reducing the
incentive to invest in projects that are long-term oriented, like CSR engagements. Consequently,
I predict that older CEOs should be less motivated to invest in CSR. On the other hand, if the
CEO has attained substantial tenure with the firm, then he or she might seek to protect the value
of his golden parachute by promoting CSR that positively enhances the stock value. Therefore, I
propose the following hypotheses:
H3a:
There is a negative association between CEO’s age and CSR-Net.
H3b:
There is a positive association between CEO’s age and CSR-Net when the CEO
has achieved substantial tenure.
H3c:
There is a positive association between CEO’s age and CSR-Net when the CEO
has a GP clause
H3d:
There is a negative association between CEO’s age and CSR-Strengths.
H3e:
There is a positive association between CEO’s age and CSR-Strengths when the
CEO has achieved substantial tenure.
H3f: There is a positive association between CEO’s age and CSR-Strengths when the
CEO has a GP clause
H3g:
There is a negative association between CEO’s age and CSR-Concerns when the
CEO has achieved substantial tenure. The presence of a GP should further
strengthen this relationship
𝐶𝑆𝑅𝑖𝑡 =
𝛼𝑖𝑡 + 𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝑔𝑒2𝑖𝑡 + 𝛽7 𝐴𝑔𝑒2𝑖𝑡 ∗
𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽10 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 +
∑𝑛𝛽=1 𝛼𝑋𝑖𝑡 + 𝜀𝑖𝑡
(2.2)
Where CEO age takes the value of 1 if the CEO is ≥ 64 and 0 if < 64. Tenure1 captures
the CEO’s longevity in service.
33
3.1.4 Does a CEO’s gender matter?
Another variable that could impact the relationships between CSR and GP is the gender
of the CEO.8 Studies have shown that men and women differ in risk aversion thus making gender
a factor in highly competitive corporate business settings (Bowles, Babcock and Lai 2007;
Niederle and Vesterlund 2007; Sapienza, Zingales and Maestripieri 2009). There are empirical
evidence to suggest that men are more risk tolerant than their female counterparts (Barsky et al.
1997), women are more risk averse than men when it has to do with risk-sensitive financial
decision-making (Sapienza, Zingales and Maestripieri 2009), and female executives are more
benevolent but less power oriented than their male counterparts (Adams and Funk 2012).
The argument that male executives have greater propensity than their female counterpart
to exhibit relative overconfidence suggests that female executives have better proclivity to
promote more value-enhancing projects (Huang and Kisgen 2013). If aligning the interests of all
stakeholders through CSR engagements fosters a better future financial prospective for the firm
then I expect the CEO with a greater penchant for identifying value-enhancing projects to
promote more CSR. Conversely, the CEO with the greater proclivity to exhibit relative
overconfidence would likely not make much effort in promoting CSR projects. Smith, Smith and
Verner (2006) show that the proportion of women in top management jobs in a company tends to
have positive effects on firm performance.
Martin, Nishikawa and Williams (2009), in observing declining changes in risk following
appointment of female CEOs, presents empirical findings that support the view that the market
8Huang,
J., and D. J. Kisgen. "Gender and corporate finance: Are male executives overconfident relative to female executives?"
Journal of Financial Economics 108 (2013), 822-839. posit that the number of female top executives in the U.S. has increased
significantly. Among major U.S. corporations in 2005, 7.5% of Chief Financial Officers (CFOs) and 1.5% of CEOs were women,
versus 3.0% and 0.5% in 1994, respectively.
34
perceives female CEOs to be more risk-averse than their male counterparts. The authors find
evidence to suggest that firms with relatively high risk (total risk and idiosyncratic risk) are more
likely to appoint female CEO’s. Empirical evidence in literature supporting the notion that
gender does play a role in corporate executive decision-making is gaining attention, even in the
international domains. Campbell and Minguez-Vera (2008) find a positive relationship between
gender diversity in the corporate board and firm performance in the Spanish market. Liu, Wei
and Xie (2013) provide empirical evidence to suggest that there is significant relationship
between board gender diversity and firm performance in Chinese corporate market. In their study
of China’s listed firms, Liu et al further argue that boards with at least three female directors
show stronger impact on firm performance.
Drawing from the literature on the importance of gender in corporate settings, for female
executives, the provision of a GP, as an insulation mechanism, should have a greater effect on
the willingness to pursue value-enhancing CSR projects. With the pressure to meet earnings
targets, the concern for personal compensation risk exposure should be higher for female
executives. Conversely, the effect of an insulating mechanism, like a GP, against such concern
should have greater effect on female executives. Thus, I propose the following hypothesis:
H4a: There is a positive association between CEO gender and CSR-Net. The presence
of a GP should further strengthen this relationship.
H4b: There is a positive association between CEO gender and CSR-Strengths. The
presence of a GP should further strengthen this relationship.
H4c: There is a negative association between CEO gender and CSR-Concerns.
𝐶𝑆𝑅𝑖𝑡 = 𝛼𝑖𝑡 + 𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
𝛽6 𝐴𝑔𝑒2𝑖𝑡 + 𝛽7 𝐴𝑔𝑒2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅_𝐹𝑖𝑡 + 𝛽11 𝐺𝑃 ∗
𝐺𝐸𝑁𝐷𝐸𝑅_𝐹𝑖𝑡 + ∑𝑛𝛽=1 𝛼𝑋𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 𝜀𝑖𝑡
(2.3)
35
Where GENDER_F is a dummy variable that takes the value of 1 if the CEO is a female
and 0 if the CEO is a male.
4.
Methodology
This study adopts comparable analysis commonly used in similar studies on executives’
compensation and corporate social responsibility; however, I extend prior studies in multiple
ways. Frist, I closely examine the effect of a special kind of contractual clause (golden
parachute) in the executive compensation package on managerial decisions on social responsible
policies. Second, by interacting golden parachute and a measure of long-term compensation, I
examine the efficacy of long-term compensation structures in aligning the interest of the
manager and with that of the stakeholders.
CSR engagements such as improved employee relations, good environmental policy, and
product quality may result in high employee morale, increased productivity, and improved firm
reputation. Consequently, these intangible and tangible benefits could drive the firm value
upwards. By engaging in socially responsibly projects a firm could enhance its employees’
motivation and morale, which should improve productivity and product quality. Berk, Stanton
and Zechner (2010) postulates that employees that develop good relationship with the firm may
accept low compensation when working for good reputation firms. All these factors should
positively enhance the value of the firm, which should enhance the value of the executive stock
options in the golden parachute.
4.1.1 Data and Sample
For the purpose of this study, the data employed were extracted from the following
sources: MSCI ESG STATS (formerly Kinder, Lydenberg, Domini Research & Analytics, Inc)
for CSR measures, Risk Metrics (formerly known as IRRC) for golden parachute and
36
governance measures, COMPUSTAT for financial and accounting measures, and EXECUCOMP
for compensation variables.
Founded in 1988, for over two decades, Kinder, Lydenberg, Domini Research &
Analytics Inc (KLD) has been providing benchmarks, analysis, research, compliance, and
consulting services related to social, governance, and environmental practices. KLD is a leading
authority and data provider of social research for institutional investors.9 Considered as the
standard for CSR measures, the KLD data has been extensively adopted by numerous scholars
and research studies (Deng, Kang and Low 2013; Di Giuli and Kostovetsky 2014; Jiao 2010;
Nelling and Webb 2009; Waddock and Graves 1997).
It is important to note that, in their earlier publication, KLD data covered S&P 500
companies. To broaden its coverage, in 2003 KLD began following and analyzing the social
performance of Russell 3000 companies. The methods of assessment encompass thirteen
different CSR dimensions. These dimensions are further classified into two key categories,
qualitative and controversial business issues areas: The qualitative issue areas consist of seven
indicators, namely: community, diversity, employee relations, environment, product
characteristics, human rights, and corporate governance. While the controversial issues areas
consist of six indicators, namely: firearms, alcohol, gambling, tobacco, military, and nuclear
power. For the qualitative areas, a binary scoring system (0/1) is used to assign points for every
strength (positive) and concern (negative). This is similarly same for the controversial areas
except that it only rates concerns. Assigning negative ratings with a binary system for whether a
firm is involved in one or more concerns.
9
In 2009, KLD was acquired by RiskMetrics, and is now a subsidiary of MSCI, a leading provider of indices and institutional
products and services.
37
4.2
Main Dependent Variable
The dependent variables employed in this research study are CSR_Net, CSR total
strengths and CSR total concerns.
4.2.1 CSR_Net
I generate a total CSR score (CSR_Net) by summing-up the net scores for 5 different
CSR qualitative areas, namely: community, environment, employee relations, product
characteristics and diversity. For each of the qualitative areas I generate a score by subtracting
the number of concerns from the number of strengths. I then obtained a total CSR score (CSRNet) by adding-up all the qualitative scores. The method of deriving CSR-Net is widely used in
similar studies (El Ghoul et al. 2011; Goss and Roberts 2011; Harjoto and Jo 2011).
4.2.2 Other measures of CSR
It has been argued that an inherit weakness of the CSR-Net is that CSR strengths and
CSR concerns can potentially offset each which could likely obscure the true nature of a firm’s
social performance(Graves and Waddock 1994; Mahoney and Thorn 2006). Thus, in order to
navigate around this purported inherent weakness, I follow the conventional method in existing
literature that have examined the associations between executive compensation and CSR by
adopting three measures of CSR, namely: Net CSR (total strength minus total concerns), Total
CSR Strengths, and Total CSR concerns (Mahoney & Thorn, 2006; J. McGuire, Dow, &
Argheyd, 2003). The last two measures attempt to navigate around the inherit weakness of the
former.
To further extend this methodology, I also run regressions substituting the dependent
variable with the different qualitative measures of CSR: Community, environment, Product,
38
Employee Relations, and Diversity. The first two measures are concerned with external socially
responsible actions, while the last three are concerned with internal socially responsible actions.
4.3
Main Independent Variable
This section describes the main independent variables employed in this research studies.
4.3.1 Executive compensation
The changes in the mix of executives within a particular firm during the sample time
period could present a potential confounding challenge in the analysis. Therefore, I delete those
firms with missing data, CEO changes within a given year, and firms with significant changes in
ownership. I divide the executive compensation into two groups: short-term and long-term. I
adopt two proxies for executive compensation: Cash Compensation (Salary plus Bonus) and
Long-term Compensation (Options Grants plus Long-term Incentive Payout). The former is
concerned with short-term compensation while the latter captures long-term compensation.
If the size of the cash compensation is significantly greater than the long-term
compensation, it might induce the executive to favor managerial decisions that are focused on
maximizing short-term value. CSR policies are usually long-term oriented. Therefore, to steer
the executive towards promoting socially responsible projects, the value of the long-term portion
of the executive compensation must be greater than that of the short-term.
4.3.2 Executive Age & Tenure
A dummy variable10 that represents executives whose ages are below 64 (0) and above 64
(1) is created. I go a step further by controlling for the CEO’s tenure. The rationale being that an
10
Murphy, K. J. "Executive compensation." Handbook of labor economics 3 (1999), 2485-2563. provide evidence to suggest that
the probability of a CEO leaving office during a given year is nearly 30 percent higher when the CEO is over age 64 than when
he is younger (e.g., see Murphy, 1999)
39
executive that has attained substantial longevity within a firm would desire to protect his or her
legacy and vested-interest that has accumulated over the course of years of service. Therefore,
older CEOs with substantial tenure should be less short-term focused than older CEOs with less
service longevity.
4:3:2 Executive Gender
For the executive’s gender, I construct a dummy variable of 0 or 1 in which zero
indicates that the CEO is female and one indicates that the executive is a male.
4.4
Control Variables
Consistent with prior studies in corporate finance on similar topic, I control for firm size
(LogSize), leverage, capital expenditures (CAPEX), performance (CF), and firm age (RETE).
Size and profitability are viewed as important economic determinants linked to executive
compensation levels (Core, Holthausen and Larcker 1999; Cuñat, Gine and Guadalupe 2013;
Mehran 1995) and could significantly influence a firm’s capacity to invest in CSR (Greening and
Turban 2000; McWilliams and Siegel 2000; Nelling and Webb 2009). Size is measured as the
natural logarithm of total sales. Cash flow (CF) on equity is used to measure profitability.
Leverage is computed as the average debt to equity ratio.
I capture firm’s age using a life-cycle proxy: ratio of retained earnings to book value of
common equity. According to the life cycle hypothesis, the early stages of a firm’s life cycle
present more growth opportunities. The firm, at this stage, usually has limited access and ability
to generate sufficient internal capital to finance its projects. Access to external funding can also
present its own challenges thus the need for firms at this stage of their life-cycle to avoid
injudicious allocation of scarce resources. After a period of growth, the firm matures as it
40
becomes older, larger and with higher retained earnings. At this stage, the cash (free cash flow)
internally generated is usually higher than can be profitable reinvested.
5.
Results and Analysis
5.1.1 Descriptive Statistics and Correlation Analysis
In tables 2.1 & 2.2, on pages 40 and 41, the summary statistics and correlation matrix are
presented. After merging all five databases and deleting missing variables, including financial
and utility firms, our final sample size shrunk to 1309 observations. The CSR-NET score ranges
between -9 to 18. The long-term compensation (LCP2) variable is slightly larger in size than the
current compensation (CCP2). The pairwise correlation matrix of all variables employed shows
that none of the variables are highly collinear, and such pass the first stage multi-collinearity test.
Table 2.1
Summary Statistics – Essay 1
Variables
Observations
Mean
Std. Dev.
Min
Max
CSR_NET
13295
0.0596465
2.955078
-9
18
CCP2
13295
6.815712
0.8448956
0
11.26353
LCP2
13295
7.490115
1.787419
0
12.84026
GP
13295
0.6628808
0.4727438
0
1
LogSize
13295
7.808722
1.512499
3.13105
13.05458
Debt
13295
0.209471
0.1718257
0
2.925137
CAPEX
13295
0.0536958
0.0537544
0
0.5578874
CF
13295
0.138683
0.090174
-1.690588
1.090199
RETE
13295
0.6568006
0.558565
1.859288
AGE2
13295
0.0939451
0.2917633
0.5717035
0
1
Tenure1
13295
10.12846
7.917997
0
61.05
GENDER_F
13295
0.0313652
0.1743092
0
1
CSRST
13295
2.200602
3.007613
0
22
CSRCN
13295
2.140955
2.098805
0
16
41
Table 2.1 (Cont.)
Summary Statistics – Essay 1
The dependent variables are CSR_NET, CSRT, and CSRCN. CSR_NET is defined as total CSR strengths minus total CSR
concerns. CSRT is the total number of strengths for the qualitative measures of CSR, while CSRCN is the total number of concerns.
CCP2 is the total executive current compensation for the day, defined by ExecuComp database as bonus plus salary. LCP2 is the
long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the ratio of total debt to
common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life
cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a
dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the
CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable
that takes the value of 1 if the firm has a GP and 0 if otherwise
5.1.2 Regression Analysis
Table 2.3 on page 43 presents the main regressions in 6 models. All the regressions are
controlled for both industry and year fixed effects. The first model is the result of the regression
that does not include the GP. CSR-NET is regressed on lagged current compensation (CCP2) and
the control variables of interest. The results suggest that CCP2 is inversely associated with CSRNET, and the relationship is statistically significant at the 10% level. That is, as the CEO salary
and bonus payments increase the firm’s CSR performance decreases. This result supports the
conflict resolution theory.
Argument can also be put forward to suggest that, for the sample used in this study, the
outcome of the previous year CSR effect on firm performance, as captured in the lagged term,
most likely influenced the managerial decision on CSR projects in the current term. If CSR
engagements in the previous period positively enhanced firm performance then this effect should
also reflect positively on the CEO’s current compensation, as bonuses are awarded based on
meeting or exceeding predetermined earnings target.
Table 2.2
Pairwise Correlation Matrix of All Variables – Essay 1
CSR_NET
CCP2
LCP2
GP
LogSize
Debt
CAPEX
CF
RETE
AGE2
Tenure1
GENDER_F
CSRST
CSR_NET
1.0000
CCP2
0.0507*
1.0000
LCP2
0.0682*
0.3515*
1.0000
GP
-0.0106
0.0092
0.0880*
1.0000
LogSize
0.2169*
0.3499*
0.3076*
-0.0583*
1.0000
Debt
-0.0048
0.1564*
0.1349*
0.0586*
0.2219*
1.0000
CAPEX
-0.0475*
0.0137
-0.0084
-0.0777*
0.0023
0.0353*
1.0000
CF
0.0680*
0.0102
0.0054
-0.0311*
0.0605*
-0.1381*
0.2280*
1.0000
RETE
0.1118*
0.1169*
0.0161
-0.0402*
0.2619*
0.0318*
0.0088
0.2416*
AGE2
-0.0470*
-0.0229*
-0.0578*
-0.0844*
-0.0701*
-0.0493*
-0.0319*
-0.0178*
-0.0019
1.0000
Tenure1
-0.0722*
-0.0175*
-0.1018*
-0.1644*
-0.1392*
-0.0696*
0.0240*
0.0195*
-0.0227*
0.2992*
1.0000
GENDER_F
0.1036*
0.0109
0.0037
0.0172*
0.0103
-0.0139
-0.0128
-0.0061
-0.0019
-0.0476*
-0.0874*
1.0000
CSRST
0.7523*
0.1954*
0.1958*
-0.0521*
0.5655*
0.0769*
-0.0386*
0.0240*
0.1606*
-0.0691*
-0.1346*
0.0928*
1.0000
-0.3297*
0.2085*
0.1846*
-0.0596*
0.5050*
0.1170*
0.0116
-0.0614*
0.0727*
-0.0328*
-0.0912*
-0.0128
0.3740*
CSRCN
CSRCN
1.0000
1.0000
The dependent variables are CSR_NET, CSRT, and CSRCN. CSR_NET is defined as total CSR strengths minus total CSR concerns. CSRT is the total s numbers of strengths for
the qualitative measures of CSR, while CSRCN is the total number of concerns. CCP2 is the lagged value of the total executive current compensation for the year, defined by
ExecuComp database as bonus plus salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is
the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle proxy used to
capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is
<64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a
dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise
42
43
Table 2.3
Association between Executive Compensation and CSR_NET
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
CSR_NET
Model 2
CSR_NET
Model 3
CSR_NET
-0.05661*
(-1.7637)
0.53931***
(23.0989)
0.62131***
(-4.4598)
4.11636***
(7.9286)
0.52498*
(1.9381)
0.30550***
(6.0094)
-0.00473*
(-1.7682)
1.45932***
(8.6570)
0.37400***
(-4.9555)
-0.05249
(-1.6297)
0.53529***
(23.0738)
0.57851***
(-4.1514)
4.02188***
(7.7363)
0.53662**
(1.9765)
0.30148***
(5.9339)
-0.00554*
(-1.7226)
1.46188***
(8.6846)
0.36796***
(-3.0047)
0.17523***
(-3.1135)
-0.00142
(-0.2418)
-0.08771*
(-1.8628)
0.53620***
(23.0758)
0.57057***
(-4.0955)
3.98926***
(7.6813)
0.56075**
(2.0655)
0.29725***
(5.8595)
-0.00524
(-1.6254)
2.09355***
(7.2706)
-0.08845
(-0.5129)
-0.53029
(-1.2663)
-0.00508
(-0.8297)
0.06167
(0.9926)
-0.88097**
(-2.5333)
-0.38876**
(-2.5455)
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
Model 4
CSR_NET
Model 5
CSR_NET
Model 6
CSR_NET
0.53986***
(22.9010)
0.62013***
(-4.4425)
4.11524***
(7.9233)
0.53777**
(1.9863)
0.29851***
(5.8571)
-0.00509*
(-1.9008)
1.45559***
(8.6384)
0.37737***
(-4.9968)
0.53524***
(22.8739)
0.57967***
(-4.1525)
4.02337***
(7.7367)
0.54759**
(2.0180)
0.29547***
(5.8018)
-0.00572*
(-1.7798)
1.45859***
(8.6677)
0.36441***
(-2.9750)
0.17132***
(-3.0369)
-0.00182
(-0.3097)
0.53658***
(22.9813)
0.56669***
(-4.0585)
3.99066***
(7.6848)
0.57461**
(2.1198)
0.29011***
(5.7052)
-0.00581*
(-1.8058)
2.07694***
(7.2222)
-0.09886
(-0.5739)
0.61916***
(-3.3209)
-0.00543
(-0.8845)
-0.02705**
(-2.1037)
-0.02332*
(-1.8070)
13,295
0.2043
13,295
0.2049
-0.86724**
(-2.4965)
-0.36937**
(-2.4168)
0.06162***
(-3.2198)
0.06879***
(2.7306)
13,295
0.2062
LCP2_GP
Observations
R-squared
13,295
0.2043
13,295
0.2050
13,295
0.2059
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variables are CSR_NET, CSRT, and CSRCN. CSR_NET is
defined as total CSR strengths minus total CSR concerns. CCP2 is the lagged value of total executive current compensation for the year, defined
by ExecuComp database as bonus plus salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the
total executive compensation. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets,
CF is measure of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of
common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive
has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that
takes the value of 1 if the firm has a GP and 0 if otherwise.
44
Table 2.3 (Cont.)
Association between Executive Compensation and CSR_NET
VARIABLES
Model 1
CSR_NET
Model 2
CSR_NET
Model 3
CSR_NET
Model 4
CSR_NET
Model 5
CSR_NET
Model 6
CSR_NET
I present the results of the following regression model. All the regression models were controlled for industry and year fixed effects:
𝐶𝑆𝑅𝑖𝑡 =α+𝛽1𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗
𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
The negative association could mean that the firm’s CSR investments did not positively increase
firm financial performance in the period.
The results on the association between the size of the firm (LogSize), Debt, capital
expenditure (CAPEX), cash-flow (CF), and firm age (RETE) support the findings in previous
studies on similar topic that suggest these variables affects a firm’s CSR performance. The
directionality of these associations is also in congruence with the findings in previous studies.
Larger firms have bigger financial capacity to pursue CSR engagements. The debt ratio of the
firm determines its flexibility to allocate financial resources to CSR projects. The higher the debt
ratio the more restriction the firm has on how to allocate financial resources. In particular, the
financial institutions that grant these loans to firms serve as monitoring mechanisms that ensure
that these funds are applied to those areas and projects specified in the loan contracts. A
departure from this might trigger a violation on debt covenants.
In line with previous studies, a firm’s capital expenditure positively affects its CSR
performance. That is, as the capital expenditure increases the firm’s willingness to allocate
resources to CSR engagements also increases. The CF variable is also positively associated with
CSR-NET. The higher the firm’s cash-flow the more funds available to commit to CSR projects.
45
This result is significant at the 10% and 5% levels but the strength of this significance increases
with the presence of the GP, as shown in the second model.
As discussed earlier, after a period of growth, a firm matures as it becomes older, larger
and with higher retained earnings. At this stage, the cash (free cash flow) internally generated is
usually higher than can be profitable reinvested. The result in our analysis support previous
studies that posit that older firms are more likely to invest in CSR projects due to their flexible
financial capacity.
The result on the association between the CEO age and CSR performance shows an
inverse relationship. That is, CEOs that are 64years or older invest less in CSR projects. The
association between CEO tenure and CSR performance is also negative. The regression results
also suggest that firms invest more in CSR projects when the CEO is a female.
The second model in table 2.3 includes the GP and an interaction term between CEO age
and tenure. The rationale behind the latter is that if the CEO has attained substantial tenure with
the firm, then he or she would seek to protect the value of his golden parachute by promoting
those CSR engagements that positively increase the stock value, and thus the value of the GP.
Our results suggest that GP is negatively associated with CSR. This pose a question whether
CSR projects truly always enhances firm financial performance.
If CSR engagements has unlimited capacity to positively increase firm’s financial
performance, then why should the GP whose value largely consist of accelerated unvested stock
options and other stock units negatively affect CSR? This could be an indication that CSR does
not necessarily have an unlimited effect on firm’s financial performance, especially when shortterm compensation (salary & bonus) is the bone of contention. GP is long-term focused and thus
should align the interest of the manager with that of the shareholders in the long-term. It could be
46
that the short-term orientation of current compensation is in conflict with the long-term
orientation of the GP.
In the third model in table 2.3, the interaction terms between GP and lag current
compensation (CCP2), GP and CEO gender (GENDER_F), and GP and CEO’s age (AGE2) are
included in the regression. The interaction between GP and CCP2 is not significant and thus
suggesting that GP and current compensation do not jointly affect CSR-NET. The interaction
between GP and GENDER_F is negative. This result suggest that for female executives that have
the GP, their willingness to pursue CSR projects is lower compared to female executives that do
not have the GP clause.
The fourth to sixth models in table 2.3 substitutes CCP2 with lag long-term compensation
(LCP2). The directionality of the association between the control variables and other variables of
interest remains unchanged, except for the interaction term between GP and LCP2 in model 6.
As predicted in our hypothesis, the presence of the GP reverses the association of LCP2 on
CSR_NET. In the model 4, the beta coefficient of LCP2 is -0.02705 while in model 6 the beta
coefficient is -0.06162. The coefficient of the interacted term between GP and LCP2 is 0.06879.
This means that for firms’ that give their CEOs, the association between LCP2 and CSR_NET is
0.06879. While for those firms that do not give their CEOs GP, the association between LCP2
and CSR_NET is -0.06162. A joint significance test validates that GP and LCP2 are jointly
associated with firms’ CSR performance. The joint association beta coefficient is 0.00735. It is
important to note this coefficient is substantially low suggesting that, perhaps, CEO’s with a GP
cautiously invest in CSR projects only to the extent that it enhances firm financial performance.
In tables 2.4 and 2.5 on pages 47 and 49, CSR strengths (CSRST) and concerns (CSRCN)
for CSR-NET are substituted for the dependent variables, respectively. The results in table 2.4
47
are quite revealing. The test for the association between CCP2 and CSRST is negative but not
statistically significant. This association is positive but not statistically significant for the
interacted term, CCP2_GP. On the other hand, in model 6 of table 2.4, the interaction between
LCP2 and GP is positive and significant at the 5percent level. This result indicates that for those
firms in which the CEO’s has a GP clause, the association between long-term compensation and
CSRST is positive with a coefficient of 0.02193 = -0.03369 + 0.05562. This finding is in support
of our hypothesis that CEOs with a GP would promote CSR engagements for as long as it
enhances firm financial performance and the CEO’s long-term wealth.
Another interesting finding in table 2.4 is the negative association between cash-flow and
CSRT. One could infer that investments in CSR projects do not always increase firm financial
performance. If it is assumed that the more profitable a firm is the more CSR projects it pursues.
Then, it should be expected that a firm would want to repeat that which has produced financial
success in its operations in the recent past. If a firm’s CSR investment in in prior period does not
enhance financial value in the prior period, the firm might decide to reduce CSR
Table 2.4
Association between Executive Compensation and CSRST
VARIABLES
CCP2
LogSize
Debt
CAPEX
Model 1
CSRST
Model 2
CSRST
Model 3
CSRST
Model 4
CSRST
Model 5
CSRST
Model 6
CSRST
-0.00268
(-0.0965)
1.26123***
(60.8909)
0.98256***
(-8.1668)
2.29097***
(5.5048)
0.00534
(0.1917)
1.25283***
(61.0543)
0.89730***
(-7.4760)
2.11078***
(5.0922)
-0.00211
(-0.0521)
1.25401***
(61.0077)
0.88566***
(-7.3775)
2.07525***
(5.0179)
1.26474***
(59.9753)
0.97655***
(-8.1009)
2.28671***
(5.4937)
1.25476***
(60.1395)
0.89441***
(-7.4373)
2.10918***
(5.0883)
1.25585***
(60.2956)
0.87963***
(-7.3168)
2.07342***
(5.0125)
48
Table 2.4 (Cont.)
Association between Executive Compensation and CSRST
VARIABLES
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
CSRST
Model 2
CSRST
Model 3
CSRST
Model 4
CSRST
Model 5
CSRST
Model 6
CSRST
0.96906***
(-4.0331)
0.19662***
(4.4631)
0.00910***
(-3.9615)
1.16656***
(7.0121)
0.23294***
(-3.6354)
0.94279***
(-3.9100)
0.18757***
(4.2742)
0.01211***
(-4.3128)
1.16902***
(7.0555)
0.29761***
(-2.8480)
0.34294***
(-7.1268)
0.00225
(0.4548)
0.91844***
(-3.8124)
0.18304***
(4.1830)
0.01172***
(-4.1684)
1.95095***
(6.4520)
-0.10821
(-0.7667)
-0.35691
(-0.9863)
-0.00021
(-0.0405)
0.01064
(0.1978)
1.09240***
(-3.0749)
-0.26202**
(-2.0750)
0.96666***
(-4.0238)
0.19486***
(4.4043)
0.00921***
(-4.0046)
1.16630***
(7.0112)
0.23420***
(-3.6553)
0.94311***
(-3.9101)
0.18746***
(4.2528)
0.01211***
(-4.3128)
1.16933***
(7.0567)
0.29725***
(-2.8447)
0.34164***
(-7.0912)
0.00222
(0.4477)
0.91932***
(-3.8162)
0.18161***
(4.1324)
0.01220***
(-4.3449)
1.94809***
(6.4275)
-0.12159
(-0.8632)
0.69835***
(-4.1507)
-0.00013
(-0.0262)
-0.01039
(-0.9048)
-0.00256
(-0.2232)
13,295
0.4254
13,295
0.4277
1.09117***
(-3.0666)
-0.24368*
(-1.9317)
-0.03369*
(-1.8975)
0.05562**
(2.4570)
13,295
0.4288
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.4253
13,295
0.4277
13,295
0.4286
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variables are CSR_NET, CSRT, and CSRCN. CSR_NET is
defined as total CSR strengths minus total CSR concerns. CSRT is the total number of strengths for the qualitative measures of CSR, while CSRCN
is the total number of concerns. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as
bonus plus salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation.
Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow,
RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a
dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm.
GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm
has a GP and 0 if otherwise. I present the results of the following regression model: 𝐶𝑆𝑅𝑆𝑇𝑖𝑡 =α+𝛽1𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
However, our result on the relationship between CF and CSRST alludes to the possibility
that, from previous experience, firms are not convinced that CSR engagements always increase
49
financial performance. It could be that an overinvestment in CSR erodes the benefits to the firm,
hence the need to reduce investments in CSR strengths to avoid overinvestment. Interestingly, in
Table 2.5 both CCP2 and LCP2 have positive associations with CSR concerns (CSRCN). The
positive associations are statistically significant across both boards. However, the magnitude of
this effect is stronger for current compensation (CCP2). Suggesting that greater emphasis on
current compensation (salary and bonus) increases CSR concerns more than long-term
compensation does.
Table 2.5
Association between Executive Compensation and CSRCN
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
GP
AGE2_Tenure1
CCP2_GP
Model 1
CSRCN
Model 2
CSRCN
Model 3
CSRCN
0.05393***
(3.0619)
0.72192***
(49.7538)
0.36125***
(-4.0982)
1.82539***
(-5.4094)
1.49404***
(-8.9960)
0.10888***
(-3.7578)
0.00438***
(-2.6472)
0.29276***
(-3.8014)
0.14106***
(3.0396)
0.05783***
(3.2845)
0.71754***
(50.0284)
0.31879***
(-3.6168)
1.91110***
(-5.6712)
1.47942***
(-8.9150)
0.11392***
(-3.9330)
0.00657***
(-3.2934)
0.29285***
(-3.8116)
0.07035
(0.9459)
0.16771***
(-4.7825)
0.00367
(1.0447)
0.08560***
(2.9100)
0.71780***
(49.9755)
0.31509***
(-3.5780)
1.91401***
(-5.6834)
1.47918***
(-8.8952)
0.11422***
(-3.9460)
0.00649***
(-3.2381)
-0.14260
(-0.8693)
-0.01977
(-0.1878)
0.17338
(0.7080)
0.00488
(1.3189)
-0.05104
Model 4
CSRCN
Model 5
CSRCN
Model 6
CSRCN
0.72488***
(49.7966)
0.35643***
(-4.0390)
1.82853***
(-5.4146)
1.50443***
(-9.0180)
0.10365***
(-3.5671)
-0.00412**
(-2.4893)
0.28929***
(-3.7575)
0.14317***
(3.0796)
0.71952***
(50.0681)
0.31474***
(-3.5689)
1.91419***
(-5.6764)
1.49070***
(-8.9370)
0.10800***
(-3.7183)
0.00639***
(-3.2020)
0.28926***
(-3.7670)
0.06717
(0.9030)
0.17032***
(-4.8382)
0.00403
(1.1455)
0.71927***
(50.0902)
0.31294***
(-3.5484)
1.91724***
(-5.6865)
1.49393***
(-8.9426)
0.10850***
(-3.7370)
0.00638***
(-3.1873)
-0.12886
(-0.7882)
-0.02273
(-0.2158)
-0.07918
(-0.7085)
0.00530
(1.4308)
50
Table 2.5 (Cont.)
Association between Executive Compensation and CSRCN
VARIABLES
Model 1
CSRCN
Model 2
CSRCN
GENDERGP_F
Model 3
CSRCN
Model 4
CSRCN
Model 5
CSRCN
-0.21143
(-1.1646)
(1.3432)
LCP2
0.01666**
(2.2771)
0.02076***
(2.8221)
13,295
0.4495
13,295
0.4507
LCP2_GP
Observations
R-squared
13,295
0.4497
13,295
0.4509
13,295
0.4511
Model 6
CSRCN
-0.22393
(-1.2366)
(1.3280)
0.02792**
(2.4145)
-0.01317
(-0.8606)
13,295
0.4509
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variables are CSR_NET, CSRT, and CSRCN. CSR_NET is
defined as total CSR strengths minus total CSR concerns. CSRT is the total number of strengths for the qualitative measures of CSR, while CSRCN
is the total number of concerns. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as
bonus plus salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation.
Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow,
RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a
dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm.
GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm
has a GP and 0 if otherwise. I present the results of the following regression model: 𝐶𝑆𝑅𝐶𝑁𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
5.3
Endogeneity, Selection Bias, and Reverse Causality
In this section I perform an instrumental variable (IV) and two-stage least squares for
panel data, specifically, utilizing the industry and year Fixed Effects (FE). Using SATA, the
assumption is to first declare all the data as panel data. The instrumental variable regression for
panel data is employed in table 2.6 on page 51. Similar to other instrumental variables testing, I
assume that one of the right-hand side variables covariates is endogenous. Specifically, I suspect
that our main independent variable, executive compensation, is correlated with the error and thee
could also be a simultaneous causality bias. The IV test should control for such biases and
similar econometric shortcomings.
51
The panel regression results in Table 2.3 allows for only industry and time varying
covariates, by treating all variables as exogenous, except for the interaction terms. However, it is
possible that the error terms in the regression may be highly correlated. As such, in table 2.6, by
performing two-stage least square estimators, I test that our main independent variables – CCP2,
LCP2, and GP – are rightly specified. In so doing, I estimate two models. First, I model that
Interlock is a function of (CCP, CCP2_GP, LogSize, Debt, CAPEX, CF, RETE, Tenure1,
GENDER_F). Second, I model that lagged CSR_NET is also a function of the (CCP, CCP2_GP,
LogSize, Debt, CAPEX, CF, RETE, Tenure1, GENDER_F).
Table 2.6
Essay 1: Test for Endogeneity, Selection Bias, and
Reverse Causality
VARIABLES
CSR_NET
CSR_NET
CSR_NET.L1
0.0454
(0.0307)*
-6.5350
(3.0192)*
-0.0993
(0.0521)*
0.0452
-0.0662
0.5451
(0.0199)***
-0.6273
(0.1704)***
4.1507
(0.6685)***
0.7434
(0.3314)*
0.3423
(0.0539)*
0.0552
(0.03264)*
-8.8915
(3.7102)*
INTERLOCK
CCP2
CCP2_GP
LogSize
Debt
CAPEX
CF
RETE
0.5462
(0.02053)***
-0.6589
(0.17715)***
4.3396
(0.70920)***
0.8554
(0.35358)*
0.3467
(0.05631)***
52
Table 2.6 (Cont.)
Essay 1: Test for Endogeneity, Selection Bias, and
Reverse Causality
VARIABLES
CSR_NET
CSR_NET
Tenure1
0.0026
(0.0074)
1.9658
(0.2743)***
-0.2491
(0.46217)*
-0.0071
-0.0059
-0.6954
(0.3219)*
-0.3130
(0.14289)*
0.0063
-0.0086
1.9386
(0.28300)***
-0.7914
(0.28196)**
-0.0099
-0.0065
-0.6891
(0.33192)*
-0.2544
(0.15259)*
-0.1033
(0.03143)**
0.1131
(0.03541)**
-3.8707
(0.24563)***
YES
YES
GENDER_F
GP
AGE2_Tenure1
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
_cons
INDUSTRY FIXED EFFECT
YEAR FIXED EFFECT
-3.9301
(0.35917)***
YES
YES
The dependent variables are CSR_NET, CSRT, and CSRCN. CSR_NET is defined as total CSR strengths minus total CSR
concerns. CSRT is the total number of strengths for the qualitative measures of CSR, while CSRCN is the total number of concerns.
CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus
salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive
compensation. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total
assets, CF is measure of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained
earnings to book value of common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64.
Tenure measures how long the executive has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a
female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise
The independent variables in these regressions are either declared the difference or lag
variables of the original. The difference estimates the change in each independent variable from
53
previous period, whereas, the lag is only used for dummy variables or those variables interacted
with dummy variables.
The instrumental variable, INTERLOCK, is defined as a dummy variable that takes the
value of 1 if the CEO is named to the compensation committee and 0 if otherwise. The choice of
INTERLOCK as a good instrumental is based on its inherit ability to directly influence the
CEO’s compensation but no directly impact CSR. It is also not correlated with the error term as
reported in STATA. Thus, it serves the purpose of a good instrument to test and control for
possible endogineity and omitted variable bias issues.
As expected, the instrumental variables regression show that the results reported earlier
does not suffer from endogeneity, selection bias, or reverse causality. The directionality for each
variable remains the same. Our concerned variables are statistically significant, and the Fstatistics which test against the null hypothesis that all are zero is valid is also strongly
statistically significant.
5.4
Disaggregated Measures of CSR
This section presents regression results in which the different qualitative measures of
CSR are substituted for the dependent variable, respectively. These qualitative social measures
are: Product quality and safety, Diversity, Employee Relations, Community, and Environment.
Table 2.7 presents the regression models in which the net score of product quality and safety
(PROD_NET) is the dependent variable. In the CCP2 model 3, the results show an insignificant
inverse association between compensation measures and PROD_NET. The interacted term
between GP and CCP2 suggest that GP and CCP2 jointly and positively increase PROD_NET.
This result is statistically significant at the 1% level with beta coefficient of 0.04229. The
GENDER_F and GP interacted term also suggest a joint positive significance at the 5% level
54
Table 2.7
Association between Executive Compensation and PROD_NET
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
PROD_NET
Model 2
PROD_NET
Model 3
PROD_NET
-0.01046
(-1.3799)
0.13458***
(-25.2672)
0.06554*
(1.9562)
0.51414***
(4.2775)
0.39282***
(5.5382)
0.03093***
(2.7024)
0.00095
(1.5181)
0.20226***
(6.7060)
0.02754
(1.5770)
-0.01048
(-1.3816)
0.13458***
(-25.3781)
0.06539*
(1.9496)
0.51472***
(4.2719)
0.39288***
(5.5375)
0.03091***
(2.6942)
0.00090
(1.1822)
0.20217***
(6.7013)
0.02505
(0.8810)
0.00079
(0.0599)
0.00017
(0.1308)
0.01345
(1.1215)
0.13420***
(-25.3953)
0.06483*
(1.9343)
0.51753***
(4.2887)
0.39650***
(5.5837)
0.03171***
(2.7659)
0.00109
(1.4208)
0.10685**
(2.1745)
0.05298
(1.2821)
0.28954***
(2.9441)
-0.00027
(-0.1937)
0.04229***
(-2.8710)
0.13243**
(2.2035)
-0.03820
(-1.0661)
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
Model 4
PROD_NET
Model 5
PROD_NET
Model 6
PROD_NET
0.13451***
(-25.2119)
0.06571**
(1.9635)
0.51397***
(4.2775)
0.39517***
(5.5643)
0.02965***
(2.5832)
0.00088
(1.4092)
0.20157***
(6.6911)
0.02692
(1.5409)
0.13447***
(-25.3231)
0.06533*
(1.9499)
0.51493***
(4.2755)
0.39512***
(5.5627)
0.02966***
(2.5795)
0.00087
(1.1342)
0.20151***
(6.6876)
0.02580
(0.9083)
0.00167
(0.1271)
0.00008
(0.0646)
0.13444***
(-25.3223)
0.06377*
(1.9036)
0.51770***
(4.2936)
0.39532***
(5.5561)
0.03020***
(2.6265)
0.00091
(1.1782)
0.10801**
(2.1975)
0.05146
(1.2474)
0.01335
(0.2975)
-0.00028
(-0.2033)
-0.00493
(-1.6094)
-0.00496
(-1.6151)
13,295
0.2281
13,295
0.2281
0.13091**
(2.1812)
-0.03589
(-1.0016)
-0.00400
(-0.8252)
-0.00157
(-0.2578)
13,295
0.2284
LCP2_GP
Observations
R-squared
13,295
0.2281
13,295
0.2281
13,295
0.2290
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; the dependent variables are PROD_NET. Which is defined as total Product
strengths minus total Product concerns. PRODST is the total number of product strengths, while PRODCN is the total number of product concerns.
CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus salary. LCP2 is the
lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the ratio of total debt
to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle proxy
used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that represents
the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F is dummy variable
that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise.
55
with a coefficient of 0.13243. This suggest that female CEOs with a GP clause promote more
product quality and safety that those without the GP clause.
Unlike the pooled regression where CSR_NET is the dependent variable, in these
regressions the association between firm size and PROD_NET are all inversely significant at the
1% level. This suggests that the larger the firm the lower the PROD_NET score. This result does
not necessary avow that larger firms do not engage in CSR projects compared to smaller firms. It
could be that the sheer size of the firm’s operations increases the challenge of product quality
management. It is much easier to monitor and manage the products and operations of a smaller
firm that it is for a bigger firm. The lager firm might actually be investing a lot of resources to
CSR in this area, but the amount of concerns outweighs the amount of resources (strengths)
invested. For these firms, the management should consider increasing efforts in reducing the
amount of product quality and safety concerns.
The relationships between long-term compensation (LCP2) are insignificant. Firm size
(LogSize) retains its inverse association. GENDER_F and GP jointly and positively increase
product quality and safety score at the 5% significance level with a beta coefficient of 0.13091.
This is higher than the female CEOs without the GP clause. Firm age (RETE), capital
expenditure (CAPEX), and leverage (Debt) are all positively associated with the net score of
product quality and safety.
Tables 2.8 and 2.9 on pages 56 and 57 presents the regression models substituting
Product Quality and Safety strengths (PRODST) for PROD_NET. In table 2.8 the results shows
that CCP2 and GP jointly reduce firms PRODST score by a negligible amount. The beta
coefficient for this joint inverse association is -0.001. LCP2 also reduces PRODST by similar
magnitude. Female CEOs promote high product quality and safety. Larger firms invest more
56
resources in PRODST. Firm age (RETE) and capital expenditure (CAPEX) are both positively
associated with product quality and safety. Our results also suggest that longer the CEO tenure
the less investment he or she allocates to PRODST.
Table 2.9 regression results suggest that CCP2 is positively associated with product
concerns (PRODCN). That is, as the CEO’s salary and bonus increases the firm’s product
concerns score also increases. However, this is not true for LCP2. The associating between LCP2
and PRODCN is negative but not significant. Overall, the results in this table show that GP
decreases PRODCN. This is evident in the interacted terms between GENDER_F and GP for
both CCP2 and LCP2. In both instances, female executives with a GP clause reduces product
quality and safety concerns. Our results also shows that CEO’s that are 64years and above
exercise significant effort in the reductions of PRODCN.
Table 2.8
Association between Executive Compensation and PRODST
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
Model 1
PRODST
Model 2
PRODST
Model 3
PRODST
Model 4
PRODST
Model 5
PRODST
Model 6
PRODST
0.00104
(1.1726)
0.01217***
(20.0489)
-0.00089
(-0.2288)
0.07343***
(5.5063)
0.00149
(0.1765)
0.00811***
(5.9889)
0.00047***
(-5.8835)
0.00118
(1.3237)
0.01203***
(19.9662)
0.00059
(0.1502)
0.07016***
(5.2793)
0.00189
(0.2237)
0.00797***
(5.8989)
0.00050***
(-5.2296)
0.00381***
(3.0512)
0.01209***
(20.0439)
0.00084
(0.2145)
0.06972***
(5.2506)
0.00261
(0.3088)
0.00795***
(5.8888)
0.00048***
(-4.9404)
0.01278***
(20.7792)
0.00015
(0.0392)
0.07270***
(5.4484)
0.00158
(0.1868)
0.00798***
(5.8724)
0.00048***
(-6.0034)
0.01263***
(20.7073)
0.00148
(0.3790)
0.06968***
(5.2414)
0.00189
(0.2242)
0.00788***
(5.8118)
0.00050***
(-5.2462)
0.01265***
(20.7342)
0.00164
(0.4208)
0.06922***
(5.2102)
0.00222
(0.2628)
0.00782***
(5.7591)
0.00050***
(-5.1991)
57
Table 2.8 (Cont.)
Association between Executive Compensation and PRODST
VARIABLES
AGE2
Model 1
PRODST
Model 2
PRODST
Model 3
PRODST
Model 4
PRODST
Model 5
PRODST
Model 6
PRODST
(3.1016)
0.00187
(0.8126)
(3.1307)
0.00212
(0.5386)
0.00605***
(-3.6523)
-0.00005
(-0.2992)
(2.4913)
0.00526
(0.9590)
0.02708**
(2.3356)
-0.00010
(-0.5277)
0.00473***
(-2.7406)
-0.01321
(-1.2720)
-0.00426
(-0.9314)
(3.1166)
0.00173
(0.7540)
(3.1478)
0.00226
(0.5752)
0.00561***
(-3.3761)
-0.00007
(-0.3843)
(2.5376)
0.00487
(0.8887)
-0.00715
(-1.1832)
-0.00010
(-0.5474)
0.00113***
(-2.8137)
-0.00101**
(-2.4902)
13,295
0.1126
13,295
0.1134
-0.01384
(-1.3269)
-0.00361
(-0.7899)
-0.00119*
(-1.8741)
0.00031
(0.3901)
13,295
0.1137
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.1121
13,295
0.1131
13,295
0.1139
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is PRODST. which is defined as total Product strengths.
CSRT is the total s numbers of strengths for the qualitative measures of CSR, while CSRCN is the total number of concerns. Both CSRT and
CSRCN are divided, respectively, by the total compensation to obtain a ratio between 0 and 1. CCP2 is the lagged total executive current
compensation for the year, defined by ExecuComp database as bonus plus salary. LCP2 is the lagged long-term elements (stock options & longterm incentives) of the total executive compensation. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures
scaled to total assets, CF is measure of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings
to book value of common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long
the executive has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy
variable that takes the value of 1 if the firm has a GP and 0 if otherwise. I present the results of the following regression model:
𝑃𝑅𝑂𝐷𝑆𝑇𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 +
𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
Table 2.9
Association between Executive Compensation and PRODCN
VARIABLES
CCP2
Model 1
PRODCN
Model 2
PRODCN
Model 3
PRODCN
0.00326**
0.00343**
-0.00020
Model 4
PRODCN
Model 5
PRODCN
Model 6
PRODCN
58
Table 2.9 (Cont.)
Association between Executive Compensation and PRODCN
VARIABLES
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
PRODCN
Model 2
PRODCN
Model 3
PRODCN
Model 4
PRODCN
Model 5
PRODCN
Model 6
PRODCN
0.04811***
(39.8839)
-0.01363*
(-1.9103)
-0.05538**
(-2.0786)
0.09692***
(-6.3433)
0.00182
(0.7579)
0.00070***
(-5.3017)
0.03502***
(-5.4733)
-0.00677*
(-1.8916)
0.04797***
(40.1020)
-0.01198*
(-1.6778)
-0.05920**
(-2.2150)
0.09655***
(-6.3248)
0.00169
(0.7019)
0.00070***
(-4.2899)
0.03486***
(-5.4590)
-0.00474
(-0.8244)
-0.00689**
(-2.3751)
-0.00017
(-0.6407)
0.04794***
(40.1276)
-0.01160
(-1.6246)
-0.06042**
(-2.2569)
0.09662***
(-6.3200)
0.00147
(0.6082)
0.00072***
(-4.4007)
-0.00159
(-0.1191)
-0.00642
(-0.7835)
-0.04898**
(-2.4597)
-0.00014
(-0.4872)
0.00633**
(2.1041)
0.04637***
(-3.1298)
0.00229
(0.3115)
0.04869***
(40.1739)
-0.01265*
(-1.7723)
-0.05605**
(-2.1043)
0.09734***
(-6.3679)
0.00198
(0.8188)
0.00069***
(-5.2580)
0.03482***
(-5.4415)
-0.00677*
(-1.8877)
0.04853***
(40.3877)
-0.01110
(-1.5544)
-0.05972**
(-2.2347)
0.09703***
(-6.3528)
0.00188
(0.7773)
0.00069***
(-4.2489)
0.03465***
(-5.4267)
-0.00476
(-0.8287)
-0.00665**
(-2.2907)
-0.00017
(-0.6254)
0.04854***
(40.4171)
-0.01052
(-1.4721)
-0.06094**
(-2.2769)
0.09662***
(-6.3152)
0.00167
(0.6885)
0.00070***
(-4.2744)
-0.00144
(-0.1074)
-0.00653
(-0.7957)
-0.01494
(-1.5942)
-0.00014
(-0.4958)
-0.00004
(-0.0620)
0.00010
(0.1536)
13,295
0.3588
13,295
0.3591
0.04652***
(-3.1429)
0.00251
(0.3409)
-0.00062
(-0.6017)
0.00126
(0.9706)
13,295
0.3597
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.3591
13,295
0.3594
13,295
0.3601
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; the dependent variable is PRODCN. Which is defined as total Product concerns.
CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus salary. LCP2 is the
lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the ratio of total debt
to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle proxy
used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that represents
the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F is dummy variable
that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise. I
present the results of the following regression model: 𝑃𝑅𝑂𝐷𝐶𝑁𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 +
𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
59
In table 2.10 the net score of the diversity (DIV_NET) CSR measure is substituted for the
dependent variable. The results of the regression analysis suggest that both CCP2 and LCP2 are
positively associated with increase firms’ diversity social performance. CCP2 is positively
significant at the 5% level, while LCP2 is positively significant at 1% level. The level of
significance is stronger for long-term executive compensation. The interacted terms between GP
and the compensation measures are statistically insignificant. CEOs that are 64years and above
do not necessary promote diversity in the workplace. This negative association is also observed
for CEOs that have achieved substantive longevity with the firm.
Female executives strongly encourage diversity social projects. The regression analysis
shows that the association between female CEOs and DIV_NET is positively statistically
significant at 1% level for both CCP2 and LCP2. The interaction terms between GP and
GENDER_F suggest that female executives with a GP clause promote less diversity that those
with a GP clause. To be specific, the beta coefficient of GENDER_F without the GP is
approximately 2.10 while the coefficient for the joint association between GENDER_F and GP is
approximately 1.00, for both current compensation and short-term compensation. This could be
as a result of an effort by the manager with a GP trying to invest in diversity social projects only
to the extent that it does not negatively affect firm financial performance, which could ultimately
decrease the value of the GP.
Firm size, CAPEX, and RETE are all positively statistically significant. These regression
results hold for both the current compensation and long-term compensation models. However,
the firm’s debt ratio and cash flow measures are negatively associated DIV_NET. These results
are all statistically significant at the 1% level for both the short-term and long-term compensation
60
models. The behavior of the control variables employed are consistent with prior research studies
on similar topics
Table 2.10
Association between Executive Compensation and DIV_NET
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
DIV_NET
Model 2
DIV_NET
Model 3
DIV_NET
0.03411**
(2.3733)
0.50170***
(54.8278)
0.27215***
(-4.2097)
0.37660*
(1.6570)
0.49679***
(-3.6095)
0.05664***
(2.6347)
0.00687***
(-5.5817)
1.11263***
(15.0237)
0.10302***
(-3.0282)
0.03334**
(2.3170)
0.50220***
(54.8794)
0.27926***
(-4.3226)
0.39575*
(1.7401)
0.49740***
(-3.6152)
0.05685***
(2.6417)
0.00734***
(-5.0016)
1.11106***
(14.9949)
-0.13718**
(-2.4420)
0.03174
(1.3325)
0.00243
(0.8829)
0.02996
(1.4350)
0.50252***
(54.8999)
0.27520***
(-4.2588)
0.38413*
(1.6910)
0.49063***
(-3.5670)
0.05530**
(2.5706)
0.00725***
(-4.9194)
1.38278***
(10.2582)
-0.09507
(-1.2868)
0.01479
(0.0811)
0.00190
(0.6725)
0.00496
(0.1851)
-0.37964**
(-2.3894)
-0.05811
(-0.8664)
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
Model 4
DIV_NET
Model 5
DIV_NET
Model 6
DIV_NET
0.49751***
(54.5824)
0.27946***
(-4.3223)
0.38194*
(1.6831)
0.50649***
(-3.6694)
0.06243***
(2.8910)
0.00655***
(-5.3236)
1.11498***
(15.0368)
0.09976***
(-2.9318)
0.49785***
(54.5881)
0.28481***
(-4.4083)
0.39808*
(1.7531)
0.50619***
(-3.6689)
0.06230***
(2.8821)
0.00719***
(-4.8971)
1.11322***
(15.0058)
-0.14107**
(-2.5141)
0.02542
(1.0641)
0.00286
(1.0430)
0.49809***
(54.5991)
0.28174***
(-4.3565)
0.38655*
(1.7044)
0.49832***
(-3.6127)
0.06112***
(2.8272)
0.00692***
(-4.7030)
1.38807***
(10.2948)
-0.09288
(-1.2572)
0.16310**
(2.0291)
0.00226
(0.8032)
0.02639***
(4.7581)
0.02601***
(4.6649)
13,295
0.4047
13,295
0.4048
-0.38335**
(-2.4112)
-0.06616
(-0.9855)
0.03504***
(4.2945)
-0.01613
(-1.5071)
13,295
0.4053
LCP2_GP
Observations
R-squared
13,295
0.4042
13,295
0.4043
13,295
0.4047
61
Table 2.10 (Cont.)
Association between Executive Compensation and DIV_NET
VARIABLES
Model 1
DIV_NET
Model 2
DIV_NET
Model 3
DIV_NET
Model 4
DIV_NET
Model 5
DIV_NET
Model 6
DIV_NET
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is DIV_NET which is defined as total Diversity strengths
minus total Diversity concerns. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as
bonus plus salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation.
Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow,
RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a
dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm.
GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm
has a GP and 0 if otherwise. I present the results of the following regression model: 𝐷𝐼𝑉_𝑁𝐸𝑇𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 +
𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
Tables 2.11 and 2.12 on pages 62 and 63 present the regression models substituting
Diversity Strengths (DIVST) for DIV_NET are presented. In table 2.11 the results shows that
both CCP2 and LCP2 are positively associated with DIVST. However, this positive association
is stronger for LCP2 with a statistical significance at the 1% level compared to the %5 level for
CCP2. The interacted terms between GP and the compensation variables are both negative but
not statistically significant. The GP is however stronger and positively associated with DIVST.
The association holds for both CCP2 and LCP2 at a statistical significance level of 1%.
Female executives have strong affinity for diversity oriented social projects. However,
female executives with the GP clause promote lesser DIVST than those without a GP clause. The
beta coefficient for female executives without a GP is approximately 0.11 for both CCP2 and
LCP2 while the beta coefficient for those with a GP is on average 0.09. The interacted term
between CCP2 and GP is negative but not statistically significant. This is also true for the
interacted term between LCP2 and GP.
Table 2.12 regression results suggest that LCP2 is negatively associated with diversity
concerns (DIVCN). That is, as the CEO’s long-term compensation increases the firm’s diversity
62
concerns score decreases. Overall, the results in this table show that GP decreases DIVCN. The
association between GENDER_F is also negative for in both the CCP2 and LCP2 regression
models. These regression results are statistically significant at the 1% level. Our regression
results also shows that firms’ diversity concerns are more likely when the CEO’s is 64years or
older. This result is statistically significant at the 1% level.
Firm size, debt ratio, and firm age are all inversely associated with firms’ diversity
concerns. This is true for both the CCP2 and LCP2 models. The CEO tenure is positively
associated with DIVCN. That is, the longer the CEO tenure the greater the likelihood of
observed diversity concerns. These regression results are all statistically significant at the 1%
level. All the regression models are controlled for both industry fixed effects and year fixed
effects.
Table 2.11
Association between Executive Compensation and DIVST
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
Model 1
DIVST
Model 2
DIVST
Model 3
DIVST
Model 4
DIVST
Model 5
DIVST
Model 6
DIVST
0.00307**
(2.0973)
0.05412***
(55.4459)
0.04585***
(-6.8465)
0.06792***
(3.0364)
0.05444***
(-3.7190)
0.00258
(1.1496)
0.00043***
(-3.5792)
0.00323**
(2.2065)
0.05392***
(55.4157)
0.04405***
(-6.5860)
0.06446***
(2.8817)
0.05376***
(-3.6666)
0.00234
(1.0436)
0.00055***
(-3.7531)
0.00363
(1.6257)
0.05396***
(55.4509)
0.04354***
(-6.5145)
0.06321***
(2.8314)
0.05310***
(-3.6213)
0.00217
(0.9711)
0.00054***
(-3.6623)
0.05389***
(55.2961)
0.04624***
(-6.9042)
0.06821***
(3.0516)
0.05524***
(-3.7655)
0.00303
(1.3475)
0.00041***
(-3.3735)
0.05364***
(55.1895)
0.04439***
(-6.6373)
0.06458***
(2.8898)
0.05455***
(-3.7123)
0.00282
(1.2497)
0.00054***
(-3.6613)
0.05366***
(55.2163)
0.04401***
(-6.5810)
0.06334***
(2.8394)
0.05389***
(-3.6653)
0.00268
(1.1892)
0.00052***
(-3.4943)
63
Table 2.11 (Cont.)
Association between Executive Compensation and DIVST
VARIABLES
AGE2
Model 1
DIVST
Model 2
DIVST
Model 3
DIVST
Model 4
DIVST
Model 5
DIVST
Model 6
DIVST
(11.9070)
-0.00198
(-0.5841)
(11.9059)
-0.00657
(-1.2048)
0.00696***
(-2.8129)
0.00026
(1.0021)
(9.0118)
-0.00523
(-0.7148)
0.00046
(0.0244)
0.00025
(0.9275)
-0.00087
(-0.3144)
-0.04441**
(-2.3745)
-0.00177
(-0.2651)
(11.9113)
-0.00173
(-0.5117)
(11.9093)
-0.00689
(-1.2654)
0.00745***
(-2.9986)
0.00030
(1.1431)
(9.0569)
-0.00506
(-0.6908)
0.00669
(0.8390)
0.00028
(1.0500)
0.00197***
(3.6054)
0.00216***
(3.9246)
13,295
0.4009
13,295
0.4014
-0.04489**
(-2.3997)
-0.00245
(-0.3660)
0.00310***
(3.7308)
-0.00170
(-1.5674)
13,295
0.4021
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.4007
13,295
0.4011
13,295
0.4017
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is DIVST, which is the total number of product strengths.
CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus salary. LCP2 is the
lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the ratio of total debt
to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle proxy
used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that represents
the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F is dummy variable
that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise. I
present the results of the following regression model: 𝐷𝐼𝑉𝑆𝑇𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 +
𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
Table 2.12
Association between Executive Compensation and DIVCN
VARIABLES
Model 1
DIVCN
Model 2
DIVCN
Model 3
DIVCN
CCP2
-0.00201
-0.00136
-0.00125
Model 4
DIVCN
Model 5
DIVCN
Model 6
DIVCN
64
Table 2.12 (Cont.)
Association between Executive Compensation and DIVCN
VARIABLES
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
DIVCN
Model 2
DIVCN
Model 3
DIVCN
Model 4
DIVCN
Model 5
DIVCN
Model 6
DIVCN
0.01881***
(-15.1559)
0.03037***
(-3.1229)
0.05766
(1.5521)
0.01332
(0.7595)
0.01088***
(-3.7752)
0.00117***
(5.8690)
0.06863***
(-8.4873)
0.02686***
(5.0645)
0.01945***
(-15.7279)
-0.02367**
(-2.4422)
0.04301
(1.1541)
0.01521
(0.8673)
0.01153***
(-4.0085)
0.00101***
(4.2994)
0.06828***
(-8.4181)
0.02634***
(3.0968)
0.02733***
(-8.1468)
-0.00013
(-0.2889)
0.01947***
(-15.7283)
-0.02383**
(-2.4592)
0.04359
(1.1691)
0.01468
(0.8373)
0.01146***
(-3.9841)
0.00100***
(4.2457)
0.07919***
(-5.8249)
0.02096*
(1.8514)
-0.02733
(-1.0925)
-0.00005
(-0.1197)
-0.00018
(-0.0492)
0.01523
(0.9206)
0.00748
(0.7127)
0.01809***
(-14.5818)
0.02913***
(-2.9934)
0.05677
(1.5291)
0.01414
(0.8051)
0.01142***
(-3.9587)
0.00114***
(5.7023)
0.06879***
(-8.5235)
0.02651***
(4.9988)
0.01882***
(-15.2228)
-0.02280**
(-2.3512)
0.04258
(1.1432)
0.01575
(0.8977)
0.01192***
(-4.1409)
0.00100***
(4.2561)
0.06838***
(-8.4428)
0.02667***
(3.1357)
0.02667***
(-7.9231)
-0.00016
(-0.3709)
0.01884***
(-15.2325)
-0.02286**
(-2.3584)
0.04315
(1.1579)
0.01516
(0.8641)
0.01189***
(-4.1294)
0.00098***
(4.1332)
0.07939***
(-5.8136)
0.02067*
(1.8267)
0.03953***
(-3.1266)
-0.00008
(-0.1845)
0.00280***
(-3.2029)
-0.00221**
(-2.5214)
13,295
0.1855
13,295
0.1893
0.01530
(0.9233)
0.00830
(0.7901)
-0.00309**
(-2.5061)
0.00156
(0.9542)
13,295
0.1894
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.1850
13,295
0.1889
13,295
0.1890
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variables is DIVCN, which is defined as the total number of
product concerns. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus
salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the
ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a
life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy
variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm.
GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm
has a GP and 0 if otherwise. I present the results of the following regression model: 𝐷𝐼𝑉𝐶𝑁𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
65
In table 2.13 on page 65 the net score of the Employee Relations (ER_NET) CSR
measure is substituted for the dependent variable. The results of the regression analysis suggest
that CCP2 is negatively associated with ER_NET. That is, as the executive current compensation
increases the firms’ employee relations declines. These results are statistically significant at the
1% level. Conversely, the association between LCP2 and ER_NET are not statistically
significant. The interaction terms between GP and the compensation variables are not
statistically significant.
CEOs that are 64years or older are inversely associated with ER_NET score. That is, as
CEOs get the age of 64 and older they invest less or nothing in employee relations projects. This
could mean that as CEOs get to that age bracket, 64 and older, they become more short-term
oriented and less willing to invest in long-term oriented social projects. Coughlan and Schmidt
(1985) posit that the probability of observing a change in a firm’s executive is one turnover in
every two cases when the CEO age is 64 or above, and for younger executives the probability of
managerial turnover is less than one out of every eleven cases. In a similar study Conyon and
Florou (2002) findings suggest that firms cutback on capital expenditures as the CEO become
older.
Table 2.13
Association between Executive Compensation and ER_NET
VARIABLES
CCP2
Model 1
ER_NET
Model 2
ER_NET
Model 3
ER_NET
0.03889***
(-3.1598)
0.03797***
(-3.0823)
0.04812***
(-2.8304)
Model 4
ER_NET
Model 5
ER_NET
Model 6
ER_NET
66
Table 2.13 (Cont.)
Association between Executive Compensation and ER_NET
VARIABLES
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
ER_NET
Model 2
ER_NET
Model 3
ER_NET
Model 4
ER_NET
Model 5
ER_NET
Model 6
ER_NET
(9.7688)
0.26140***
(-4.6415)
0.67498***
(3.2870)
0.76362***
(7.2629)
0.04104**
(2.0900)
-0.00220**
(-2.0425)
0.03467
(0.6329)
0.10706***
(-3.6661)
(9.7108)
0.25245***
(-4.4653)
0.65263***
(3.1798)
0.76506***
(7.2723)
0.04054**
(2.0638)
-0.00192
(-1.4715)
0.03606
(0.6590)
-0.08089*
(-1.7375)
-0.03862*
(-1.7654)
-0.00194
(-0.8570)
(9.7333)
0.24980***
(-4.4222)
0.64331***
(3.1347)
0.77050***
(7.3224)
0.03925**
(1.9981)
-0.00187
(-1.4304)
0.23787**
(2.4330)
-0.02774
(-0.4323)
-0.14244
(-0.9333)
-0.00262
(-1.1022)
0.01753
(0.7832)
-0.28161**
(-2.4193)
-0.07386
(-1.2574)
(9.0814)
0.27244***
(-4.8142)
0.68259***
(3.3265)
0.76882***
(7.2895)
0.03908**
(1.9872)
-0.00226**
(-2.0988)
0.03229
(0.5896)
0.10717***
(-3.6597)
(8.9969)
0.26298***
(-4.6320)
0.65875***
(3.2121)
0.77018***
(7.2990)
0.03868**
(1.9667)
-0.00199
(-1.5242)
0.03379
(0.6178)
-0.08084*
(-1.7338)
-0.04171*
(-1.9019)
-0.00197
(-0.8649)
(9.0384)
0.25980***
(-4.5772)
0.64962***
(3.1662)
0.77694***
(7.3599)
0.03741*
(1.9021)
-0.00192
(-1.4675)
0.22905**
(2.3393)
-0.02621
(-0.4076)
-0.06751
(-0.9361)
-0.00269
(-1.1274)
-0.00043
(-0.0858)
0.00038
(0.0749)
13,295
0.1830
13,295
0.1833
-0.27314**
(-2.3440)
-0.07568
(-1.2835)
-0.00272
(-0.3759)
0.00558
(0.5843)
13,295
0.1837
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.1837
13,295
0.1839
13,295
0.1844
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is ER_NET, which is defined as total Employee
Relations strengths minus total Employee Relations concerns. CCP2 is the lagged value of total executive current compensation for the year, defined
by ExecuComp database as bonus plus salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the
total executive compensation. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets,
CF is measure of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of
common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive
has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that
takes the value of 1 if the firm has a GP and 0 if otherwise. I present the results of the following regression model: 𝐸𝑅_𝑁𝐸𝑇𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 +
𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
67
The regression results in table 2.13 also shows that firms’ debt ratio and CEO tenure are
both inversely associated with ER_NET. The size of the firm, CAPEX, and CF are all positively
associate with the firms employee relations net score. These results are statistically significant at
the 1% level for both current and long-term compensation models and robust to standard error
specifications.
In tables 2.14 and 2.15 on pages 68 and 69 presents the regression models substituting
Employee Relations Strengths (EMPST) and Employee Relations Concerns (ERCN) for
ER_NET, respectively. In table 2.14 the results shows that CCP2 is inversely associated with
EMPST. That is, as executive current compensation increases the firm’s employee relations
strength score decreases. However, this is not true for the LCP2 models. The interaction terms
between GP and CCP2 is not statistically significant. This is also true for the interaction terms
between GP and LCP2.
The results in table 2.14 also suggest that executives that are 64years or older do not
necessarily promote employee relations. The regression results show inverse association between
this group of employees and EMPST. This inverse relationship is also true for this group of
executives that have achieved longer tenure. The relationship between female executives and
EMPST is not significant in all models, except for the interaction terms between GP and
GNEDER_F in which the result suggest that female executives with a GP invest less resources
towards employee relations. The significance of this association is arguably negligible, as the tscore is 1.71 with a 10% significant level. The presence of the GP reduces EMPST, and this
result is statistically significant at the 1% level.
In table 2.14, the regression analyses also suggest that the LCP2 variable is not associated
with EMPST. The result is not statistically significant, even at with the interaction term between
68
GP and LCP2. Larger firms, those with higher capital expenditure, and firms with higher cashflow promote and invest more resources towards employee relations. These control variables are
all statistically significant at the 1% level. In contrast, the higher the firm’s debt ratio the lower it
invests in employee relations. This could be as a result of the restricting character of the debt
covenants.
Table 2.14
Association between Executive Compensation and EMPST
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
Model 1
EMPST
Model 2
EMPST
Model 3
EMPST
0.00482***
(-3.1891)
0.03857***
(37.3620)
0.04413***
(-6.5145)
0.08222***
(3.2409)
0.03355***
(2.5988)
-0.00064
(-0.2729)
0.00052***
(-3.8615)
0.00151
(0.2278)
-0.00859**
(-2.4127)
0.00452***
(-2.9807)
0.03822***
(37.2363)
0.04075***
(-6.0104)
0.07543***
(2.9769)
0.03473***
(2.6880)
-0.00105
(-0.4456)
0.00070***
(-4.1958)
0.00149
(0.2257)
-0.01453**
(-2.5492)
0.01332***
(-4.9095)
0.00031
(1.1457)
-0.00393*
(-1.7298)
0.03824***
(37.2421)
0.04044***
(-5.9615)
0.07481***
(2.9520)
0.03499***
(2.7065)
-0.00113
(-0.4821)
0.00070***
(-4.1621)
0.01935
(1.5160)
-0.01619**
(-2.0373)
-0.00500
(-0.2587)
0.00034
(1.1694)
-0.00115
(-0.4041)
-0.02500*
(-1.7055)
Model 4
EMPST
Model 5
EMPST
Model 6
EMPST
0.03797***
(36.6115)
0.04512***
(-6.6349)
0.08290***
(3.2703)
0.03431***
(2.6551)
-0.00097
(-0.4135)
0.00053***
(-3.9591)
0.00121
(0.1822)
-0.00867**
(-2.4294)
0.03755***
(36.4136)
0.04180***
(-6.1451)
0.07606***
(3.0044)
0.03539***
(2.7368)
-0.00132
(-0.5595)
0.00071***
(-4.2528)
0.00122
(0.1844)
-0.01447**
(-2.5338)
0.01357***
(-4.9937)
0.00030
(1.1120)
0.03755***
(36.4210)
0.04149***
(-6.0957)
0.07545***
(2.9800)
0.03554***
(2.7462)
-0.00143
(-0.6094)
0.00072***
(-4.2956)
0.01851
(1.4495)
-0.01624**
(-2.0411)
-0.01972**
(-2.0552)
0.00033
(1.1438)
-0.02424*
(-1.6517)
69
Table 2.14 (Cont.)
Association between Executive Compensation and EMPST
VARIABLES
Model 1
EMPST
Model 2
EMPST
Model 3
EMPST
Model 4
EMPST
Model 5
EMPST
-0.00063
(-0.9527)
-0.00030
(-0.4578)
13,295
0.2223
13,295
0.2240
(0.3349)
LCP2
LCP2_GP
Observations
R-squared
13,295
0.2229
13,295
0.2245
13,295
0.2247
Model 6
EMPST
(0.3504)
-0.00081
(-0.8020)
0.00089
(0.6996)
13,295
0.2242
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is EMPST, which is defined as total Employee Relations
strengths. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus salary.
LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the ratio of
total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle
proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that
represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F is
dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a GP and
0 if otherwise. I present the results of the following regression model: 𝐸𝑀𝑃𝑆𝑇𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 +
𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
Table 2.15
Association between Executive Compensation and EMPCN
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
Model 1
EMPCN
Model 2
EMPCN
Model 3
EMPCN
Model 4
EMPCN
Model 5
EMPCN
Model 6
EMPCN
0.00106
(0.7114)
0.03535***
(35.5668)
-0.00123
(-0.1791)
-0.04304*
(-1.7140)
0.11880***
(-8.7957)
0.00729***
(-3.1386)
-0.00016
(-1.1845)
0.00128
(0.8574)
0.03505***
(35.2900)
0.00134
(0.1936)
-0.04749*
(-1.9012)
0.11764***
(-8.7083)
0.00769***
(-3.3101)
0.00042***
(-2.5908)
0.00357
(1.5717)
0.03504***
(35.3865)
0.00125
(0.1804)
-0.04674*
(-1.8728)
0.11808***
(-8.7295)
0.00758***
(-3.2631)
-0.00042**
(-2.5723)
0.03587***
(36.3420)
-0.00033
(-0.0480)
-0.04367*
(-1.7399)
0.11876***
(-8.7910)
0.00738***
(-3.1732)
-0.00017
(-1.2394)
0.03552***
(35.9775)
0.00205
(0.2962)
-0.04788*
(-1.9173)
0.11771***
(-8.7085)
0.00772***
(-3.3185)
0.00042***
(-2.5911)
0.03549***
(35.9409)
0.00193
(0.2785)
-0.04716*
(-1.8875)
0.11850***
(-8.7507)
0.00766***
(-3.2949)
0.00045***
(-2.7173)
70
Table 2.15 (Cont.)
Association between Executive Compensation and EMPCN
VARIABLES
AGE2
Model 1
EMPCN
Model 2
EMPCN
Model 3
EMPCN
Model 4
EMPCN
Model 5
EMPCN
Model 6
EMPCN
(-0.6515)
0.00762**
(1.9820)
(-0.6879)
-0.00363
(-0.5890)
0.00957***
(-3.5703)
0.00068**
(2.2654)
(-1.5611)
-0.01171
(-1.3761)
0.01664
(0.8696)
0.00079**
(2.5091)
-0.00409
(-1.4553)
0.01799
(1.3140)
0.01130
(1.4556)
(-0.6433)
0.00751*
(1.9534)
(-0.6773)
-0.00354
(-0.5744)
0.00925***
(-3.4412)
0.00067**
(2.2344)
(-1.5040)
-0.01220
(-1.4346)
-0.01688*
(-1.8001)
0.00079**
(2.5156)
-0.00090
(-1.4339)
-0.00065
(-1.0288)
13,295
0.2755
13,295
0.2764
0.01743
(1.2667)
0.01201
(1.5469)
-0.00110
(-1.1272)
0.00079
(0.6436)
13,295
0.2767
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.2754
13,295
0.2764
13,295
0.2768
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is EMPCN, which is defined as total Employee
Relations concerns.. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus
salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the
ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a
life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy
variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm.
GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm
has a GP and 0 if otherwise. I present the results of the following regression model: 𝐸𝑀𝑃𝐶𝑁𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
In Table 2.15, the regression analysis examining the association of CCP2 and EMPCN is
positive both not statistically significant. This result holds in all models. However, the interaction
term between CCP2 and GP is negative and also not statistically significant. This result suggests
that for firms with the GP clause the CCP2 is negatively associated with employee relations
concerns. The beta coefficient of this joint association is -0.002. The firm’s level of EMPCN
increases when the CEO is 64years or older. But this is somewhat mitigated when the CEO has
71
achieved substantive tenure. The joint association of AGE2 and Tenure1 on EMPCN is negative
with a beta coefficient of -0-003 at the 5% significant level.
The provision and presence of the GP reduces employee relations concerns in all models
in table 2.15. Those firms with greater capital expenditure, cash-flow, and older are all inversely
associated with employee relations concerns, respectively. In contrast, the larger the firm the
greater its employee relations concerns. This result is statistically significant at the 1% level.
This result suggests that lager firms should allocate more resources and commit greater efforts
towards improving its employee relations. The association between LCP2 and EMPCN is
negative but not statistically significant. The interacted term between GP and LCP2 is also not
statistically significant.
Table 2.16 presents the regression models substituting Community net score
(COMM_NET) for the dependent variable. The regression results show that CCP2 without a GP
clause is not associated with COMM_NET. However, the result of the interaction term between
GP and CCP2 suggest that, for those firms with a GP clause, CCP2 is positively associated with
COMM_NET. This result is statistically significant at the 1% level with beta coefficient of 0.013 for the joint association of GP and CCP2 on COMM_NET. Older CEOs that are 64years
and older do not commit firm resources towards COMM_NET. This is true for those CEOs that
Table 2.16
Association between Executive Compensation and COMM_NET
VARIABLES
CCP2
Model 1
COMM_NET
Model 2
COMM_NET
Model 3
COMM_NET
0.00424
(0.5449)
0.00510
(0.6527)
0.02783**
(2.4128)
Model 4
COMM_NET
Model 5
COMM_NET
Model 6
COMM_NET
72
Table 2.16 (Cont.)
Association between Executive Compensation and COMM_NET
VARIABLES
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
COMM_NET
Model 2
COMM_NET
Model 3
COMM_NET
Model 4
COMM_NET
Model 5
COMM_NET
Model 6
COMM_NET
(21.4170)
0.12287***
(-4.1068)
0.56812***
(5.1610)
0.18691***
(-3.5033)
0.04761***
(4.3037)
-0.00059
(-1.0291)
-0.04534
(-1.6014)
0.04717***
(-2.8660)
(21.3561)
0.11436***
(-3.8257)
0.54777***
(4.9857)
0.18521***
(-3.4606)
0.04702***
(4.2503)
-0.00048
(-0.6877)
-0.04431
(-1.5646)
-0.03082
(-1.1162)
0.03603***
(-2.8950)
-0.00128
(-1.0085)
(21.4756)
0.11280***
(-3.7727)
0.54490***
(4.9481)
0.17869***
(-3.3414)
0.04704***
(4.2520)
-0.00026
(-0.3641)
0.00013
(0.0024)
0.00892
(0.2249)
0.24951**
(2.5301)
-0.00186
(-1.3886)
0.04075***
(-2.7344)
-0.06288
(-0.9943)
-0.05436
(-1.6140)
(21.5908)
0.12072***
(-4.0414)
0.56663***
(5.1494)
0.18720***
(-3.5091)
0.04759***
(4.2838)
-0.00060
(-1.0433)
-0.04509
(-1.5954)
0.04733***
(-2.8730)
(21.5352)
0.11259***
(-3.7716)
0.54676***
(4.9780)
0.18579***
(-3.4721)
0.04717***
(4.2464)
-0.00047
(-0.6784)
-0.04401
(-1.5565)
-0.03073
(-1.1131)
0.03539***
(-2.8352)
-0.00129
(-1.0135)
(21.5622)
0.11131***
(-3.7257)
0.54373***
(4.9522)
0.18285***
(-3.4199)
0.04662***
(4.1949)
-0.00051
(-0.7212)
0.00319
(0.0582)
0.00365
(0.0918)
0.10647***
(-2.7446)
-0.00177
(-1.3206)
-0.00140
(-0.5127)
-0.00068
(-0.2497)
13,295
0.1739
13,295
0.1745
-0.06642
(-1.0531)
-0.04793
(-1.4176)
-0.00652
(-1.5582)
0.01049*
(1.9182)
13,295
0.1749
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.1739
13,295
0.1746
13,295
0.1754
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is COMM.NET, which is defined as total Community
total strengths minus Community total concerns. CCP2 is the lagged value of total executive current compensation for the year, defined by
ExecuComp database as bonus plus salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total
executive compensation. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF
is measure of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of
common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive
has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that
takes the value of 1 if the firm has a GP and 0 if otherwise. I present the results of the following regression model: 𝐶𝑂𝑀𝑀_𝑁𝐸𝑇𝑖𝑡 = α + 𝛽1 𝐶𝐶𝑃2𝑡−1 +
𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
73
have achieved significant tenure. The relationship between female executives and COMM_NET
is negative but not statistically significant. The GP is inversely associated with COMM_NET, at
the 1% significance level. The longer the CEO’s tenure with the firm the lower the firm’s
COMM_NET scores, ceteris paribus.
The association between LCP2 and COMM_NET is negative but not statistically
significant across all models. However, the interaction term between GP and LCP2 suggest that
for those firms with a GP clause, the association between LCP2 and COMM_NET is positive
and statistically significant at the 10% level with a joint significance beta coefficient of 0.004.
Tables 2.17 and 2.18 on pages 74 and 75 presents the regression models substituting
Community Strengths (COMMST) and Community Concerns (COMMCN) for the dependent
variable, respectively. In table 2.17 the results shows that CCP2 is positively associated with
COMMST. That is, as executive current compensation increases the firm’s community strength
score increases. However, the provision and presence of a GP clause reverses this relationship.
That is, for those CEOs with a GP the association between CCP2 and COMMST is negative and
statistically significant at the 1% level. Nonetheless, the beta coefficient of this joint effect of GP
and CCP2 on COMMST is negligible at -0.0003. In table 2.17, the results also indicates that
executives that are 64years and older commit less firm resources towards COMMST. This is also
true for those CEOs that have achieved substantive tenure with the firm. Larger firms invest
significantly more resources towards COMMST than smaller firms. The average t-statistics
across all models in Table 2.17 is significantly high at approximately 35.11.
Also, the regression results of this observation are all statistically significant at the 1%
level across all models. It is also important to note that CAPEX and RETE are also both
positively associated with COMMST at the 1% statistical significance level.
74
Also, the regression results of this observation are all statistically significant at the 1% level
across all models. It is also important to note that CAPEX and RETE are also both positively
associated with COMMST at the 1% statistical significance level.
Table 2.17
Association between Executive Compensation and COMMST
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
COMMST
Model 2
COMMST
Model 3
COMMST
0.00217**
(1.9767)
0.02616***
(35.1133)
0.02072***
(-4.9717)
0.04162***
(2.8542)
0.03580***
(-4.9463)
0.00522***
(3.4943)
-0.00016*
(-1.9404)
-0.00102
(-0.2523)
-0.00585**
(-2.4805)
0.00229**
(2.0788)
0.02602***
(35.0372)
0.01936***
(-4.6645)
0.03887***
(2.6672)
0.03534***
(-4.8683)
0.00507***
(3.3878)
-0.00023**
(-2.3037)
-0.00102
(-0.2522)
-0.00801**
(-2.0100)
0.00537***
(-3.0753)
0.00011
(0.5962)
0.00555***
(3.4208)
0.02610***
(35.1412)
0.01907***
(-4.5883)
0.03824***
(2.6236)
0.03425***
(-4.7259)
0.00504***
(3.3791)
-0.00019*
(-1.9418)
0.01005
(1.2129)
-0.00118
(-0.2000)
0.03603**
(2.5611)
0.00001
(0.0695)
0.00586***
(-2.7541)
-0.01558*
(-1.6726)
-0.00936*
(-1.9240)
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
Model 4
COMMST
Model 5
COMMST
Model 6
COMMST
0.02645***
(35.1760)
0.02023***
(-4.8622)
0.04129***
(2.8279)
0.03613***
(-4.9810)
0.00536***
(3.5643)
-0.00015*
(-1.8727)
-0.00088
(-0.2193)
-0.00582**
(-2.4642)
0.02628***
(35.1200)
0.01893***
(-4.5662)
0.03861***
(2.6457)
0.03571***
(-4.9074)
0.00523***
(3.4762)
-0.00022**
(-2.2501)
-0.00088
(-0.2181)
-0.00807**
(-2.0228)
0.00531***
(-3.0360)
0.00012
(0.6343)
0.02631***
(35.1324)
0.01873***
(-4.5064)
0.03796***
(2.6010)
0.03511***
(-4.8294)
0.00514***
(3.4213)
-0.00022**
(-2.1842)
0.01081
(1.3063)
-0.00182
(-0.3064)
-0.00898
(-1.6240)
0.00003
(0.1698)
0.00022
(0.5752)
0.00035
(0.9009)
13,295
13,295
LCP2_GP
Observations
13,295
13,295
13,295
-0.01635*
(-1.7568)
-0.00869*
(-1.7779)
-0.00003
(-0.0412)
0.00068
(0.8718)
13,295
75
Table 2.17 (Cont.)
Association between Executive Compensation and COMMST
VARIABLES
Model 1
COMMST
Model 2
COMMST
Model 3
COMMST
Model 4
COMMST
Model 5
COMMST
Model 6
COMMST
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is COMMST, which is defined as total Community
total strengths. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus salary.
LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the ratio of
total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle
proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that
represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F is
dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a GP and
0 if otherwise. I present the results of the following regression model: 𝐶𝑂𝑀𝑀𝑆𝑇𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 +
𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
In contrast, the regressions in table 2.17 shows that the firm’s debt ratio and its cash-flow
are both inversely associated with the COMMST. That is, as these two variables increases the
firm COMMST decreases, respectively. The tests for the association between GENDER_F and
COMMST is negative both not statistically significant. However, the interaction term between
GENDER_F and GP is statistically significant and also negative. Thus, for female executives
with the GP clause, the negative association between gender and COMMST still holds and is
statistically significant at the 10% level. The test for the association between LCP2 and
COMMST is positive but not statistically significant.
Table 2.18
Association between Executive Compensation and COMMCN
VARIABLES
CCP2
Model 1
COMMCN
Model 2
COMMCN
Model 3
COMMCN
0.00219***
0.00220***
0.00169
Model 4
COMMCN
Model 5
COMMCN
Model 6
COMMCN
76
Table 2.18 (Cont.)
Association between Executive Compensation and COMMCN
VARIABLES
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
COMMCN
Model 2
COMMCN
Model 3
COMMCN
Model 4
COMMCN
Model 5
COMMCN
Model 6
COMMCN
0.01583***
(23.7246)
-0.00489
(-1.3428)
0.07186***
(-4.5963)
-0.01306**
(-1.9654)
-0.00273**
(-2.2715)
-0.00008
(-1.2813)
0.00978***
(2.8020)
0.00155
(0.9106)
0.01577***
(23.7831)
-0.00465
(-1.2786)
0.07170***
(-4.5585)
-0.01273*
(-1.9150)
-0.00284**
(-2.3675)
0.00020***
(-2.6545)
0.00956***
(2.7386)
-0.00504**
(-1.9923)
-0.00046
(-0.3146)
0.00043***
(3.6338)
0.01578***
(23.7139)
-0.00454
(-1.2470)
0.07211***
(-4.5804)
-0.01252*
(-1.8755)
-0.00290**
(-2.4143)
0.00020***
(-2.6108)
0.01848**
(2.2243)
-0.00300
(-0.7627)
-0.00585
(-0.5330)
0.00040***
(3.2062)
0.00089
(0.5301)
-0.01244
(-1.3913)
-0.00283
(-0.7903)
0.01592***
(24.0082)
-0.00474
(-1.3025)
0.07196***
(-4.5976)
-0.01350**
(-2.0262)
-0.00250**
(-2.0783)
-0.00007
(-1.0951)
0.00992***
(2.8362)
0.00164
(0.9638)
0.01585***
(24.0499)
-0.00450
(-1.2376)
0.07182***
(-4.5618)
-0.01316**
(-1.9748)
-0.00262**
(-2.1728)
-0.00019**
(-2.5640)
0.00970***
(2.7716)
-0.00516**
(-2.0406)
-0.00056
(-0.3796)
0.00044***
(3.7419)
0.01586***
(24.0788)
-0.00445
(-1.2244)
0.07221***
(-4.5907)
-0.01283*
(-1.9219)
-0.00263**
(-2.1853)
-0.00018**
(-2.3029)
0.01887**
(2.2825)
-0.00270
(-0.6844)
0.01135***
(2.5798)
0.00041***
(3.2702)
0.00075***
(2.5932)
0.00079***
(2.7050)
13,295
0.2237
13,295
0.2241
-0.01275
(-1.4306)
-0.00338
(-0.9397)
0.00163***
(3.4361)
-0.00151**
(-2.3762)
13,295
0.2246
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.2240
13,295
0.2243
13,295
0.2245
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is COMMCN, which is defined as total Community
total Concerns. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus
salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the
ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a
life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy
variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm.
GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm
has a GP and 0 if otherwise. I present the results of the following regression model: 𝐶𝑂𝑀𝑀𝐶𝑁𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
77
In table 2.18, the regression results suggest that both CCP2 and LCP2 are both strongly
associated with COMMCN. However, for those firms with a GP clause, the association between
LCP2 and COMMCN is negative and statistically significant at the 5% level. The interaction
term between GP and LCP2 is negative indicating a joint significance with of -0.00012. The
interaction term between GP and CCP2 is not statistically significant. CEOs that are 64years or
older that have achieved substantive tenure do make an effort to reduce the firm’s community
concern score. The test for this joint association is significant at the 1% level with beta
coefficient of -0.005.
The results in tables 2.18 also indicate that the association between female executives is
positive and statistically significant at the 1% level. . This suggests that female CEOs commit
strong effort and resource towards ensuring that the COMMCN is significantly reduced. Older
firms (RETE) and ensure that their COMMCN is kept at bay with a statistical significance level
of 1% across all models. The firm’s Cash-Flow (CF) and Capital Expenditure (CAPEX) are both
inversely associated with COMMCN. That is, as these variables increase in size, the firm’s
COMMCN decreases. In contrast, the firm’s size is positively and strongly associated with its
COMMCN. This result suggests that larger firms should commit more resources towards
mitigating its COMMCN performance.
Table 2.19 presents the regression models substituting Environment net score
(ENV_NET) for the dependent variable. The results in the regression output without the GP
interaction, though not statistically significant, suggest that CCP2 is negatively associated with
ENV_NET. In the regression in which GP is interacted with CCP2, the result shows that both
variables jointly increase ENV_NET. That is, for those firms with a GP clause the joint
association between CCP2 ENV_NET is positive and statistically significant at 1% level. The
78
beta coefficient of this joint association is 0.019. The association between LCP2 and ENV_NET
for firms with GP is positive and statistically significant with a joint beta coefficient of 0.004. In
contrast, the association between LCP2 and ENV_NET for firms without the GP is negative but
not statistically significant. The regression result in table 2.19 also indicates that corporate
executives that are 64 years and older do not promote investment in environmental social
responsibility. The association between the group of managers and ENV_NET is negative across
Table 2.19
Association between Executive Compensation and ENV_NET
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
Model 1
ENV_NET
Model 2
ENV_NET
Model 3
ENV_NET
-0.00834
(-0.7805)
0.05865***
(7.3289)
0.03890
(0.8787)
1.70522***
(8.3599)
0.05595
(0.7572)
0.07383***
(4.5807)
0.00134
(1.5872)
0.07567
(1.4212)
0.12825***
(-5.1393)
-0.00731
(-0.6831)
0.05771***
(7.2541)
0.04940
(1.1137)
1.68107***
(8.2252)
0.05843
(0.7903)
0.07297***
(4.5293)
0.00131
(1.2544)
0.07661
(1.4406)
0.11738***
(-2.9438)
-0.04374**
(-2.3525)
-0.00097
(-0.5459)
-0.04123**
(-2.3902)
0.05749***
(7.2114)
0.04987
(1.1209)
1.67448***
(8.2005)
0.05963
(0.8045)
0.07175***
(4.4586)
0.00119
(1.1327)
0.20250**
(2.1723)
-0.06029
(-1.0577)
0.44339***
(-3.1211)
-0.00168
(-0.8883)
0.06053***
(2.8522)
-0.17453
Model 4
ENV_NET
Model 5
ENV_NET
Model 6
ENV_NET
0.05951***
(7.3800)
0.04039
(0.9150)
1.70413***
(8.3537)
0.05824
(0.7882)
0.07248***
(4.4836)
0.00126
(1.4953)
0.07509
(1.4109)
0.12899***
(-5.1635)
0.05844***
(7.2918)
0.05029
(1.1372)
1.68073***
(8.2230)
0.06026
(0.8152)
0.07186***
(4.4479)
0.00128
(1.2241)
0.07615
(1.4320)
0.11661***
(-2.9249)
-0.04255**
(-2.2815)
-0.00105
(-0.5935)
0.05873***
(7.3332)
0.05325
(1.2018)
1.67412***
(8.1936)
0.06568
(0.8874)
0.07064***
(4.3772)
0.00120
(1.1433)
0.19634**
(2.1127)
-0.06138
(-1.0751)
0.18286***
(-3.1345)
-0.00181
(-0.9623)
-0.16893
79
Table 2.19 (Cont.)
Association between Executive Compensation and ENV_NET
VARIABLES
Model 1
ENV_NET
Model 2
ENV_NET
GP_AGE2
Model 3
ENV_NET
Model 4
ENV_NET
Model 5
ENV_NET
-0.08038
(-1.5899)
LCP2
-0.00601
(-1.4858)
-0.00512
(-1.2636)
13,295
0.2260
13,295
0.2263
LCP2_GP
Observations
R-squared
13,295
0.2259
13,295
0.2263
13,295
0.2272
Model 6
ENV_NET
-0.07696
(-1.5170)
0.01661***
(-2.8428)
0.02061**
(2.5675)
13,295
0.2270
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is ENV_NET which is defined as total Environment
strengths minus total Environment concerns. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp
database as bonus plus salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive
compensation. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure
of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity.
AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO
of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of
1 if the firm has a GP and 0 if otherwise. I present the results of the following regression model: 𝐸𝑁𝑉_𝑁𝐸𝑇𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗
𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗
𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
all models and statistically significant at the 1% level. Female executives with a GP do show a
distinct habitude towards engaging and investing firm resources in social projects that protect
and enhance the environment. This is inferred by the positive association between female
executives that have a GP clause and ENV_NET. The relationship is statistically significant at
the 5% level with a joint beta coefficient of 0.123.
The firm’s size, capital expenditure, and age are all positively associated with
ENV_NET. Thus, when these firm variables increase the engagement and investment in
ENV_NET also increases. These results are all statistically significant across the all models at
the 1% level. The test for the association between the firm’s debt ratio and its level of
80
engagement socially responsible projects that protect and enhance the environment is positive
but not statistically significant.
In tables 2.20 and 2.21 on pages 80 and 81, Environment Strengths (ENVST) and
Environment Concerns (ENVCN) are substituted for the dependent variable, respectively. The
regression output in table 2.20 shows that both CCP2 and LCP2 are both no associated with
ENVST. However, the interaction between LCP2 and GP suggest is negative and statistically
significant at the 5% level. The beta coefficient for this joint association is -0.022. Overall, the
test for the effect of the GP reduces the firm’s engagement in socially responsible environment
projects.
The association between AGE2 and ENVST is negative and statistically significant at the
1% level. This suggest that corporate executives that are 64years and older do not promote
socially responsible environment projects. The provision of the GP further exacerbates this
relationship, as indicated by the interaction between GP and AGE2. The association between
Female executives and ENVST is positive and statistically significant at the 1% level. However,
for those female executives with a GP clause the beta coefficient of this positive association is
marginally reduced by 0.01; from an average of 0.022 across all models to 0.011 in the
interaction model with the GP.
Table 2.20
Association between Executive Compensation and ENVST
VARIABLES
Model 1
ENVST
Model 2
ENVST
Model 3
ENVST
CCP2
0.00130
0.00155
-0.00026
Model 4
ENVST
Model 5
ENVST
Model 6
ENVST
81
Table 2.20 (Cont.)
Association between Executive Compensation and ENVST
VARIABLES
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
ENVST
Model 2
ENVST
Model 3
ENVST
Model 4
ENVST
Model 5
ENVST
Model 6
ENVST
0.04165***
(44.3946)
-0.00940*
(-1.7572)
0.10057***
(4.9044)
0.05784***
(-5.8803)
0.01029***
(5.0672)
-0.00016
(-1.5119)
0.02149***
(2.9358)
0.01701***
(-5.7391)
0.04140***
(44.4596)
-0.00675
(-1.2599)
0.09480***
(4.6300)
0.05708***
(-5.7957)
0.01003***
(4.9487)
-0.00023*
(-1.7521)
0.02161***
(2.9635)
0.01753***
(-3.5244)
0.01079***
(-4.7804)
-0.00003
(-0.1200)
0.04142***
(44.4416)
-0.00643
(-1.1963)
0.09351***
(4.5707)
0.05628***
(-5.7181)
0.00985***
(4.8687)
-0.00022*
(-1.6954)
0.04808***
(3.2345)
-0.00821
(-1.1405)
-0.03006*
(-1.9349)
-0.00015
(-0.5772)
0.00318
(1.3677)
-0.03690**
(-2.2030)
-0.01297**
(-2.1140)
0.04199***
(44.2253)
-0.00883*
(-1.6478)
0.10017***
(4.8842)
0.05795***
(-5.8832)
0.01031***
(5.0603)
-0.00016
(-1.5185)
0.02156***
(2.9458)
0.01704***
(-5.7511)
0.04169***
(44.2582)
-0.00630
(-1.1737)
0.09454***
(4.6172)
0.05728***
(-5.8062)
0.01010***
(4.9683)
-0.00023*
(-1.7309)
0.02171***
(2.9752)
0.01753***
(-3.5257)
0.01065***
(-4.7039)
-0.00003
(-0.1192)
0.04174***
(44.3182)
-0.00579
(-1.0770)
0.09324***
(4.5563)
0.05628***
(-5.7081)
0.00990***
(4.8725)
-0.00023*
(-1.7234)
0.04805***
(3.2313)
-0.00862
(-1.1962)
0.02382***
(-3.2453)
-0.00015
(-0.5761)
-0.00030
(-0.5900)
-0.00006
(-0.1178)
13,295
0.3361
13,295
0.3372
-0.03691**
(-2.2025)
-0.01237**
(-2.0142)
-0.00122*
(-1.6528)
0.00209**
(2.0944)
13,295
0.3380
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.3361
13,295
0.3373
13,295
0.3380
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is ENVST, which is defined as total Environment
strengths minus total Environment concerns. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp
database as bonus plus salary. LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive
compensation. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure
of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity.
AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO
of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of
1 if the firm has a GP and 0 if otherwise. I present the results of the following regression model: 𝐸𝑁𝑉𝑆𝑇𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗
𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 + 𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗
𝐺𝑃𝑖𝑡 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
82
The firm’s size, capital expenditure, and age are all positively associated with ENVST
and statistically significant at the 1% level. In contrast, the firm’s debt ratio, and cash flow are
both inversely associated with the ENVST. The relationship between the debt ratio and ENVST
is statistically significant at the 10% level. While the cash flow negative relationship is stronger
with a statistical significance at the 1% level.
In table 2.21, the result shows that both proxies for executive compensation, CCP2 and
LCP2, are both positively associated with ENVCN. This positive association is stronger for the
CCP2. However, for both the CCP2 and LCP2 the provision of the GP mitigates these positive
associations. The joint association between GP and CCP2 on ENVCN is negative with a beta
coefficient of -0.002. While the joint association between GP and CCP2 on ENVCN is -0.001.
This means that for those firms that include the GP clause in their executive compensation
contract, the association between executive compensation, CCP2 and LCP2, is negative.
Table 2.21
Association between Executive Compensation and EVNCN
VARIABLES
CCP2
LogSize
Debt
CAPEX
CF
RETE
Model 1
ENVCN
Model 2
ENVCN
Model 3
ENVCN
Model 4
ENVCN
Model 5
ENVCN
Model 6
ENVCN
0.00173*
(1.6611)
0.02799***
(34.4710)
-0.00991**
(-2.2481)
0.15695***
(-7.1170)
0.05555***
(-6.4150)
-0.00114
(-0.7833)
0.00181*
(1.7480)
0.02789***
(34.5580)
-0.00895**
(-2.0277)
0.15894***
(-7.1914)
0.05524***
(-6.3713)
-0.00125
(-0.8553)
0.00479***
(2.6093)
0.02795***
(34.5671)
-0.00873**
(-1.9753)
0.15921***
(-7.2106)
0.05465***
(-6.2948)
-0.00124
(-0.8494)
0.02805***
(34.2941)
-0.00981**
(-2.2351)
0.15701***
(-7.1220)
0.05590***
(-6.4390)
-0.00096
(-0.6558)
0.02793***
(34.3546)
-0.00886**
(-2.0152)
0.15901***
(-7.1972)
0.05561***
(-6.3950)
-0.00105
(-0.7187)
0.02793***
(34.3796)
-0.00882**
(-2.0058)
0.15929***
(-7.2095)
0.05541***
(-6.3656)
-0.00107
(-0.7273)
83
Table 2.21 (Cont.)
Association between Executive Compensation and EVNCN
VARIABLES
GENDER_F
AGE2
Model 1
ENVCN
Model 2
ENVCN
Model 3
ENVCN
Model 4
ENVCN
Model 5
ENVCN
Model 6
ENVCN
(-3.7050)
0.00669
(1.6360)
0.00271
(1.0139)
(-3.4008)
0.00671
(1.6409)
0.00166
(0.3898)
-0.00382*
(-1.9162)
0.00005
(0.2475)
(-3.1756)
0.01298
(1.4454)
0.00284
(0.4598)
0.03311**
(2.3117)
0.00003
(0.1330)
-0.00535**
(-2.4653)
-0.00887
(-0.8947)
-0.00153
(-0.2808)
(-3.5957)
0.00680*
(1.6643)
0.00279
(1.0417)
(-3.3461)
0.00682*
(1.6697)
0.00155
(0.3638)
-0.00393**
(-1.9621)
0.00006
(0.3128)
(-3.2229)
0.01368
(1.5322)
0.00268
(0.4324)
0.00406
(0.7094)
0.00005
(0.2290)
0.00063
(1.6387)
0.00072*
(1.8697)
13,295
0.4161
13,295
0.4163
-0.00953
(-0.9659)
-0.00154
(-0.2820)
0.00129**
(2.1846)
-0.00102
(-1.2780)
13,295
0.4164
GP
AGE2_Tenure1
CCP2_GP
GENDERGP_F
GP_AGE2
LCP2
LCP2_GP
Observations
R-squared
13,295
0.4161
13,295
0.4163
13,295
0.4168
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is ENVCN, which is defined as total Environment
concerns. CCP2 is the lagged value of total executive current compensation for the year, defined by ExecuComp database as bonus plus salary.
LCP2 is the lagged value of the long-term elements (stock options & long-term incentives) of the total executive compensation. Debt is the ratio of
total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle
proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that
represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F is
dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a GP and
0 if otherwise. I present the results of the following regression model: 𝐸𝑁𝑉𝐶𝑁𝑖𝑡 =α+𝛽1 𝐶𝐶𝑃2𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽4 𝐿𝐶𝑃2𝑡−1 +
𝛽5 𝐿𝐶𝑃2𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽6 𝐴𝐺𝐸2𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 + 𝛽11 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
Also in table 2.21, the regression results shows that the firm’s debt ratio, capital
expenditure, cash flow, GP, and CEO tenure are all negatively associated with environmental
concerns. These results are all strongly statistically significant at the 1% level. In contrast, the
larger the firm the greater its environmental concerns score. These results suggest that lager
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firms should invest more effort and resources towards reducing their environmental concerns
score. The sheer size of the firm makes it imperative that greater emphasis should be implored in
a continuous promulgation and enforcement of corporate policies that protect and enhance the
environment.
6.
Conclusion
In this essay, I explore the association between executive compensation and CSR. I
extend previous research on similar topic by examining the moderating effect of the golden
parachute. Given that the largest portion of the GP payments usually come from the accelerated
payments of unvested stock options and other stock units, I argue that CEOs with the GP clause
would behave differently towards CSR from those CEOs without it. If CSR projects are value
enhancing, then the CEO with a GP would promote CSR engagements for as long as it increases
firm financial performance.
Using a large sample of 1301 unique US firms from 1993 to 2013, the findings suggest
that there exists an inverse relationship between current (long-term) compensation and firms’
CSR engagements. While the direct association between the golden parachute and CSR is also
negative, the test for a moderating effect reveals that the GP and long-term compensation jointly
and positively increase firms’ CSR performance. This is consistent with the expectation that
executives with a GP clause would desire to maximize their long-term wealth by approving only
value-enhancing CSR projects that positively enhance firm financial performance. Furthermore,
the results also suggest that female executives are more likely than their male counterparts to
promote CSR engagements. Older executives are less willing to engage in CSR even with the GP
clause.
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The result of the analysis on the relationship between CF and CSRST alludes to the
possibility that, from previous experience, firms are not convinced that CSR engagements always
increase financial performance. It could be that an overinvestment in CSR erodes the benefits to
the firm, hence the need to reduce investments in CSR strengths to avoid overinvestment. The
findings are robust to model specification, endogeneity and selection bias issues, and sufficient
control variables.
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CHAPTER 3
EXECUTIVE COMPENSATION, CSR, AND FIRM PERFORMANCE: THE
EFFECTUATING CAPACITY OF THE GOLDEN PARACHUTE
3.
Introduction
A socially responsible firm is particularly mindful of how its operations affect the
wellbeing of its stakeholders, protect the environment and positively contribute to the
community from which it extracts profit. The debate on why firms invest in socially responsible
projects is long-standing. There are competing arguments on why and how firms can “do well by
doing good.” Some argue that firms can create shareholder value by meeting the needs of the
other stakeholders (Freeman et al. 2010; Porter and Kramer 2011). The underlying reasoning
behind this contention is that when firms fail to align the interest of its stakeholders, it could
result in negative outcomes like consumer boycotts (Sen, Gürhan‐Canli and Morwitz 2001),
difficulty in hiring and retaining talented employees (Greening and Turban 2000), or incurring
punitive fines from regulatory bodies.
In contrast, some studies argue that firms could potentially actually destroy shareholders’
wealth by investing in CSR11 projects like integrating environmental and social policies in its
business operations (Friedman 2007; Galaskiewicz 1997; Navarro 1988). Proponents of this
11
It has been defined as the actions which a firm chooses to take that substantially enhances the wellbeing of its stakeholders Frooman, J.
"Socially Irresponsible and Illegal Behavior and Shareholder Wealth A Meta-Analysis of Event Studies." Business & Society 36 (1997), 221249.. This encompasses the economic, legal, ethical, and discretionary expectations of the society Carroll, A. B. "A three-dimensional conceptual
model of corporate performance." Academy of management review 4 (1979), 497-505.. Jo, H., and M. A. Harjoto. "Corporate governance and
firm value: The impact of corporate social responsibility." Journal of Business Ethics 103 (2011), 351-383. define CSR as how a firm conducts its
business operations to generate an overall positive impact on the society as regards to serving people, community, and environment, in a manner
that exceeds the legal requirement.
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school of thought argue that managers are recipients of private gains from investing the firm’s
financial resources in value-destroying CSR projects. They argue that such actions are usually to
the detriment of the shareholders’ wealth. Consequently, such investments could produce
negative financial implications like a higher cost structure for the firm (Brown, Helland and
Smith 2006).
The conflicting arguments presented in empirical findings on the relationship between
CSR and firm value could be as a result of methodological model misspecifications (Margolis,
Elfenbein and Walsh 2007). It might be that the existent urge to capture a positive impact rather
than identify the channel(s) through which CSR could affect firm value is responsible for the
conflicting findings(Servaes and Tamayo 2013). Instead of assuming a direct-link between CSR
and firm value, in this research an indirect link is examined. Specifically, I hypothesize that an
appropriate executive compensation structure should increase the probability of a positive
association between firm CSR engagements and its effect on financial performance. In
examining 153 randomly-selected firms in 1979-1980, Mehran (1995) provides evidence to
suggest that the mechanics, rather than the amount of compensation, is what aligns the
executive’s interest with that of the shareholders. That is, the design and structure of the
executive compensation mitigates the agency conflict.
A puzzling conundrum to this analysis is that most CSR benefits, if any, are not always
realized in the same time period as the cost incurred. Thus, when evaluating current managerial
decision, it could be difficult to accurately forecast CSR impact on stock returns and shareholder
wealth. There is empirical evidence to suggest that corporate managers are unable to forecast
returns past 100 days (Jenter, Lewellen and Warner 2011). Thus, the likelihood of the manager
88
be able to accurately forecast the probable outcome of decisions on CSR projects on firm value
in the distant future does seem like a tall-order.
Pressure to meet an earnings target could produce an undesirable unintended
consequence. If meeting short-term earnings targets is overly emphasized in the firm’s executive
evaluation metric, then this might induce the manager to promote a subjective partiality towards
those projects with very high certainty of producing immediate value in achieving the earnings
target. This could undermine the ultimate goal of the firm, which is to align the manager’s
interest with that of the shareholders at all times.
As hinted above, it is a common practice for firms to tie the executive’s compensation to
firm performance. That is, the executive’s compensation is, to some degree, dependent on how
much value the manager creates for the firm. In this essay, the association between CSR, a
contractual clause in the executives’ compensation package, and the firm’s profitability is
examined. In particular, the impact of a special type of compensation mechanism, the golden
parachute (GP),12 on the relationship between CSR and firm performance is closely examined.
If the association between CSR projects and firm performance is positive, then it
behooves the executive to engage in value-enhancing CSR projects. The GP should reduce the
manager’s concern as in regards to short-term earnings target expectations. In this study, I
subscribe to the incentive hypothesis. which states that an executive employment contracts like
12
The Golden Parachute (GP) refers to the benefit received by a CEO either in the event that a firm is acquired, employment is
terminated, or the CEO remains with the firm through a recessionary cycle Bebchuk, A. Cohen, and C. C. Wang. "Golden
Parachutes and the Wealth of Shareholders." Journal of Corporate Finance 25 (2014a), 140-154, Fich, E. M., A. L. Tran, and R.
A. Walkling. "On the importance of golden parachutes." Journal of Financial and Quantitative Analysis 48 (2013), 1717-1753,
Lambert, R. A., and D. F. Larcker. "Golden parachutes, executive decision-making, and shareholder wealth." Journal of
Accounting and Economics 7 (1985), 179-203.
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GPs alleviate managerial concerns regarding short-term profits (Narayanan 1985; Stein 1988;
Stein 1989). This should align the manager’s (agent) interest with that of the shareholders
(principal). With a GP, the manager particularly profits in the enhanced firm performance as,
oftentimes, the largest portion of a GP payment comes from accelerated invested stock options
and other stock units.13 Therefore, by promoting value-enhancing socially responsible
engagements, the manager ensures that the value of the GP (stock options premium) is
maximized. To do so, the manager will exercise prudence and exert judicious effort to promote
mostly those CSR projects with greater propensity of enhancing firm value. Thus, in this
research, I explore the follow questions:
1. Does the provision of a golden parachute increase (decrease) the association between
CSR and firm performance?
2. Does the provision of a GP encourage (discourage) managerial overinvestment in
CSR and what impact does this have on firm performance?
3. What types of CSR projects have the most positive (negative) impact of firm
performance and what effect does the provision a GP have on the firm’s preference in
these CSR projects?
4. What impact does the provision of a GP have on the relationship between CSR, firm
risk, and firm performance?
The rest of this chapter is organized as follows: Section 3.1 discusses the theoretical
arguments on why firms invest in CSR; Section 3.2 discusses the literature on the relationship
between CSR, executive compensation, and firm performance; Section 3.3 discusses the effect of
information asymmetry on CSR; Section 3.4 discusses the research design and hypothesis
13
According to Bloomberg, often, the largest portion of severance comes from accelerated payment of unvested stock options
and other stock units that would otherwise not be eligible for a payout – http://www.bloomberg.com/news/2013-06-06/goldenparachutes
90
development; Section 3.6 presents the hypothesis and empirical models; Section 3.7 discusses
the result and analysis.
3.1
Motives Behind CSR Engagements
The true motives of corporate managers that invest firm’s resources in CSR projects
remain a puzzle. Firms’ investments in CSR projects should not only be viewed as altruistic
engagements but also as a business strategy to improve profit. There are several compelling
theories that attempt to provide a better insight on why and how firms engage in CSR projects. In
this present study, four of these theories are discussed and examined.
First, the conflict resolution hypothesis stems from the stakeholder theory and states that
top managers use CSR as a device to develop and build good relationships with the firm’s
internal and external stakeholders. A good relationship with the employees could yield increases
in productivity. While a good relationship with the regulatory agencies and the community could
save the firm cost associated with litigation fees, consumer boycotts, reputation damage, and
regulatory fines. A good product quality also increases the likelihood of return satisfied
customers and a decrease in the costs associated with products defect.
Second, the overinvestment hypothesis suggests that top managers use CSR as a tool for
self-aggrandizement. This argument suggests that managers may overinvest in CSR projects to
satisfy a selfish desire to burnish their reputation as good global citizens at the expense of the
shareholders (Barnea and Rubin 2010; Goss and Roberts 2011). That is, managers may seek to
overinvest in CSR, regardless of its effect on shareholders wealth, for their private gains.
Consistent with the overinvestment hypothesis, some studies find a positive association between
CSR and CEO compensation (Cai, Jo and Pan 2011; Mahoney and Thorn 2006). Shareholders’
are weary of managers that overinvest in a social cause to enrich themselves.
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Third, the strategic-choice hypothesis posits that incumbent managers strategically
select in which CSR projects to invest. The motivation being a desire to generate likability and
support from environmental and social activists in order to reduce the manager’s employment
risk by decreasing the probability of future turnover (Cespa and Cestone 2007; Harjoto and Jo
2011). The strategic-choice hypothesis is centered upon the argument that when stakeholder
protection is entrusted upon the discretionary voluntary initiatives of mangers, the outcome could
result in an increase of managerial opportunism. Cespa and Cestone (2007) assert that relations
with social activists could become an effective entrenchment strategy for inefficient managers.
That is, in a desperate attempt to build a good relationship with social activists, the manager
could strategically choose to invest in selected CSR projects, even if doing so reduces
shareholders’ wealth. Such CSR projects could be in the form of donations to charitable
organizations that brings positive visibility to the manager, or funding costly overelaborated
campaign to promote diversity among the company’s workforce.
The costs associated with CSR projects are mostly immediate while the benefits are not
usually realized in the same time alignment. However, there could be some exceptions. For
instance, diversity is one of the qualitative measures used in evaluating a firm’s social
performance. Social pressure from the public or government agency could compel a firm to
adopt policies that promote diversity in its workforce. Such obligatory expectations could
restrain the firm’s ability to espouse merit when making employment decisions. That is,
candidates with superior talents might be overlooked if they don’t fall within the specifications
of the diversity promotion agenda. If merit is sacrificed to appease social pressure, it could
adversely affect firm performance. Hiring a lesser competent employee could result in reduced
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productivity, decline in product quality, meager creativity, increase in litigation risk, and other
cost attributably contrived by the hiring decision.
Of the many discussions and debates on CSR, some arguments are centered upon its
business imperatives. These arguments hinge on the economic value of CSR projects, resulting
in questions like: (1) Do firms that invest in higher CSR projects achieve higher, lower, or
similar degrees of firm performance relative to comparable firms that do not meet the same CSR
criteria? (2) Or is CSR a form of profits redistribution? (Lev, Petrovits and Radhakrishnan
2010). Some studies present arguments for CSR stating that it enhances firm financial
performance as it is geared towards building a better relationship with internal and external
stakeholders (Jones 1995; Margolis, Elfenbein and Walsh 2007). Others argue that not all
investment in CSR actions are directly linked to the core business operations of the firm. Some
CSR projects often go beyond explicit transaction interests of the firm’s business operations
(Godfrey, Merrill and Hansen 2009; Jayachandran, Kalaignanam and Eilert 2013; McWilliams
and Siegel 2000).
Fourth, the resource-based-view is often cited as the process through which CSR
engagement could generate financial benefits for the firm (Hart 1995b; McWilliams and Siegel
2001; Russo and Fouts 1997; Wernerfelt 1984). The benefits could be achieved through the
improvement of stronger and better relationships with customers (Brown and Dacin 1997)
enhancement of future revenue growth (Lev, Petrovits and Radhakrishnan 2010) motivated and
enhance employees’ morale which could increase productivity (Turban and Greening 1997),
increase investors support(Luo and Bhattacharya 2006), or by providing an ‘insurance like’
protection for the firm and its shareholders should incase a negative event occurs (Gardberg and
Fombrun 2006; Godfrey 2005). In sum, the resource based view posits that, by engaging in CSR,
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firms procure legitimacy in the public eye, which could be strategically capitalized upon to
enhance the firm’s value. A brief summary of these CSR hypotheses and their definitions is
tabulated in appendix E.
3.2
CSR, Executive Compensation and Firm Performance
Prior studies have examined the relationships between a firm’s social performance and
executive compensation (Cai, Jo and Pan 2011; Mahoney and Thorn 2006; Riahi‐Belkaoui
1992), cost of capital (El Ghoul et al. 2011; Goss and Roberts 2011) and financial performance
(Brammer, Brooks and Pavelin 2006; Dhaliwal et al. 2011; Di Giuli and Kostovetsky 2014;
Nelling and Webb 2009). In this present study I extend the previous literature by introducing the
golden parachute (GP). I posit that the presence of the GP alleviates the executive’s short-term
concerns and incentivizes him/her to maximize firm performance in the long-term. This should
significantly change the calculus of the findings in previous literature on CSR.
Executive compensation can serve as critical tool in aligning the interest of the manager
(agent) with that of the shareholders (owners). If well designed, it could also help in monitoring
the activities and steering the decisions of the manager. This monitoring tool could unintendedly
restrict the manager’s decision making; a restriction that could negatively and adversely affect
the degree of CSR commitment. With the uncertainty surrounding CSR payoffs, as evidenced in
literature, deciding or agreeing on the amount of resources to allocate to CSR engagements could
prove challenging for firms.
If there is a divergence in opinion between the manager and the shareholders views on
CSR commitment is significantly wide, this could infringe upon the flow and success of the CSR
campaign. A CSR commitment in excess of the shareholders’ willingness to commit could have
negative consequences for the manager if earnings targets are not met due to the cost of CSR
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investments. Thus, the manager might become reluctant in assuming the risk associated with the
uncertainty of CSR payoffs. Job security and compensation risk are some of the risks that
managers face.
Is the manager protected from these risks? The manager’s concerns about the
repercussion of assuming greater risk by investing in CSR engagements could be alleviated by a
type of compensation mechanism that insulates the manager from employment risk. A golden
parachute provision in the executive compensation contract requires that substantial benefits be
given to the manager in the event that his employment is terminated. With such a provision, the
manager could become more willing to explore and promote CSR investments. It is also
important to note that this newfound liberty could compel managers to invest in more valueenhancing CSR engagements.
A school of thought in finance and economics literature argues that long-term
compensation schemes are designed to focus the managers’ efforts on optimizing the long-term
goals of the firm. The long-term compensation strategy is expected to align and direct the
managers’ attention towards decisions that increases firm value in the long-run (Mahapatra
1984). Mahoney and Thorne (2005) find a relationship between long-term compensation and
CSR weakness, suggesting that firms that include long-term compensation in their executive pay
package are more likely to mitigate weaknesses in the product and environment dimensions of
the CSR measure.
Fixed and shorter incentive arrangements are presumably designed to focus the
managers’ attention on projects geared towards immediate term performance. Short-term
performance values are usually captured using retrospective accounting numbers (Mahoney and
Thorne 2005). On the other hand, a longer-term compensation arrangement is more focused on
95
the expectation that managers optimize the firm’s value in the long-run, thus, it should motivate
managers to invest in CSR engagements (Kane 2002). Longer term compensation arrangements
are usually based upon market valuation. When rightfully and efficiently implemented, CSR
investments could drive the value of the firm upwards.
There is no consensus in the literature on the impact of CSR on firm performance. There
is some evidence to suggest a positive association between a firm’s CSR engagements and its
financial performance (Barnett and Salomon 2006; Graves and Waddock 1999; Preston and
O’bannon 1997; Ruf et al. 2001). In contrast, some empirical studies present negative association
(Aupperle, Carroll and Hatfield 1985; Boyle, Higgins and Rhee 1997; Brammer, Jackson and
Matten 2012). Others find no association (Guerard Jr 1997; Moore 2001). A research conducted
on CSR-firm performance studies using meta-analysis further reveals the ambiguity and
conflicting empirical findings in literature (Margolis, Elfenbein and Walsh 2007). In the metaanalysis study, the authors investigated and documented the pattern of empirical findings and
arguments presented in literature on CSR-firm performance. They find that on average the
relationship between the two variables of interest are positive but weak. In their meta-analysis
study, 58 percent of the studies investigated showed no significant relationship between the
variables, while only 27 percent showed significant findings
The skepticism emanating from arguments centered upon the value-enhancing potentials
of CSR has compelled some to posit that it is antithetical to sound business practice as it dilutes
its focus on shareholders’ wealth creation (Clement-Jones 2005; Friedman 2007; Murray 2005).
However, advocates of CSR argue that it is necessary and vital for sustainable business
operations and thus imperative that firms look beyond narrow economic returns and embrace the
wider social impact of CSR (Rudolph ; Rudolph 2005).
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With the uncertainties surrounding the payoffs of CSR investments firms are faced with
the challenge of identifying an optimal level of resource(s) to commit to CSR investments. As
decisions makers, managers are drivers of CSR in their firms (Godos-Díez, Fernández-Gago and
Martínez-Campillo 2011). Occasionally, the manager should be willing to sacrifice corporate
goals, interest and needs in favor of socially responsible actions (Hunt, Kiecker, & Chonko,
1990; Quazi, 2003; Swanson, 2008; Wood, Chonko, & Hunt, 1986). As noted, with the
uncertainty surrounding CSR payoffs, as evidenced in literature, managers might become
reluctant in entertaining or pursuing CSR engagements. Hence, the need to alleviate the
manager’s personal concerns through a mechanism that somewhat insulates them from
employment and compensation risks, the GP.
3.3
CSR and Information Asymmetry
When one party in a transaction has more or superior information compared to another,
information asymmetry is present. The degree of a firm’s CSR commitment could be influenced
by the constraint of informational asymmetry. It could be that the agent (manager) has superior
information about the possible impact of CSR on firm value than the principal (shareholders).
The reverse could also be the case. This could result in a conflict of interest between the
managers and shareholders due to differing CSR vision and goals.
The manager’ and shareholders’ degree of willingness to commit to CSR might differ
significantly. The manager’s willingness to commit and invest in CSR might exceed or fail to
meet the shareholders desire to commit. For example, if the manager foresees a possible future
takeover attempt he/she might become motivated to embark on measures to increase or improve
the firm’s reputation which could translate to greater value during tender offer negotiation. The
improved firm value could also deter hostile takeover attempts. Conversely, drawing from the
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‘private information hypothesis’,14 a top manager who has private information that his or her
firm is likely to be acquired might aggressively seek and request for the inclusion of a GP in the
executive contractual agreement (Bebchuk, Cohen and Wang 2014a; Lambert and Larcker
1985). It is importance to note that this managerial impulse could be motivated by a selfish
desire to amass private wealth or it could be a strategic defense measure by the manager in
attempt to protect the interest of the shareholders.
3.3.1 CSR and Adverse Selection
In an acquisition of a firm by another it is essential that the target firm’s management and
its shareholders strategically employ measures to protect and maximizes the firm’s value.
Establishing a defense mechanism to either repel or negotiate a higher expected premium should
always be a focal strategic tool at the dispensation of the target firm. In addition to GPs, CSR
could be used as a mechanism to either repel or negotiate a higher premium. The improved
public image, good product quality, and other value adding attributes that CSR brings to the firm
could help increase the firm’s overall worth. This increase in firm value should position the firm
strategically to effectively repel a takeover (making the takeover too costly for the acquirer) or
negotiate a higher premium if the takeover is in the best interest of the target firm shareholders.
It could also be that the target firm, anticipating a tender offer from another firm, grants
or readjusts its manager’s GP in order to deter a possible takeover or position itself to bargain
and negotiate a higher premium. Whatever the case may be, this superior information might not
be ‘equally’ accessible or available to both the manager and owners of the firm at the same time.
Tender offers could be either friendly or unfriendly. Regardless of its character, friendly or
14
This hypothesis predicts that an executive may have superior information on the high likelihood of his/her firm to
receive tender offer(s) than suggested by publicly observation variables like: size, performance etc.
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unfriendly, it behooves the target firm to ensure that it is in an advantageous position to repel or
negotiate a higher premium. The strategic measure taken to include or readjust the GP in its
CEO’s contractual clause, by firms with a high a likelihood of being targets in a hostile corporate
takeover, can be viewed as an example of adverse selection.
3.3.2 CSR Moral Hazard
The insulation that the GP provides for managers could also produce unintended
consequences, resulting in a moral hazard problem. If the manager’s willingness to commit to
CSR is less than that of the shareholders when a GP is not part of the compensation
arrangements, then with the protection of a GP, the manager could become even less willing to
pursue CSR. The manager, knowing that the likelihood of getting fired is reduced due the
provision of GP, might take undue advantage of this protection and start shirking. The manager
could also overinvest in CSR projects that might not necessarily increase shareholders’ wealth
but improve the manager’s private gains (..e.g reputation and image building). Jensen and
Murphy (1990b) assert that firm business strategies which increase (decrease) the firm’s market
value by millions of dollars may only marginally affect the financial benefits of the managers.
Thus, a self-serving manager’s concern about the probable negative impact of a CSR decision on
his or her financial welfare might be insignificant compared to the negative impact the CSR
decision could have on the shareholders’ wealth.
3.4
Research Design and Hypothesis Development
In the empirical analysis of the above arguments, I will proceed in the following manner.
First, I examine the risk tolerance behavior of the firms and the sensitivity of the manager’s
compensation to firm performance. Next, I will examine the relationship between CSR and firm
performance. If this relationship is positive, then is it expected that the provision of the GP
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should incentivize managers to pursue more value-enhancing CSR projects that maximizes firm
financial performance and value of the GP (stock options granted). If the relationship is negative,
then it is expected that the GP empowers the manager to reduce or completely eliminate valuedestroying CSR projects. This could also mean that, in the presence of overinvestment, the
provision of the GP incentivizes the manager to move towards achieving an optimal level of
CSR engagement that positively maximizes firm performance.
3.4.1 Firms’ Risk-taking
The willingness and capacity of firms to undertake risk differ across corporations and is
somewhat unique to firms’ business environment and leadership structure. The top management
of a firm significantly influences the company’s risk-taking decisions. It is crucially important to
stress that the propensity of managerial risk-taking varies across firms. Managers associate risktaking with the expectations of their jobs, hence the import of a personal predilection(March and
Shapira 1987). Risker operations could produce volatile returns which could expose the firm
and its shareholders to more uncertainties. The uncertainty surrounding CSR payoffs could
increase (decrease) a firm’s risk exposure levels. Thus potentially stretching the threshold of the
firm’s risk tolerance level. The decision making of the top manager plays a critical role in
establishing and maintaining this risk threshold. Therefore, it is important to take into account
the risk-taking capacity and willingness of firms from the lens of the managers.
Top managers compensation and incentive structures could induce changes in
investments and leverage policies of the firm, which theoretically should have an impact on the
future risk of the firm and its equity (Baber, Janakiraman and Kang 1996; Gaver and Gaver
1993; May 1995; Rajgopal and Shevlin 2002; Smith Jr and Watts 1992; Tufano 1996). The
golden parachute alleviates the manager’s concerns about job security. This could increase the
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manager’s willingness to undertake more risky business decisions. In this study I examine the
impact of the provision of the GP on the relationship between the firm’s risk-taking behavior and
the CEO pay-to-performance sensitivity, and how this affects the CSR decisions and firm
performance. To do so, I adopt the pay-for-performance sensitivity model by Jensen and
Meckling (1976), which was later modified in Schaefer (1998) with the introduction of industry
effects.
The capacity and willingness to undertake risk could differ significantly across firms and
industries. In pursuit of profit, risk is a necessary factor that a firm must consider in its business
operations. The type and amount of risk a firm is willing to undertake could substantially
influence its profit. In general, firms strive to undertake risks to the extent that it is valueenhancing. The conflicting evidence in literature on the value-adding tendency of CSR projects
complicates or makes more complex the firm’s risk-taking decisions. The top manager bears a
significant portion of the decision making burden on what type of risk the firm should undertake,
and how much of this risk should it assume. It is important to examine the relationship between
CSR and firm risk-taking.
For the purpose of this study, the proxy for risk taking is derived as the standard
deviation of the firms’ earnings (EBITDA) scaled by the average value of its total assets. This
proxy is employed to capture a firm’s degree of risk-taking in its business operations based on its
earnings. First, in line with prior studies on similar topic, a proxy for firms’ earnings volatility is
used. This is defined as the square root of the average squared deviation of the earnings data
from its mean earnings (Brick, Palmon and Wald 2012; Coles, Daniel and Naveen 2006; Core
and Guay 1999). The standard deviation (SD) of the firms’ earning returns is derived in the
equation below:
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1
2
𝜎 = √𝑁−1 ∑𝑁
𝑖=1(𝑥𝑖 − 𝑥̅ )
(3.1)
Where σ is the firm standard deviation, xi is firm earnings values, x̅ is the mean of the
firm earnings values for the number of years observed, and N is the number of the observations
for each firm over the number of periods (years) observed in the sample.
In the next equation the standard deviation (σ) of the firm is divided by the average asset
value.
𝜎
𝐴𝑇
+ 𝐴𝑇𝑡
( 𝑡−1
)
2
(3.1.2)
Where AT is firm Total Asset for the preceding year (t-1) and present (t)
For the industry classification, the Fama and French (1997) 48 industry groupings is
employed. This industry classification is widely used in finance literature (Chan, Lakonishok and
Swaminathan 2007; Daniel and Titman 2006; Flannery and Rangan 2006; Graham and Kumar
2006; Hong, Torous and Valkanov 2007; Pástor and Stambaugh 1999), economics literature
(Bebchuk and Grinstein 2005; Wulf 2002), and accounting literature (Chan, Frankel and Kothari
2004; Francis et al. 2005).
3.4.2 CEO Pay-For-Performance Sensitivity
When compensation is based on the pay-for- performance principle it could be effective
in inducing a higher level of managerial efforts and productivity. However, it is important to note
that pay-for-performance sensitivity encourages managerial repetition of only those actions and
decisions that has produced success in the past. This behavior could hamper creativity,
innovations, and other similar projects like CSR which may produce an uncertain payoff
outcome. The non-guaranteed payoffs of CSR projects might elevate managerial concerns about
102
probable negative consequences that might result in investing in CSR projects. Such
consequence could increase the probability of an undesirable outcome that affects the manager’s
compensation and job security. The presence of a GP could alleviate this managerial concern,
which should result in increase in managerial willingness to promote and undertake more valueenhancing projects like CSR.
Some studies argue that cash base salaries provide an incentive for managers to be more
risk-averse, thereby inducing managers to act in the interest of bondholders (Brick, Palmon and
Wald 2012; Haugen and Senbet 1981; Jensen and Meckling 1976). However, given that the
provision of GP alleviates managerial concerns about compensation and employment risk, this
research argues that the firm’s risk-taking behavior could increase with the presence of a GP.
This study predicts that the pay-for-performance sensitivity should increase with the presence of
the GP. This change is expected to the extent that CSR increases firm value. In the presence of a
GP clause, a negative impact of CSR on firm value should result in a greater managerial
departure from CSR engagements. It is also important to note that the effect of CSR on firm
performance is particularly important to the executive with a GP. An increase in stock price
increases the premium on the executive’s stock option grants.
In examining pay-for-performance sensitivity, Schaefer (1998) modified an earlier linear
model by Jensen and Meckling (1976). This modification introduced a control for industry effect
as shown in equations 3.1.3 and 3.1.4. As an extension of this equation, this research will include
the presence of a golden parachute as moderating variable in the equation. The beta coefficients
are estimated and examined to show the linkage between firm value and the extent to which the
manager’s compensation (wealth) depends on the wealth of the firm’s shareholders. That is, the
degree to which changes in the firm’s value (performance) impacts the manager’s compensation.
103
Equation 3.1.3 is the linear regression model by (Schaefer 1998), while equation 3.1.4 includes
the presence of the GP as introduced by the present study:
Δ (wage)it = α0 + α1Δ (firm value)it + α2(Industry Effect)it + εit
(3.1.3)
Where wage is the CEO salary and firm value is total market value
Δ (wage)it =
α0 + α1Δ (firm value)it + α2(GP) + α3(GP)* α4Δ(firm value)it + α5(Industry Effect)it + εit
(3.1.4)
Where wage is the CEO salary plus bonus (ΔCComp) and firm value is total market
value. GP is binary variable that takes the value of one if the CEO is endowed with a GP clause
and 0 if a GP is not included in the compensation package. I also run a regression substituting
change in long-term compensation (ΔLComp) and change in total compensation (ΔTComp) for
the dependent variable.
Table 3.1 examines the effect of the GP on the pay-to-performance sensitivity. The GP is
interacted with the change in firm value (ΔFirm Value_GP). The results in all the regression
models suggest that the presence of the GP exacerbates the sensitivity of the CEOs’ wealth to
firms’ earnings. When change is salary (ΔSalary) is used as the dependent variable, the GP
increases the pay-to-performance sensitivity 0.06733. When change is salary plus bonus
(ΔCComp) is used as the dependent variable, the presence of the GP increases the pay-toperformance sensitivity by 0.07566. When change is long-term plus compensation (ΔLComp) is
used as the dependent variable, the presence of the GP increases the pay-to-performance
sensitivity by 0.87166. When change is total compensation (ΔTComp) is used as the dependent
variable, the GP increases the pay-to-performance sensitivity by 0.94732.
Table 3.1
Pay-For-Performance Sensitivity
WAGE 1
Δ Salary
VARIABLES
Δ Salary
Δ Firm Value
0.074507***
(5.98)
0.03038***
(3.42)
Δ CComp
WAGE 2
Δ CComp
0.11394***
(6.49)
0.06439***
(3.40)
Δ LComp
WAGE 3
Δ LComp
1.00487***
(6.03)
0.43473***
(4.92)
Δ TComp
WAGE 4
Δ TComp
1.11881***
(6.60)
0.49912***
(5.19)
GP
0.00982**
(1.87)
0.00182**
(2.09)
0.21472*
(3.14)
0.21654**
(2.41)
Δ Firm Value _ GP
0.06733***
(3.36)
0.07566*
(2.42)
0.87166***
(4.02)
0.94732***
(4.28)
R2
0.1801
0.1946
0.1624
0.1753
0.1613
0.1846
0.1904
0.1959
Observations
13,295
13,295
13,295
13,295
13,295
13,295
13,295
13,295
Robust t-statistics is in parenthesis. ***p<0.01, **p<0.05, *p<0.1; Wage 1, 2 and 3 are the different proxies for CEOs’ wealth employed. ΔSalary is the change in CEOs’ annual salary. ΔCComp is the
change in CEOs’ salary plus bonus. ΔLComp is the change in the CEOs’ long-term compensation. ΔLComp is the change in the CEOs’ total compensation. The t value is reported in parenthesis. GP is
binary variable that takes the value of one if the CEO is endowed with a GP clause and 0 if a GP is not included in the compensation package. I also run a regression substituting change in long-term
compensation (ΔLComp) and change in total compensation (ΔTComp) for the dependent variable. Δ (wage)it = α0 + α1Δ (firm value)it + α2(GP) + α3(GP)* α4Δ(firm value)it + α5(Industry Effect)it + εit
Overall, these results suggest that the provision of the GP stimulates CEOs to be more risk tolerant. Highly risky projects could
significantly enhance firm value when the outcome is good. It could also significantly erode firm value when the outcome is bad.
Motivated by the desire to maximum private wealth, the CEOs’ increase in risk-taking could be as a result of the insulation that the GP
provides against job loss. The likelihood of a CEO getting fired is significantly reduced when the CEO has a GP. Bebchuk, Cohen and
104
105
Wang (2014a) postulate that the GP places a hefty cost burden on the paying firm and
directly depletes funds available for business operations.
3.4.3 Hypotheses and Empirical Models
If the conflict resolution theory is true, then a manager could use CSR as an effective
tool to develop good relations with the employees, good environmental policy, and good
product quality. This could result in high employee morale, increased productivity, and
improved firm reputation. Consequently, these intangible and tangible benefits could drive
the value of the firm upwards, increasing profitability. This leads to a hypothesis predicting a
positive association between CSR and firm performance. In this case, the presence of a GP
should amplify this positive effect on firm performance. That is, the GP should further
stimulate the manager by alleviating the short-term concerns associated with short-term
earnings target. The GP should also incentivize the manager to strive towards making
decisions aimed at maximizing the stock value in the long-term, which should maximize the
premium on the executive stock options grants.
H1a: There is positive association between CSR and firm performance, β1 > 0
H1b: This association is positively amplified with the provision of a GP, β3 > 0
Alternatively, if the overinvestment theory is true, then managers could use CSR as a
tool to enhance their personal reputation and other private gains, even if this is to the
detriment of the shareholders’ interest. This could also mean that managers would increase
firm’s CSR projects for as long as it improves their private gains. The anticipation of such
behavior from managers leads to the next hypothesis which predicts a negative association
between CSR and firm performance. If such is the case, the provision of a GP should
mitigate this negative effect on firm performance. A negative effect on stock price would
106
negatively affect the value of the stock option in the GP contract, an undesirable outcome
that managers with a GP would greatly detest.
H2a: There is a negative association between CSR and firm’s performance, β1 < 0
H2b: The presence of a GP mitigates the negative association between CSR and
firm performance, β3 > 0
𝑅𝑂𝐴𝑖𝑡 = 𝛼 + 𝛽1 𝐶𝑆𝑅_𝑁𝐸𝑇𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝑆𝑅_𝑁𝐸𝑇𝑡−1 ∗ 𝐺𝑃 + 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 +
𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + ∑𝑛𝛽=1 𝛼𝑋𝑖𝑡 + 𝜀𝑖𝑡
(3.1.5)
Where ROA is the firms’ performance measured as Earnings before Interest Expense
and Taxes (EBIT) scaled to the firms’ total asset value. CSR_NET is the one year lag of the
sum of total strengths minus the sum of total concerns; GP is a binary variable that takes the
value of one if the CEO has a GP in his compensation contract and Zero if otherwise. X is the
set of control variables, and ε = error term.
The uncertainty surrounding the payoffs of CSR projects could add to the firm’s risk
in its business operations. Arguments can also be made that CSR investments that improves
product quality, employee relationships, and protect the environment should lead to reduction
in the cost associated with product defect, litigation fees, and regulatory fines. Thus, valueenhancing CSR investments can reduce firm risk. The incentivizing capacity of the GP
should compel the executive to apply judicious prudence when making decisions on CSR
projects. That is, the manager will only promote value-enhancing CSR projects. When
managers benefit financially from “doing good” the desire to pursue more socially
responsible projects increases. In contrast, when managers suffer financially from investing
in CSR project, then, the willingness to promote such investments decreases. Therefore,
managers will seek to approve of mostly those socially responsible projects with the greatest
107
likelihood of bringing financial benefits. As the outcome of such decision has a direct impact
on the executive’s future wealth.15
This leads to the next hypothesis which predicts a negative association between CSR
and firm risk if conflict-resolution is the case. This could be as a result of reduction in cost
associated with employee turnover, regulatory fines, reduction in product defects and
improved product quality. I expect that the provision of a GP should further affirm/amplify16
this effect.
H3a There is a negative association between CSR and firm risk, β1 < 0.
H3b: The presence of a GP amplifies the negative association between CSR,
firm risk, β3 < 0.
𝑅𝑖𝑠𝑘𝑖𝑡 = 𝛼 + 𝛽1 𝐶𝑆𝑅_𝑁𝐸𝑇𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝑆𝑅_𝑁𝐸𝑇𝑡−1 ∗ 𝐺𝑃 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + ∑𝑛𝛽=1 𝛼𝑋𝑖𝑡 + 𝜀𝑖𝑡
(3.1.6)
Where Risk is the standard deviation of the firms’ earnings (EBITDA) scaled by the
average of total assets (Brick, Palmon and Wald 2012; Coles, Daniel and Naveen 2006). CSR
_NET is the one year lag value of the sum of total strengths minus the sum of total concerns,
X is the set of control variables, and ε is the error term.
15
According to Bloomberg, often, the largest portion of severance comes from accelerated payment of unvested
stock options and other stock units that would otherwise not be eligible for a payout –
http://www.bloomberg.com/news/2013-06-06/golden-parachutes
16
For the purpose of this study, the term ‘amplify’ is defined as the increasing (strengthening) effect on the
coefficient of the independent variables that result to a stronger impact in influencing the behavior of the
dependent variable in the regression analysis.
108
In contrast, if the overinvestment hypothesis is true and the manager increases valuedestroying investment in CSR projects for personal gains, there should be a positive
association between CSR and firm risk. An unconscientious self-serving manager might
choose to make large donations to charitable organizations instead of investing in CSR
projects that improve employees’ morale, reduction in pollution emission, and improvement
in product quality. This displacement of firm priorities could increase the firm exposure to
risk of incurring regulatory fines, low productivity, increase in cost associated with product
defects and low product quality, and difficulty attracting and retaining talented employees.
In this case, the provision of a GP should mitigate this negative effect on firm performance.
A positive association between the volatility of firms’ earnings and CSR investments
could also be as a result to the inherit uncertainty surrounding the CSR payoffs. As evidenced
and documented in prior literature, some studies show that CSR is positively associated with
firm performance. That is, the greater the firm’s investment in CSR, the higher the firm’s
performance (Barnett and Salomon 2006; Eccles, Ioannou and Serafeim 2012; Graves and
Waddock 1999; Preston and O’bannon 1997; Ruf et al. 2001). Some find negative
association (Boyle, Higgins and Rhee 1997; Brammer, Jackson and Matten 2012; Krueger
2013; Moore 2001; Shane and Spicer 1983; Wright and Ferris 1997). Others find no
association (Aupperle, Carroll and Hatfield 1985; Bauer, Koedijk and Otten 2005; Guerard Jr
1997). This conflicting findings, establishes the uncertainty of a probable financial payoff
when firms invest in CST projects. Consequently, it can be argued investment CSR projects
constitute a risk to the firm. Thus, I hypothesize a positive association between CSR and
firms’ risk.
H4a: There is a positive association between CSR and firm risk, β1 > 0.
109
H4b: The GP mitigates the positive association between CSR and firm risk, β3 < 0.
𝑅𝑖𝑠𝑘𝑖𝑡 = 𝛼 + 𝛽1 𝐶𝑆𝑅_𝑁𝐸𝑇𝑡−1 + 𝛽2 𝐺𝑃𝑖𝑡 + 𝛽3 𝐶𝑆𝑅_𝑁𝐸𝑇𝑡−1 ∗ 𝐺𝑃 +
𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + ∑𝑛𝛽=1 𝛼𝑋𝑖𝑡 + 𝜀𝑖𝑡
(3.1.7)
Where Risk is the standard deviation of the firms’ earnings (EBITDA) scaled by the
average of total assets (Brick, Palmon and Wald 2012; Coles, Daniel and Naveen 2006). CSR
_NET is the one year lag value of the sum of total strengths minus the sum of total concerns,
X is the set of control variables, and ε is the error term.
3.5
Data Sample
The data samples selected for this study were collected from the following sources:
MSCI ESG STATS (formerly Kinder, Lydenberg, Domini Research & Analytics, Inc) for
CSR measures, Risk Metrics (formerly known as IRRC) for golden parachute and
governance measures, COMPUSTAT for financial and accounting measures.
Founded in 1988, for over two decades, Kinder, Lydenberg, Domini Research &
Analytics Inc (KLD) has been providing benchmarks, analysis, research, compliance, and
consulting services related to social, governance, and environmental practices. KLD is a
leading authority and data provider of social research for institutional investors.17 Considered
as the standard for CSR measures, the KLD data has been extensively adopted by numerous
scholars and research studies (Deng, Kang and Low 2013; Di Giuli and Kostovetsky 2014;
Jiao 2010; Nelling and Webb 2009; Waddock and Graves 1997). It is important to note that,
in their earlier publication, KLD data covered S&P 500 companies.
17
In 2009, KLD was acquired by RiskMetrics, and is now a subsidiary of MSCI, a leading provider of indices and
institutional products and services.
110
To broaden its coverage, in 2003 KLD began following and analyzing the social
performance of Russell 3000 companies. The methods of assessment encompass thirteen
different CSR dimensions. These dimensions are further classified into two key categories,
qualitative and controversial business issues areas: The qualitative issue areas consist of
seven indicators, namely: community, diversity, employee relations, environment, product
characteristics, human rights, and corporate governance. While the controversial issues areas
consist of six indicators, namely: firearms, alcohol, gambling, tobacco, military, and nuclear
power. For the qualitative areas, a binary scoring system (0/1) is used to assign points for
every strength (positive) and concern (negative). This is similarly same for the controversial
areas except that it only rates concerns. Assigning negative ratings with a binary system for
whether a firm is involved in one or more concerns. These characteristics are shown in
Appendix D.
In this study, five of the qualitative measures of CSR are employed, namely:
Community, Diversity, Employee Relations, Environment, and Product Quality & Safety. To
generate the CSR net score variable, the total strengths score of these five qualitative
measures is subtracted from the total concerns score.
3.5.1 Measurement of the Main Dependent Variable
Return on Assets (ROA) is a widely used proxy to measure firm performance
(Eisenberg, Sundgren and Wells 1998; Fahlenbrach and Stulz 2011; Li, Sun and Ettredge
2010). A firm’s ROA measures managerial efficiency in generating earnings for its
shareholders while using firm’s assets. In essence, it shows current and potential investors
what earnings are generated from invested capital (assets). In this study, I compare regression
results using different measures of firm performance. This should provide a more robust
111
insight on the empirical findings on the association between CSR and firm performance, and
the effect of the GP on this relationship. Below is the formula for deriving a firm’s ROA:
𝑅𝑂𝐴 =
EBIT
Total Assets
(3.1.10)
Where ROA is the firms’ performance measured as Earnings before Interest Expense
and Taxes (EBIT) scaled to the firms’ total asset value.
3.5.2 Measurement of the Main Independent Variables
In this study I follow the approach commonly used in similar studies on executives’
compensation, corporate social responsibility, and firm performance; however, I extend prior
studies in multiple ways. Frist, I examine the effects of a special kind of contractual clause
(golden parachute) in the executive compensation package on managerial decisions on
socially responsible policies and firm performance. Second, I segregated the CSR measures
into internal and external social factors. The former is concerned with those socially
responsible activities that are internal to the firm in enhancing the quality of its immediate
work environment and product. The CSR factors that fall into this classification are:
Employee relations, Product Quality & Safety, and Diversity. The latter is concerned with
those CSR factors that are more of the external socially responsible activities the firm choose
to engage in beyond the minimum legally required by law. The CSR factors that fall into this
classification are community and environment.
The CSR factors might not actually be equally important. I argue that the relative
degree of importance to firm performance should somewhat differ between internal and
external socially responsible factors. More than the latter, the former should have a more
direct and immediate impact on firm operating performance. A manager who is trying to
112
maximize the premium on his stock options might focus more on the internal socially
responsible actions that facilitates a more immediate enhancement of operating productivity.
By engaging in socially responsibly projects a firm could enhance its employees’ motivation
and morale, which should improve productivity and product quality. Berk, Stanton and
Zechner (2010) postulates that employees that develop a good relationship with the firm may
accept low compensation when working for good reputation firms. All these factors should
positively enhance the value of the firm, which also enhances the value of the executive stock
options in the golden parachute.
The changes in the mix of executives within a particular firm during the sample time
period could present a potential confounding challenge in the analysis. Therefore, I delete
those firms with missing data, CEO changes within a given year, and firms with significant
changes in ownership. After deleting the utility and financial firms, and firms with missing
data, the data sample reduced from 18,309 yearly observations to 13,295. The number of
firms also reduced from 1,814 to 1, 225 for the period 1992 through 2013. For parsimony,
CUSIP and PERNO where used to merge the different data sources.
3.5.3 Control Variables
Consistent with prior studies in corporate finance on similar topic, I control for firm
size (LogSize), leverage, capital expenditures (CAPEX), performance (CF), and firm age
(RETE). Studies have argued that firms’ size and financial performance are viewed as
important economic determinants linked to executive compensation levels (Core, Holthausen
and Larcker 1999; Cuñat, Gine and Guadalupe 2013; Mehran 1995) and could significantly
influence a firm’s capacity to invest in CSR (Greening and Turban 2000; McWilliams and
Siegel 2000; Nelling and Webb 2009). Size is measured as the natural logarithm of total
113
sales. Average debt ratio is measured as the beginning plus ending debt to equity ratio
divided by two. A more detailed definitions of these variables is tabulated in Appendix B.
I capture firm’s age (maturity stage) using a life-cycle proxy: ratio of retained
earnings to book value of common equity (RETE). According to the life cycle hypothesis, the
early stages of a firm’s life cycle present more growth opportunities. The firm, at this stage,
usually has limited access and ability to generate sufficient internal capital to finance its
projects. Access to external funding can also present its own challenges thus the need for
firms at this stage of their life-cycle to avoid injudicious allocation of scarce resources. After
a period of growth, the firm matures as it becomes older, larger and with higher retained
earnings. At this stage, the cash (free cash flow) internally generated is usually higher than
can be profitable reinvested.
3.6
Result and Analysis
This section presents the results of the regression models. The implications are
discussed and analyzed.
3.6.1 Descriptive Statistics and Correlation Analysis
In tables 3.2 and 3.3 on pages 114 and 115 the summary statistics and correlation
matrix are presented. After merging all five databases and deleting missing variables,
including financial and utility firms, the final sample size shrunk to 13,295 observations. The
pairwise correlation matrix of all variables employed shows that none of the variables are
highly collinear, as such pass the first stage multi-collinearity test. I also performed the
Variance Inflation Factor (VIF) test after each regression. The maximum VIF score observed
in any regression model was 3.42. This result is well below the threshold of 10. As such, the
regression model does not suffer from multi-collinearity problems.
114
Table 3.2
Essay 2: Summary Statistics
Variable
ROA
Obs
13295
Mean
0.154586
Std. Dev.
0.092768
Min
-1.690588
Max
1.183424
CSR_NET
13295
0.059647
2.955078
-9
18
LogSize
13295
7.808722
1.512499
3.13105
13.05458
Debt
13295
0.209471
0.171826
0
2.925137
CAPEX
13295
0.053696
0.053754
0
0.557887
CF
13295
0.138683
0.090174
-1.690588
1.090199
RETE
13295
0.656801
0.558565
0.5717035
1.859288
AGE2
13295
0.093945
0.291763
0
1
GENDER_F
13295
0.031365
0.174309
0
1
13295
0.662881
0.472744
0
1
CSRST
GP
13295
2.200602
3.007613
0
22
CSRCN
13295
2.140955
2.098805
0
16
The dependent variable is Return on Asset (ROA). CSR_NET is defined as total CSR strengths minus total CSR concerns. CSRT is the total
number of strengths for the qualitative measures of CSR, while CSRCN is the total number of concerns. Debt is the ratio of total debt to
common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle proxy
used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that
represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F
is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a
GP and 0 if otherwise
3.6.1 Regression Analysis
Table 3.4 on page 116 presents the pooled regression analysis that examines the
association between CSR_NET and ROA. The results suggest that CSR_NET is positively
associated with ROA is all three regression models. Across all models, the positive
coefficients show that an increase in CSR_NET increases ROA. Regressions were also ran
using multiple proxies for firm performance and the results were similar. Specifically, for
robustness check, Tobin’s Q, Return on Equity, Return on Sales and Operating Performance
all produced similar results.
Table 3.3
Essay 2 Pairwise Correlation Matrix of All Variables
ROA
CSR_NET
LogSize
Debt
CAPEX
ROA
1.0000
CSR_NET
0.0969*
1.0000
LogSize
0.0938*
0.2168*
1.0000
Debt
-0.1250*
-0.0049
0.2217*
1.0000
CAPEX
0.2120*
-0.0477*
0.0023
0.0358*
1.0000
CF
0.9317*
0.0679*
0.0610*
-0.1372*
0.2272*
CF
RETE
AGE2
GENDER_F
GP
CSRST
CSRCN
1.0000
RETE
0.2959*
0.1117*
0.2616*
0.0314*
0.0089
0.2422*
1.0000
AGE2
-0.0144*
-0.0470*
-0.0702*
-0.0489*
-0.0320*
-0.0181*
-0.002
1.0000
GENDER_F
-0.0042
0.1036*
0.0103
-0.0138
-0.0129
-0.0063
-0.0019
-0.0476*
1.0000
GP
-0.0499*
-0.0108
-0.0580*
0.0594*
-0.0788*
-0.0325*
-0.0400*
-0.0845*
0.0170*
1.0000
CSRST
0.0676*
0.7523*
0.5658*
0.0773*
-0.0392*
0.0233*
0.1606*
-0.0693*
0.0927*
-0.0528*
1.0000
CSRCN
-0.0394*
-0.3299*
0.5055*
0.1176*
0.0111
-0.0623*
0.0728*
-0.0332*
-0.0129
-0.0606*
0.3737*
1.0000
The main dependent variable is Return on Asset (ROA). CSR_NET is defined as total CSR strengths minus total CSR concerns. CSRT is the total s numbers of strengths for the qualitative measures of
CSR, while CSRCN is the total number of concerns. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow,
RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is
≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy
variable that takes the value of 1 if the firm has a GP and 0 if otherwise
These results are significant at the 1% level. Model I presents the regression without the GP variable. Model 2
115
introduces the GP variable. Model 3 includes the interaction between the GP and CSR_NET to the regression. To test for the effect of
116
the presence of the GP, the GP variable is interacted with CSR_NET, the resulting variable is
CSR_NET_GP. The statistically significant coefficient of the CSR_NET_GP, 0.0004,
suggests that the presence of the GP contributes significantly to the positive association
between CSR_NET and ROA. This result is consistent with the expectation predicted in
hypothesis H1a and H1b. The joint significance test validates that CSR_NET and GP jointly
increases ROA. The F statistics is 28.71 at the 1% significance level. This is clearly more
than sufficient to reject the null hypotheses.
The firms’ size (LogSize), cash flows (CF), and firm age (RETE) are all positively
associated with ROA in table 3.4. These results are statistically significant at the 1% level.
The firms’ debt to equity (Debt), CEO tenure (Tenure1), and GENDER_F are all negatively
associated with ROA. These results are statistically significant at the 1% level. When
GENDER_F is interacted with GP the results also produced an inverse relationship,
suggesting that for those firms whose female CEOs are endowed with the GP clause the
associations between GENDER_F and ROA is negatively exacerbated. The test for the
association between CEO’s age and Q is positive but not statistically significant.
Table: 3.4
Association between CSR_NET and ROA
VARIABLES
CSR_NET
LogSize
Debt
Model 1
ROA
Model 2
ROA
Model 3
ROA
0.00059***
(6.2983)
0.00070***
(2.7623)
0.01118***
0.00058***
(6.0713)
0.00064**
(2.5296)
0.01025***
0.00031*
(1.8462)
0.00064**
(2.5539)
0.01022***
117
Table: 3.4 (Cont.)
Association between CSR_NET and ROA
VARIABLES
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
ROA
Model 2
ROA
Model 3
ROA
0.01817
(1.5545)
0.93046***
(38.8704)
0.00988***
(9.6526)
0.00011***
(-2.9910)
0.00365***
(-2.6083)
0.00140
(1.4943)
0.01621
(1.3965)
0.93071***
(38.9372)
0.00980***
(9.6371)
0.00013***
(-2.8215)
-0.00357**
(-2.5718)
0.00151
(1.0497)
0.00374***
(-5.3516)
-0.00003
(-0.4081)
13,295
0.8830
13,295
0.8833
0.01618
(1.3875)
0.93077***
(38.9215)
0.00974***
(9.5856)
0.00013***
(-2.8263)
0.00687*
(1.8925)
-0.00055
(-0.2780)
0.00367***
(-4.7405)
-0.00000
(-0.0416)
0.00041**
(2.2074)
0.01462***
(-3.8946)
0.00298
(1.5606)
13,295
0.8835
GP
AGE2_Tenure1
CSR_NET_GP
GENDERGP_F
GP_AGE2
Observations
R-squared
Robust t-statistics is in parentheses. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is Return on Assets (ROA). The main independent
variable is CSR_NET. CSR_NET_GP is the interacted term between GP and CSR_NET. Debt is the ratio of total debt to common equity,
CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle proxy used to capture
firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable that represents the CEO
age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F is dummy variable
that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise.
GENDERGP_F is the interacted term between GENDER_F and GP. GP_AGE2 is the interacted term between AGE2 and GP. I present the
results of the following regression model: 𝑅𝑂𝐴𝑖𝑡 =α+𝛽1 𝐶𝑆𝑅_𝑁𝐸𝑇𝑡−1 + 𝛽2 𝐿𝑜𝑔𝑆𝑖𝑧𝑒𝑖𝑡 + 𝛽3 𝐷𝑒𝑏𝑡𝑖𝑡 + 𝛽4 𝐶𝐴𝑃𝐸𝑋𝑖𝑡 + 𝛽5 𝐶𝐹𝑖𝑡 + 𝛽6 𝑅𝐸𝑇𝐸𝑖𝑡 +
𝛽7 𝐴𝐺𝐸2𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝐺𝐸𝑁𝐷𝐸𝑅_𝐹𝑖𝑡 + 𝛽10 𝐺𝑃𝑖𝑡 + 𝛽11 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽13 𝐶𝑆𝑅𝑁𝐸𝑇 𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + + 𝛽13 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗
𝐺𝑃𝑖𝑡 + 𝛽14 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
The negative association between Debt and ROA could be as a result of a substantial
increase in debt, which could potentially lower the firms’ revenue. This might be due to the
118
increase in the money needed to service that debt. However, if the acquired debt is used to
enhance production and this leads to significant rise in revenues, then the substantial increase
in debt may positively enhance ROA. Notably, a caveat in the debt and ROA relationship
depend on whether the cost of debt places a hefty burden on the firm financial structure thus
significantly cutting into the net income. That is, if the firms’ debt financing of operations
increases revenue, but net income declines due to the increased expense, then ROA would be
negatively impacted.
In table 3.5 in page 119 CSR_NET is replaced with CSR total strengths score
(CSRST) as the main independent variable. The results suggest that CSRST is positively
associated with ROA in all the regression models. When the moderating effect of the GP on
the association between CSRST and ROA is examined the results is statistically significant at
the 10% significance level.
The test for the joint association of the GP and CSRST on firm performance validates
the result which suggests that these two variables jointly enhance ROA. The statistically
significant coefficient of the interaction term, CSRST_GP, is 0.00031. This shows how much
the presence of the GP positively affects (increases) the association between CSRST and
ROA. The control variables maintain their respective relationships with ROA as produced in
table 3.4.
In table 3.6 CSR total concerns score (CSRCN) is employed as the main independent
variable. The test for the association between ROA and CSRCN is not statistically significant
across all regression models in the table. The interacted term, CSRCN_GP, produced a
negative coefficient, however, this is not statistically significant. The regression also suggest
that, in isolation, CSR concerns are not directly associated with firm performance.
119
Table 3.5
Association between CSR Total Strengths
(CSRST) and ROA
VARIABLES
CSRST
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
ROA
Model 2
ROA
Model 3
ROA
0.00092***
(7.4783)
-0.00014
(-0.4347)
0.01066***
(-3.6034)
0.01851
(1.5791)
0.93167***
(38.7718)
0.00988***
(9.6347)
0.00011***
(-2.8315)
0.00386***
(-2.7663)
0.00139
(1.4895)
0.00088***
(6.9864)
-0.00016
(-0.4790)
0.00981***
(-3.3754)
0.01667
(1.4334)
0.93185***
(38.8344)
0.00981***
(9.6270)
0.00012***
(-2.6444)
0.00375***
(-2.7121)
0.00156
(1.0860)
0.00354***
(-5.0048)
-0.00003
(-0.4476)
13,295
0.8832
13,295
0.8835
0.00067***
(3.6656)
-0.00013
(-0.3845)
0.00974***
(-3.3435)
0.01650
(1.4144)
0.93191***
(38.8119)
0.00976***
(9.5716)
0.00013***
(-2.7023)
0.00621*
(1.7063)
-0.00057
(-0.2889)
0.00418***
(-4.0710)
-0.00000
(-0.0491)
0.00031*
(1.7599)
0.01393***
(-3.6973)
0.00302
(1.5788)
13,295
0.8837
GP
AGE2_Tenure1
CSRST_GP
GENDERGP_F
GP_AGE2
Observations
R-squared
Robust t-statistics is in parentheses. ***p<0.01, **p<0.05, *p<0.1; The dependent variables are Return on Assets (ROA). The main
independent variable is the one year lag of CSR Total Strengths (CSRST). CSRST _GP is the interacted term between GP and CSRST. Debt
is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow,
RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2
is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO
of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the
value of 1 if the firm has a GP and 0 if otherwise. GENDERGP_F is the interacted term between GENDER_F and GP. GP_AGE2 is the
interacted term between AGE2 and GP. I present the results of the following regression model: 𝑅𝑂𝐴𝑖𝑡 =α+𝛽1 CSRST𝑡−1 + 𝛽2 𝐿𝑜𝑔𝑆𝑖𝑧𝑒𝑖𝑡 +
𝛽3 𝐷𝑒𝑏𝑡𝑖𝑡 + 𝛽4 𝐶𝐴𝑃𝐸𝑋𝑖𝑡 + 𝛽5 𝐶𝐹𝑖𝑡 + 𝛽6 𝑅𝐸𝑇𝐸𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝐺𝐸𝑁𝐷𝐸𝑅_𝐹𝑖𝑡 + 𝛽10 𝐺𝑃𝑖𝑡 + 𝛽11 𝐴𝐺𝐸2𝑖𝑡 ∗
𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽13 CSRST𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + + 𝛽13 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽14 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 +
𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
120
Table 3.6
Association between CSR Total Concerns
(CSRCN) and ROA
VARIABLES
CSRCN
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
ROA
Model 2
ROA
Model 3
ROA
0.00027
(1.4844)
0.00082***
(2.7141)
0.01147***
(-3.9235)
0.02112*
(1.8447)
0.93118***
(38.7082)
0.01009***
(9.8980)
0.00011***
(-3.0313)
-0.00271*
(-1.9296)
0.00114
(1.2222)
0.00023
(1.2369)
0.00078***
(2.5973)
0.01053***
(-3.6621)
0.01896*
(1.6693)
0.93136***
(38.7673)
0.01000***
(9.8763)
0.00013***
(-2.8543)
-0.00266*
(-1.9151)
0.00128
(0.8931)
0.00381***
(-5.4817)
-0.00003
(-0.4302)
13,295
0.8827
13,295
0.8830
0.00029
(1.3656)
0.00078***
(2.6211)
0.01039***
(-3.6128)
0.01864
(1.6357)
0.93136***
(38.6988)
0.00994***
(9.8273)
0.00013***
(-2.8607)
0.00753**
(2.0965)
-0.00050
(-0.2575)
0.00335***
(-3.4008)
-0.00001
(-0.0725)
-0.00014
(-0.5652)
0.01428***
(-3.8457)
0.00251
(1.3285)
13,295
0.8832
GP
AGE2_Tenure1
CSRCN_GP
GENDERGP_F
GP_AGE2
Observations
R-squared
Robust t-statistics is in parentheses. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is Return on Assets (ROA). The main independent
variable is the one year lag of CSR Total Concerns (CSRCN). CSRCN _GP is the interacted term between GP and CSRCN. Debt is the ratio
of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a
life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy
variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm.
GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if
the firm has a GP and 0 if otherwise. GENDERGP_F is the interacted term between GENDER_F and GP. GP_AGE2 is the interacted term
between AGE2 and GP. I present the results of the following regression model: 𝑅𝑂𝐴𝑖𝑡 =α+𝛽1 CSRCN𝑡−1 + 𝛽2 𝐿𝑜𝑔𝑆𝑖𝑧𝑒𝑖𝑡 + 𝛽3 𝐷𝑒𝑏𝑡𝑖𝑡 +
𝛽4 𝐶𝐴𝑃𝐸𝑋𝑖𝑡 + 𝛽5 𝐶𝐹𝑖𝑡 + 𝛽6 𝑅𝐸𝑇𝐸𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝐺𝐸𝑁𝐷𝐸𝑅_𝐹𝑖𝑡 + 𝛽10 𝐺𝑃𝑖𝑡 + 𝛽11 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 +
𝛽13 CSRCN𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + + 𝛽13 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽14 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
121
3.6.3 Internal and External CSR
In this session the focus is on the Internal and External CSR. The Internal CSR
(INTCSR_NET) represents those socially responsible projects that firms undertake that
directly affects it daily operations. These qualitative measures includes: Employee Relations,
Product safety & Quality, and Diversity. The employees are directed related to the everyday
operational activities of the firm. Their wellbeing, as it relates to their productivity, is critical
to the performance of the firm. The firms’ product safety & quality is also a very important
aspect of its internal operations. A failure or inefficiency in this facet could have a direct and
immediate negative effect on the firms’ value. Diversity is another internally oriented CSR
measure. Argument can be made that it possess elements of external CSR, given than its
implementation is usually as a result of societal pressure on the firm to promote diversity.
However, the immediate benefits of this type of CSR projects and their direct long-term
impact on firm operational performance qualify it as Internal CSR.
The external CSR (EXTCSR_NET) consists of those CSR qualitative measures that
firms extend into the community. These socially responsible projects are more visible to the
general stakeholders that do not necessarily have access to the internal operational activities
of the firms. Some of these external CSR projects include community development
programs, environmental protection and sustainability initiatives, and philanthropic
charitable contributions. To capture the firms’ EXTCSR_NET the net score of the community
and environment aspects of the CSR qualitative measure is used.
Table 3.7 on page 122 presents regression models in which INTCSR_NET and
EXTCSR_NET are the main independent variables. The association between INTCSR_NET
and firm performance, ROA, is examined.
122
Table 3.7
Association between Internal & External CSR Net
Scores and ROA
VARIABLES
INTCSR_NET
EXTCSR_NET
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
ROA
Model 2
ROA
Model 3
ROA
0.00064***
(3.9745)
0.00050***
(2.6900)
0.00065**
(2.4592)
0.01122***
(-3.8105)
0.01849
(1.5822)
0.93042***
(38.8481)
0.00992***
(9.6767)
0.00011***
(-2.9348)
-0.00366**
(-2.5702)
0.00138
(1.4740)
0.00064***
(4.0335)
0.00045**
(2.4580)
0.00058**
(2.2116)
0.01026***
(-3.5459)
0.01651
(1.4226)
0.93065***
(38.9133)
0.00984***
(9.6599)
0.00013***
(-2.7796)
-0.00361**
(-2.5588)
0.00149
(1.0354)
0.00380***
(-5.4733)
-0.00003
(-0.4112)
13,295
0.8830
13,295
0.8833
-0.00002
(-0.0693)
0.00065**
(2.5586)
0.00061**
(2.3376)
0.01027***
(-3.5357)
0.01660
(1.4238)
0.93060***
(38.8800)
0.00974***
(9.6212)
0.00013***
(-2.8035)
0.00735**
(2.0164)
-0.00059
(-0.3002)
0.00386***
(-4.8902)
-0.00001
(-0.0818)
0.00106***
(3.2401)
-0.00033
(-0.9722)
0.01541***
(-4.0804)
0.00306
(1.5978)
13,295
0.8835
GP
AGE2_Tenure1
INTCSR_NETGP
EXTCSR_NETGP
GENDERGP_F
GP_AGE2
Observations
R-squared
Robust t-statistics is in parentheses. ***p<0.01, **p<0.05, *p<0.1; The dependent variables are Return on Assets (ROA). The main
independent variables are the one year lag values of Internal CSR net score (INTCSR_NET) and External CSR net score (EXTCSR_NET).
INTCSR_NETGP is the interacted term between GP and INTCSR_NET. EXTCSR_NETGP is the interacted term between GP and
EXTCSR_NET Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is
measure of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of
common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the
executive has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a
dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise. GENDERGP_F is the interacted term between GENDER_F
123
Table 3.7 (Cont.)
Association between Internal & External CSR Net
Scores and ROA
VARIABLES
Model 1
ROA
Model 2
ROA
Model 3
ROA
and GP. GP_AGE2 is the interacted term between AGE2 and GP. I present the results of the following regression model: 𝑅𝑂𝐴𝑖𝑡 =α
+ 𝛽1 INTCSR_NET𝑡−1 + 𝛽2 EXTCSR_NET𝑡−1 + 𝛽3 𝐿𝑜𝑔𝑆𝑖𝑧𝑒𝑖𝑡 + 𝛽4 𝐷𝑒𝑏𝑡𝑖𝑡 + 𝛽5 𝐶𝐴𝑃𝐸𝑋𝑖𝑡 + 𝛽6 𝐶𝐹𝑖𝑡 + 𝛽7 𝑅𝐸𝑇𝐸𝑖𝑡 + 𝛽8 𝐴𝐺𝐸2𝑖𝑡 +
𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅_𝐹𝑖𝑡 + 𝛽11 𝐺𝑃𝑖𝑡 + 𝛽12 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽13 INTCSR_NET𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽14 EXTCSR_NET𝑡−1 ∗
𝐺𝑃𝑖𝑡 + + 𝛽15 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽16 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
The results suggest that INTCSR_NET is positively associated with ROA. The
relationships are statistically significant at the 1% level.
In Model 3, by interacting the GP and INTCSR_NET the coefficient of the interacted
term, INTCSR_NETGP, is positive and statistically significant at the 1% level. In the same
model 3, the coefficient of the INTCSR_NET variable becomes negative and statistically
insignificant. A test for joint significance validates that the GP profoundly amplifies the
positive association between INTCSR_NET and ROA. That is, CEOs that have a GP clause
in their compensation contract have a special affinity for internal CSR projects. It could be
that CEOs with a GP believe that internal CSR projects have a more direct and immediate
effect on the daily operating efficiency and productivity of the firm. This could translate to a
more assured potential enhancement of firm financial value.
In the same Model 3, by interacting the GP variable with EXTCSR_NET, the
coefficient of the interacted term, EXTCSR_NETGP, is negative and not statistically
significant. However, the EXTCSR_NET variable in the same model maintains its positive
statistical significance at the 5% significance level. This result suggests that for the firms
with the GP clause that association between EXTCSR_NET and ROA is negative. That is,
124
CEOs with the GP clause are fond of external CSR projects like they are for internal CSR
projects. In contrast, CEOs without the GP clause tend to pursue more external CSR projects
than the internal CSR projects. The test for joint significance validates these findings and its
supporting arguments.
Table 3.8 presents the regression models in which INTCSR_ST and EXTCSR_ST are
the main dependent variables. The associations between INTCSR_ST and EXTCSR_ST and
ROA are examined. The results in Models 1 & 2 suggest that both INTCSR_ST and
EXTCSR_ST are both positively associated with ROA and statistically significant at the 1%
level.
In Model 3, when the INTCSR_ST is interacted with the GP variable, the coefficient
of the interacted term, INTCSR_STGP is positive and statistically significant at the 1% level.
However, the coefficient of the INTCSR_ST variable in the same model becomes negative
and statistically insignificant. This shows that the GP incentivizes the CEOs to promote and
engage in more internal CSR projects and the outcome of this is an increasing enhancement
of firm, financial performance. This should also benefit the CEOs as the value of their GPs is
also enhanced by the value added.
In the same Model 3, when EXTCSR_ST is interacted with the GP variable, the
coefficient of the interacted term, EXTCST_STGP, is negative and statistically significant at
the 1% level. However, the EXTCSR_ST variable in the same model is positively
statistically significant at the 1% significance level. This result suggests that the presence of
the GP negatively impacts the association between external CSR projects and ROA. That is,
CEOs with a GP clause do not especially invest in external CSR projects like they do when it
125
comes to internal CSR projects. Joint significance tests validate the results and argument
presented.
Table 3.8
Association between Internal & External CSR
Strengths Scores and ROA
VARIABLES
INTCSR_ST
EXTCSR_ST
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
ROA
Model 2
ROA
Model 3
ROA
0.00572***
(4.7659)
0.00787***
(4.0438)
-0.00012
(-0.3551)
0.01081***
(-3.6608)
0.01823
(1.5492)
0.93163***
(38.6662)
0.00988***
(9.5661)
0.00010***
(-2.7736)
0.00365***
(-2.5912)
0.00141
(1.4988)
0.00546***
(4.5000)
0.00757***
(3.8696)
-0.00014
(-0.4133)
0.00995***
(-3.4280)
0.01638
(1.4025)
0.93182***
(38.7300)
0.00981***
(9.5575)
0.00012***
(-2.5924)
-0.00355**
(-2.5429)
0.00159
(1.1069)
0.00358***
(-5.0596)
-0.00003
(-0.4685)
13,295
0.8832
13,295
0.8835
-0.00173
(-0.9382)
0.01406***
(5.9858)
-0.00009
(-0.2646)
0.00998***
(-3.4308)
0.01679
(1.4300)
0.93169***
(38.7083)
0.00969***
(9.4758)
0.00012***
(-2.6595)
0.00706*
(1.9441)
-0.00054
(-0.2722)
0.00495***
(-4.6932)
-0.00001
(-0.1294)
0.01150***
(5.1845)
0.01025***
(-3.7068)
0.01501***
(-3.9988)
0.00305
(1.5952)
13,295
0.8838
GP
AGE2_Tenure1
INTCSR_STGP
EXTCSR_STGP
GENDERGP_F
GP_AGE2
Observations
R-squared
126
Table 3.8 (Cont.)
Association between Internal & External CSR
Strengths Scores and ROA
VARIABLES
Model 1
ROA
Model 2
ROA
Model 3
ROA
Robust t-statistics is in parentheses. ***p<0.01, **p<0.05, *p<0.1; The dependent variables are Return on Assets (ROA). The main
independent variables are the one year lag values of Internal CSR total strengths score (INTCSR_ST) and External CSR total strengths score
(EXTCSR_ST). INTCSR_STGP is the interacted term between GP and INTCSR_ST. EXTCSR_STGP is the interacted term between GP
and EXTCSR_ST. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF
is measure of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of
common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the
executive has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a
dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise. GENDERGP_F is the interacted term between GENDER_F
and GP. GP_AGE2 is the interacted term between AGE2 and GP. I present the results of the following regression model: 𝑅𝑂𝐴𝑖𝑡 =α
+ 𝛽1 INTCSR_ST𝑡−1 + 𝛽2 EXTCSR_ST𝑡−1 + 𝛽3 𝐿𝑜𝑔𝑆𝑖𝑧𝑒𝑖𝑡 + 𝛽4 𝐷𝑒𝑏𝑡𝑖𝑡 + 𝛽5 𝐶𝐴𝑃𝐸𝑋𝑖𝑡 + 𝛽6 𝐶𝐹𝑖𝑡 + 𝛽7 𝑅𝐸𝑇𝐸𝑖𝑡 + 𝛽8 𝐴𝐺𝐸2𝑖𝑡 +
𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅_𝐹𝑖𝑡 + 𝛽11 𝐺𝑃𝑖𝑡 + 𝛽12 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽13 INTCSR_ST𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽14 EXTCSR_ST𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
+ 𝛽15 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽16 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
Table 3.9 presents the regression models in which the total Internal CSR Concerns
score (INTCSR_CN) and External CSR Concerns score (EXTCSR_CN) are the main
independent variables. The associations between these two main independent variables and
ROA are examined. The results show that EXTCSR_CN is positively associated with ROA
and statistically significant at the 1% level. The interaction between EXTCST_CN and the
GP variable, EXTCSR_CNGP, is negative though not statistically significant.
Table 3.9
Association between Internal & External CSR
Concerns Scores and ROA
VARIABLES
INTCSR_CN
EXTCSR_CN
Model 1
ROA
Model 2
ROA
Model 3
ROA
0.00079
(0.7013)
0.00631***
0.00037
(0.3289)
0.00630***
0.00130
(0.7814)
0.00666***
127
Table 3.9 (Cont.)
Association between Internal & External CSR
Concerns Scores and ROA
VARIABLES
LogSize
Debt
CAPEX
CF
RETE
Tenure1
GENDER_F
AGE2
Model 1
ROA
Model 2
ROA
Model 3
ROA
0.00069**
(2.2966)
0.01144***
(-3.9171)
0.02210*
(1.9524)
0.93137***
(38.6939)
0.01009***
(9.9080)
0.00011***
(-2.9915)
-0.00281**
(-2.0015)
0.00113
(1.2121)
0.00064**
(2.1624)
0.01050***
(-3.6554)
0.02001*
(1.7807)
0.93153***
(38.7517)
0.01001***
(9.8871)
0.00013***
(-2.7995)
-0.00279**
(-2.0107)
0.00131
(0.9141)
0.00380***
(-5.4951)
-0.00003
(-0.4622)
13,295
0.8828
13,295
0.8831
0.00065**
(2.1880)
0.01037***
(-3.6092)
0.01972*
(1.7493)
0.93151***
(38.6868)
0.00994***
(9.8429)
0.00013***
(-2.7823)
0.00739**
(2.0664)
-0.00050
(-0.2534)
0.00309***
(-3.2221)
-0.00001
(-0.1100)
-0.00160
(-0.7596)
-0.00104
(-0.4386)
0.01426***
(-3.8504)
0.00256
(1.3488)
13,295
0.8833
GP
AGE2_Tenure1
INTCSR_CNGP
EXTCSR_CNGP
GENDERGP_F
GP_AGE2
Observations
R-squared
Robust t-statistics is in parentheses. ***p<0.01, **p<0.05, *p<0.1; the dependent variable is Return on Assets (ROA). The main independent
variables are the one year lag values of Internal CSR total concerns score (INTCSR_CN) and External CSR total concerns score
(EXTCSR_CN). INTCSR_CNGP is the interacted term between GP and INTCSR_CN. EXTCSR_CNGP is the interacted term between GP
and EXTCSR_CN. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF
is measure of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of
common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the
executive has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a
dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise. GENDERGP_F is the interacted term between GENDER_F
and GP. GP_AGE2 is the interacted term between AGE2 and GP. I present the results of the following regression model: 𝑅𝑂𝐴𝑖𝑡 =α
+ 𝛽1 INTCSR_CN𝑡−1 + 𝛽2 EXTCSR_CN𝑡−1 + 𝛽3 𝐿𝑜𝑔𝑆𝑖𝑧𝑒𝑖𝑡 + 𝛽4 𝐷𝑒𝑏𝑡𝑖𝑡 + 𝛽5 𝐶𝐴𝑃𝐸𝑋𝑖𝑡 + 𝛽6 𝐶𝐹𝑖𝑡 + 𝛽7 𝑅𝐸𝑇𝐸𝑖𝑡 + 𝛽8 𝐴𝐺𝐸2𝑖𝑡 +
𝛽9 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽10 𝐺𝐸𝑁𝐷𝐸𝑅_𝐹𝑖𝑡 + 𝛽11 𝐺𝑃𝑖𝑡 + 𝛽12 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽13 INTCSR_CN𝑡−1 ∗ 𝐺𝑃𝑖𝑡 + 𝛽14 EXTCSR_CN𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
+ 𝛽15 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽16 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
128
Table 3.10 presents the regression models in which RISK_F is the dependent variable.
The regression results suggest that CSR is positively associated with firm risk at the 1%
significance level. That is, as firms engage in more CSR, the uncertainty surrounding the
probable financial payoffs of such investments, as evidenced in literature, increases the
dispersion or variation in the firms’ earnings. Though not statistically significant, a test to see
if the provision of a GP mitigates the association between CSR_NET and RISK_F produced
an inverse beta coefficient.
GP is also positively associated with RISK_F. This could be as result of the boost in
confidence that the GP provides for the CEO. When the CEO is insulated by the GP, the
willingness to increase risk-taking behavior, with the aspiration of making more profit,
should be expected. The CEOs seek to maximize their wealth and thus will engage in more
risky investments in hopes of achieving their desired outcome. The likelihood of the CEO
getting fired is significantly reduced, as the payment of the GP places a hefty cost on the firm
(Bebchuk, Cohen and Wang 2014b).
Table 3.10
Association between CSR_NET and Firm Risk
Model 1
Model 2
Model 3
VARIABLE
ROA
ROA
ROA
CSR_NET
0.00860A***
0.00888***
0.01017**
(2.69)
(2.78)
(2.16)
-0.60388***
0.60303***
0.60277***
(74.42)
(74.18)
(74.14)
-0.41745***
0.43148***
0.42990***
(5.97)
(6.16)
(6.13)
LogSize
Debt
129
Table 3.10 (Cont.)
Association between CSR_NET and Firm Risk
VARIABLE
CF
RETE
AGE2
Tenure1
GENDER_F
Model 1
Model 2
Model 3
ROA
ROA
ROA
(1.07)
(0.96)
(0.97)
1.73447***
1.73083***
1.73482***
(9.52)
(9.50)
(9.52)
0.05779***
0.05877***
0.05846***
(2.69)
(2.74)
(2.72)
-0.02042
-0.03433
0.01237
(0.58)
(0.61)
(0.16)
-0.00360***
-0.00356**
-0.00349**
(2.59)
(2.19)
(2.14)
0.19037***
0.18873***
0.25170**
(3.34)
(3.31)
(2.24)
0.05694**
0.06648***
(2.56)
(2.80)
0.00125
0.00065
(0.41)
(0.21)
GP
AGE2_Tenure1
CSR_NET_GP
-0.00228
(0.41)
GENDERGP_F
-0.08769
(0.68)
GP_AGE2
-0.06559
(0.93)
Observations
13,295
13,295
13,295
R-squared
0.4916
0.04919
0.4920
Robust t-statistics is in parentheses. ***p<0.01, **p<0.05, *p<0.1; The dependent variable is standard deviation of firms’ earnings (RISK_F).
The main independent variable is CSR_NET. CSR_NET_GP is the interacted term between GP and CSR_NET. Debt is the ratio of total debt
to common equity, CAPEX is defined as total capital expenditures scaled to total assets, CF is measure of cash flow, RETE is a life cycle
proxy used to capture firm age. It is measured as the ratio of retained earnings to book value of common equity. AGE2 is a dummy variable
that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure measures how long the executive has been the CEO of the firm. GENDER_F
is dummy variable that is 1 if the CEO is a female and if the CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a
GP and 0 if otherwise. GENDERGP_F is the interacted term between GENDER_F and GP. GP_AGE2 is the interacted term between AGE2
and GP. I present the results of the following regression model: 𝑅𝐼𝑆𝐾_𝐹𝑖𝑡 =α+𝛽1 𝐶𝑆𝑅_𝑁𝐸𝑇𝑡−1 + 𝛽2 𝐿𝑜𝑔𝑆𝑖𝑧𝑒𝑖𝑡 + 𝛽3 𝐷𝑒𝑏𝑡𝑖𝑡 + 𝛽4 𝐶𝐴𝑃𝐸𝑋𝑖𝑡 +
𝛽5 𝐶𝐹𝑖𝑡 + 𝛽6 𝑅𝐸𝑇𝐸𝑖𝑡 + 𝛽7 𝐴𝐺𝐸2𝑖𝑡 + 𝛽8 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽9 𝐺𝐸𝑁𝐷𝐸𝑅_𝐹𝑖𝑡 + 𝛽10 𝐺𝑃𝑖𝑡 + 𝛽11 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝑇𝑒𝑛𝑢𝑟𝑒1𝑖𝑡 + 𝛽13 𝐶𝑆𝑅𝑁𝐸𝑇 𝑡−1 ∗ 𝐺𝑃𝑖𝑡 +
+ 𝛽13 𝐺𝐸𝑁𝐷𝐸𝑅𝐹 𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 + 𝛽14 𝐴𝐺𝐸2𝑖𝑡 ∗ 𝐺𝑃𝑖𝑡 𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝑌𝐸𝐴𝑅 𝐹𝐼𝑋𝐸𝐷 𝐸𝐹𝐹𝐸𝐶𝑇𝑆 + 𝜀𝑖𝑡
Other interesting findings in the table 3.10 includes: a negative association between
firm size and RISK_F; negative association between debt ratio and RISK_F; a firm’s age is
130
positively associated with RISK_F; the standard deviation of the firms’ earnings is increases
when the CEO is a female; and the longer the CEOs’ tenure with the firm the lower the
standard deviation of the firms’ earnings.
3.7
Endogeneity Tests
So far, the test for the association between CSR and firm performance has shown that
CSR affects firms’ performance. Even after controlling for time and industry effects, CSR
impact on the performance variables are still valid and maintained its directionality all
through. However, it is possible that CSR may be endogenous. If indeed CSR is endogenous,
then the reliability of our variables may be at best spurious in nature as it suffers from
specification bias and the possibility of reverse causality. As such, there is need to perform a
test for endoginiety, reverse causality, and omitted variable bias issues.
Table 3.11 presents the test results for endoginiety and omitted variable bias issues.
The Generalized Methods of Moments (GMM) approach is employed. The Instrumental
Variables used are the Industry average of CSR_NET and the three years lag value of
CSR_NET. These IV are not correlated with the error term as reported in STATA. Thus, it
serves the purpose of good instruments to test and control for possible endoginiety and
omitted variable bias issues. The first stage estimates to test for the validity of the IVs
produced adjusted R2 value of 15.7%. The test for over-identification restriction is also met.
Thus, the IV variables are very strong instruments.
As expected, the IV regression show that the results reported earlier does not suffer
from endogeneity, selection bias, or reverse causality. The directionality of the main
independent variable of interest remains the same, and statistically significant. The variables
131
of interest are also statistically significant, and the F-statistics which test against the null
hypothesis that all are zero is valid is also strongly statistically significant.
Table 3.11
Test for Endogeniety
VARIABLE
ROA
CSR_NET
0.00201***
(4.93)
LogSize
0.00037
Debt
-0.00174
(1.44)
(0.67)
CAPEX
0.01252
(1.25)
CF
0.93494***
(40.92)
RETE
0.01096***
AGE2
0.002339**
(12.02)
(2.40)
Tenure1
0.00013***
(3.76)
GENDER_F
-0.00282
(1.70)
GP
-0.00333
(5.31)
Observations
13,294
R-squared
0.8731
Robust Z-statistics is in parentheses. Generalized Methods of Moments (GMM) is used in the analysis. The dependent variable is Return on
Assets (ROA.). The main independent variable is CSR_NET. The instrumental variables employed are the Industry average of CSR _NET
and the three years lag value of CSR_NET. Debt is the ratio of total debt to common equity, CAPEX is defined as total capital expenditures
scaled to total assets, CF is measure of cash flow, RETE is a life cycle proxy used to capture firm age. It is measured as the ratio of retained
earnings to book value of common equity. AGE2 is a dummy variable that represents the CEO age, where 1 is ≥ 64 and 0 is <64. Tenure
measures how long the executive has been the CEO of the firm. GENDER_F is dummy variable that is 1 if the CEO is a female and if the
CEO is male. GP is a dummy variable that takes the value of 1 if the firm has a GP and 0 if otherwise. GENDERGP_F is the interacted term
between GENDER_F and GP. GP_AGE2 is the interacted term between AGE2 and GP.
132
The result of this test for endoginiety and omitted variable bias issues validates that
CSR positively affects firms’ performance. It shows that results produced in table 2.3 is valid
and does not suffer from endoginiety, reverse causality, and omitted variable bias issues.
3.8
Summary and Conclusion
In this essay the association between CSR and firm performance is explored. Previous
studies on similar topic have produced mixed and conflicting findings. Some studies show
that CSR is positively associated with firm performance. That is, the greater the firm’s
investment in CSR, the higher the firm’s performance (Barnett and Salomon 2006; Eccles,
Ioannou and Serafeim 2012; Graves and Waddock 1999; Preston and O’bannon 1997; Ruf et
al. 2001). Some find negative association (Boyle, Higgins and Rhee 1997; Brammer, Jackson
and Matten 2012; Krueger 2013; Moore 2001; Shane and Spicer 1983; Wright and Ferris
1997). Others find no association (Aupperle, Carroll and Hatfield 1985; Bauer, Koedijk and
Otten 2005; Guerard Jr 1997).
The findings in this essay suggest that the association between CSR and firm
performance, ROA, is positive. The test to examine the moderating effect of the GP produced
empirical evidence to suggest the GP amplifies the positive association between CSR and
ROA. That is, CEOs that have the GP clause in their executive compensation contract engage
in more value-enhancing CSR projects than their counterparts that do not have the GP clause.
This result supports the hypotheses 1a and 1b which states which predicts a positive
association between CSR and firm performance, and a positive effect of the GP on this
association.
The empirical findings in this study support the conflict resolution theory which
posits that top managers could use CSR as effective tool to develop good relations with the
133
employees, good environmental policy, and good product quality. This could result in high
employee morale, increased productivity, and improved firm reputation. Consequently, these
intangible and tangible benefits could drive the value of the firm upwards, increasing
profitability
For further analysis, the CSR score in divided into Internal and External CSR. The
empirical findings suggest that CEOs with a GP clause do not especially invest in external
CSR projects like they do when it comes to internal CSR projects. That is, CEOs that have a
GP clause in their compensation contract have a special affinity for internal CSR projects. It
could be that CEOs with a GP strongly presume that internal CSR projects have a more direct
and immediate effect on the daily operating efficiency and productivity of the firm. This
could translate to a more assured potential enhancement of firm financial value.
The findings in this essay also lend credence to the argument that the uncertainty
surrounding the CSR payoffs could indeed pose a risk to the firm. To empirically test this, I
examined the association between CSR net score and firms’ risk. Risk is defined as the
standard deviation of firms’ earnings scaled to the average total assets. The regression results
produced a positive statistically significant relationship. This finding supports the argument
that the uncertainty surrounding payoffs in the CSR investments could increase the volatility
of the firms’ earnings.
In sum, based on the findings in this essay, it is important that corporate executives
identity and pursue an optimal value-enhancing CSR strategy. CSR investments are
beneficial to both the society and the firms. These positive characteristics should not be
undermined by an inability to optimally and efficiently identify avenues through which this
practice of societal good, CSR, could enhance the wellbeing of all stakeholders. CEOs with a
134
GP clause should be encouraged to pursue and promote more value-enhancing CSR projects.
In so doing, the alignment of the interest of all stakeholders could be achieved.
135
CHAPTER 4
SUMMARY, CONCLUSION, AND FUTURE RESEARCH
This dissertation study contributes to the literature on executive compensation, CSR,
and firm performance. The associations between these corporate elements are revisited and
further examined by introducing the GP. CSR campaign has continued to gain wide
acceptance both in the general society and corporate domains. GP on the other hand, continue
to receive criticisms from the society. Critics and detractors of this corporate practice frown
upon its very existence as they claim that it is only linked to a change of control of the firm
and is executed even when the CEO is terminated due to bad performance (Ling 2012).
It has been argued that the execution of the GP places a hefty cost burden on the
paying firm and directly depletes funds available for business operations (Bebchuk and Fried
2004). Some studies find empirical evidence that seems to suggest that entrenched managers
introduce GP contracts in order to stall or hamper the disciplinary effect of corporate
takeovers (Dann and DeAngelo 1983; Dann and DeAngelo 1988; DeAngelo and DeAngelo
1989; Gompers, Ishii and Metrick 2003; Singh and Harianto 1989; Subramaniam and Daley
2000; Wade, O'Reilly III and Chandratat 1990). In contrast, Machlin, Choe and Miles (1993)
find evidence to suggest that GPs increase the probability of a takeover.
Proponents of the GP argue that it is a necessary competitive recruiting tool for
attracting and retaining talented executives (Frydman and Saks 2010; Rau and Xu 2013;
Rosen 1981; Terviö 2008). Some argue that an antitakeover provision like GP is aimed to
align the manager’s interest with that of the shareholders, thus maximizing firm value,
mostly in the event of a takeover (Baron 1983; Comment and Schwert 1995; Harris 1990;
136
Lambert and Larcker 1985; Machlin, Choe and Miles 1993; Singh and Harianto 1989; Stein
1988). Jensen (1988) posit that an efficient and effective implementation of GP can help
reduce the conflict of interest between the shareholders and the managers.
In part, this dissertation study aim to identify avenues through which CSR and GP
can coexist and cooperatively generate the desired benefits that the stakeholders and CEOs
seek. The society promotes CSR and generally frowns upon the GP clause. On the other
hand, the CEOs seek to maximize their wealth and mitigate their compensation and
employment risk. The provision of the GP serves this purpose.
The society dislike for the GP is profound as they seek to abolish its practice.
Overtime, this societal desire has continued to endure and debates ensue. The financial crisis
of 2007 put the hopes of abolishing the GP to rest as firms exponentially increased their
willingness and practice of granting CEOs the GP as part of their compensation package.
This turn of event weakened the campaign against the GP. It became glaring that the die is
cast; the GP is here to stay. This dissertation seeks to find ways to make these two interests,
CSR and GP, amiably coexist. If empirical evidence is provided to show that CSR
investments could enhance firm value, then the CEOs endowed with the GP clause should be
more willing to engage in value-enhancing CSR. This behavior should be borne out of the
CEOs’ desire to maximize their wealth. If CSR is value-enhancing then it behooves the
CEOs with a GP clause to promote more CSR.
Treading the path of previous studies on similar topics, this present study expounds
the relevance of CSR and GP, and the importance of their value to various facets of the
society. The society campaigns for the expansion of CSR, while the corporations continue to
practice the use of the GP in order to stay competitive. Arguments have been presented in
137
literature that CSR has the capacity to enhance firm value. If this argument is true, then it is
befitting to the corporate executives to capitalize on the value-enhancing characteristics of
CSR to achieve it corporate goals, which is ultimately to maximize firm value.
Apart from public pressure, the benefits of CSR engagements to firms are numerous
as evident in empirical literature. Dhaliwal et al. (2011) finds a reduction in cost of equity for
firms that initiate disclosure of CSR engagements in subsequent year after a preceding year
of high cost of equity. The authors further postulate that when firms’ voluntary engages in
CSR investments, it can help deter government regulations, which should ultimately reduce
compliance costs. Skinner (1994) posit that, in order to preempt potential lawsuits, voluntary
CSR disclosure is more likely in firms that are facing a higher level of litigation risk. Lev,
Petrovits and Radhakrishnan (2010) note that consumers that strongly value a particular
social issue will gravitate toward patronizing firms that engage in CSR activities in
promotion of such cause. An increased consumer presence and customer loyalty should
ultimately bring about superior sales and financial performance. Richardson and Welker
(2001) articulate that is important to acknowledge the influence of a firm’s CSR
engagements on potential socially aware investors who are willing to pay a premium for
securities of socially responsible firms.
4.1
Essay 1
In this essay, I explore the association between executive compensation and CSR. I
extend previous research on similar topic by examining the moderating effect of the golden
parachute. Given that the largest portion of the GP payments usually come from the
accelerated payments of unvested stock options and other stock units, I argue that CEOs with
the GP clause would behave differently towards CSR from those CEOs without it. If CSR
138
projects are value enhancing, then the CEO with a GP would promote CSR engagements for
as long as it increases firm financial performance.
Using a large sample of 1301 US firms from 1992 to 2013, the findings suggest that
there exists an inverse relationship between current (long-term) compensation and firms’
CSR engagements. While the direct association between the golden parachute and CSR is
also negative, the test for a moderating effect reveals that the GP and long-term
compensation jointly and positively increase firms’ CSR performance. This is consistent with
the expectation that executives with a GP clause would desire to maximize their long-term
wealth by approving only value-enhancing CSR projects that positively enhance firm
financial performance. Furthermore, the results also suggest that female executives are more
likely than their male counterparts to promote CSR engagements. Older executives are less
willing to engage in CSR even with the GP clause.
The result of the analysis on the relationship between CF and CSRST alludes to the
possibility that, from previous experience, firms are not convinced that CSR engagements
always increase financial performance. Perhaps, it could be that an overinvestment in CSR
erodes the benefits to the firm, hence the need to reduce investments in CSR strengths to
avoid overinvestment. Or it could be that some CSR projects are less value-enhancing that
others. The findings in this essay are robust to model specification, endogeneity and
selection bias issues, and sufficient control variables.
4.2
Essay 2
In this essay the association between CSR and firm performance is explored. Previous
studies on similar topic have produced mixed and conflicting findings. Some studies show
that CSR is positively associated with firm performance. That is, the greater the firm’s
139
investment in CSR, the higher the firm’s performance (Barnett and Salomon 2006; Eccles,
Ioannou and Serafeim 2012; Graves and Waddock 1999; Preston and O’bannon 1997; Ruf et
al. 2001). Some find negative association (Boyle, Higgins and Rhee 1997; Brammer, Jackson
and Matten 2012; Krueger 2013; Moore 2001; Shane and Spicer 1983; Wright and Ferris
1997). Others find no association (Aupperle, Carroll and Hatfield 1985; Bauer, Koedijk and
Otten 2005; Guerard Jr 1997).
The findings in this essay suggest that the association between CSR and firm
performance, ROA, is positive. The test to examine the moderating effect of the GP produced
empirical evidence to suggest the GP amplifies the positive association between CSR and
ROA. That is, CEOs that have the GP clause in their executive compensation contract engage
in more value-enhancing CSR projects than their counterparts that do not have the GP clause.
This result supports the hypotheses 1a and 1b in essay 2 which states which predicts a
positive association between CSR and firm performance, and a positive effect of the GP on
this association.
The empirical findings in this study support the conflict resolution theory which
posits that top managers could use CSR as effective tool to develop good relations with the
employees, good environmental policy, and good product quality. This could result in high
employee morale, increased productivity, and improved firm reputation. Consequently, these
intangible and tangible benefits could drive the value of the firm upwards, increasing
profitability. For further analysis, the CSR score in divided into Internal18 and External19
18
Internal CSR consists of the following qualitative measures: Product Quality & Safety, Employee
Relationship, and Diversity.
19
External CSR consists of the following qualitative measures: Community and Environment.
140
CSR. The empirical findings suggest that CEOs with a GP clause do not especially invest in
external CSR projects like they do when it comes to internal CSR projects. That is, CEOs
that have a GP clause in their compensation contract have a special affinity for internal CSR
projects.
It could be that CEOs with a GP strongly presume that internal CSR projects have a
more direct and immediate effect on the daily operating efficiency and productivity of the
firm. This could translate to a more assured potential enhancement of firm financial value.
The findings in this essay also lend credence to the argument that the uncertainty
surrounding the CSR payoffs could indeed pose a risk to the firm. To empirically test this, I
examined the association between CSR net score and firms’ risk. Risk is defined as the
standard deviation of firms’ earnings scaled to the average total assets. The regression results
produced a positive statistically significant relationship. This finding supports the argument
that the uncertainty surrounding payoffs in the CSR investments could increase the volatility
of the firms’ earnings.
4.3
Conclusion and Future research
One of the major purposes of this research exposition is to incite an intellectual quest
to continue to seek empirical evidence that ties the value of the GP to the value-enhancing
properties of CSR. When CSR enhances firms’ financial value the stock options in the GP is
also positively enhanced. This way, the society will get what its wants, CSR, and the
corporate executives with the GP clause are incentivized to promote more value-enhancing
CSR projects.
In sum, based on the findings in this essay, it is important that corporate executives
identity and pursue an optimal value-enhancing CSR strategy. CSR investments are
141
beneficial to both the society and the firms. These positive characteristics should not be
undermined by an inability to optimally and efficiently identify avenues through which this
practice of societal good, CSR, could enhance the wellbeing of all stakeholders. CEOs with a
GP clause should be encouraged to pursue and promote more value-enhancing CSR projects.
In so doing, the alignment of the interest of all stakeholders could be achieved.
For future research, it would be a valuable contribution to the literature on CSR, and
beneficial to its campaign, if research is conducted to examine if CSR enhances (decreases)
the value of the target firms. That is, does CSR value deter hostile takeovers? Does it position
the target firm to negotiate a higher premium if a tender offer is in the best interest of the
shareholders?
Another interesting to angle to explicatively expound upon this area of research is to
examine the acquiring firms’ shareholders’ response to the news of an acquisition of a firm
with high CSR reputation. Specifically, how does the market and stock price of the acquiring
firm react to such news? This could also be explored further to see if the merger of a CSR
firm and non-CSR firm creates value for the newly merged corporate entity.
Lastly, testing for overinvestment in CSR and examining the moderating effect of the
GP does seem like an interesting research path worthy of exploration. Given that the value of
the GP, which consist mostly of stock options, greatly depends on the financial performance
of the firm, it would be interesting to investigate the impact of the presence a GP on firms
propensity to overinvest in CSR projects. An overinvestment in CSR projects could
adversely impact the financial wellbeing of the firm thus an undesirable outcome that could
negatively affect the wealth of the CEO as it regards to the value of the GP.
142
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APPENDIX A
Selected Literatures on the Association between CSR and Firm Performance
Study
Barnett and
Salomon
(2006)
Measure of
Social
Responsibility
Socially
Responsible
Investing (SRI)
Graves and
Waddock
(1999)
Corporate Social
Performance
(CSP)
Preston and
O’bannon
(1997)
Fortune Magazine
corporate
reputation Survey
Ruf et al.
(2001)
Antunovich,
Laster and
Mitnick (2000)
Calculated a
composite
measure of CSR
using KLD
database
Survey
instruments
adopting Carroll’s
(1979) four-part
model defining
CSR
Fortune Magazine
corporate
reputation Survey
Frooman
(1997)
Event studies
with CSR events
Aupperle,
Carroll and
Hatfield (1985)
Krueger (2013)
Boyle, Higgins
and Rhee
(1997)
Event studies
with CSR events
Defense
Industries
Initiative (DII)
agreement
Performance Criteria
Data Source
Findings and Implications (Positive,
Negative or No significance)
Risk-adjusted Performance
(RAP): defined as the average
monthly return, measured as
the percentage change in a
fund’s market value from the
beginning to the end of a given
month, adjusted by the fund’s
specific beta (Sharpe 1964)
Two-year averages
(1991-92) of three indicators:
return on assets (ROA), return
on equity (ROE), and return on
sales (ROS)
Return on Asset (ROA),
Return on Equity (ROE), and
Return on Investment (ROI)
Social
Investment
Forum and
CRSP
Fnd that financial performance varies with
the types of social screens used.
Community relations screening increased
financial performance, but environmental
and labor relations screening decreased
financial performance
ROE, ROS, Sales Growth
+/KLD and
COMPUSTAT
Positive (+)
Fortune
Magazine
Survey and
COMPUSTAT
KLD and
COMPUSTAT
ROA ( employed both shortterm 1 year and long-term 5
year,
Value Line and
Carroll’s
(1979) fourpart model
defining CSR
Return on Stocks and Return
on Investment (ROI)
Fortune
Magazine
Survey and
COMPUSTAT
ABI/INFORM,
INFORTRAC,
LEXIS AND
PERI and
CRSP
KLD CSR
Internet
appendix
containing
numerous
representative
events and
CRSP
Return on stocks.
Return on Stocks
Return on Stocks and Return
on Assets (ROA)
CRSP and
COMPUSTAT
Positive (+) Correlation
Positive (+)
No relationship
Positive (+)
Negative (-)
Find that investors respond strongly
negatively to negative events and weakly
negatively
to positive events.
Negative (-)
Negative (-)
157
APPENDIX A (Cont.)
Selected Literatures on the Association between CSR and Firm Performance
Study
Measure of
Social
Responsibility
Performance Criteria
Eccles,
Ioannou and
Serafeim
(2012)
Social
Performance.
ASSET4
Return on Assets (ROA)
Wright and
Ferris (1997)
Socially
responsible
divestments
Return on Stocks
Bauer, Koedijk
and Otten
(2005)
Moore (2001)
Socially
responsible
investing
Social
Performance
risk-adjusted returns
Return in Capital employed,
growth in EPS, growth in
product Turnover, and profit
before depreciation
Data Source
Findings and Implications (Positive,
Negative or No significance)
Thomson
Reuters
ASSET4
database and
COMPUSTAT
CRSP and
Investor
Responsibility
Research
Center (IRRC)
CRSP and
Datastream
Positive (+)
Ethical
Investment
Research
Service
(EIRIS)
Negative (-)
No relationship
Negative (-)
158
APPENDIX B
Essay 1 Variables Descriptions
Variable
Description
Source
Dependent Variables
CSR-Net
Total CSR strengths minus total CSR concerns
CSR-Strengths (CSRST)
Total CSR strengths for the qualitative social measures
CSR-Concerns (CSRCN)
Total CSR concerns for the qualitative social measures
MSCI ESG STATS
(formerly KLD)
MSCI ESG STATS
(formerly KLD)
MSCI ESG STATS
(formerly KLD)
Main Independent Variables
Golden Parachute (GP)
Short-term Compensation (CCP)
Long-term Compensation (LCP)
A binary variable that equals one if the firms have adopted
golden parachutes in the year and zero otherwise (GP)
Natural logarithm of Current compensation measured as
salary + bonus
Natural Logarithm of Total compensation minus CCP.
** Total compensation comprises of the following: Salary,
Bonus, Other Annual, Total Value of Restricted Stock
Granted, Total Value of Stock Options Granted (using
Black-Scholes), Long-Term Incentive Payouts
RISKMETRICS
Computed as the average debt to equity ratio
Capital Expenditures scaled to total assets
Measured as the natural logarithm of total sales
Life Cycle Proxy: ratio of retained earnings to book value
of common equity
The age of the CEO measured using dummy variable
where 0 represents ≤ 64 and 1 is > 64
The gender of the CEO. A dummy variable representing 1
if female and 0 if male
How long the CEO has been serving in that capacity for
the firm. Calculated as the time left office minus the time
became CEO
Operating income before depreciation minus interest
expense, taxes, preferred dividends, and common
dividends
COMPUSTAT
COMPUSTAT
COMPUSTAT
COMPUSTAT
EXECUCOMP
EXECUCOMP
Control Variables
DEBT
CAPEX
Size
RETE
Age2
GENDER_F
Tenure1
Cash Flow (CF)
INTERLOCK
Is a dummy variable that takes that value of 1 if the CEO
is named to the compensation committee
EXECUCOMP
EXECUCOMP
EXECUCOMP
COMPUSTAT
159
APPENDIX C
Essay 2 Variables Descriptions
Variable
Description
Source
Dependent Variables
ROA
Return on Asset calculated as the firms’ Earnings Before
Interest Expense and Taxes (EBIT) scaled to the firms’
total assets
COMPUSTAT
RISK_F
The standard deviation of firms’ earnings scaled to the
average total assets
COMPUSTAT
Is the one year lag of the sum of total CSR strengths minus
total CSR concerns
Is the one year lag of total CSR strengths for the
qualitative social measures
Is the one year lag of total CSR concerns for the
qualitative social measures
A binary variable that equals one if the firms have adopted
golden parachutes in the year and zero otherwise (GP)
MSCI ESG STATS
(formerly KLD)
MSCI ESG STATS
(formerly KLD)
MSCI ESG STATS
(formerly KLD)
Computed as the average debt to equity ratio
Capital Expenditures scaled to total assets
Measured as the natural logarithm of total sales
Life Cycle Proxy: ratio of retained earnings to book value
of common equity
The age of the CEO measured using dummy variable
where 0 represents ≤ 64 and 1 is > 64
The gender of the CEO. A dummy variable representing 1
if female and 0 if male
How long the CEO has been serving in that capacity for
the firm. Calculated as the time left office minus the time
became CEO
Operating income before depreciation minus interest
expense, taxes, preferred dividends, and common
dividends
COMPUSTAT
COMPUSTAT
COMPUSTAT
COMPUSTAT
IND_CSR
Industry average of CSR score using Fama French 48
Industry classification
MSCI ESG STATS
(formerly KLD)
CSRNET_Lag3
The three years lag value of CSR_NET score
MSCI ESG STATS
(formerly KLD)
Main Independent Variables
CSR-Net
CSR-Strengths (CSRST)
CSR-Concerns (CSRCN)
Golden Parachute (GP)
RISKMETRICS
Control Variables
DEBT
CAPEX
LogSize
RETE
Age2
GENDER_F
Tenure1
Cash Flow (CF)
EXECUCOMP
EXECUCOMP
EXECUCOMP
COMPUSTAT
Instrumental Variables
160
APPENDIX D
List of CSR Qualitative Measures
Community
Diversity
Employee
Relations
Environment
Product Quality
and Safety
Strengths
Concerns
Innovative giving
Support for housing giving
Generous giving
Support for education
Indigenous Peoples relations
Non-U.S. Charitable giving
Other strength
Investment controversies
Negative economic impact
Indigenous people relations s ('00-'01)
Tax Disputes (added '05)
Other concerns
CEO
Promotion
Board of Directors
Work/Life Benefits
Women/Minority Contracting
Employment of the Disabled
Gay & Lesbian Policies
Other Strength
Controversies
Non-Representation
Other Concern
Union Relations
No Layoff Policy (ended ’94)
Cash Profit Sharing
Involvement
Strong Retirement Benefits
Health and Safety strength (added ’03)
Other strength
Union Relations
Safety Controversies
Workforce Reductions
Pension/Benefits (added ’92)
Other Concern
Beneficial Products and Services
Pollution Prevention
Recycling
Clean Energy
Transparency/communications (added ’96, moved ’05)
Property, Plant, and Equipment (ended ’95)
Other Strength
Hazardous Waste
Regulatory Problems
Ozone Depleting Chemicals
Substantial Emissions
Climate Change (added '99)
Other Concern
Quality
R&D/Innovation
Benefits to Economically Disadvantaged
Other Strength
Product Safety
Marketing/contracting controversy
Antitrust
Other Concerns
161
APPENDIX E
CSR Theories and Definitions
CSR Theories
Conflict Resolution
Overinvestment
Strategic Choice
Resource Based View
Definition
States that top managers use
CSR as a device to develop
and build good relationships
with the firm’s internal and
external stakeholders
Suggests that managers may
overinvest in CSR projects to
satisfy a selfish desire to
burnish their reputation as
good global citizens at the
expense of the shareholders
(Barnea & Rubin, 2010; Goss
& Roberts, 2011)
Posits that incumbent
managers strategically select
in which CSR projects to
invest. The motivation being
a desire to generate likability
and support from
environmental and social
activists in order to reduce
the manager’s employment
risk by decreasing the
probability of future turnover
(Cespa & Cestone, 2007;
Harjoto & Jo, 2011)
The processes through which
CSR engagements could
generate financial benefits for
the firm
Arguments
A good relationship with the employees could yield increases in
productivity
Good relationship with the regulatory agencies and the
community could save the firm cost associated with litigation
fees, consumer boycotts, reputation damage, and regulatory
fines.
A good product quality also increases the likelihood of return
satisfied customers and a decrease in the costs associated with
products defect
Managers may seek to overinvest in CSR, regardless of its effect
on shareholders wealth, for their private gains
Consistent with the overinvestment hypothesis, some studies
find a positive association between CSR and CEO compensation
(Cai et al., 2011; Mahoney & Thorn, 2006)
Centered upon the argument that when stakeholder protection is
entrusted to the voluntary initiatives of mangers, the probability
of managerial opportunism increases.
Cespa and Cestone (2007) assert that relations with social
activists could become an effective entrenchment strategy for
inefficient managers. That is, in a desperate attempt to build a
good relationship with social activists, the manager could
strategically choose to invest in selected CSR projects, even if
doing so reduces shareholders’ wealth
Such CSR projects could be in the form of donations to
charitable organizations that brings positive visibility to the
manager, or funding costly overelaborated campaign to promote
diversity among the company’s workforce.
Improvement of stronger and better relationships with customers
(T. J. Brown & Dacin, 1997)
Enhancement of future revenue growth (Lev et al., 2010)
Motivated and enhance employees’ morale which could increase
productivity (Turban & Greening, 1997)
Providing an ‘insurance like’ protection for the firm and its
shareholders should incase a negative event occurs (Gardberg &
Fombrun, 2006; Godfrey, 2005)
162
VITA
Collins Emeka Okafor received a Bachelor of Business Administration with a major
in Accounting Information Systems from Stetson University in May 2008. Upon graduating
from Stetson, he proceeded to Texas A&M International University where he obtained three
Masters Degrees: MBA with concentration in International Banking, M.Sc. in Management
Information Systems, and MPacc in Professional Accounting.
Mr. Okafor’s research interests include Corporate Finance, Corporate Governance,
Executive Compensation, Corporate Social Responsibility, Accounting Disclosures for
Capital Markets, and Earnings Management. He may be reached at No. 10 Bida Road, Sabon
Gari Zaria, Kaduna State, Nigeria. His email address is okafor.e.collins@gmail.com