OKAFOR-DISSERTATION-2015
Transcription
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. viii 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 84 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. 85 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. 86 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. 87 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. 89 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. 91 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 92 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, 93 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 94 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). 96 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 97 ‘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. 98 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 99 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 100 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: 101 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. 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(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 [email protected]