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Essays on corporate social responsibility Barnea, Amir 2005

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ESSAYS ON CORPORATE SOCIAL RESPONSIBILITY by  Amir Barnea  B . A . , T h e Hebrew University of Jerusalem, 1998 M . A . , T h e Hebrew University of Jerusalem, 2000  A THESIS S U B M I T T E D IN P A R T I A L F U L F I L M E N T O F THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in T H E F A C U L T Y OF G R A D U A T E STUDIES (Business A d m i n i s t r a t i o n , Finance)  T H E UNIVERSITY OF BRITISH C O L U M B I A J u l y 2005 © A m i r Barnea, 2005  Abstract Corporate Social Responsibility (CSR) is very high on corporations' agenda in recent years. C S R means different things to different stakeholders but generally refers to serving people, communities and the environment in a way that goes beyond what is legally required of a firm. In this paper-based dissertation we analyze some potential driving forces behind this corporate behavior. The first paper explores the role of Socially Responsible Investing (SRI) - making investment decisions according to both financial and ethical criteria. We analyze the effect of SRI on the investment decisions of firms that fail the screen ('polluting' firms) and on their decisions to adopt a CSR-approved technology. These issues are examined in an equilibrium setting with endogenous investment decisions. We find that the presence of socially responsible investors can lead to under-investment by polluting firms but their current proportion among all investors (11%) is not enough to induce polluting firms to change their technology. The second paper further explores the role of SRI in a richer theoretical framework. We model a capital market in which some investors get direct utility from owning firms that spend on CSR. We also assume different categories of firms: those with good C S R fundamentals and those with poor C S R fundamentals. In equilibrium, investors' C S R considerations shape their financial portfolio decisions, affect stock prices and influence corporate C S R spending decisions. We also examine optimal tax policy questions, looking to maximize total individual donations plus corporate C S R spending less the tax rebates given for such spending. The third paper argues that insiders (managers and large blockholders) who are affiliated with the firm may want to over-invest in C S R for their private benefit since it improves their reputation.  We test this hypothesis by investigating the relation  between firms' C S R ratings and their ownership and capital structure. We employ a unique dataset that sorts 3,000 U S corporations according to their social record. We find that insiders' ownership and leverage are negatively related to the social rating of firms, while institutional ownership is uncorrelated with it. These results support the hypothesis that C S R is a source of a conflict between different shareholders.  11  TABLE OF CONTENTS ABSTRACT  ii  LIST O F T A B L E S  v  LIST O F F I G U R E S  vi  ACKNOWLEDGMENTS  vii  CO-AUTHORSHIP STATEMENT CHAPTER I  ix  INTRODUCTION  1  1.1  C S R and Profitability  1  1.2  Socially Responsible Investing - Exclusionary Screening  3  1.3  Socially Responsible Investing - Other Investing Methodologies  1.4  C S R as a Conflict Between Shareholders  .  REFERENCES CITED C H A P T E R II  7 9 11  G R E E N INVESTORS A N D CORPORATE INVESTMENT 13  2.1  Introduction  13  2.2  The Model  18  2.3  Examples of Different Reforming Costs  22  2.4  Conclusions  32  REFERENCES CITED C H A P T E R III  33  D O I N G LESS B A D L Y B Y D O I N G G O O D : C O R P O R A T E SOCIAL RESPONSIBILITY  34  3.1  Introduction  34  3.2  The Model  38  3.3  Equilibrium  41 iii  3.4  The Impact of the Proportion of Altruistic Investors  46  3.5  The Impact of Tax Policy Parameters  50  3.6  Conclusion  56  REFERENCES CITED C H A P T E R IV  58  C O R P O R A T E SOCIAL RESPONSIBILITY AS A CONFLICT B E T W E E N SHAREHOLDERS 59  4.1  C S R as a Conflict between Different Shareholders  63  4.2  Data  67  4.3  Multivariate Analysis  75  4.4  C S R and Corporate Governance  87  4.5  Conclusions  91  REFERENCES CITED  93  CHAPTER V  96  CONCLUSIONS  iv  LIST O F T A B L E S  Table  Page  II. 1 Total investment in three different levels of reforming costs III. L Equilibrium values for various levels of I /I IV. 1 Definition and source of major variables IV.2 The distribution of SR (Socially Responsible) and SI (Socially Irresponsible) firms by two-digit SIC code IV. 3 Difference of means tests IV.4 The relation between CSR and the conflict variables - probit regressions IV. 5 The relation between RCSR and the conflict variables - OLS regressions IV.6 Piecewise regressions of Insiders' Ownership: the relation between CSR (RCSR) and the conflict variables IV.7 First stage of the Instrumental Variable regressions IV.8 Instrumental variable regressions: CSR (RCSR) and the conflict variables IV.9 Robustness analysis by size and industry: CSR (RCSR) and the conflict variables IV.lOThe relation between the GIM index and the conflict variables - OLS regressions a  v  32 45 69 72 76 77 81 83 85 86 88 92  LIST OF FIGURES Figure  Page  Ll  The growth of SRI investments ($bn) in the USA for the period 1997 - 2003 4 II. 1 Total investment in the economy as a function of I when C —> oo . . 24 11.2 The number of reformed firms, NR, as a function of I when C —> 0 . 25 11.3 The number of reformed firms, NR, as a function of I in intermediate cases 28 11.4 Total investment for intermediate cases 30 III. 1 Bad firms' share price and donations as a function of Ia / I 46 111.2 Good firms' share price and donations as a function of Ia / I 47 111.3 Total donations as a function of corporate tax rate (Ia / I = 0.4) . . 51 111.4 The cost of lost tax revenues as a function of corporate tax rate (Ia / I = 0.4) 52 111.5 Social Surplus (T-C) as a function of corporate tax rate (Ia / I = 0.4) 53 111.6 Social Surplus as a function of corporate tax rate and donations' ceiling (Ia / I = 0.4) 55 g  g  g  vi  ACKNOWLEDGMENTS The completion of this thesis also marks the end of a beautiful period of five years in Vancouver and at UBC. I would like to use this opportunity to thank not only those who directly contributed to the dissertation but also to those that made this period so special for me. Thanks so much to the following: • My wife, Tami, my life-partner who joined me for this journey five years ago and was part of every small step that I made • My daughter, Shirley, born only 12 months ago but already made our life so much happier • My parents, Pnina and Alex and my sister, Sharon, that although 13,000km away in Israel, play a major role in every single day of my life and are always so involved and carrying • Alan Kraus, my thesis supervisor for his great support, guidance and creative ideas. I couldn't imagine a better supervisor. Thanks for being so accessible and supportive - I really appreciate it! • Rob Heinkel, my committee member, the hard worker that can use his pencil to solve anything that I can solve using Mathematica • Kai Li, my committee member, for her endless energies and great advice • Ralph Winter, my committee member, for his sharp observations and great support • Ron Giammarino, for demonstrating what passion for research is and for his daily support during the job market period • Amir Rubin, my co-author that I enjoyed spending hours and hours of work with him • Hernan Ortiz-Molina, for sharing with me his great straight-forward approach for life • Marcin Kaspercik for being a great friend vii  • Janet Gannon, that without her the Sauder School of Business was much more boring • Sally Bei, the ultimate Finance administrator • Elaine Cho, the ultimate PhD program administrator • Jan Schneider, my fellow student and friend • Sthephan Siegel and Cornelia Kullmann for their advice • Gilles Chemla for many white nights at the business school • Adlai Fisher for his good advice • Murray Carlson for his useful comments • Jeff Colpitts that it is always fun to have him around  vm  CO-AUTHORSHIP STATEMENT  Complying with the U B C guidelines for a manuscript-based thesis, I state here the role of each co-author in each manuscript. Chapter II of the thesis includes work done in collaboration with Alan Kraus, my committee chair and Rob Heinkel a member of my committee. The chapter is a natural extension of previous work by Rob Heinkel, Alan Kraus and Joseph Zechner. Alan Kraus proposed the initial idea of this work. M y role started by developing the model and performing the calculations and numerical simulations that were needed in order to solve it. Throughout the work on the project the three of us were working very closely together, dealing with technical difficulties that arose and gaining the economic understanding of the results. A l l of us contributed for the manuscript preparation. The chapter is scheduled for publication at the journal Structural Change and Economic Dynamics in 2005. Chapter III of the thesis also includes work done in collaboration with Alan Kraus and Rob Heinkel. In this work Rob Heinkel was the major contributor for the development of the model while Alan Kraus and myself worked closely with him on the assumptions and specifications of the model. I also performed the numerical and computational aspects of the work. A l l of us contributed to the manuscript preparation. Again, throughout the development of the project we were working closely, meeting very frequently, gaining together the economic intuitions of the results and overcoming technical difficulties. Chapter I V of the thesis includes work done in collaboration with Amir Rubin. We started the project when Amir Rubin was a Ph.D. student at U B C . He has since then become an assistant professor at Simon Fraser University. The work is a joint effort from the initial idea through the execution of the empirical analysis and the manuscript preparation.  ix  CHAPTER I INTRODUCTION The flowering of Corporate Social Responsibility (CSR) is one of the most significant corporate trends of the last decade. Definitions of CSR vary but generally refer to serving people, communities and the environment in a way that goes above and beyond what is legally required of a firm. This alignment of business operations with social values is by now an industry in itself, with full-time staff in corporations, hundreds of websites, newsletters, professional associations and consultants. Students can earn an M B A degree in CSR and they attend seminars on careers in CSR. Most major companies have a special annual report dedicated to CSR; others devote a big section of the report to the documentation of social goals advanced and good works undertaken. The FTSE and the Dow Jones have both launched indices of socially responsible companies joining similar indices around the world. This dissertation analyzes some of the potential driving forces behind this new corporate behavior. 1.1  CSR and Profitability One can argue that firms' interest in CSR is driven solely by profit max-  imization. For example, a high CSR expenditure by a firm may enhance its employees' productivity (for example, day-care benefits that are provided) or increase consumers' demand for the firm's product (for example, fair trade coffee). As such, CSR may be a simple response to the changing preferences of firms' stakeholders; today's consumers, employees and suppliers demand higher social and environmental standards and firms are responding to this call. It is important to note that even if this observed, high level of CSR expenditure is consistent with maximizing profitability, it has to be the case that the general relation between CSR expenditure and firm value is non-monotonic with an inverted U-shape curve. When CSR expenditure is low, an additional dollar 1  invested in C S R may have a positive contribution to firm value (good publicity, higher productivity, etc.), but at some point the marginal effect of an additional dollar of C S R expenditure is less than the amount spent and so decreases firm value as there is no limit to the amount that a firm can transfer to its stakeholders or to the society. To illustrate the point, consider for example donations made by corporations to the 2004 tsunami victims in Asia. (Corporate donations is one of the most popular forms of CSR). W i t h an initial, small amount donated, it is reasonable to assume that firms gain good publicity and reputation benefits that may translate into higher profitability at some point. But if firms increase the amount that they donate further, it is clear that, at some point, the marginal dollar donated will reduce firm value. Therefore, theoretically, there should be an optimal level of CSR expenditure (with variation across firms and across industries) which is consistent with maximizing shareholders' wealth. The vast majority of research on C S R analyzes the empirical relation between the social performance and the financial performance of firms. Dozens of papers, almost all in the business ethics literature, investigate the possible relation between the two in various ways. The standard approach is to place on the left hand side of the regression some kind of a financial measure (e.g., return on equity/ return on assets / Tobin's q) and on the right hand side some measure of social performance and a list of control variables. In a large survey, Griffin and Mahon (1997) scan some 70 papers that investigate this relationship and conclude that although the results are incomparable, inconsistent and suffer from severe estimation problems, out of the 70 papers reviewed, a majority document a positive relation between the financial and social performance of firms. From a theoretical perspective, this result is puzzling. If there are financial benefits for social spending why don't all firms pursue them? As Mc Williams and Siegel (2001) argue, while there should be variations in the level of C S R expen2  ditures across companies and across industries, once the appropriate controls are applied there shouldn't be any correlation between financial and social measures. Indeed, in an empirical paper, McWilliams and Siegel (2000) find no correlation between the two.  1.2  Socially Responsible Investing - Exclusionary Screening A second potential driving force behind  firms'  urge to improve their social  record is the concept o f Socially Responsible Investing (SRI). SRI reflects an investing approach that integrates social and environmental concerns into investment decisions. SRI first gained widespread public awareness with the boycott of firms engaged in operations in South Africa during the apartheid regime in the late 1980s. These days, a typical exclusionary screening practice would be to use all firms included in the S&P 500 as the initial opportunity set and exclude from an ethical portfolio firms in the tobacco, weapons and gambling businesses or those who have poor employer-employee relationship. Exclusionary screening can follow two types of screening methodologies. An investor who is using perse screening, excludes all firms in a particular sector (e.g. tobacco) from his portfolio. Alternatively, according to a qualitative screening approach, firms are ranked along many ethical / social / environmental dimensions and only those who pass some threshold are eligible for investment. It is important to note that no matter which screening method is applied, the result is the same - excluding securities from the investment universe of the investor. The number of socially responsible investors has increased rapidly in the last decade. Funds under management that are subject to some form of ethical screening account for about 11% of total managed funds in the US and about 4% in Canada (see Figure 1.1 for US numbers). It is important to note, though, that the group of socially responsible investors is not a homogenous one. So3  GROWTH OF SRI INVESTMENTS ($ BILLIONS) 1997-2003 $2,500 S2.143 $2,010  $2,000  • 1997  H1999  H2001  H2003 -  $1,497  $1,500  $1,000 §529  $500  SO  -I  •  I  I  I  r -  Screening Source: Social Investing Forum, "2003 Report on Socially Responsible Investing Trends in the U S "  Figure 1.1: The growth of SRI investments ($bn) in the U S A for the period 1997 - 2003 cial investors include individuals, businesses, universities, hospitals, foundations, pension funds, corporations, religious institutions, and other non-profit organizations. Different investors have different ideologies with respect to the good and bad in the world. Therefore, each investor may have a different "target" list of firms to be boycotted. Despite their impressive presence, it is still not clear what the role of socially responsible investors is. Do they simply want to feel good about themselves by not receiving returns from "sinful" industries or do these investors want to make a difference by changing corporate behavior. Moreover, even if all socially responsible investors join forces and act in coordination, do they have enough power to change corporate behavior towards a more socially responsible agenda? 4  And if they do so, what will be the rate of return on their portfolio relative to that of conventional portfolios? SRI-related literature has focused so far on the empirical analysis of the performance of portfolios that are subject to SRI strategy (usually mutual funds) versus non-constraint portfolios. From the theory side, there are only a few papers that investigate the issue. Hamilton, Jo and Statman (1993) present three competing hypotheses with respect to the relative performance of socially responsible firms which they test empirically. The first hypothesis is that the expected risk-adjusted returns of socially responsible stocks is equal to the expected risk-adjusted returns of conventional stocks or in other words, that stocks have horizontal demand curves. In this world, socially responsible investors have no impact on prices because whenever they wish to buy stocks of socially responsible companies they find enough conventional investors ready to sell them, such that the prices of the stocks do not rise. The second hypothesis is that stocks have downward sloping demand curves. Therefore, the expected returns of socially responsible stocks may be lower than the expected returns of conventional stocks. This hypothesis implies that socially responsible investors can have an impact on stock prices. In particular, they increase the valuation of socially responsible companies relative to the valuation of conventional companies and drive down the cost of capital of socially responsible companies and the expected returns of their stocks. The third hypothesis is that the expected returns of socially responsible stocks are higher than the expected returns of conventional stocks. This is possible if a sufficiently large number of investors consistently underestimate the probability that negative information would be released about companies that are not socially responsible. For this hypothesis to hold, it is not enough that socially responsible firms will have better financial performance. Asymmetric information among 5  investors is the crucial assumption for this hypothesis to hold. The second hypothesis was further explored by Wall (1995) and Angel and Rivoli (1997) who numerically evaluate the financial consequences (increased cost of capital) of ethical screening using Merton's (1997) framework of segmented markets and by Heinkel, Kraus and Zechner (2001) who develop an equilibrium model where socially responsible investors can affect firms' cost of capital. The first paper (second chapter) of the dissertation extends the model proposed by Heinkel, Kraus and Zechner (2001). They analyze the effect of exclusionary screening in lowering a polluting firm's share price to the point where maximizing share value supports paying a fixed cost to reform, allowing the firm's shares to be held by the investors applying the social screen. However, in that model investment by firms is held constant. In the first paper, we endogenize investment decisions and examine the potential impact that exclusionary screening have on total economy-wide investment. Answering the question what is the critical mass of socially responsible investors that is required in order to create this impact is one of the main issues addressed in this work. It seems that the current proportion of these investors is not enough to change corporate behavior. Even if one assumes that all socially responsible investors are homogenous in their preferences and that the cost involved in changing firms' technology to one which is "SRI-approved" is low, the model predicts that if socially responsible investors account for less than 35% of the total number of investors, no firm will find it optimal to change its technology to a socially responsible one. A t current estimates of up to 11%, the effect of SRI on corporations seems to be insignificant. On the empirical side of SRI-related literature, most studies analyze the performance of socially responsible portfolios such as mutual funds in the US. Major studies are those by Hamilton, Jo and Statman (1993), Diltz (1995), Sauer (1997) Goldreyer and Diltz (1999), Statman (2000), Bauer, Otten and Rad (2004) and  6  Geczy, Stambaugh and Levin (2004). There are also a few papers documenting the effects of divesting shares of firms engaged in operations in South Africa during the apartheid regime in the late 1980s, for example, Teoh, Welch, and Wazzan (1999). In broad terms, all of the empirical studies document similar performances for SR portfolios versus conventional ones. This evidence supports that first hypothesis described above or simply illustrates that the number of socially responsible investors is too low to create a significant impact on prices.  1.3  Socially Responsible Investing - Other Investing Methodologies Not all socially responsible investors use an exclusionary screening method-  ology. Moderate socially responsible investors may simply want to hold fewer shares of firms that their business is not viewed as moral by these investors instead of strictly boycotting them. On the other hand, some investors may wish not only to avoid holding shares but even to short sell shares of firms that they consider irresponsible. Moreover, it is plausible that even among those investors who value social expenditures made by corporations, some investors may prefer to make their own private decisions with respect to the cause that their money is directed to. In other words, they may prefer to receive higher dividends from the corporation and choose by themselves whether or how to allocate these funds to a good cause. The theoretical framework of the second paper (third chapter) "allows" investors this freedom in their decisions. Another important feature that the third chapter models is that CSR behavior may be viewed quite differently by investors when done by different firms. For firms with a clean technology, a healthy product and good labor relations, CSR expenditures may not have the same marginal impact on investors as CSR expenditures by a firm with a polluting technology, poor labor relations and an 7  unhealthy product. The latter firm may still be viewed negatively on balance by investors, but the CSR expenditure might have a greater positive impact on investors than for the clean, healthy firm. Lastly, the third chapter examines optimal tax policy questions. Individuals can deduct private donations from their taxable income. Similarly, corporations can deduct most CSR related expenditure from their revenue for tax purposes but only up to a ceiling (percentage of revenue) which is set by the government. We show that there is a way to maximize a "Social Surplus" which is defined as total individual donations plus corporate CSR spending less the tax rebates given for such spending, using the different tools that the government has: tax rates for individuals and corporations and the ceiling for CSR expenditure. Small and Zivin (2002) develop a related but much simpler model that shares some similarities to the third chapter developed here. They model an economy in which investors with utility that is concave in consumption and donations (both the investor's and the corporation's) make donations and invest in two riskless firms' shares. One firm makes a fixed donation and one does not. Investors consume out of the end-of-period riskless cash flows from their shareholdings, less what they donate. There are no frictions, such as taxes in the model. In this simple world, Small and Zivin (2002) develop a "Modigliani-Miller" irrelevance result. Suppose that investors optimally wish to donate. The two firms' share prices will be equal and will be independent of the level of donation made by the donating corporation. The idea is that if the donating firm changes its donation level, investors can offset the effect of this by altering their private donation. The model that we develop here can duplicate this "irrelevance result" if one uses the same assumptions as in Small and Zivin (2002): (i) a riskless technology, (ii) exogenous level of corporate investment and CSR spending, (iii) only one type of investor (our "altruistic" investors) and (iv) no taxes. 8  1.4  C S R as a Conflict Between Shareholders  The third paper (fourth chapter) of the dissertation is an empirical work that tests a different potential explanation for the dramatic increase in C S R expenditure. The hypothesis is that these actions are advanced by insiders - affiliated shareholders such as corporate managers and large blockholders. Insiders' reputation, identity or heritage is closely tied to the firm and since actions taken by the corporation are associated with them on a personal level, they may have an interest to increase C S R expenditure to a level which is higher than that which maximizes firm value. A good CSR record would enhance their reputation as being decent individuals who respect their employees, communities and the environment and care about society. While insiders are closely associated with a specific firm, non-affiliated owners hold shares in firms as part of a well diversified portfolio and have a relation with each individual firm that does not go beyond its effect on their portfolio value. Therefore, they may not approve a high C S R expenditure level if it reduces firm value given that they don't share the "warm glow" effect of giving. Therefore, CSR may be the source of a conflict between affiliated and non-affiliated shareholders. The group of insiders is composed of three subgroups: managers, blockholders who are not part of the daily management team, and directors who are not part of the first two groups. It is hard to hypothesize which group gains more from being associated with a socially responsible firm. However, we argue that all three subgroups care about the firm's C S R rating more than does a diversified shareholder. For example, consider the following three individuals: Steven Jobs, the C E O of Apple Computer, Warren Buffet, a large blockholder of The Coca-Cola Company and Roy Disney, a director of The Walt Disney Company. A l l three individuals are strongly affiliated with their corresponding firm. Our 9  hypothesis is that these individuals gain from the fact that these firms have a high CSR rating more than does a diversified shareholder such as Fidelity, whose image is not affected by the social rating of one specific firm. In order to test this potential conflict we analyze the relation between CSR and the ownership and capital structure of the 3,000 largest US corporations. If insiders gain unique benefits at the expense of other shareholders, their degree of ownership should matter in setting the level of CSR expenditure in the firm. The level of ownership by insiders can have two potential effects: on the one hand, with high ownership comes entrenchment, which allows insiders to pursue a pro-CSR agenda more easily. But on the other hand, when insiders' ownership is high, insiders bear more of the cost of the CSR expenditure. Therefore, if CSR expenditure is at a level at which it reduces firm value, insiders' ownership should be negatively related to the level of CSR expenditure since insiders bear more of the cost associated with this expenditure as their degree of ownership rises. The capital structure of the firm may also influence the CSR conflict. When firms have high interest payments, it limits the ability of insiders to over-invest in CSR. A high debt level also induces creditors to play a more active monitoring role which may help to mitigate the conflict. We find supportive evidence to our hypothesis: firms that have a higher social ranking tend to have looser monitoring mechanisms, giving insiders the freedom to spend more on CSR without paying a significant portion of this amount out of their own pocket.  10  REFERENCES  CITED  1. Angel, James J , and Pietra Rivoli, (1997), "Does Ethical Investing Impose a Cost Upon the Firm? A Theoretical Perspective" The Journal of Investing 6(4): 57-61. 2. Bauer, Rob, Roger Often and Alireza Tourani Rad (2004), "Ethical investment in Australia: is there a financial penalty?"  Maastricht University,  working paper. 3. Diltz, J.D. (1995), 'Does Social Screening Affect Portfolio Performance?", The Journal of Investing, Spring, pp. 64-69 4. Geczy Christopher O , Robert F . Stambaugh and David Levin (2004), "Investing in Socially Responsible Mutual Funds", working paper, Wharton School, University of Pennsylvania. 5. Goldreyer, Elizabeth and J. David Diltz (1999). "The Performance of Socially Responsible Mutual Funds: Incorporating Sociopolitical Information in Portfolio Selection," Managerial Finance, vol. 25, no. 1: 23-36. 6. Griffin, Jennifer J . and John F . Mahon (1997), "The corporate social performance and corporate financial performance debate: 25 years of incomparable research", Business and Society, 36(1), 5-31. 7. Hamilton, Sally, Hoje Jo and Meir Statman (1993). "Doing Well While Doing Good: The Investment Performance of Socially Responsible Mutual Funds," Financial Analysts Journal, November/December: 62-66. 8. Heinkel, Robert, Alan Kraus and Josef Zechner (2001). "The Effect of Green Investment on Corporate Behavior," Journal of Financial and Quantitative Analysis, vol. 36, no. 4 (December): 431-449. 11  9. Mc Williams, A . , Siegel, D., (2000), "Corporate social responsibility and financial performance: correlation or misspecification?", Strategic Management Journal 21, 603-609. 10. McWilliams, A . , Siegel, D., (2001), "Corporate social responsibility: a theory of the firm perspective", Academy of Management Review 26 (1), 117— 127. 11. Merton, Robert C. (1987), " A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance 42(3): 483-510. 12. Sauer, D . A . (1997), 'The Impact of Social-Responsibility Screens on Investment Performance: Evidence from the Domini 400 Social Index and Domini Equity Mutual Fund', Review of Financial Economics, Vol. 6, No. 2, pp. 137-149 13. Small Arthur A . , and Joshua Graff Zivin, (2002) " A Modigliani-Miller Theory of Corporate Social Responsibility", working paper, Columbia University 14. Statman, Meir (2000), "Socially responsible mutual funds", Financial Analyst Journal, 56 (3), 30-39. 15. Teoh, Siew Hong, Ivo Welch, and C. Paul Wazzan (1999), "The Effect of Socially Activist Investment Policies on the Financial Markets:  Evidence  from the South African Boycott", Journal of Business 72(1): 35-87. 16. Wall, Larry D, (1995), "Some Lessons from Basic Finance for Effective Socially Responsible Investing," Economic Review 8, 1-12.  12  CHAPTER II GREEN INVESTORS AND CORPORATE INVESTMENT 2.1 Introduction Green investing, or socially responsible investing (SRI), refers to making investment decisions according to both financial and ethical criteria. SRI first gained widespread public awareness with the boycott of firms engaged in operations in South Africa during the apartheid regime in the late 80Is. Teoh, Welch and Wazzan (1999) argue that, at that time, the magnitude of funds that were subject to this boycott policy and the impact of these actions were negligible. On the other hand, during the last decade the amounts of investments that are subject to SRI policies have increased more than tenfold. According to the Social Investing Forum, an association dedicated to promoting the concept of green investing, the amount of money involved in SRI reached a level of $2.2 trillion in 2003, accounting for about 11 percent of all managed funds in the US.  1  The Social Investing Forum defines three strategies that are used by investors who wish to promote socially and environmentally responsible business practices: screening, shareholder activism and community investing. We focus on screening,  the practice of including or excluding publicly traded securities from investment portfolios or mutual funds based on social and/or environmental criteria. A typical exclusionary screening practice would be to use all firms included in the S&P 500 as the initial opportunity set and exclude from an ethical portfolio firms in the tobacco, weapons and gambling businesses. On the other hand, an inclusionary screening approach involves selecting companies based on their positive contributions to society such as outstanding employer-employee relations, excellent environmental practices and so on. Exclusionary screening can follow °This chapter, co-authored with Rob Heinkel and Alan Kraus is scheduled for publication in Structural Change and Economic Dynamics in 2005. ^ee also Statman (2000) for a discussion about the magnitude of funds invested using SRI.  13  two types of screening methodologies. A n investor who is using per-se screening excludes all firms in a particular sector (e.g. tobacco) from his portfolio. Alternatively, according to a qualitative screening approach, firms are ranked along many ethical/social/environmental criteria and only those who pass some threshold are eligible for investment.  It is important to note that no matter  which screening method is applied, the result is the same - excluding securities from the investment universe of the investor. Previous research in the area has considered the impact of stakeholders on the social behavior of the firm. McWilliams and Siegel (2001), for example, analyze the impact of consumers on firms' decisions to engage in corporate socially responsible (CSR) actions ("reform" in our terminology). Russo and Fouts (1997) claim that a corporation with a good environmental performance has a positive impact on its employees, technology and reputation which leads to higher profitability. Jones (1995) argues that firms that devote resources to C S R have a competitive advantage over other firms in the product market. While these researchers suggest that the motive for the social behavior of the firm is stakeholders such as employees, consumers and regulators, this chapter analyzes the potential impact of green investors on the investment decisions of firms and on their decisions to reform. We focus on exclusionary screening, which is by far the most popular SRI practice, accounting for over $2.0 trillion of the $2.2 trillion mentioned above. Heinkel, Kraus and Zechner (HKZ, 2001) analyze the effect of exclusionary screening in lowering a polluting firm's share price to the point where maximizing share value supports paying a fixed cost to reform, allowing the firm's shares to be held by the investors applying the screen. However, in that model investment by firms is held constant.  In this chapter, we endogenize investment and examine the  impact that exclusionary screening has on total economy-wide investment. In our model, risk-neutral entrepreneurs have projects that they wish to im14  plement and sell to risk-averse investors. The entrepreneur chooses a cumulative investment amount K and sells the firm to investors for P, earning the investment's net present value, P — K? This assumes the entrepreneur orders projects by NPV and takes projects until NPV = 0 for the next best project. The projects belong to a set of two types. Half of them have a clean technology (JV = .5) and C  the other half have a polluting technology (N — .5). The expected returns and p  variances of the two technologies are identical, but the correlation between the returns is less than 1.0, thus offering diversification benefits to investors. Risk-averse investors are composed of two types of individuals: neutral investors, who do not practice exclusionary screening and green investors, who do. Green investors refuse to hold shares of firms with polluting technologies. The fraction of green investors in the economy, ^f, is set exogenously between 0 and 1. Both green and neutral investors have the same level of risk aversion. Entrepreneurs having polluting technology projects can, before selling their stock to the public, spend C and become reformed. Reformed firms retain the characteristics of the polluting technology (i.e., mean, variance and correlation with the clean technology), but they are now acceptable to green investors. The number of firms with polluting technologies that switch from polluting to reformed is endogenous (N varies from 0 to .5) to satisfy the equilibrium condition P —K — C = P — K . r  r  r  p  p  That is, in equilibrium no polluting firm can benefit from reforming. Green investors hold clean and reformed firms but in order to have no arbitrage we limit neutral investors (as in HKZ (2001)) to hold clean and polluting firms only and prohibit short selling shares of reformed firms by these investors. Otherwise, the neutral investors could earn a riskless arbitrage profit by shorting the reformed firms and buying the polluting firms since the latter use exactly the same technology but their share price is lower (when there are positive reforming costs). A l lfirmswithin each of the three firm categories are identical but they 2  W e assume that the market for new projects has positive N P V opportunities due to limited access.  15  choose their investment atomistically and not as a cartel. Our interest is in how varying the fraction of green investors from 0 to 1 alters the prices and investment levels of clean, polluting and reformed (if they exist) firms. For expositional reasons, we describe this process as though -f were J  increasing. However, since we have a single-period model, the analysis is actually that of comparative statics. We first analyze two extreme cases; one in which C is very high and one in which C equals zero. Later we discuss intermediate cases. Suppose C, the cost of reforming, is infinite. As investors change from neutral to green (Jf goes from 0 to 1), firms with polluting technologies never find it optimal to reform since the cost of doing so is always too large. This results in the price and investment level of the polluting firms dropping, as the demand for their shares decreases. Since the demand for the shares of the clean firms is relatively constant, because both the green and neutral investors hold shares of clean firms, total investment in the economy also falls. In this extreme case the green investors have the largest negative impact on total investment in the economy. The other extreme case is one in which C = 0. Then, when reforming is costless, firms with polluting technologies start switching to reformed, making them acceptable to green investors, as soon as  is positive. As we formally  show later, when C = 0, the rate at which polluting firms switch to reformed is a linear function of the number of green investors. This strong result implies that green investors have no real effect on the economy other than reforming polluting firms. As neutral investors are switching to green {^f goes from 0 to 1) polluting firms are reforming at a proportional rate that perfectly satisfies the diversification needs of green investors. Reformed firms are very valuable to green investors because by holding them they can gain access to the polluting technology. Moreover, only green investors hold reformed firms. But when C = 0, the linearity of the reformation rate implies that there is never a shortage or 16  surplus i n the supply of reformed firms per green investor.  A s a result, their  share prices and investment levels remain constant for any proportion of green investors as does the total investment i n the economy. In order to discuss less extreme cases of reforming costs we first define / * as the level i n which the first polluting firm switches to reformed. For I  g  the number of reformed firms, N , r  < I*  equals zero and then rises to i V = .5 when r  — = 1. Intermediate cases are those w i t h reforming costs C (0 < C < o o ) , such that 0 < / * < 1. E v e r y intermediate case can be divided to two phases related to the two extreme cases described above. A n intermediate case always begins w i t h a phase that resembles the C —> oo case. In this phase, since the benefits of avoiding being boycotted by the green i n vestors do not compensate for the reforming costs, no firm reforms. Consequently, the price and investment level of the p o l l u t i n g firms and the total investment i n the economy drop. A t / * firms start to reform and the intermediate case enters its second phase. There are two differences between this phase and the C = 0 case described above. First, i n the C = 0 case / ' « 0  while intermediate cases have / * > 0. T h e second  difference is that while i n the C = 0 case the reformation rate is linear, i n the second phase of intermediate cases the reformation rate is convex. These two differences yield interesting results as we further explain. Recall that holding shares of reformed firms is valuable for green investors as these shares provide diversification benefits. However, since i n intermediate cases I* > 0, reformed firms first appear only after some mass of green investors is already present. Once the first p o l l u t i n g firm switches to reformed, its shares are i n high demand by the green investors, which results i n a high price and high investment level.  One can also view this situation as a shortage i n supply of  reformed firms relative to the C = 0 case where the number of reformed firms is proportional to the number of green investors and diversification benefits are 17  always at an optimum. The convexity of the reformation rate implies that this relative shortage in reformed firms disappears only when all firms have reformed and all investors are green, at y = 1. This results in the economy exhibiting its maximum total investment at the extremes when If = 0 or*-f= 1. Any fraction of green investors between 0 and 1 yields lower investment levels. The Social Investing Forum estimates that more than one out of every nine dollars under professional management in the United States today is involved in socially responsible investing. If we use these estimates as an approximation for the proportion of green investors in the population, we conclude that this investment practice is decreasing the total investment in the economy and that an increase in the proportion of green investors from its current level will result in an additional decrease in total investment.  2.2 The Model Firms As discussed above, there are three categories of firms: clean, polluting and reformed, denoted c, p and r, respectively; there are A , firms of type i, 7  i€  {c, p, r} and N firms in total. A polluting firm that reforms switches to the reformed class by paying a fixed cost of C. This means that it will retain its polluting technology, but will be acceptable for investment by green investors.  3  Firm's i output is given by the following production technology: Y = FiXi where Fi — Kj  1  {pf < 1) and Xi ~ N (p^Vi).  The fact that reformed firms  i  retain their polluting technologies, implies: j = j . The covariance between Xi r  p  and Xj is denoted by Vij and the correlation by ^ •. We assume that the outputs of firms of the same type are perfectly correlated with each other. 3  We  s o l v e d t h r e e different cases for t h e r e f o r m e d  p o l l u t i n g technology, i n the second, the reformed  firms.  firms  I n t h e first one, the r e f o r m e d  firms  retain their  s w i t c h to a clean technology a n d i n the t h i r d ,  the  r e f o r m e d f i r m s a d o p t a r e f o r m e d t e c h n o l o g y t h a t is s o m e w h e r e b e t w e e n t h e c l e a n a n d p o l l u t i n g technologies. In  this p a p e r w e present the case i n w h i c h the reformed  firms  retain their polluting technology to avoid  c o n f u s i n g the issue b y i n t r o d u c i n g d i v e r s i f i c a t i o n benefits to b o t h the green a n d the n e u t r a l  18  investors.  An entrepreneur of a firm of type i,  i € {c,p, r} chooses an investment level  Ki, that maximizes his net present value, { p — Ki}. The entrepreneurs in our economy are not price takers with respect to their own share prices. If they were, they would simply choose K* = 0 to maximize Pi — Ki for fixed p . We do assume, however, that each entrepreneur takes the investment decisions of other entrepreneurs as given so that the investment level of each industry is not set in a collusive way. Therefore, the first order conditions are taken with respect to the specific Kji, of entrepreneur j. In order to demonstrate how the FOCs are taken, consider for example equation (II.7) which represents the price of one share of each clean firm (they are all identical ). K appears twice in this equation: as the first variable and inside c  the brackets multiplied by N , the total size of the industry which is composed c  of many firms.  / P -  K  lc  Pc  {Ig + In)  \ K2°N  V + K?*N V  C  r  C  R  \ iq +cvK2 +a iq +... ai  c  c  a  CTV  +  K^N V P  CJP  J  c  (II. 1) Although in equilibrium all entrepreneurs in the clean industry choose the same K*, from the point of view of a single entrepreneur a more accurate representation of the term K2 N C  C  is  OL\K1  c  + a_-K_c  weight of firm j in the clean industry and  +  a K^ + 3  C  where otj is the  = VY «?• In other words, a single  entrepreneur, say entrepreneur 1, chooses his optimal level of investment, K\ , C  taking all other K' s as given. Failing to do so by taking the FOC with respect c  to some general K , creates a cartel effect that we want to avoid. It would be C  like setting one optimal K* for the whole industry in a collusive way because the total output of the industry is taken into account in the maximization decision of every single entrepreneur. We further assume that each industry is composed of many identical firms and that each one is sufficiently small (<x, ~ 0) such that the derivative with respect 19  to ctjKj is negligible and hence, we ignore it. c  Investors and Green Screening There are two types of investors: neutral and green, denoted n and g, respectively. There are Ik investors of type k and / investors in total. Neutral investors are willing to invest in all types of firms but green investors refuse to hold shares in polluting firms. Each investor has constant absolute risk aversion ( C A R A ) preferences (i.e., negative exponential utility) with a risk tolerance parameter denoted by r . Based on the assumptions of normally distributed output and C A R A preferences, a representative neutral investor has the following expected utility function:  lc c c F  X  U  x Fn  n  nc  c  +  c  -f- x  x pFpfj,„ n  nc  n  c  F V  X  —  r  -\~ Zx x F F V  C  l,r r  +  X  F /j,  nr  \2x x pF FpV p  + l  V  nc  nr  c  r  ~\~  cp  (II.2)  ZT 2x x pF Fp\^p^  c  nr  n  r  2r (^nc  ^nc)Pc  iS^nr  (*^np  ^nr)Pr  ^np) Pp  A representative green investor has the following expected utility function (with 9P  X  =  0)  :  TJ _ r? Ug — Xg r H C  C  C  , rp _ -r Xg r fJ>p r  [ gc c^c x  + Xg F^V  F  r  +  p  0  r  2x x F F V p\ gc  gr  c  r  C  v  ^/  ZT ( nc x  ^nc)Pc  ( nr x  ^nr^)Pr  where, x „ , i G {",5'}, j G {c,r,p} is the number of shares of firm j held by investor i and Uij, i £ {n,g},  j G {c,r,p} is the number of shares of firm j  endowed to investor i. Time Line of Events Our model is a one period model, but it is useful to imagine the actions taking place in the following sequence of events. First, the polluting 20  firms decide whether to reform or not and the entrepreneurs sell shares to investors. After raising the funds, the entrepreneurs invest  K ,K , c  K  r  p  (the amount  that they were committed to) using the capital that was raised by issuing shares. The entrepreneurs of reformed firms also pay C out of the funds raised from the share issue. Lastly, future outputs  are revealed and distributed to the  Y ,Y ,Y c  r  p  investors. Equilibrium The market clearing conditions are: (II.4)  In  + Ig gr  x  I X*  =  (II.5)  Nr  X  n r  (II.6)  N  In order to have no arbitrage we must prohibit short selling of reformed shares by the neutral investors. Otherwise, the neutral investors could short the reformed firms and buy the polluting firms. Since the latter use exactly the same technology but their share price is lower (when there are positive reforming costs), neutral investors could earn a riskless arbitrage profit. Therefore, in equilibrium we set x* = 0. nr  The resulting equilibrium prices are:  p  c  — Ki\ iP — p  p p  Pp  ~  (  .  T  1 T  (Ig + l )T n  P  r  =  Kr  P  P  (Ig+I )T  P  s  (K^N V C  + K7*N V  C  r  (II.7)  + K; N V ) p  CiP  p  CtP  V  \  l V (II.8)  c  K2°N V c  + K; N V p  CtP  r  p  + KpNp^f-  + K? N p  In r  *  n  n  C.  c  * IgV  c  (II.9)  where  <f> = V V C  P  -  V  2 c p  A Nash equilibrium is a solution that satisfies the following conditions: 21  1.  dPi/dKi  = 1,  i £ {c,p, r} (first order condition for maximizing net present  value) 2. ( P — K*) = (P — K*)— C (gain from reforming just covers fixed reforming p  r  cost) The solutions to these four equations give the optimal investment levels {K*, K*, and the number of polluting firms that reform in equilibrium, N*. A n interesting observation is that the price and investment level of the clean firms, P and K c  that is,  c  are relatively insensitive to the number of green investors,  « 0 and ffi- « 0. The reason is that in the price equation of the  clean firms, equation II.7, I does not appear as a direct parameter. Therefore, g  P depends on I only through a second order effect from N , N , K c  g  r  p  r  and K . p  Using numerical simulations we verified that this secondary effect is indeed very small. This result is similar to H K Z (2001) where the price of the clean firms is completely independent of I . g  2.3  Examples of Different Reforming Costs The complexity of the equilibrium conditions does not allow us (except in  some cases) to get analytical solutions for the optimal investment levels and for N*, the number of firms that reform in equilibrium. Therefore, in order to explore the model's predictions we solve it numerically. We present two extreme cases and two intermediate cases. The two extreme cases that we analyze are one in which C is very high (C —> oo) and one in which C equals zero. Calibration We present a case with infinite reforming costs, as well as three cases in which reforming costs vary from 0% to 10% of the investment levels {K*, K*, K*}. The resulting cost of capital in equilibrium in the zero and intermediate cases is in the range of 4% to 12% for each type of firm. Parameters: 22  Technology: 7 = _; l = \] p  C  Random shocks' means: p = 1 ;  // = 1  c  Random shocks' variances: K = 1 ; Correlation and covariance:  V^, = 1  = 0.70;  p  cp  => V  c>p  =  p #\fVc\fV c  v  = 0.7  Risk tolerance: r = 5 Initial proportion of firms : N = 0.5,  AT = 0.5  4  c  p  Investors: I = I + I = 1 g  n  Infinite Reforming Costs (C —> oo) When there are infinite reforming costs, there is no option for polluting firms to reform. This is the case in which the green investors' impact is the largest. As the number of investors who boycott the polluting firms increases, the demand for polluting firms falls and their price drops. An alternative way to describe it would be from the side of the neutral investors. As the number of neutral investors decreases, and since polluting firms never reform, a smaller group of neutral investors is forced to hold the fixed supply of polluting firms. As this group gets smaller, the price of the polluting firms must get lower and lower in order to compensate that group for the extra risk that it is bearing. The decrease in the price of the pollutingfirmsis accompanied by a decrease in the investment level of these firms and as a result, a decrease in the total investment of the economy. Figure II. 1 shows the total investment in the economy (defined as N K + N K ) C  C  p  p  as a function of I for the infinite g  reforming costs case. Zero Reforming Cost (C — 0) We define I* to be the critical level of green investors at which the first firm reforms. When there are no reforming costs, the reformation process starts immediately, that is, I* equals zero. In the absence of reforming costs, there is a frictionless flow of firms from K L D (Kinder, Lydenberg, Domini and Co.) have constructed the Domini 400 Social Index, which is a portfolio of 400 ethically screened stocks. Out of the 500 stocks that compose the S & P 500 index, 252, or about 50%, have passed the K L D ethical screening. 4  23  Total  Invstrrent  0.18 0.16 0.14 0.12  0.2  0.4  0.6  0.8  1  ig/i  Figure II. 1: Total investment in the economy as a function of I when C —>• co g  the polluting category to the reformed one. As soon as some neutral investors switch to green, some polluting firms find it beneficial to reform, at no cost, and avoid being boycotted by the green investors. As reflected in Figure II.2, the reforming process starts as soon as some neutral investors become green (/* = 0), and continues at a linear rate until all investors are green and all polluting firms have reformed. We summarize this intuition more formally in the following propositions. Proposition 1  When reforming costs are zero, the rate at which polluting firms  reform is a linear function of the number of green investors. Specifically, N = r  Proof. Using our argument from section 2.2, the first order conditions in equations (II.7)-(II.8) are taken only with respect to the first component, Ki i £ {c,r,p}. Therefore, the FOC for firm i is: dKi ^Pi = 2K  Vi  {  1  KJ Ki ie{c,r,p}. h  2Ki  (Since ^ = \ = 7 i  24  \/i)  Figure II.2: T h e number of reformed firms, N R , as a function of I when C —* 0 g  Note that C = 0, P = 2K r  applied to equilibrium condition 2:  and P = 2K  r  p  P  (P - K;) = (P - K* )- C , yields P = P and K = K = K. p  r  r  r  p  r  p  We use this to solve equations (II.8)=(II.9) for N : r  ^-  ; n K  ^  1  (V w + Km v c  ClP  r  IJ^iTr ( ^ c W c , + Km V  -  P  p  P  r w  p  K^N/fJ^  +  r  Km/f^  +  %  + ICN %  p  => i P ^ I / p + K~<N ^ + KiN y$r  +i  p  = K^N V + K^N ^ P  r  P  r  + K^N^f-^ (divide  9  n  i V y + A>p% + J V y y ^ = N V + i V y % + / V p ^ (use N = \ - N ) r  p  P  P  p  9  =• (2iV - 1) y + ( | - 2N ) % + N f$-  = ( | - /V ) ^  I  r  p  r  (2N - I ) i + =  I  r  i  fi  +0  2  2+  + a  A  N  r  (divide by £ )  r  (2N -\)+N f r  r  = (J - iV )  r  (\-N ) f I  r  1  /__+__  2  /„  (JM+LL J  n  r  n  (use I + I = g  lI g  n  = -I 25  n  1)  (use 0 = K ^ - V ^ > )  QED. Proposition 2 When reforming costs are zero, the economy is independent of the number of green investors. The share prices and investment levels of all firms are equal and constant for every level of  *-f.  Proof. We substitute the result of proposition 1 in the FOCs of equations (II.7) and (II.8) to show that the optimal investment levels are constant for every level of I and therefore, total investment in the economy is constant. Start with g  the FOC for P : c  P,  => 1 = 2K,  Pc  K  7 = 7  = Kp = K,  r  1=  ijr^  1  C  Pc  p  2 c n  C  r  CtP  tn)  -11/  and N — \ — N p  r  (K2N V C  r  use I + I = l and 7V = | ) g  (Ig \~y +i  = 7  (Ig + In)  + KpNpVcp)  p  C  L  t,  use  (K2<N V + K? N V  -  +  C  K^V ) C}P  C  2  I  Pc  c  K* is a function of constants  K -V2 -c  +  y  c  fV  T  K2-V  (11.10)  J  v  V , V ) and K, independent of I .  (fi ,T,  c  c  CtP  g  The FOC for P : p  1 - ____ 2K  n  P  L  (use  K  P  = K  r  p  1 =  = K  C  C  P  P  + K?N ^  r  g  p  +  r  P  n  r  = § (1 -  I) g  \Kpi- *  K^Jf^  = \f  1  (Ig + In)r  ^  K2N V , + K;N V I )r\ , N = \l and N = \ - N  (Ig +  tf2W_K,  .  + ini (1 -  /,)  v  p  + K^\i % g  +  K'Wfi)  1= x  2  P  1 = I/<7-l 2 P  ^ P - ; ( ^ . K ,  1=  P  +  ^  Pv--[Kr^  P  ry  26  -2  + K^-Vp  (11.11)  =>• K* = K* = K* is a function of constants (n , r , Vp, y p) and K , independent Cj  c  of/,. Solving the system of equations (11.10) and (11.11) yield unique close form solutions for K* and K* which are constant and independent of I . Moreover, as g  long as as fi = fx , V = V and 7 = 7 as in our calibration in section 2.3, p  c  p  c  C  p  K* = K* = K* VI which also implies P* = P; = P * V / . r  QED.  g  r  g  •  We focus on the analysis of investment levels. As the first neutral investor becomes green, he divests his holdings in the polluting firms. B y doing so, he loses the diversification benefit of holding both technologies. This green investor has a potential demand for shares of reformed firms (if they existed) because these shares offer him access to the polluting technology. Simultaneously, some of the polluting firms suffer from the divestment of their shares by green investors. But since reforming is costless, some polluting firms immediately reform in order to fill the demand for reformed firms and avoid being boycotted by the green investors. As stated formally above, this results in a linear reformation process which begins as soon as the first green investor appears. Consequently, the price and investment levels of the reformed firms, P and K , equal those of the pollutr  r  ing firms and overall investment in the economy, defined as ^_  NiKi,  remains  i=c,r,p  constant for every level of I . g  Intermediate Cases (0 < C < oo) When reforming is costly, polluting firms do not find it optimal to reform as soon as the first green investor appears. The aggregate effect of green investors boycotting the polluting firms on their share price has to be large enough to compensate for paying the reforming costs and this is not usually the case when I is small. In the previous subsections we g  discussed two extreme cases. One, when the cost to reform is infinite and firms 27  never find it optimal to reform and second, when the cost to reform is zero and firms start to reform as soon as the first green investor appears. Here, we discuss intermediate cases in which reforming costs are positive but not so high that firms never reform. Then, there will be a critical mass of green investors, /*, at which the first firm reforms.  Ig/I  Figure II.3: The number of reformed firms, NR, as a function of I in intermediate cases. g  Dashed line: reforming cost = 10%; Solid line: reforming cost = 6% An interesting observation is that in intermediate cases, an economy that has no green investors (I = 0) and an economy that has only green investors g  (I = 1) have the same investment levels and share prices. Formally, P (I = 0) = g  c  g  P (I = 1), and P (I = 0) = P (I = 1). The reason for this symmetry is the c  g  p  g  r  g  following: at I = 0, there are only neutral investors in the economy and two g  types of firms, clean and polluting. At I = 1, there are only green investors g  in the economy and two types of firms, clean and reformed. Since the reformed firms and the polluting firms are using the same technology (polluting), the two economies described above are essentially the same. This implies identical 5  5  T h e economy with I = 1 has incurred N C in fixed costs, to reform all polluting firms. g  P  28  outcomes i n terms of prices and investment levels i n the two economies. Figure II.3 demonstrates two examples of intermediate cases w i t h different reforming costs that represent six and ten percent of total investment.  When  reforming costs equal six percent of investment, / * ~ 0.15 and when they are ten percent, I* « 0.5. W e view every intermediate case as if it is divided into two different regimes; the first when 0 < I  g  < I* and the second when I* < I  g  < I.  T h e first phase is identical to the C —» oo case described earlier. A s more investors switch from neutral to green, they divest their holdings i n the p o l l u t i n g firms and increase their demand for the clean firms. T h i s drives down P and p  K, p  the share price and investment of the polluting firms, and pushes up slightly the price and investment of the clean firms. Since the effect on the p o l l u t i n g firms is much larger t h a n that on the clean firms, total investment i n the economy falls. A t some point i n the process (j  g  = / * ) , polluting firms start to reform and  a t h i r d category of firms is created: reformed firms that use the polluting technology. F r o m here, we move to the second phase. T h e actual behavior of t o t a l investment i n this phase depends on the size of the reforming costs, which determines the level of / * . W h e n reforming costs are high, I* is also high; for example, i n the case presented here, reforming costs of ten percent of investment result i n 1 ~  0.5. T h e  high level o f / * implies that the reformation process, once begun, w i l l be relatively fast. T h i s happens because at I  g  = 1 the number of p o l l u t i n g firms must equal  0 (as there are no neutral investors) and therefore, the number of reformed firms must change from 0 to | as I goes from / * to I g  g  = 1. T h i s rate of reformation is  higher than i n a case where / * is closer to 0. T h e intensity of the reformation rate is translated into an increase i n the total investment i n the economy. T h e reformed firms are very valuable to the green investors and therefore their price and investment level are higher t h a n those  29  Figure II.4: T o t a l investment for intermediate cases. Dashed line: reforming cost = 10% Solid line: reforming cost = 6%  of the polluting firms, which are less valuable to investors due to their larger supply.  In the reformation process, every p o l l u t i n g firm w i t h low investment  level is replaced w i t h a reformed one w i t h a high investment level and since the rate of reformation is high, total investment goes up. A lower reformation cost of approximately six percent of the initial investment, results i n a lower value of I* « 0.15. T h e prices and investment levels of the reformed and p o l l u t i n g firms exhibit similar behavior to the case of high reforming costs.  W i t h respect to total investment, the behavior is a little bit  more complicated, as reflected i n F i g u r e II.4. T h e difference is that the total investment doesn't increase immediately at I* as it d i d w i t h higher reforming costs. T h i s happens because around / * , the rate of firms reforming is very low, and the supply of reformed firms is so small that every new green investor who divests his holding i n the polluting firms creates mainly demand for the clean firms. T o t a l investment eventually recovers, but only when the rate of reformation increases. 30  In order to better understand why the change i n total investment can be positive or negative as I  passes / * , we need to consider the marginal changes  g  i n each industry's investment.  Since the clean industry investment is almost  constant, as we argued earlier, this means that the variation comes from industries r and p, specifically from the sum of the changes i n the two. T h e sum of the investments i n industries r and p is simply S = N K + N K . T h e term that dS we are interested i n is , ^ ' , the total derivative of the sum w i t h respect to the dl r>p  r  r  p  p  p  g  number of green investors. A s the following sign calculation shows, the sign of the total derivative is not clear. s  •  i dS \ /  i  rp  g  n  .„  „,dN  (  +  T  (+)  )  v  (+)  g  „ d K  ( ^ f )  V  When I  ^ dK  r  r  =  (-)  '  (-)  v  (-)  < I*, the decline i n the polluting  firm's  impact on the total investment (see Figure II.4).  ^  p  >  .  n  T  ^ ^  .  ' investments has a major  Once firms start to reform,  polluting firms w i t h low investment levels are replaced w i t h reformed firms that invest much more, but this might not be enough to push the total investment up again. A s equation 11.12 shows, the sign of the total derivative also depends on  dN  r  the intensity of the reformation rate, ~QJ~- If this rate is very small around / * , as i n the first intermediate case that we present here, total investment continues to drop i n the beginning of the reformation process. O n the other hand, if the reformation process is intense around / * , as i n the second intermediate case, total investment increases as soon as the first firm reforms. To summarize, the rate at which the reformed industry replaces the polluting industry explains the patterns of the total investment i n the economy.  If the  total derivative of the s u m of changes i n industries r and p switches signs, total investment continues to drop as I passes I* and picks up at a later stage as total g  investment must be equal at I = 0 and I = 1. g  g  Table II. 1 summarizes the m a i n results of the three cases that we discuss i n  31  +  _  Case  Cost  Total Investment  Infinite reforming costs  C -> oo  Maximum at I = 0  Zero reforming costs  C = 0  Constant V /  Intermediate cases  0 < C < oo  Maximum at J = 0 or 7 = 1  g  5  s  S  Table II. 1: Total investment in three different levels of reforming costs section 2.3.  2.4 Conclusions This chapter explores the effects of ethical screening on firms' decisions to reform and on their investment level. These issues are examined in an equilibrium setting with endogenous investment decisions and endogenous future outputs. The effects on total investment are examined in the presence of various levels of reforming costs. The results of our model indicate that if reformation costs are infinite, ethical screening reduces total investment in the economy significantly. When reforming is costless, green investors have no impact at all and total investment remains constant for every level of —. In intermediate cases when reforming costs are positive but not so high that firms never reform, the economy exhibits its maximum total investment at the extremes, i.e., when there are either no green investors (I = 0) or when there are only green investors (I = 1). g  g  No fraction of green investors strictly between 0 and 1 generates as much investment as all (I = 0) or none (I = 1). For relatively low I , say around 10% g  g  g  to 12% as estimated to be the fraction of total managed funds which are subject to SRI strategies, increasing I lowers total investment. g  32  REFERENCES  CITED  1. Heinkel Robert, A l a n K r a u s and Josef Zechner, "The Effect of Green Investment on Corporate Behavior", Journal of Financial and Quantitative Analysis, V o l . 36, N o . 4, December 2001, pp. 431-449 2. Jones Thomas, "Instrumental Stakeholder Theory: A Synthesis of Ethics and Economics", Academy of Management Review, V o l . 20. N o . 2, 1995, pp. 404437. 3. M c W i l l i a m s A b a g a i l and D o n a l d Siegel, "Corporate Social Responsibility: A Theory of the F i r m Perspective", Academy of Management Review, V o l . 26. N o . 1, 2001, pp. 117-127. 4.  Russo M i c h a e l V . and P a u l A . Fouts, " A Resource-Based Perspective o n Corporate Environmental Performance and Profitability", Academy of Management Journal, V o l . 49. N o . 6, 1997, pp. 534-559.  5.  Statman Meir, "Socially Responsible M u t u a l Funds", Financial Analyst Journal, V o l . 56. N o . 3, 2000, pp. 30-39.  6.  Teoh Siew Hong, Ivo Welch and C . P a u l Wazzan, " T h e Effect of Socially A c t i v i s t Investment Policies on the F i n a n c i a l Markets: Evidence from the South African B o y c o t t " , Journal of Business, 1999, vol. 72, no. 1, pp. 35-89  7.  The Globe and Mail, M a r c h 8, 2003  8.  Social Investment F o r u m , "2003 Report on Socially Responsible Investing Trends i n the U n i t e d States", December 2003.  33  CHAPTER III DOING LESS BADLY BY DOING GOOD: CORPORATE SOCIAL RESPONSIBILITY 3.1  Introduction T h e concept of corporate social responsibility ( C S R ) is becoming more promi-  nent. Hopkins and Cowe (2004) portray C S R as defining the "ethical corporation," and categorize C S R as covering human rights, labor conditions, environmental impacts and health issues. Hopkins and Cowe (2004) point to events that indicate non-shareholder stakeholders are becoming increasingly aware of C S R . Increasing globalization makes local regulation of companies more difficult. T h e E a r t h Summit of 1992 and anti-globalization protests at the Seattle W T O meetings i n 1999 indicate an increasing awareness of C S R . Hopkins and Cowe (2004) report the results of an international survey of C E O s which shows that 79% feel sustainability is necessary to maintain profitability. T h e y report on evidence that investors are also becoming more CSR-sensitive. E x i s t i n g models of C S R behavior fall p r i m a r i l y into two camps. F i r s t , there are models where C S R expenditures improve operating income. For example, providing day-care facilities for employees may attract more productive employees, a l l else equal, leading to greater revenues and/or lower costs. In these models, C S R expenditures w i l l increase (up to some point) share prices regardless of the ownership structure of the  firm.  T h e second camp of C S R models assumes that C S R expenditures are made because the corporate decision-maker or other, non-shareholder, stakeholders feel better for having supported their community w i t h C S R spending, even w i t h no benefit to operating income. For example, a corporate executive may gain personal utility from donating corporate (i.e., shareholder) funds to sponsor a local little league team. 34  The model we develop here falls between these two camps. We assume that corporate executives are firm-value-maximizers, but CSR spending has no impact on operating income. Rather, the mix of heterogenous investors (some of whom value C S R and some of whom do not) in the economy leads to share prices that may react to C S R spending. If so, value-maximizing firms will make C S R expenditures. Our paper considers the case of some fraction of investors valuing CSR; that is, some investors gain utility from owning companies that are active in CSR. We will show that investors' portfolio choices impact stock prices in a way that leads value-maximizing managers to make C S R expenditures. C S R behavior may be viewed quite differently by investors when done by different firms. For firms with a "clean" technology, a healthy product and good labor relations, C S R expenditures may not have the same marginal impact on investors as C S R expenditures by a firm with a "polluting" technology, poor labor relations and an unhealthy product. The latter firm may still be viewed negatively by investors, but the C S R expenditure might have a greater marginal impact on investors than for the clean, healthy firm. Why would investors react, in their financial decisions, to CSR? We hypothesize that investors gain utility from their own community involvement and also from corporate social expenditures, in proportion to their holdings in the firm. If an investor owns 5% of a company and it donates a dollar, that gives the investor utility that is equivalent to a personal donation of S.05.  1  These social expenditures matter to investors. This means that these concepts will enter equilibrium prices, because investors portfolio decisions will be influenced by C S R activity. How should investors react to a company that has a poor CSR record? They O f course, it is possible that the investor values $1 of CSR where he owns 5% of the firm by more $.05 personal donations. 1  35  could not only avoid holding these firms i n their portfolios, they could actually short the stock of firms w i t h poor C S R performance.  Alternatively, investors  could continue to own the firms w i t h poor C S R but use the wealth generated from their portfolio to support their community through personal donations. There is little theoretical work i n finance that explores equilibrium C S R behavior. Heinkel, K r a u s and Zechner (2001) and Barnea, Heinkel and K r a u s (2004) construct a model i n which one class of investors is assumed to boycott a class of firms that do not meet their standards for anti-pollution efforts (or other social criteria). If enough investors boycott, the authors show that these neglectful firms can be induced to clean up. Instead of assuming that one class of investors boycotts (has a zero position in) certain stocks, here we assume one class of investors ("altruistic") has utility from corporate social expenditures, as well as utility from personal social expenditures. T h i s might allow investors to continue to hold stocks that have less-than-perfect social records (to benefit the investors' risk-sharing possibilities) while using their own wealth to gain utility from social expenditures. Contrary to our assumption, Navarro (1988) and W e b b (1996) make the assumption that corporate donations are part of the firm's advertising strategy. Navarro (1988) assumes that corporate C S R spending improves the quantity of sales of the firm's product at any price, while W e b b (1996) assumes that C S R spending improves price, at any given output level.  Webb (1996) focusses on  the issue of corporate giving either directly or through a foundation, i n a profitm a x i m i z a t i o n model. Navarro (1988) also focusses on profit m a x i m i z a t i o n as the objective, but he also allows for the agency possibility that the manager gains personal benefits beyond the profit-maximizing level of C S R . Navarro (1988) examines comparative statics results of the profit-maximization equation, constrained by a takeover threat that limits the agency problem of C S R spending. Alternatively, our interest is i n developing equilibrium implications b y assuming 36  different types of value-maximizing firms and a market-clearing condition. Barnea and R u b i n (2005) test a model i n which management makes C S R expenditures to maximize its own self interest, at the expense of shareholders. T h e y find some evidence consistent w i t h this agency story. Small and Graff Z i v i n (2004) develop a simple model that shares some similarities to the one developed here. A n investor w i t h utility that is concave i n consumption and donations (both hers and a corporation's) makes donations and invests i n two riskless firms' shares. One firm makes a fixed donation and one does not. T h e investor consumes out of the end-of-period riskless cash flows from her shareholdings, less what she donates. There are no frictions i n the model, such as taxes. In this simple world, Small and Graff Z i v i n (2004) develop a "ModiglianiM i l l e r " irrelevance result. Suppose that the investor optimally wishes to donate. T h e two firms' share prices w i l l be equal and they w i l l be independent of the level of donation made by the donating corporation. T h e idea is that i f the donating firm changes its donation level, the investor can offset the effect of this by altering her private donation. O u r model below can duplicate this "irrelevance result" if we assume the conditions i n Small and Graff Z i v i n (2004): (i) assume a riskless technology, (ii) fix exogenously the level of corporate investment and C S R spending, (iii) assume only one type of investor (our "altruistic" investors) and (iv) assume no taxes. There are several interesting aspects to the resulting equilibrium i n our model. W h e n there are few altruistic investors, their preferences have little impact on market equilibrium and they find it utility-maximizing to short firms w i t h poor C S R records. However, as the fraction of altruistic investors i n the economy rises, they do wield market power and value-maximizing firms find it optimal to make C S R expenditures. E a c h altruistic investor makes personal social contributions that increase as the fraction of altruistic investors rises until, at very high fractions of altruistic investors, each investor reduces her donation level. T h e rate of  37  increase in personal donations as the fraction of altruistic investors rises diminishes once firms begin CSR expenditures. Firms do not undertake C S R spending at low fractions of altruistic investors, but do as that fraction rises. If there are caps to the tax break provided for C S R spending, firms may continue to increase their C S R spending as the fraction of altruistic investors rises, even without the tax break. Social surplus, defined as the total economy-wide social spending (corporate C S R and personal donations) less the tax breaks given for such spending, is increasing in the fraction of altruistic investors. We examine the tax break policy and its impact on social surplus. For example, at an intermediate level of altruistic investors, social surplus is monotonically decreasing in the tax break given to individuals; an additional dollar of tax break generates less than a dollar of new giving. On the other hand, social surplus is non-monotonic and concave in the corporate tax break given to CSR. A t low tax breaks, increasing the tax break by one dollar generates more than one dollar in new C S R and personal giving. This reverses when the tax break is larger.  3.2  The Model  There are two types of firms: there are N  good  g  firms that, because of their  technology, have better corporate social responsibility (CSR) attributes at any social expenditure level than bad firms. These fundamentally good firms make social expenditures of D each. There are N bad firms that, because of their g  0  technologies, are seen as fundamentally poorer at any level of social expenditure than good firms. Each bad firm can improve its social commitment by making corporate social expenditures of Db- The entrepreneurs of a firm type j, j G {b, g} can raise Kj dollars, of which Kj — Dj is invested in a production technology that produces normally distributed end-of-period cash flows to investors. The 38  expected end-of-period cash flow of a firm of type j is M = h(K, - Dj) - (l/2)k (K  f  j  2  (III.1)  - Df  3  3  There are two types of investors: there are I  neutral investors who care  n  only about their financial portfolios, i.e., they ignore C S R behavior; there are also I altruistic investors who do care about C S R and the dollar equivalent of a  their utility is enhanced by C S R behavior in the amount W(Db, D , Dr, x , x ), g  ab  ag  where Dj is the donation made by each altruistic investor and x b and x a  ag  are  the number of bad and good firm shares held by an altruistic investor. We assume that altruistic investors have preferences that are separable over wealth and donations and all investors have C A R A utility over terminal wealth. For convenience, we also assume that the riskless rate is zero. Neutral investors choose shareholdings x  and x  nb  in bad and good firms to  ng  maximize: U  X \Xg  n  -\~ X  ng  n b  jl  -(Xng  -  2  b  \ ng® X  g  nb  ~ {x b  UJ g)Pg n  (T  x  ~ U  n  ~f~  b  n  b  )P  '2x X O~ \ ng  nb  bg  (III.2)  b  where r is the investor's risk tolerance. Good and bad firms have standard deviations of ending cash flows of a and g  <7b  and the two cash flows have a covariance of a . bg  and u> are each neutral  uj b  ng  n  shareholder's endowment of shares in bad and good firms. Altruistic investors choose shareholdings x  ag  and x  ab  in good and bad firms  and their individual charitable donations, Dr, to maximize: U = XagPg  + XabPb  a  -(Xag  where  ~ UJ )P ag  g  -  (X  ab  -  LO )P ab  b  ~  ^T^ag^g  + ^  + W(D , D , Dj, b  g  b +  X  a b  , X^)  ^Xa] ag  ab  bg  - (1 - ti)Dj  (III.3)  is the personal tax rebate provided to the donor for one dollar of dona-  tion. 39  W e choose the following dollar-equivalent of the utility of altruistic investors for donations and corporate social expenditures.  W = oaiuiD! - {l/2)vDJ} + a x [u D b  +a x [u D g  ag  g  where T = I Dj + N D a  b  - {l/2)vD + ND  b  g  b  - (l/2)vD  - w]  2  b  b  b  - w ) + pJT - {1/2) T  2  g  ab  (III.4)  2  g  g  V  is total donations and corporate social expen-  g  ditures, and aj, a , a , (5 and 77 are positive constants. b  g  T h e first term i n W is the value to an altruistic investor from her personal donation, TJ/, and the second and t h i r d terms represent the dollar-equivalent utility of corporate social expenditures by b and g firms. If x  ab  or x  ag  = 0, then  that firm's corporate social expenditures do not benefit the altruistic investor (except through their inclusion i n total expenditures, T ) . T h e last two terms represent the dollar-equivalent of utility for total corporate social expenditures and donations, T = N D h  b  + ND g  + J D .  g  a  7  T h e constants i n W define the participants i n this economy. A l t r u i s t i c i n vestors have  ctjUj >  1, for  j  = {b, g}. A s shown below, this means that altruistic  investors' utility gains from corporate social expenditures w i l l induce those expenditures at some level of altruistic investors, I  a  < I. (3 > 0 and 77 > 0 i m p l y  that altruistic investors have utility for total social expenditures, as well as for each expenditure separately. This induces some substitutability between personal donations and corporate social expenditures. G o o d and bad firms have the same production technologies, but they differ i n how altruistic investors view their operations. Specifically, we assume  u >u > b  g  Ui  >v  (III.5)  and w > w > 0 a  g  40  (III.6)  For the same level of C S R expenditure by b and g firms, equation III.5 means that the expenditure by b firms generates more marginal utility for an altruistic investor than does the expenditure by g firms. Equation III.6 implies that, at low C S R expenditure levels, b firms provide lower utility to altruistic investors than does the same expenditure by a g firm. Thus, b firms are held in lower esteem by altruistic investors, but C S R expenditures by b firms have higher marginal utility than the same expenditure by a g firm. Entrepreneurs sell the two technologies at their market values: good firms get P and bad firms get P . Both types of entrepreneurs choose Kj and Dj to g  b  maximize: P + t [A D 3  c  3  + (1 - Aj)Dj]  3  (III.7)  - Kj  where t is the corporate tax rebate provided by making one dollar of social c  expenditures , as long as the social expenditure is below some limit set by law 2  (expressed in our model as a fraction of // •, expected ending cash flow), Dj = IjPjWhen C S R expenditures are below this limit, Dj < Dj, then Aj = 1, and when the expenditures exceed this limit, Aj = 0 for Dj > Dj.  3.3  Equilibrium The investors' first order conditions are: SU + cr x  — = (J x S^rig 2  bg  ng  =  7 1  Sx  °~bgX g  nb  + V X b  (III.8)  r(fj, - P ) = 0  (III.9)  g  -  2  n  - T(U - P ) = 0  nb  b  b  nb  SU  a  2  = vtXag +  SU  7—^ =  ox  VbgXag  +  P ) - TCX G = 0  (III. 10)  0~lx - r((M - P ) - TCX B = 0  (III.ll)  O gX b  -  ab  T(\L  ab  -  b  g  b  g  b  ab  Note that t applies only to CSR expenditures by the firm, as distinct from the firm's tax rate on net income. The latter is reflected in fij, which we hold constant in later comparative statics results from varying 2  c  t. c  41  where B = u D - (l/2)vD  - w  2  b  b  b  and G =uD g  - {l/2)vD  - w  2  g  g  g  from the W function.  or su  a  = Oiim - vDi) + Pl - vhT - (1 - U) = 0 a  (111.12)  Solving equations III.8 through III. 11 simultaneously gives: T  X.ng, = -[(^  - P )oi  g  g  - {fi - P )a ]  (111.13)  - (^ - P )a ]  (111-14)  b  b  bg  V T  x.  nb  Xag  T ,  2  6  b  2  g  g  bg  — * b}"g  - P )a  [(jig  [0z - P )a  =  b  -  -  (jJL  b  P )cr b  +  b g  cx G(J  - a Ba ]  2  g  b  b  <b = -jliPb - Pb)a ~ (Hg - P )o- g + cx Ba  2  g  where <f> = a a\ 2  g  -  g  b  b  g  (111.15)  bg  - cxgGa g\ b  (111.16)  a . 2  g  T h e market clearing conditions are: I X*  + I X*  Ix  + I x* = N  n  ng  n  nb  a  a  = Ng  ag  ab  (111.17) (III. 18)  b  Substituting the o p t i m a l shareholdings III. 13 - III. 16 into III. 17 and III. 18 yields the equilibrium prices: Pb = Pb~ ^[NgO- g + N a } +  -fa B  2  b  9  = Pg-  b  (111.19)  1  IT P  J  b  j^Wg^g + ^bg] N  42  +ja G g  (111.20)  The price of good firms, P , is a positive function of the marginal utility, a G = g  g  and the price of bad firms, P , is a positive function of the marginal utility, b  aB = b  both multiplied by the fraction of altruistic investors in the economy,  LL I •  Substituting these equilibrium prices back into the investors' shareholdings shows: * nb  N  b  ~  I  * ng —  N I  * ab —  N  * ag ~~  N I  X  X  X  X  (111.21)  9  (111.22)  bg\  T  (111.23)  b  I  (111.24)  9  where In =  I~Ia  In the absence of social expenditure considerations, given their identical preferences and beliefs, altruistic and neutral investors would hold ^ and ^f- shares of bad and good firms, respectively. However, because altruistic investors value corporate social expenditures, the two types of investors hold different amounts of each firms' shares. The difference in holdings from ^ and  depends upon the marginal utility  of social expenditures versus risk. Suppose, for example, that ^ 2 <  (see  equation III.24): the reward-to-risk of g holdings for the altruistic investor is less than the reward-to-risk of b holdings. In this case, x* < ^f. Then, from ag  equation III.22, neutral investors will hold more than ^f. The altruistic investor must also choose her charitable donation, Dj. Equation III. 12 shows that the optimal personal contributions are the maximum of zero or aim + PI - vh{N D a  D l =  b  b  + ND)  * iz lV+v  43  g  a  •  - (1 - U) (IIL25)  Finally, the firms choose Kj and Dj to maximize Pj+t [AjDj  + (1 — A )Dj] —  c  3  Kj. The resulting first-order conditions for K* and D*, respectively, are: h - k (K* - D*) - I = 0  (111.26)  2  and - h + k (K* - D)) + jcxjiiij  - vD*) + t Aj = 0.  2  (111.27)  c  The first two terms in the D* first order condition are equal to —1 by the firstorder condition for K*. The third term is  which represents the marginal  utility of a dollar of social expenditure by firm j. The last term is the tax rebate generated by firm j with a dollar social expenditure. Since t < 1 and Aj is zero c  or one, the first order condition for Dj at Dj = 0 shows that a small I  a  could  lead to an optimal negative Dj, which is not allowed. Thus, for some range of h, D* = 0: D) = Max{0,  (!)[_,- - (i.)l=JA] l  V  (IH.28)  }  OLj  a  We define the critical l values where each D* switches from zero to positive: a  I  ab  and I , where D* = 0 for I < I ag  b  a  ab  and D* = 0 for I < I . a  ag  For exposition, we compute a numerical example of the equilibrium for various levels of I . The input parameters are: a  fci = 6  r = 200  k =1  Ui =  2  a = 0.6  a = 20  u =4  a = 0.6  2  b  Og =  20  b  g  b  9  U  =  0 =6  3  <r = 200  v = 2.5  N = 0.5  Wfc  N = 0.5  ™9 =  t = 0.4  h = 0.3  bg  b  g  c  «i = 0.1  rj = .5  = 4  / = 1.0 = .05  2  Equilibrium values for various levels of I are shown in Table III.l. a  44  • 'L  w 8' § w c o  >~  S c  g o  3  o  o  8 00  CO  d o f~  o  '-  *  o.  o  d  (Tt Ci d o  «<  :;  g  §g  o  o  So f"!  ^™  •  *o «x>  00 o o  cf  m  *.  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CO o d d  <o  to  <o  to  to  C-l CO CO • CO OJ tq tq fi to T_ cn, cn cn CM C N — _ — >o to to to SO to tO to to to to t o ' O m  o  o  o  o  o  o  ss to  O  co  o  to  8  o  a H  r~  o  -r T O  d  fl  <r to  CO -T o t o CO o d O O  d  O  t~-  d  o  : 4. i ^. 4  C  t—  Q  cn CO CO cr ••1 vf T  cn  :n  _ eo ?,  o  o  •3 c  <jn '6 '.'1  o  d  o  d  o  o  o  c» o  <b  o  r i r« f l  s s?8 to  T '4,  CTd  o  ••  o  o  r> c  w  C  r-i  o  -  t !  a s  g  o a  cr» CO CO t o •o to »j *J  <© to  ITS  o  f<  d  si o  o  ss s o so  ft d  §  o  o o  o X  o  ?! o* $  o  5  S  o  s 4 o o  d  d  «  o  Bs  o  X  o  o  o  >o T O o  o o  o  o  O  to  CO w' 0> o Q O  o>  o  -3 —  Table III.l: Equilibrium values for various levels of I /I a  45  P b, D b  Figure I I I . l : B a d firms' share price and donations as a function of Ia / I (price - solid line, donations - dashed line)  3.4  T h e Impact of the P r o p o r t i o n of A l t r u i s t i c Investors  Several results of interest relate to changes i n the level of I . a  Result P l : K* — D*, j G {b,g} are independent of the number of altruistic investors. T h i s follows from equation III.26, the first order condition for Kj. T h e investment decision is not influenced by the presence of altruistic investors. Result P 2 : I /I  = .28 and I /I  ab  ag  = .33, after which (for larger I ) D* and D* a  b  are increasing w i t h I . A s seen i n equation III.27, when I = 0, a dollar of C S R a  a  only generates a t a x shield of t Aj < 1, making such expenditures unprofitable. c  However, when I  a  > I j, the combination of the impact o n price i n addition to a  the t a x shield is great enough to make the social expenditure profitable. Result P 3 : A t very high levels of I , it is possible that firms w i l l make C S R a  expenditures even past the amount that generates a tax rebate. I n the numerical example i n Table I I I . l , D exceeds that amount (D — .875) i f I b  b  a  is above .95.  Past this point, the preponderance of altruistic investors means that the price 46  Figure III.2: G o o d firms' share price and donations as a function of Ia / I (price - solid line, donations - dashed line) impact of C S R expenditures is so great that no additional tax rebate incentive is required. Result P 4 : Stock prices, P and P , are non-monotonic i n the fraction of altruisb  g  tic investors. T h i s is seen i n Figures III. 1 and III.2. For example, as I  a  increases  from 0 to 1, P first decreases, until Db goes positive and starts increasing i n I . b  a  Pb then increases until D  g  becomes positive. T h e increasing attractiveness of g  firms causes Pb to then decrease over the remainder of the I  range.  a  T h e nonlinearity of Pj i n I follows from E q u a t i o n III.28, which shows that Dj a  is nonlinear i n I , and the definition of B and G, which have B and G nonlinearly a  related to D and D and finally that B and G enter P and P i n equations III. 19 b  g  b  g  and III.20. T h e expected returns to the firms, E(rj)  = (Hj/Pj) — 1, differ whenever the  stock prices differ since both firms have the same production technology and so set the same expected end-of-period cash flows, \i  h  expected returns as I  a  = \x .  T h e pattern of  changes is, therefore, just the inverse of the stock price  47  patterns described above. R e s u l t P 5 : a and n investors obtain different portfolio expected returns  as  3  I varies from 0 to 1. Using the optimal portfolio weights shown in Table III.l a  multiplied by the firms' expected returns shows that, at all I levels, neutral a  investors earn a higher expected portfolio return than do altruistic investors. B y caring about CSR, optimal portfolios of altruistic investors shift risk to neutral investors, who demand a higher expected return for bearing this risk. R e s u l t P 6 : When there are few altruistic investors, their best tool for gaining utility is to short the bad firms. In our example, for small I ,  —  a  bg  a  which implies that, for small I , x a  ab  < 0 and x  nb  >  < 0 a  g  In this example, altruistic  investors short b shares as long as I < .33. a  Shorting bad firms by altruistic investors makes them happier than not shorting, but it does not encourage C S R expenditures by the corporations until there are enough altruistic investors that depress the bad technology stock price (P is b  decreasing in I from I = 0 to about I = .25). The bad technology firms react a  a  a  to the low stock price by commencing social expenditures (b begins first). R e s u l t P 7 : The donation per individual altruistic investor, D}, is non-monotonic in I , reaching a maximum at about I = .80. As the number of altruistic ina  a  vestors increases, each such investor optimally reduces her individual donation. It is also the case that total personal donations, I D]}, is monotonically increasing a  in I . a  R e s u l t P 8 : Total C S R expenditures and donations, T = I D\ + N D* + N D* , a  is monotonically increasing in I . a  b  b  g  g  Altruistic investors contribute on their own,  but they also induce firms to make social expenditures by affecting stock prices. R e s u l t P 9 : As /„ changes from 0 to 1, both total personal donations, I D}, and a  corporate social expenditures, N Dl + N D*, increase. In fact, in the numerical b  example, as 3  g  increases from .20 to .30 in ten equal increments of .01, the  W e assume that rj = 0, so the returns we refer to here are excess returns over rj.  48  correlation of total personal donations with total corporate social expenditures is .91. This result has an interesting interpretation. If we assume that our one-period model applies over time, with I increasing in a way that is totally unanticipated a  by entrepreneurs and investors, then we would see both total personal donations and corporate social expenditures moving up in a highly correlated way. Thus, it would appear, over time, that personal donations and corporate social expenditures are complements, not substitutes . 4  As a simple test of this implication, we gathered data on total individual and corporate charitable giving from a publication titled Giving USA: the Annual Report on Philanthropy . We divided total personal donations per year by an5  nual G D P and also divided total corporate donations by GDP. The correlations between these donations is -.01 from 1954 to 2001, .147 from 1981 to 2001 and .298 from 1991 to 2001. These correlations are substantially less than our model's estimate of around .9. This could be due to many factors. It is highly likely that more is changing over time than just I . Investors' utility for C S R spending may be changing in a  ways that are not related to wealth (GDP). In addition, our measure of corporate C S R spending is restricted only to charitable giving; we cannot measure how much of their capital budget is devoted to CSR-like expenditures that are not classified as donations. The correlation did grow as the observation period was shortened to just the last ten years. Perhaps only in this period are many investors recognizing their utility for C S R spending. R e s u l t P10: Assume that I = .40. At this level of altruistic investors, both b a  and g firms are donating, but below the maximum allowable for tax deduction This occurs despite the fact that the altruistic investor's iso-utility curves are downward sloping in (Dj,Di) space: the presence of total donations, T, in the utility function gives this aspect of substitutability between Dj and Df. 4  See the bibliography.  D  49  purposes. This appears to be the case empirically. Evidence from the publication Giving USA: the Annual Report on Philanthropy, lists tax-deductible donations as a fraction of net income before taxes, by industry, for 1998. Most industries were well below the maximum of 10%: Finance and Insurance gave .4%; Manufacturing gave 1.4% and Information gave 2.1%. The largest donating industries were Agriculture (8.3%) and Mining (8.1%). This evidence also suggests that b firms spend more on C S R than do g firms. Mining would be considered much more of a 6 industry and information technology much more of a g firm. The big social contributors are individuals. W i t h I Dj = 2.206 and N D a  b  +  b  NgDg = .400, the ratio of personal donations to corporate C S R is 5.5 times. If we take recent levels of personal donations relative to business donations (source: Giving USA: the Annual Report of Philanthropy) this ratio is about 15 times. However, we believe that the reported corporate contributions underestimate the amount of C S R spending because some amount of C S R is not actual donations but capital expenditures or normal business expenses. R e s u l t P l l : F i r m entrepreneurs' payoffs, Pj + t [AjDj c  + (1 — Aj)Dj] — Kj  are decreasing over the range of I from 0 to 1. This payoff can be rewritten as a  Pj + t (l — Aj)Dj — (\ — t Aj)Dj c  c  — (Kj — Dj) and the last term is constant. Then,  this payoff declines as I increases because the increasing optimal expenditures, a  Dj, are greater than the increases in Pj, when Pj increases. For example, in Table III.l, when P rises over the range I £ [.25, .50] (where Aj = 1), (1 — t )D b  a  c  b  rises faster, driving down the firm's total payoff.  3.5  The Impact of Tax Policy Parameters  For a given proportion of altruistic investors, I , tax policy, in the form of a  parameters ti, t and lj = jf-, will impact the level of total donations, T = c  50  0.2  0.4  0.6  0.8  1  Figure III.3: T o t a l donations as a function of corporate tax rate (Ia / I = 0.4)  I D*j + N Dl a  b  N t [A D* b c  b  b  + N D*, g  as well as the cost of lost tax revenues, C = IaUD} +  + (1 - A )D ] b  b  + N t [A D* g c  g  g  + (1 - A )D ). g  g  W e define T - C as  the social surplus of total donations and C S R expenditures less the tax cost of inducing this activity: SS = T — C. R e s u l t T l : Social surplus is monotonically decreasing i n tj, the tax break given for personal donations.  A n additional dollar of tax break to individuals does  not generate an additional dollar of total C S R and personal donations.  This  is because corporate donations (see equation III.28) are independent of the tax break given to individuals.  Thus, while individuals give more as t  T  increases,  corporations don't, and marginal total donations are less t h a n the marginal tax breaks given. In our model, allowing individuals to deduct donations does not appear to be an efficient policy. R e s u l t T2: Social surplus is non-monotonic and concave i n the corporate tax break, t . c  Figures III.3 through III.5 plot, as a function of the rebate rate on  corporate C S R , t , total individual donations plus corporate C S R expenditures, c  T , and lost tax revenue, C , and the difference, termed social surplus, SS, for the 51  c  Figure III.4: T h e cost of lost tax revenues as a function of corporate tax rate (Ia / I = 0.4)  case when I  = .40. Other levels of I  a  a  offer qualitatively similar results. There  are five segments to the plots. In the first segment (t < .05), neither b nor g firms make C S R expenditures. c  A n d , individual donations, D}, are independent of t . c  Thus, T is limited to  (constant) individual donations, C is a constant, and so is SS. In the second segment (.06 < t  c  with t .  < .28) Dl becomes non-zero and increases  Because C S R spending is rising, so is C , but at a slower rate, so SS  c  is increasing i n this tax region. In this segment the tax break is not enough to induce g firms to make C S R expenditures. In the t h i r d segment (.29 < t  c  < .56), b o t h firm types increase their C S R  spending as t rises, so total donations are rising faster t h a n the tax break makc  ing social surplus increase. T o t a l donations rise even though individual donations, I D*j, are dropping. E q u a t i o n 111.25 shows that D] is decreasing i n total a  corporate C S R spending. It is i n this segment that social surplus reaches its m a x i m u m . T h e m a x i m u m is reached because the tax rebate gets so large that it offsets the increases i n 52  Figure III.5: Social Surplus ( T - C ) as a function of corporate tax rate (Ia / I = 0.4) corporate C S R spending generated by the higher rebate rate. In the fourth segment (.56 < t  c  < .80), b firms have reached the m a x i m u m  donation that qualifies for a tax rebate (5% of expected cash flow, fj.) and, without the t a x incentive, they hold the C S R at D  b  = D. b  D  g  continues upwards w i t h  t , but the increase i n C S R spending is less t h a n the tax cost increase so SS is c  falling over this segment. Finally, above t  c  = .81, b o t h firm types have used up a l l the tax-allowed  C S R , so they do not donate more as t rises, but the rebates do rise, meaning C c  increases and SS falls. A t many levels of I , we can find an interior o p t i m u m to the social surplus, a  as a function of t , given the tax limits, lj. c  R e s u l t T 3 : T h e o p t i m a l rebate rate, t , that maximizes social surplus, varies c  w i t h the upper limit on tax-deductible C S R expenditures, lj. For example, at  I = -40: a  A limit of: .025  o p t i m a l t a x rebate rate of .42  for a social surplus of: 1.750  53  .050  .49  1.799  .075  .49  1.799  This can be seen in Figure III.6. As we move from left to right (increasing lj), the rebate rate, t , that maximizes social surplus increases until the maximum c  social surplus continues to occur at t = .49 and remains constant at 1.799. c  A tight upper limit on the amount of C S R that generates a tax rebate, lj = .025, leads to a lower optimal tax rebate rate, t and a lower (maximum) social c  surplus, 1.750, than if the limit is lj = .05. However, loosening the upper limit beyond some point does not change the optimal rebate rate. From above, the optimal t remains at .49 at a limit of c  lj = .075 (or higher). So, as lj increases beyond about lj = .05, total donations and tax revenue lost remain constant, meaning that social surplus is also constant. This result has policy implications. Whatever the reason for limiting the tax rebate on C S R spending (e.g., agency concerns), the tax rebate rate that maximizes social surplus is a function of the chosen lj, only if lj is below some point (about lj = .05 in our numerical example). If lj is above this point, the optimal t is the same for any lj. c  This optimal (lj, t ) relationship only holds for intermediate values of I . At c  a  low values of I (0 to .30 in our example), D = D = 0 and so the tax rebate and a  b  g  limit policy variables have no impact on corporate C S R spending, and individual donations are independent of these policy variables, so social surplus is unaffected by the policy variables. At high values of I , the optimal tax rebate rate for any limit is t a  c  = 0.  In these cases, the market power of altruistic investors is so great that no tax incentive is necessary to generate social surplus. 54  Figure III.6: Social Surplus as a function of corporate tax rate and donations' ceiling (Ia / I = 0.4)  55  3.6  Conclusion This chapter assumes that C S R spending is not just a way of increasing rev-  enues or decreasing costs. In fact, one could argue that such expenditures should not even be called C S R spending. We define C S R spending as having utility for some investors. B y assuming that some investors gain utility from owning firms that practice CSR, we show how this concern impacts investors' risk-sharing opportunities, equilibrium prices and so, value-maximizing firms' decisions about practicing CSR. We choose a set of parameter values, shown in Table III.l, with I = .40, that a  provides an equilibrium with empirically reasonable implications, including: •  Both types of investors hold both types of firms. Altruistic investors hold the stock of firms with poor C S R fundamentals, but less than is optimal from a pure risk-sharing viewpoint. This requires neutral investors to hold more of the firms with poor C S R fundamentals than they would prefer for risksharing, leading to poor-CSR firms' stock price being less than good-CSR firms. Since both firms make the same optimal investment, the P / E ratio for the poor-CSR firms is lower than the P / E ratio for the (risk-equivalent) good-CSR firms.  •  This investor behavior induces firms with poor C S R fundamentals to improve their C S R record (Db > 0). Firms with better C S R fundamentals also spend on C S R (D > 0), but they spend less than the firms with poor C S R g  fundamentals. •  Investors also make individual donations which, in aggregate, are several times the size of corporate social spending.  •  If, over time, I /I, a  the fraction of investors that value C S R spending, in-  creases in a way that is unanticipated by investors, both individual donations, I D , a  r  and corporate C S R spending, N D b  56  b  + ND, g  g  will increase with  a very high correlation, making them appear as complements, despite the aspect of substitutability built into the assumed utility function of altruistic investors. We also find that policy variables, £/, t and lj, influence the social surplus in c  important ways. First, for many parameter values, social surplus is monotonically decreasing in the tax rebate given to individual donations, tj. Because changing the individual tax rebate rate does not influence corporate CSR spending, raising the rebate rate generates less new individual donations than the additional tax rebates given, causing social surplus to be lower. Second, social surplus is non-monotonic in the corporate tax rebate. That is, there is a social-surplus-maximizing level for the corporate tax rebate rate, for any given set of parameters. One of the important parameters is lj, the limit on net income that can be used for C S R spending and qualify for a tax rebate. Any CSR spending beyond lj generates no additional tax rebate. We take the rebate limit as given. This limit may exist as a political compromise between groups favoring C S R tax rebates and those that feel such spending is outside the area of corporate responsibility. Or some may view C S R spending as an agency problem, benefitting management at the expense of shareholders. Whatever the reason for the tax rebate limit, its level influences the social surplus-maximizing level for the corporate tax rebate rate. Raising the tax rebate limit leads to higher optimal tax rebate rates, up to a maximum, past which the optimal tax rebate rate is constant. As corporate social responsibility rises in prominence, it's impact on capital market equilibrium and optimal CSR behavior will increase. This chapter begins to explore that equilibrium.  57  REFERENCES  CITED  1. Barnea, Amir and Amir Rubin, 2005, Corporate Social Responsibility as an Agency Conflict, working paper, University of British Columbia and Simon Fraser University. 2. Barnea, Amir, Robert Heinkel and Alan Kraus, 2004, Green Investors and Corporate Investment, Structural Change and Economic Dynamics, forthcoming. 3. Giving U S A : The Annual Report on Philanthropy, Giving U S A Foundation, from The Trust for Philanthropy of the American Association of Fund-raising Counsel, various years. 4. Heinkel, Robert, Alan Kraus and Josef Zechner, 2001, The Effect of Green Investment on Corporate Behavior, Journal of Financial and Quantitative Analysis, 36, 431-449. 5. Hopkins, Michael and Roger Cowe, 2004, Corporate Social Responsibility: Is There a Business Case?, mimeo, Association of Certified Chartered Accountants. 6. Navarro, Peter, 1988, Why Do Corporations Give to Charity?, Journal of Business, 61, 65-93. 7. Small, Arthur A . I l l , and Joshua Graff Zivin, 2004, A Modigliani-Miller Theory of Corporate Social Responsibility, forthcoming, Topics in Economic Analysis and Policy. 8. Webb, Natalie J., 1996, Corporate Profits and Social Responsibility: "Subsidization" of Corporate Income Under Charitable Giving Tax Laws, Journal of Economics and Business, 48, 401-421. 58  CHAPTER IV CORPORATE SOCIAL RESPONSIBILITY AS A CONFLICT BETWEEN SHAREHOLDERS One of the most significant corporate trends of the last decade is the growth of Corporate Social Responsibility ( C S R ) . Definitions of C S R vary but generally refer to serving people, communities and the environment i n a way that goes above and beyond what is legally required of a firm. T h e alignment of business operations w i t h social values is by now an industry i n itself, w i t h full-time staff i n corporations, hundreds of websites, newsletters, professional associations and consultants. M o s t major companies have a special annual publication dedicated to C S R ; others devote a big section of their annual report to the documentation of social goals advanced and good works undertaken. In this chapter we wish to gain a better understanding for this dramatic i n crease i n C S R expenditure. We argue that the relation between C S R expenditure and firm value has to be non-monotonic. W h e n C S R expenditure is low, it has a positive contribution to firm value, for example by increasing productivity of employees or avoiding costs such as bad reputation and pollution fines. B u t at some point, the marginal effect of an additional dollar of C S R expenditure decreases shareholders wealth as there is no limit to the amount that a firm can donate to society. If firms decision-making were done solely by value maximizing individuals then the chosen level of C S R expenditure would have been consistent w i t h that objective (e.g., Demsetz and L e h n (1985)). However, we claim that insiders (corporate managers and large blockholders) who are affiliated w i t h the firm may have an interest to increase C S R expenditure to a higher level t h a n that which maximizes firm value. T h e y may do so because they gain unique benefits from a high C S R rating. A good social rating enhances their reputation as being decent individuals who respect their employees, communities and the environment and care about society. W h i l e insiders may benefit from C S R , other 59  shareholders may not approve of a high C S R expenditure if it reduces firm value. Therefore, C S R may be the source of a conflict between different shareholders. In order to test this potential conflict we analyze the relation between C S R and the ownership and capital structure of firms. If insiders gain unique benefits at the expense of other shareholders, their degree of ownership should matter i n setting the amount of C S R expenditure i n the firm. T h e level of ownership by insiders can have two potential effects. O n the one hand, as argued by Demsetz (1983) and F a m a and Jensen (1983), w i t h high ownership comes entrenchment, which allows insiders to pursue a proC S R agenda more easily. Morck, Shleifer, and V i s h n y (1988) argue that entrenchment is reached at relatively low levels of ownership (between 5% to 25%). B u t on the other hand, when insiders' ownership is high, insiders bear more of the cost of the C S R expenditure. Thus, given that insiders are entrenched, their ownership should only be associated w i t h better alignment w i t h other shareholders. In other words, if C S R expenditure is at a level i n which it reduces  firm  value then, ceteris paribus, insiders' ownership should be negatively related to the level of C S R expenditure since insiders bear more of the cost associated w i t h this expenditure as their degree of ownership rises. If a C S R conflict indeed exists, insiders gain at the expense of other shareholders. These include institutional and small i n d i v i d u a l investors. W h i l e small individual shareholders do not have an impact on the decision-making process i n the firm, there is some evidence that institutions play a role i n mitigating agency conflicts (e.g., Hartzell and Starks (2003) and Bhojraj and Sengupta (2003)). Therefore, institutional ownership is one of the variables that we incorporate i n the analysis. T h e capital structure of the firm may also influence the C S R conflict. W h e n firms have high interest payments, it limits the ability of insiders to over-invest i n C S R . T h i s is similar to arguments suggested by Jensen (1986) and Zweibel (1996). 60  High debt levels also induces creditors to play a more active monitoring role (e.g., Diamond (1991), Gilson (1990)), which may help to mitigate the conflict. We employ a unique and large data set that categorizes firms in the Russell 3000 index to being either socially responsible (SR) or socially irresponsible (SI). Controlling for industry and firm characteristics, we show that insiders' ownership is negatively and significantly correlated with C S R ratings. A n increase of one standard deviation in total insiders' ownership of a firm decreases by 3.8% the probability that it will be classified as SR. The result supports our hypothesis that insiders gain personal benefits from CSR. Assuming that there is a positive monotonic relation between the level of C S R expenditure of the firm and the probability that the firm receives an SR rating, the negative correlation upholds the claim that insiders reduce C S R expenditure depending on their degree of ownership. A t high levels of ownership they bear more of the cost involved in CSR and are more aligned with firm value maximization. The fact that they choose to reduce C S R expenditure shows that the marginal dollar spent on C S R reduces firm value. In addition we find that an increase of one standard deviation in the leverage of a firm decreases the probability that it will be defined as SR by 2.2%. This result also supports the C S R conflict hypothesis since higher debt levels reduce the ability of insiders to over-invest in CSR. In contrast, we find that institutional ownership is not correlated with the social ratings. This provides supportive evidence to the claim made by Woidtke (2002) that public institutions may care about social issues more than about maximizing the value of their portfolio. The results are persistent throughout the study for different specifications and robustness checks. To rule out possible endogeneity problems we use an instrumental variable (IV) approach. One of the contributions of the chapter is the development of a relative C S R measure (RCSR). The need for such a measure comes from the fact that our 61  raw data consist of a binary C S R rating that does not distinguish between firms w i t h i n each of the two groups (i.e., SI and S R ) . O u r methodology maps the binary C S R measure into a continuous one by taking into account firm characteristics such as industry, size, age and growth opportunities. T h e results are robust to this alternative approach.  T h e C S R conflict is somewhat different than typical agency conflicts since a l l insiders (and not only managers) may gain personal benefits from a high C S R rating. However, it is very common to link C S R w i t h corporate governance. A r guably, this link is due to the perception that a high C S R expenditure and good corporate governance mechanisms are b o t h to be found i n so called ethical firms. W e therefore examine whether the C S R conflict is related to the presence of standard corporate governance mechanisms. We use the governance index suggested by Gompers, Ishii and Metrick (2003) ( G I M ) to learn about this possible relation and find that the C S R ratings and the G I M index are uncorrelated.  Despite the enormous interest i n C S R , the literature has so far concentrated on the relation between C S R and financial performance (see Griffin and M a h o n (1997) for a survey). We focus on the decision-making process i n the firm by looking at firms' ownership and capital structure. To the best of our knowledge, the only paper that bears some similarities to ours is Navarro (1988) who studies the nature of corporate giving to charity. However, his focus is on tax policies w i t h respect to corporate donations.  T h e remainder of the chapter proceeds as follows. In Section 4.1 we present the CSR-conflict hypothesis and the different mechanisms that can potentially affect it. I n Section 4.2 we describe the data and the variables that we use i n the empirical analysis. In Section 4.3 we conduct the empirical analysis. Section 4.4 investigates the relation between C S R and the G I M index. Section 4.5 concludes. 62  4.1  C S R as a Conflict between Different Shareholders  T h e conflict that we analyze can be regarded as a conflict between two types of shareholders: insiders, who are affiliated w i t h the firm, and other shareholders such as institutions or small individual investors, who are not affiliated w i t h the firm. Affiliated owners are those investors whose either reputation, identity or heritage is related to the firm, while non-affiliated owners are the majority of investors who hold shares i n the firm as part of a well diversified portfolio and have a relation w i t h the firm that does not go beyond its affect on their portfolio value. O u r hypothesis is that insiders, the affiliated shareholders, may gain private benefits from being identified w i t h a firm that has a high C S R rating, or stated similarly, insiders bear a cost from being associated w i t h a firm which is classified as socially irresponsible. T h e group of insiders is composed of three subgroups: managers, blockholders who are not part of the daily management team, and directors who are not part of the first two groups (i.e., hold less than 5% of the firm's equity and not part of the daily management team). It is hard to hypothesize which group would gain more from being associated w i t h a socially responsible firm. However, we argue that a l l three subgroups care about the firm's social rating more t h a n a diversified shareholder. For example, consider the following three individuals: Steven Jobs, the C E O of A p p l e Computer, W a r r e n Buffet a large blockholder of T h e CocaC o l a C o m p a n y and R o y Disney, a director of T h e W a l t Disney Company. A l l three individuals are strongly affiliated w i t h their corresponding firm. O u r claim is that these individuals gain from the fact that these firms have a high C S R rating more than a diversified shareholder such as Fidelity, whose image is not affected by the social rating of one specific firm. In what follows, we explore how this potential C S R conflict may be affected by different attributes of the firm; the most important being the ownership and 63  capital structure. In addition, we discuss how free cash flow and the composition of the board of directors may affect the conflict.  Insiders A s argued above, insiders are typically affiliated w i t h the firm and may benefit from the fact that a firm is classified as S R . O n the other hand, if C S R expenditure is at a level i n which it reduces firm value the degree of ownership of insiders should matter. Jensen and Meckling (1976) claim that deviation from value-maximization declines as management ownership rises. Others argue that w i t h more control comes also more entrenchment (Demsetz (1983), F a m a and Jensen (1983)), which may result i n management engaging i n non-valuem a x i m i z i n g activities. Whereas the alignment hypothesis predicts that larger stakes by insiders may reduce the CSR-conflict, the prediction of the entrenchment hypothesis is less clear-cut. For example, Morck, Shleifer and V i s h n y (1988) claim that entrenchment is reached at levels of ownership below 25% and that an increase i n ownership above that level does not result i n more entrenchment but further increases alignment w i t h shareholders.  Institutions Shleifer and V i s h n y (1986) argue that institutional shareholders, by virtue of their large stockholding, have incentives to monitor corporate decisionmaking. Consistent w i t h this hypothesis, a few studies document institutional i n vestors' voting against harmful amendments (Jarrell and Poulsen (1988), Brickly, Lease, and S m i t h (1988)). Other papers show that institutional investors enhance firm value as measured by Tobin's Q ( M c C o n n e l l and Servaes (1990, 1995)), i n crease pay for performance for executives (Hartzell and Starks (2003)) and reduce agency costs between shareholders and bondholders (Bhojraj and Sengupta (2003)). O n the other hand, Black (1992) points out that institutional investors are agents whose objective may differ t h a n that of their unit holders. W o i d t k e (2002) finds supporting evidence for this claim by showing that public pension funds do 64  not enhance firm value. She argues that these funds are often managed by officials that have their own personal agendas, such as campaigning for public office. Under such circumstances, these institutions may find that a p r o - C S R agenda coincides w i t h their private objectives even if it reduces firm value. Moreover, it is conceivable that even for private funds a higher priority would be given for voting against golden parachutes compared to voting against donations to the tsunami victims, for example. W h e n discussing the impact that institutions may have on C S R , some attention should also be given to Socially Responsible Investing (SRI), which refers to making investment decisions that consider also social criteria. A typical S R I fund would avoid holding shares of firms that have a poor C S R rating. According to the Social Investing F o r u m , an association dedicated to promoting S R I , the amount of funds involved i n S R I reached a level of U S $ 2.2 trillion as of December 2003, accounting for about 11 percent of a l l managed funds i n the U S . However, 1  only 20 percent of this amount is invested i n portfolios controlled by institutions who also advocate on various social and environmental issues w i t h i n the firms. T h i s suggests that while S R I may lead to high ownership of institutions i n socially responsible firms, the direct impact of these institutions on the C S R policy of these firms is currently limited.  Leverage Over-investment is easier when firms have a lot of cash i n place (e.g., Jensen (1986) and Zweibel (1996)).  Therefore, debt servicing obligations may  help to discourage possible over-investment i n C S R by self serving insiders. Moreover, banks and debt holders can also be active investors. T h e y have investments i n the firm, and want to see the returns on these investments materialize. W h i l e they do not have voting rights, they have other means to monitor the  firm's  policy. F i r m s occasionally have to raise additional capital from creditors which ^ 0 0 3 Report on Socially Responsible Investing Trends in the United States, Social Investment Forum.  65  results in their ability to influence decisions. Gilson (1990) documents that U.S. banks play a major governance role by replacing managers and directors. Creditors, compared to shareholders, typically keep their debt holdings for a longer period. This has some advantages, such as the ability to influence corporate management by patient, informed investors. Free Cash Flow Jensen (1986) suggests that it is easier for managers to consume perks in firms with substantial free cash flow as these managers do not have to raise more funds from questioning investors.  2  While Jensen's theoretical argu-  ment is solid, testing it empirically is very difficult since the level of free cash flow is unobservable. Consider, for example, one of the most commonly used measures of free cash flow, proposed by Lehn and Poulsen (1989):  FCF  = INC - TAX - INT EXP  - PFDDIV  -  COMDIV  where, FCF = free cash flow INC = operating income before depreciation TAX  = total taxes  INTEXP  = gross interest expenses on short and long-term debt  PFDDIV  = total dividend on preferred shares  COMDIV  = total dividend on ordinary shares  This free cash flow measure does not represent the availability of cash; rather, it represents the cash left in the company after perks were potentially consumed. In the context of this chapter, this free cash flow measure is a bad proxy for the CSR expenditure potential because C S R costs have already been incurred in the operating income. Hence, the observable measure is net of CSR. Jensen (1986) also argues that the likelihood of perk consumption by managers is especially high mature firms operating in low growth industries. 2  66  Moreover, since any measure of free cash flow is a measure of net free cash flow (as oppose to the unobservable gross free cash flow), using it as an explanatory variable results i n a severe endogeneity problem. For these reasons we do not use free cash flow i n the analysis.  B o a r d of Directors T h e corporate finance literature recognizes board composition as an additional mechanism that may affect standard agency conflicts. For example, R y a n and Wiggins (2004) claim that independent directors help i n aligning managers' objectives w i t h those of other shareholders. It is important to note, however, that the CSR-conflict is not between managers and other shareholders; rather, it is between affiliated and non-affiliated shareholders.  We view b o t h  inside and outside directors as affiliated shareholders since their reputation may be affected by the firm's C S R rating. Therefore, if a l l board members h a d the same ownership level, we would not expect to find a correlation between C S R and board composition. We are aware of the fact that board composition is correlated w i t h insiders' ownership; however, employing board composition i n the analysis is not helpful since we use a direct measure of insiders' ownership.  4.2  Data  D a t a Source O u r data are gathered from a variety of sources. T h e first is a unique database that we have obtained from K i n d e r , Lydenberg and D o m i n i Research & Analytics, Inc.  ( K L D ) , the leading research group i n providing ratings of  corporate social performance to investors. T h e K L D database screens close to 3,000 firms and categorizes them to be either socially responsible (SR) or socially irresponsible (SI). To the best of our knowledge we are among the first to use this comprehensive database, which was launched i n 2001. O u r sample includes firms 3  Aggarwal and Nanda (2004) use similar data to study the impact of the size of a firm's board of directors on managerial incentives. 3  67  that account for 98% of the total market value of US public equities. Other data sources that we use are proxy statements, 13F schedules, CRSP, and Compustat. Our database is cross-sectional and it is composed of the most recent data as of the third quarter of 2003 (September 2003). Table IV. 1 provides a complete 4  description of the main variables used in the study. The CSR Measure K L D launched in 2001 the Broad Market Social Index (BMSI). The BMSI, a subset of close to 3,000 firms that compose the Russell 3000 index, is generated after a C S R screening process takes place. In this process, K L D divides firms to three different categories: SR, SI due to exclusionary reasons and SI due to qualitative reasons. Only SR firms are eligible for inclusion in the BMSI. Sorting firms into these three categories involves a two-stage social screening process. First, K L D applies an exclusionary social screening. In this stage SI firms are defined as follows: companies that derive any revenues from alcohol, tobacco, or gambling; companies that derive more than 2% of gross revenues from the production of military weapons; and electric utilities that own interests in nuclear power plants or derive electricity from nuclear power plants in which they have an interest. It is important to note that the exclusionary screening that K L D applies is a per-se criterion. As long as Philip Morris, for example, continues to produce cigarettes, it is defined as SI. Thus, even if Philip Morris' expenditure on CSR is relatively high, it would never get an SR rating from K L D . Firms that fail in this screening stage can not be reconsidered to be SR unless they shut-down the "unethical" side of their business. In some cases, as in the case of Philip Morris, this means shutting-down the firm. Out of the 2,837 firms that were considered, 187 are defined as SI due to exclusionary reasons. In the second stage, K L D applies a qualitative social screening on the reNote that corporate social performance is a long term screening measure that does not vary over a period of time. 4  68  Conflict variables Insiders' ownership  Insiders' control Institutional ownership  Institutional H H I  Description  Source  Percent of common stock held by all the officers and directors of the company plus beneficial owners who own more than 5 percent of the subject company s stock as disclosed in the most recent proxy statement. A dummy variable that equals 1 if insiders' ownership is greater than 50%. Percent of common stock held by all the reporting institutions as a group. It is calculated as total shares owned by institutions divided by total shares outstanding. The Herfindahl-Hirschman Index (HHI) of concentration of the top 15 institutional owners (as  Proxy statement  Proxy statement 13F schedule  13F schedule  15  reported on 13f). It is defined as ^hf , where h( is /•=i  the percentage ownership of institution i. The book value of long term debt (data item #9) divided by the book value of assets (data item #6)  Leverage  Control variables L n (total assets) Market to book  Return volatility Firm's age 2-digit SIC code  Other Turnover  Compustat  Natural log of book value of total assets (data item #6) The ratio of the market value of assets (book value of assets (data item #6) plus the difference between the market value of equity (data item #24 Ldata item #25) and the book value of equity (data item #60)) to the book value of assets (data item #6). The standard deviation of share returns during the previous 60 months. The year in which the firm's share price (data item P R C ) first appeared on C R S P . The 2-digit Standard Industry Classification code  Compustat  The three months average of the monthly volume (data item V O L ) divided by the number of shares outstanding (data item S H R O U T )  CRSP  Table IV. 1: Definition and source of major variables  69  Compustat  CRSP CRSP CRSP  maining firms. Qualitative screening includes areas such as community relations, workforce diversity, employee relations, environment, non-US operations, and product safety and use. In each of the areas, K L D investigates a range of sources to determine, for example, whether the company has paid fines or penalties i n an area or has major strengths i n the area (e.g., strong family policies for the employees' relations category). Where possible, K L D uses quantitative criteria to determine the rating (e.g., dollar amount paid i n fines; percentage of employees receiving certain kinds of benefits). Some subjective judgment is necessary, of course, i n the determination of the cutoff point for a negative rating, as well as i n borderline cases. In our sample, 2,278 firms passed the qualitative social screening and are defined as S R firms, while 372 firms d i d not pass the qualitative screening and are defined as SI firms. T h e dependent variable i n most of our analysis is the C S R rating of each firm. Optimally, we would like to have a continuous measure of the C S R rating, but the data are not available. O u r substitute is the binary variable, CSR, which equals one i f a firm passes the screening conducted by K L D and zero if it fails.  Our  underlying assumption is that there is a monotonic relation between the C S R expenditure of the firm and the probability that the firm receives an S R rating from K L D . W i t h respect to the qualitative screening we feel comfortable w i t h this assumption since it is a comprehensive analysis that looks into many dimensions of social issues (more t h a n 200 sections) and it is reasonable to assume that firms w i t h higher C S R expenditure tend to receive an S R rating. O n the other hand, SI firms due to exclusionary screening receive their rating due to a failure i n one "unethical" dimension, which is controversial at best. These firms can not be employed i n the analysis because they can not be considered as firms w i t h low (nor high) C S R expenditure. Thus, we omit these firms from the sample and left w i t h 2650 firms i n the analysis. Table I V . 2 reports the number of S R and SI firms, sorted by 2-digit S I C codes 70  to sixty-four industries. The ratio of ^  over the whole sample is approximately  6. There are, of course, large variations across industries. Some industries, such as the high-tech industry are dominated by SR firms, while other industries, such as basic materials, have a higher proportion of SI firms.  Conflict Variables As mentioned above, when considering the ownership structure we focus on two groups of investors: insiders and institutions. We use two measures for ownership by insiders. The first is Insiders' ownership, the percent of common stock held by all officers and directors of the company plus beneficial owners who own more than 5 percent of the subject company's stock as disclosed in the most recent proxy statement. Our second measure is Insiders' control, a dummy variable which equals one if the combined ownership of insiders is more than 50% of the shares outstanding, and zero otherwise. This allows us to isolate cases in which insiders (jointly) have control over of the firm. For institutional ownership we also use two measures. Institutional ownership is the aggregate holdings of common stocks held by all reporting institutions as a group. It is calculated as a percent of the total number of shares outstanding. The second measure is Institutional HHI, which is the Herfindahl-Hirschman Index (HHI) of concentration of the top 15 institutional owners for every single firm. It is defined as  X)i=i  where hi is the percentage of ownership of institution i. We  are using a measure of the concentration of institutional ownership in addition to a measure of the total ownership since previous work showed that institutions influence more when they are large shareholders (Shleifer and Vishney (1986)) and when they can form a coalition (Black (1992)). The concentration measure can capture this ability better than the total ownership measure. The monitoring ability of debtholders and availability of cash flow are captured by firms' leverage.  The variable Leverage is defined as long-term debt  divided by the total book value of assets. 71  SR Firms and SI Firms correspond to the number of SR and SI firms classified by twodigit standard industry classification (SIC) code. Total Number of Firms corresponds to the total number of firms in each industry. Percent of SI Firms is SI Firms divided by Total Number of Firms. Percent of SI Industry Description Total SIC SR SI Number Firms Code Firms Firms of Firms Metal mining 4 6 10 10 60% 12 Coal mining 3 100% 0 3 13 Oil and gas extraction 54 12 66 18% 14 Nonmetallic minerals, except 3 1 4 25% fuels General building contractors 19 16% 15 16 3 Heavy construction, except 1 16 5 6 17% buildings 17 Special trade contractors 5 0 5 0% Food and kindred products 20 38 8 46 17% 21 Tobacco products 0 0 0 — 22 Textile mill products 8 0 8 0% 23 Apparel and other textile 15 1 16 6% products 24 Lumber and wood products 10 4 14 29% Furniture and fixtures 14 2 25 16 13% Paper and allied products 26 25 3 28 11% 27 Printing and publishing 30 9 39 23% 28 Chemical and allied products 163 48 211 23% Petroleum and coal products 4 14 29 10 71% 30 Rubber and miscellaneous 17% 15 3 18 plastic products 31 Leather and leather products 9 1 10 10% 32 Stone, clay, and glass products 4 11 7 36% 33 Primary metal industries 26 7 33 21% 34 Fabricated metal products 22 4 26 15% 12 141 Industrial machinery and 9% 35 129 equipment 36 Electronic and other electrical 165 11 176 6% equipment 37 Transportation equipment 30 7 37 19% 38 Instruments and related 125 5 130 4% products 39 Miscellaneous manufacturing 15 1 16 6% products 40 Railroad transportation 4 4 8 50% 42 Trucking and warehousing 2 17 12% 15 44 Water transportation 7 7 0 0% 45 Transportation by air 17 1 18 6% Table IV.2: The Distribution of SR (Socially Responsible) and SI (Socially Irresponsible) Firms by Two-Digit SIC Code 72  SIC Code  Industry Description  SR Firms  SI Firms  46 47 48 49  Pipelines, except natural gas Transportation services Communications Electric, gas, and sanitary services Wholesale trade - durable goods Wholesale tradenondurable goods Building materials and gardening General merchandise stores Food stores Auto dealers and service stations Apparel and accessory stores Furniture and home furnishings Eating and drinking places Miscellaneous retail Depository institutions Nondepository institutions Security and commodity brokers Insurance carriers Insurance agents, brokers, services Real estate Holding and other investment offices Hotels and other lodging places Personal services Business services Auto repair, services, and parking Motion pictures Amusement and recreation services Health services Legal services Educational services Social services Engineering and management services Conglomerates  1 7 70 56  50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 67 70 72 73 75 78 79 80 81 82 83 87 99 Total  Percent of SI Firms  0 2 9 16  Total Number of Firms 1 9 79 72  44 17  2 4  46 21  4% 19%  5  1  6  17%  19 11 14 36 17 29 48 253 21 29 79 15  2 2 2 6 1 3 7 42 4 5 17 1  21 13 16 42 18 32 55 295 25 34 96 16  10% 15% 13% 14% 6% 9% 13% 14% 16% 15% 18% 6%  4 137  4 11  8 148  50% 7%  7 5 269 5  2 4 19 0  9 9 288 5  22% 44% 7% 0%  8 2  3 5  11 7  27% 71%  30 1 11 2 42  14 0 0 1 8  44 1 11 3 50  32% 0% 0% 33% 16%  4  1  5  20%  2278  371  2649  14%  Table IV.2: continued 73  0% 22% 11% 22%  Control Variables W e include several control variables i n the analysis to control for industry and firm characteristics.  T o capture industry effects, we include  sixty-four d u m m y variables for each 2-digit S I C code. F i r m size is measured by the natural log of the book value of total assets. W e proxy for growth opportunities using the market to book ratio, calculated as the market value of assets divided by the book value of assets. T h e 60 months return volatility of the firm's share is our proxy for firm's risk. F i r m ' s age is measured by the number of years since the firm's share price appeared on the C R S P tape.  Summary Statistics Table I V . 3 presents difference of means tests between S R and SI firms. SI firms represent 14% of our sample. T h e table provides the t-statistics and the Industry Adjusted t-statistics, where each observation is adjusted by subtracting the 2-digit S I C code industry mean of the relevant variable.  The  later provides a cleaner way to test the significance of the variable once industry effects are accounted for. W e find that S R firms have an insiders' ownership level which is lower by 4% than that of SI firms. Moreover, 17% of SI firms are controlled by insiders (i.e., insiders' ownership of more t h a n 50%) while this is the case i n only 9% of the S R firms. W h i l e there is a distinct difference i n the holdings of insiders between S R and SI firms, there is no significant difference i n the institutional ownership measures. Consistent w i t h our hypothesis, S R firms tend to have lower leverage than SI firms. W i t h respect to age and size, S R firms are younger and smaller than SI firms. T h e univariate analysis also suggests that S R firms tend to have a higher market to book ratio and that their shares are more volatile t h a n those of SI firms. Concerning firms' classification, 51.6% of S R firms are listed on the Nasdaq stock exchange compared to 28% of SI firms. There is also some evidence that west coast firms are more socially responsible; 27.5% of S R firms' headquarters are i n the west cost, compared to only 18.3% of SI firms. F i r m s 74  which are part of the S & P 500 represent 18.9% of our sample. However, included in the S & P 500 are 14.6% of the SR firms and 27.9% of the SI firms. This again suggests that size is an important factor determining the classification of a firm to be either SR or SI.  4.3  Multivariate Analysis  Multivariate Analysis of C S R In this section we investigate the relation between CSR and the conflict variables. Our measure of the social performance of firms, is CSR, a dummy variable which equals one if a firm has passed the qualitative screening conducted by K L D and zero if it failed. The model that we test is the following: CSR = 7o + 7i (Insider ownership) + 7 (Institutional 2  +  7 (Leverage) + "j _ (Control 3  A  7  ownership)  variables) + ~f _ (Two — digit SIC code) + e 8  71  (IV. 1) On the right hand side we interchangeably use the variables Insiders' ownership and Insiders' control as measures of ownership by insiders. Our measures of ownership by institutions are the variables Institutional ownership and Institutional HHI; we use these variables interchangeably as well. Leverage captures potential capital structure effects. The control variables are Ln total assets, Market to book, Return volatility and Firm's age as well as sixty four 2-digit SIC code dummy variables to control for industry effects. The results with robust standard deviations are presented in Table IV.4. The most striking result in our analysis is that the coefficients of insiders' ownership and leverage are negative and significant at the 1% level across all specifications. On the other hand, the coefficients of institutional ownership are insignificant with inconsistent signs.  The economic interpretation of the probit results is  that ceteris paribus, at the sample means, an increase of one standard deviation 75  Insiders ownership is the percent of common stock held by all the officers and directors of the company plus beneficial owners who own more than 5 percent of the stock. Insiders' control is a dummy variable that equals 1 if insiders as a group have more than 50% of the shares outstanding. Institutional ownership is the percent of common stock held by all the reporting institutions as a group. Institutional HHI is the Herfindahl-Hirschman Index calculated based on the holdings of the 15 largest institutional investors. Leverage is the book value of long-term debt divided by the book value of total assets. Ln total assets is the natural log of the book value of assets. Market to book is defined as the ratio of the book value of assets plus the difference between the market value of equity and the book value of equity to the book value of assets. Return volatility is the standard deviation of share returns during the previous 60 months. Firm s age is measured based on the date in which the firm s share price first appeared on the C R S P tape. The classification dummy variables Nasdaq, West coast and S&P 500 equal 1 if the f i r m is traded on Nasdaq, if the firm s headquarter is in the west coast and if the firm is part of the S & P 500 index, respectively. The table provides the ^statistics and the Industry Adjusted ^statistics, where each observation is adjusted by subtracting the 2-digit SIC code industry mean of the relevant variable. The table provides significance at the five percent (*) level. N  SR Firms  SI Firms  tstatistic  Industry Adjusted t-statistic  Number of firms  2650  2278  372  Conflict variables Insiders' ownership (%) Insiders' control (%) Institutional ownership (%) Institutional H H I (%) Leverage (%)  2650 2650 2641 2650 2589  18.29 9.00 60.22 2.26 17.79  22.37 17.20 60.00 2.32 24.37  3.61* 4.88* -0.16 0.34 5.85*  3.58* 4.28* -0.29 0.13 4.91*  Control variables L n total assets ($000,000) Market to book Return volatility (%) Firm's age (years)  2597 2594 2648 2649  6.81 1.70 17.11 15.57  7.74 1.51 14.84 20.22  9.93* -2.72* -4.35* 5.52*  9.15* -2.59* -2.52* 3.13*  Classification Nasdaq (%) West coast (%) S & P 500 (%)  2650 2650 2650  51.62 27.48 14.62  27.96 18.28 23.66  -8.58* -3.75* 4.44*  -6.54* -1.90 3.55*  Table IV.3: Difference of means teats  76  Insiders ownership is the percent of common stock held by all the officers and directors of the company plus beneficial owners who own more than 5 percent of the stock. Insiders' control is a dummy variable that equals 1 if insiders as a group have more than 50% of the shares outstanding. Institutional ownership is percent of common stock held by all the reporting institutions as a group. Institutional HHI is the HerfindahlHirschman Index calculated based on the holdings of the 15 largest institutional investors. Leverage is the book value of long-term debt divided by the book value of total assets. Ln total assets is the natural log of the book value of assets. Market to book is defined as the ratio of the book value of assets plus the difference between the market value of equity and the book value of equity to the book value of assets. Return volatility is the standard deviation of share returns during the previous 60 months. Finn s age is measured based on the date in which the firm s share price first appeared on the C R S P tape. A l l specifications include 2-digit SIC code indicators. The table provides ^-statistics calculated with robust standard deviations.  Intercept Insiders' ownership  (1) 1.8623 (2.34) -0.0098 (-5.09)  Insiders' control Institutional ownership  0.0006 (0.35)  (2) 1.5431 (1.99)  (3) 1.9173 (2.44) -0.0102 (-6.10)  -0.5341 (-4.76) 0.0019 (1.07)  Institutional H H I  (4) 1.6810 (2.19)  -0.5943 (-5.79)  Leverage  -0.5884 (-3.06)  -0.6073 (-3.18)  0.0683 (0.08) -0.5786 (-3.01)  L n (total assets)  -0.2067 (-7.69) 0.0548 (1.42) 0.3011 (0.57) -0.0008 (-0.33)  -0.1960 (-7.37) 0.0582 (1.51) 0.3686 (0.70) -0.0002 (-0.07)  -0.2060 (-7.91) 0.0550 (1.42) 0.2849 (0.54) -0.0008 (-0.34)  -0.1910 (-7.53) 0.0613 (1.56) 0.3062 (0.58) -0.0003 (-0.13)  2537  2537  2546  2546  0.143  0.141  0.143  0.141  Market to book Return volatility Firm's age  N "Pseudo R " 2  -0.0438 (-0.05) -0.5880 (-3.09)  Table IV.4: The Relation between C S R and the Conflict Variables - Probit Regressions  77  in total insiders' ownership of firm i, decreases the probability that K L D would define firm i as socially responsible by 3.8%. Similarly, an increase of one standard deviation in the leverage of firm i, decreases the probability that K L D would define firm i as socially responsible by 2.2%. In contrast, an increase in the total institutional ownership or in the institutional concentration of firm i, does not change the probability that K L D would define firm i as socially responsible. Some additional information regarding the prospects of SR firms can be learned from the coefficients of the control variables. We find that SR firms tend to be smaller in size as measured by book value of assets. On the other hand, the multivariate analysis suggests that the growth prospects of firms, their risk and their age do not add significant contribution in explaining the variance of CSR. Our results show that insiders' holdings are negatively correlated with C S R ratings. According to our hypothesis, insiders who are affiliated with the firm are those who gain private benefits from a high C S R rating. The interpretation of this negative correlation in light of our hypothesis is that at high ownership levels, insiders' cost from increasing CSR expenditure (which yields a higher CSR rating) is larger than their benefits. In other words, insiders downplay the importance of their private benefits compared to firm value simply because they own more of the firm. Thus, the negative relation suggests that the cost incorporated in CSR is significant.  5  The negative correlation between leverage and C S R also supports the CSRconflict hypothesis. If leverage plays a conflict mitigating role as suggested by the literature (e.g., Harvey, Lins and Roper (2004)), a higher leverage makes firms spend less on CSR. Lastly, the results reveal that institutional holdings are not Throughout the paper we assume for presentation simplicity that all insiders gain private benefits from CSR expenditure. However, the interpretation of the empirical results remains the same even if only a portion of insiders benefit from CSR. Under such circumstances, an increase in the ownership of insiders who do not benefit from CSR should mitigate the CSR-conflict due to better monitoring, and even strengthen our results. 0  78  correlated w i t h C S R . T h i s may be attributed to the reasons discussed above. A Relative C S R Measure ( R C S R ) One of the limitations of the study is that we do not observe a continuous measure for C S R ratings and are constrained to use a binary one. T h e problem w i t h this measure is that it does not provide a cardinal C S R rating that distinguishes between different S R and SI firms. For example, it imposes the assumption that all S R firms (and similarly all SI firms) have the same rating across different firm industries. To illustrate the problem, consider for example a firm i n a high-tech industry and a firm i n an o i l industry. B y the nature of these two industries it is easier for a high-tech company to achieve a higher social rating as its operations do not pollute the environment.  In fact, an o i l company that has the same C S R  rating as a high-tech company probably needs a much higher C S R expenditure i n order to achieve this rating. In other words, the importance of the conflict variables should be larger i n firms which defy their characteristics. Other firm characteristics such as size, age and growth opportunities may also be important i n defining the relation between the conflict variables and the C S R ratings. In order to overcome this problem, we develop a methodology that maps the binary dependent variable into a continuous one. W e are doing so by decomposing the explained component of CSR  that is due to firm characteristics and giving a  higher weight to firms that defy their characteristics. This allows us to investigate the relation between the conflict variables and the C S R rating i n a way that emphasizes the importance of firm characteristics i n setting C S R ratings. T h e methodology is composed of three steps. First, we r u n a probit regression where the dependent variable CSR  CSR  =  7Q + l\{Ln  is regressed on firm characteristics.  total assets) + 7 (Marfce£ to book) + ^y (Return 2  +7 (Firm's age) + ^ _ (Two 4  5  68  3  — digit SIC code) + e  F r o m this regression we obtain the predicted probability, CSR,  79  volatility)  (IV.2)  that a firm re-  ceives an S R rating (CSR  = 1) solely due to its characteristics.  In the second step we define a relative corporate social responsibility measure,  RCSR.  A higher RCSR  RCSR  =  [sign (£)] (ef  where £  =  CSR  -  CSR  value represents a more socially responsible  technically capped i n the interval [—1,1] since CSR T h e RCSR  (IV.3)  firm.  RCSR  is  is a probability measure.  measure conserves the sign and squares the magnitude of the error.  6  Since a high e denotes a high divergence from the predicted probability as defined by the firm's characteristics, the RCSR  measure rewards S R firms w i t h a high e  and punishes SI firms w i t h a high e. It emphasizes firms that do not confirm to their characteristics. In the final step, we study the conflict variables' impact on ratings by running different specifications of the following relation:  RCSR  = 6 +Si (Insider owner ship)+6 0  2  (Institutional  owner ship)+63 (Lev erage)+e  (WA) T h i s regression allows us to study whether the conflict variables' explanatory power changes once the observations are rescaled to reflect the degree of conformity w i t h the firm's peers. B y way of construction, the RCSR  measure is not normally distributed. It is  capped i n the range [—1,1] and because some industries have more observations than others, there are many clusters of observations i n certain ranges of the variable. T h e common way of estimating a regression under such circumstances is to employ a bootstrap methodology. We randomly draw, w i t h replacement, observations (where N is the original sample size) from the data set. Using each 6  N o t e that w i t h o u t squaring the errors this m e t h o d o l o g y  ( t a b l e IV.4)  into two steps.  80  s i m p l y splits the one step probit  regression  ownership is the percent of common stock held by all the officers and directors of the company plus beneficial owners who own more than 5 percent of the stock. Insiders' control is a dummy variable that equals 1 if insiders as a group have more than 50% of the shares outstanding. Institutional ownership is percent of common stock held by all the reporting institutions as a group. Institutional HHI is the Herfindahl-Hirschman Index calculated based on the holdings of the 15 largest institutional investors. Leverage is the book value of long-term debt divided by the book value of total assets. The standard deviations used to compute ^-statistics are calculated using the bootstrap methodology.  Insiders  Intercept Insiders' ownership  (2) -0.0505 (-3.75)  (1) -0.0256 (-1.60) -0.0013 (-4.39)  Insiders' control Institutional ownership  -0.0804 (-3.93) 0.0001 (0.76)  0.0000 (0.08)  Institutional HHI Leverage N R  1  (3) -0.0244 (-2.86) -0.0013 (-4.80)  (4) -0.0411 (-5.53) -0.0852 (-4.26)  -0.0825 (-3.07)  -0.0808 (-3.02)  0.0031 (0.02) -0.0818 (-3.08)  0.0018 (0.01) -0.0789 (-3.01)  2537  2537  2546  2546  0.017  0.016  0.016  0.015  Table IV.5: The relation between RCSR and the conflict variables - OLS regressions  sample, we calculate the coefficients. We repeat this procedure 10,000 times to build a dataset of estimated coefficients. This allows us to calculate the  standard  deviations of the coefficients and compute their ^statistics accurately.  Table IV.5 reports OLS regressions where RCSR  is regressed on the  conflict  variables. Similar to our previous findings, we find that ownership by insiders and debt have a significant negative effect on RCSR. We also find that ownership by institutions has no significant effect on RCSR.  We view the RCSR measure as an important addition to our analysis. Therefore, throughout the rest of the study we provide the regression results for both CSR and RCSR. 81  Piece-wise Regression So far, our analysis allowed only for a linear relation between ownership by insiders and CSR. In order to analyze whether a possible non-linearity is present in the data, we follow Morck, Shleifer and Vishny (1988) and perform piece-wise regressions which allow the coefficients of Insiders' ownership to vary over three different segments of ownership. This procedure allows us to investigate the trade-off between the alignment and entrenchment of insiders. At low levels of ownership, an increase in insiders' holdings not only makes them bear more of the cost of CSR expenditure, but also gives them more control to pursue a pro-CSR agenda. Therefore, it is not clear which is the dominant force and how the C S R rating should be affected. However, once insiders are entrenched, a further increase in their ownership should only result in bearing more of the cost associated with CSR. The results of the piece-wise regressions are shown in Table IV.6. The analysis suggests that at low levels of ownership by insiders (up to 25%) there is no relation between insiders' ownership and CSR, while at levels above 25% the relation is negative and highly significant. This is somewhat consistent with Morck Shleifer and Vishny (1988) who document a positive relation with Tobin's Q at small holdings of 0%-5%, a negative relation at holdings of 5%-25% and a positive relation again, at holdings greater than 25%.  Instrumental Variable (IV) Approach One may argue that our analysis potentially suffers from an endogeneity problem. Specifically, one could claim that insider and institutional ownership are determined by the C S R rating and not vice versa. For example, it may be the case that socially responsible investing (SRI) plays an important role in setting the holdings of institutional investors. Since most socially responsible investors implement their investing strategy using institutions such as mutual funds and pension funds, one could expect to see higher ownership by institutions at SR firms relatively to SI firms. In order to 82  Insiders' ownership is divided to three different segments of ownership. Following Morck, Shleifer and Vishney (1988), Insiders 0 to 5 equals Insiders' ownership if Insiders' ownership < 5% and equals 5% if Insiders' ownership > 5%; Insiders 5 to 25 equals 0% if Insiders' ownership < 5%, equals Insiders' ownership - 5% if 5% < Insiders' ownership < 25% and equals 20% if Insiders' ownership > 25%; Insiders over 25 equals 0% if Insiders' ownership < 25% and equals Insiders' ownership - 25% if Insiders' ownership > 25%. Institutional ownership is percent of common stock held by all the reporting institutions as a group. Institutional HHI is the Herfindahl-Hirschman Index calculated based on the holdings of the 15 largest institutional investors. Leverage is the book value of long-term debt divided by the book value of total assets. Ln total assets is the natural log of the book value of assets. Market to book is defined as the ratio of the book value of assets plus the difference between the market value of equity and the book value of equity to the book value of assets. Return volatility is the standard deviation of share returns during the previous 60 months. Firm s age is measured based on the date in which the f i r m s share price first appeared on the CRSP tape. Specifications (1) and (2) include 2-digit SIC code indicators. The table provides ^-statistics with robust standard deviations (specifications (1) and (2)) and ^statistics that were calculated using the bootstrap methodology (specifications (3) and (4)). Dependent Variable Intercept Insiders 0 to 5 Insiders 5 to 25 Insiders over 25 Institutional ownership  CSR (Probit) (2) 1.9411 (2.45) -0.0268 (-0.94) -0.0036 (-0.59) -0.0127 (-4.32)  (1) 1.8949 (2.36) -0.0264 (-0.92) -0.0035 (-0.55) -0.0122 (-3.99) 0.0006 (0.33)  Institutional HHI Leverage  -0.5834 (-3.02)  Ln (total assets) Market to book Return volatility Firm's age  N R 1 "Pseudo R " 2  1  .  0.1113 (0.12) -0.5741 (-2.98)  R C S R (OLS) (3) -0.0291 (-1.43) -0.0022 (-0.61) -0.0001 (-0.12) -0.0020 (-3.52) 0.0000 (0.08)  (4) -0.0280 (-2.09) -0.0023 (-0.64) -0.0001 (-0.12) -0.0020 (-3.58)  -0.0805 (-3.00)  0.0169 (0.09) -0.0798 (-3.02)  -0.2072 (-7.48) 0.0557 (1.44) 0.3008 (0.57) -0.0008 (-0.31)  -0.2063 (-7.70) 0.0560 (1.44) 0.2874 (0.55) -0.0008 (-0.32)  2537  2546  2537  2546  0.144  0.144  0.019  0.018  Table IV.6: Piecewise regressions of Insiders' Ownership: the relation between C S R (RCSR) and the conflict variables  83  disproof this potential problem we use an instrumental variable approach. There are three variables that potentially suffer from endogeneity: Insiders' ownership, Insiders' control, and Institutional ownership. We follow Bennett,  Sias and Starks (2003) and use Turnover as an instrument for the insider ownership variables. Table IV.8 presents the results of the instrumental variable 7  regression analysis. In regressions (1) and (2) we replace Insiders' ownership and Insiders' control with the predicted value of these variables regressed on Turnover, Ln total asset, Market to book, Firm's age, Return volatility and 2-digit  SIC dummy variables. In regressions (3) and (4) we replace Insiders' ownership and Insiders' control with the predicted value of these variables regressed on Turnover alone. The reason for omitting the other control variables is that these are already part of the RCSR measure. Table IV.7 report the results of the first stage of the IV methodology. In order to avoid a potential endogeneity problem with the variable Institutional ownership, we perform the regressions with Institutional HHI. We view Institutional HHI as a purely exogenous variable (consistent with Hartzell and Starks (2003)) as there is no theoretical reason to believe that the concentration of institutional ownership is the result of the CSR policy of the firm. Consistent with our earlier results, we find that ownership by insiders and debt are significant and negatively related to firms' CSR ratings and that ownership by institutions is uncorrelated with the ratings. Robustness Analysis In this section we perform robustness checks. We start with a robustness analysis with respect to size. While we do control for size in our analysis, one may still wonder whether the results hold for subsets of the sample. For example it may be the case that small firms attract less attention from private investors and institutions and therefore it is easier for insiders to Turnover is defined as a three months average of the monthly volume divided by the number of shares outstanding. 7  84  The table presents the results of the first stage in the Instrumental-variable, two-stage probit / OLS regressions of CSR and RCSR, where Turnover is used as an instrument for insiders' ownership. In regressions (1) and (2) Insiders' ownership (Insiders' control) is regressed on Turnover, Ln total asset, Market to book, Return volatility, Firm's age and 2 digit SIC codes. In regressions (3) and (4) Insiders' ownership (Insiders' control) is regressed on  Turnover. The table provides ^-statistics in parenthesis. Dependent Variable Intercept Turnover Ln (total assets) Market to book Return volatility Firm's age N R  1  insiders' ownership (3) (1) 21.3842 52.0808 (41.11) (2.75) -2.0182 -1.4710 (-7.34) (-9.22) -1.9406 (-6.48) 0.5954 (1.76) 12.0498 (2.13) -0.2040 (-6.88)  insiders' control (4) (2) 0.0641 0.1259 (0.22) (16.15) -0.0212 -0.0142 (-4.72) (-6.25) -0.0112 (-2.43) 0.0117 (2.24) 0.1427 (1.63) -0.0022 (-4.81)  2592  2648  2592  2648  0.160  0.020  0.094  0.008  Table IV.7: First stage of the Instrumental Variable regressions  85  Instrumental-variable, two-stage probit / O L S regressions of C S R and R C S R , where Turnover is used as an instrument for insiders' ownership. The Predicted value of insiders' ownership (insiders' control) in regressions (1) and (2) is the predicted value obtained by regressing Insiders' ownership (Insiders' control) on Turnover, Ln total asset, Market to book, Return volatility, Firm's age and 2 digit SIC codes. The Predicted value of insiders' ownership (insiders' control) in regressions (3) and (4) is the predicted value obtained by regressing Insiders' ownership (Insiders' control) on Turnover. Institutional HHI is the Herfindahl-Hirschman Index calculated based on the holdings of the 15 largest institutional investors. Leverage is the book value of long-term debt divided by the book value of total assets. Ln total assets is the natural log of the book value of assets. Market to book is defined as the ratio of the book value of assets plus the difference between the market value of equity and the book value of equity to the book value of assets. Return volatility is the standard deviation of share returns during the previous 60 months. Firm s age is measured based on the date in which the firm s share price first appeared on the C R S P tape. Specifications (1) and (2) include 2-digit SIC code indicators. The table provides z-statistics with robust standard deviations (specifications (1) and (2)) and ^-statistics that were calculated using the bootstrap methodology (specifications (3) and (4)). Dependent Variable Intercept Predicted value of insiders' ownership Predicted value of insiders' control Institutional H H I Leverage  L n (total assets)  C S R (Probit) (2) (1) 2.2492 3.1515 (3.35) (3.18) -0.0286 (-2.05) -2.7226 (-2.05) -0.1381 -0.1381 (-0.13) (-0.13) -0.6071 -0.6071 (-3.29) (-3.29)  R C S R (OLS) (3) (4) 0.0090 -0.0166 (0.35) (-1.09) -0.0031 (-2.26) -0.3199 (-2.29) -0.0181 -0.0181 (-0.09) (-0.09) -0.0797 -0.0797 (-2.98) (-2.99)  -0.2413 (-5.70) 0.0560 (1.50) 0.2158 (0.41) -0.0045 (-1.26)  -0.2165 (-6.50) 0.0708 (1.86) 0.2603 (0.50) -0.0046 (-1.28)  N  2546  2546  2546  2546  R 1 "Pseudo 7?"  0.128  0.128  0.006  0.006  Market to book Return volatility Firm's age  1  Table IV.8: Instrumental variable regressions: C S R (RCSR) and the conflict variables  86  affect the CSR policy in these firms compared to large firms. We perform the first robustness check by splitting our sample to two based on the book value of assets. The results of this analysis are reported in Panel A of Table IV. 9. In all four specifications ownership by insiders and leverage are negatively significant while institutional ownership is marginally significant in only one specification. While the results of the table reconfirm the CSR-conflict hypothesis, the significance levels and size of insiders' ownership coefficients are larger in small firms. This suggests that the presence of the CSR-conflict is larger in these firms. In a second robustness analysis we split the sample based on industries' average CSR ratings, where industries are defined by 2-digit SIC codes. Firms are partitioned to two groups according to the percentage of SR firms in their industry; 86.5% is the overall industries median value. Arguably, industry classification is the most important factor in defining the ability of the firm to be classified as SR. Therefore, using this criterion in order to split the sample is a good robustness check. Panel B of table IV.9 reports the results of these regressions. We find some differences between the two sub-samples. While insiders' ownership coefficients are negative and significant in both sub-samples, they are more significant in SI Industries (industries that have less than 86.5% SR firms). With respect to debt, while it is always negatively correlated with the CSR and RCSR measures, it is significant only in SR Industries. Put together, these results show that insiders' ownership is the dominant conflict-mitigating mechanism in SI Industries, while leverage is the dominant mechanism in SR Industries.  4.4  CSR and Corporate Governance  We argue that the CSR-conflict is different than traditional agency conflicts on two dimensions. First, the traditional conflict is between the manager and the shareholders, while the CSR-conflict is between insiders and the other sharehold87  In Panel A, the sample of firms is partitioned according to size (book value of total asset). Large Firms refer to large cap firms and Small Firms refer to small cap firms respectively. In Panel B, the sample of firms is partitioned according to the percentage of SR firms in the industry, where industry is defined according to the 2-digit SIC code. Firms that belong to an industry where the percentage of SR firms is higher than 86.5% (overall industry median value) are part of the first sub sample, and firms that belong to an industry where the percentage of SR firms is lower than 86.5% are part of the second sub sample. Insiders ownership is the percent of common stock held by all the officers and directors of the company plus beneficial owners who own more than 5 percent of the stock. Insiders' control is a dummy variable that equals 1 if insiders as a group have more than 50% of the shares outstanding. Institutional ownership is percent of common stock held by all the reporting institutions as a group. Institutional HHI is the HerfindahlHirschman Index calculated based on the holdings of the 15 largest institutional investors. Leverage is the book value of long-term debt divided by the book value of total assets. Ln total assets is the natural log of the book value of assets. Market to book is defined as the ratio of the book value of assets plus the difference between the market value of equity and the book value of equity to the book value of assets. Return volatility is the standard deviation of share returns during the previous 60 months. Firm s age is measured based on the date in which the firm s share price first appeared on the CRSP tape. Specifications (1) and (2) include 2-digit SIC code indicators. The table provides ^-statistics with robust standard deviations (specifications (1) and (2)) and ^statistics that were calculated using the bootstrap methodology (specifications (3) and (4))Panel A: S ize Partitioning Dependent Variable Intercept Insiders' ownership Institutional ownership Leverage  CSR (Probit) Large Firms Small Firms (2) (1) 1.0200 2.2609 (1.05) (2.23) -0.0049 -0.0149 (-1.81) (-5.15) 0.0039 -0.0026 (1.53) (-0.96) -0.5704 -0.5371 (-1.73) (-1.95)  RCSR (OLS) Large Firms Small Firms (4) (3) -0.0712 0.0274 (-2.93) (1.32) -0.0007 -0.0020 (-1.67) (-4.89) 0.0005 -0.0005 (1.44) (-1.78) -0.0763 -0.0864 (-2.31) (-1.83)  -0.2182 (-5.72) 0.2917 (3.49) 0.3854 (0.39) -0.0003 (-0.10)  -0.2837 (-3.29) -0.0258 (-0.70) 0.1209 (0.19) -0.0028 (-0.51)  A^  1216  1175  1268  1269  R j "Pseudo i ? "  0.152  0.135  0.011  0.032  Ln (total assets) Market to book Return volatility Firm's age  2  Table IV.9: Robustness Analysis by Size and Industry: CSR (RCSR) and the Conflict Variables 88  Panel B : Industry Partitioning Dependent Variable  Intercept Insiders' ownership Institutional ownership Leverage  L n (total assets) Market to book Return volatility Firm's age  N R 1 "Pseudo R " 2  2  C S R (Probit) SR Industries SI Industries (2) (1) 1.9831 1.9985 (3.48) (2.39) -0.0119 -0.0060 (-1.82) (-4.93) 0.0014 -0.0007 (-0.24) (0.59) -1.0272 -0.2108 (-0.84) (-3.80)  R C S R (OLS) SR Industries SI Industries (3) (4) 0.0024 -0.0399 (-1.82) (0.10) -0.0008 -0.0018 (-2.07) (-4.20) -0.0003 0.0001 (-1.09) (0.45) -0.0482 -0.1116 (-3.12) (-1.23)  -0.0997 (-2.11) 0.0124 (0.29) 0.5783 (0.73) 0.0032 (0.68)  -0.2560 (-7.56) 0.0800 (1.32) 0.1621 (0.22) -0.0024 (-0.79)  1244  1293  1292  1293  0.057  0.134  0.017  0.024  Table IV.9: continued  89  ers. Second, corporate social responsibility has a positive public appeal, while traditional agency conflicts have a negative appeal. In fact, in contrary to the theme of this chapter, which claims that CSR activity may decrease firm value, there is a perceived link that good corporate governance and good corporate social responsibility go together. Perhaps this is because both are regarded as an ethical behavior on part of the firm. It is interesting, therefore, to examine whether this link has some empirical evidence that supports it. We use the index proposed by Gompers, Ishii and Metrick (2003) (GIM) as our measure of the corporate governance level of the firm. The index is constructed by analyzing 24 distinct corporate governance provisions. It adds one point for every provision that reduces shareholder rights; that is, a high score represents bad corporate governance. The univariate correlation between the GIM index and CSR is marginally negative ( — -04) and it is marginally positive with RCSR (0.01). Furthermore, in a multivariate analysis that we do not report here, we find that the GIM index is not significant in explaining either CSR nor RCSR.  We  conclude that there is no empirical evidence that supports the relation between CSR and corporate governance as measured by the GIM index. Throughout the chapter the results indicate that insiders' ownership and debt are negatively related to firms' CSR ratings, while institutional ownership does not affect them. While there are reasons why institutions may choose not to affect CSR (see our discussion above), the question is still left open. We use the GIM index to get a better understanding of this phenomenon. Similarly to the CSR ratings, the GIM index should be related to the ownership structure of the firm as the shareholders are those who set the conflictmitigating mechanisms in place. Table IV. 10 reports the results of regressing the GIM index on the ownership structure, the capital structure and the control variables of our analysis. We find that ownership by insiders is significant in improving corporate governance. Similarly, there is strong evidence that insti90  tutional ownership concentration positively affects corporate governance. These results support the idea that institutions tend to be active at least on some standard corporate governance issues such as poison pills and golden parachutes provisions. On the other hand, the fact that institutions do not affect CSR hints that they find it hard to oppose it or that they do not consider CSR at the same token as other types of conflicts. 4.5 Conclusions In this chapter we find strong supportive evidence to the hypothesis that CSR is a source of a conflict between different shareholders. In this conflict insiders personally benefit from the fact that they are associated with firms that have a high CSR rating. The conflict is mitigated if insiders hold a large fraction of the firm. Similarly, debt serves as a conflict-mitigating mechanism. Lastly, we find no evidence that institutions have a monitoring role on CSR policies. The CSR-conflict can be viewed from two different normative perspectives. On the one hand, we find supportive evidence to the claim that the chosen level of CSR expenditure is greater than that which maximizes firm value. This typically has a negative connotation as it decreases value for shareholders. On the other hand, the CSR-conflict leads to the promotion of a social agenda, which can be viewed in a positive way. Given that most agency conflicts are perceived as selfserving behavior of managers at the expense of other shareholders, it is somewhat ironic to show that the CSR-conflict results in greater alignment of corporate and social goals. From a social welfare perspective, whether this conflict increases total welfare depends on the question whether firms have a relative advantage in contributing to the society.  91  The G I M index is regressed on the conflict and control variables used in this paper. GIM is the "Governance Index" proposed by Gompers, Ishii and Metrick (2003). Insiders ownership is the percent of common stock held by all the officers and directors of the company plus beneficial owners who own more than 5 percent of the stock. Insiders' control is a dummy variable that equals 1 if insiders as a group have more than 50% of the shares outstanding. Institutional ownership is percent of common stock held by all the reporting institutions as a group. Institutional HHI is the Herfindahl-Hirschman Index calculated based on the holdings of the 15 largest institutional investors. Leverage is the book value of long-term debt divided by the book value of total assets. Ln total assets is the natural log of the book value of assets. Market to book is defined as the ratio of the book value of assets plus the difference between market value of equity and the book value of equity to the book value of assets. Return volatility is the standard deviation of share returns during the previous 60 months. Firm s age is measured based on the date in which the firm s share price first appeared on the C R S P tape. A l l specifications include 2-digit SIC code indicators.  Intercept Insiders' ownership  (1) 10.1588 (17.51) -0.0334 (-7.21)  Insiders' control Institutional ownership  -0.0049 (-1.16)  (?) 11.4096 (17.05)  L n (total assets) Market to book Return volatility Firm's age  N R  2  (41_ 10.2011 (21.59)  -1.2602 (-4.79)  -1.3245 (-4.10) 0.0032 (0.76)  Institutional H H I  Leverage  (3) 10.9211 (22.79) -0.0290 (-7.53)  -4.8082 (-3.09)  -5.5401 (-3.50)  0.4865 (1.34) 0.0296 (0.51) -0.1075 (-1.65) -5.0147 (-4.92) 0.0306 (6.58)  0.3773 (1.02) 0.0747 (1.31) -0.1160 (-1.76) -4.4515 (-4.35) 0.0336 (7.16)  0.4991 (1.38) 0.0171 (0.30) -0.1257 (-1.93) -4.9951 (-5.07) 0.0316 (6.82)  0.4490 (1.20) 0.0621 (1.08) -0.1313 (-2.00) -4.9231 (-5.00) 0.0332 (7.11)  1417  1417  1422  1422  0.203  0.182  0.207  0.188  Table IV. 10: The Relation between G I M and the Conflict Variables - O L S Regressions  92  REFERENCES  CITED  1. Aggarwal, Rajesh K . and Dhananjay Nanda 2004, Access, common agency, and board size, working paper, The University of Virginia. 2. 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Zweibel, Jeffrey, 1996, Dynamic capital structure under managerial entrenchment, American Economic Review 86, 1197-1215.  95  CHAPTER V CONCLUSIONS CSR receives a higher priority on corporate agendas in recent years and firms allocate more and more resources to CSR. In this dissertation we analyze potential driving forces behind this corporate behavior focusing on socially responsible investing and potential conflicts between affiliated and unaffiliated shareholders. The second chapter explores the effects of ethical screening on firms' decisions to reform and on their investment levels. These issues are examined in an equilibrium setting with endogenous investment decisions and endogenous future outputs. The effects on total investment are examined in the presence of various levels of reforming costs. The results indicate that in intermediate cases when reforming costs are about 6% of revenue, the economy exhibits its maximum total investment when there are either no socially responsible investors or when there are only socially responsible investors. If one assumes that socially responsible investors account for about  10C12%  of total investors, as estimated to be the  fraction of total managed funds which are subject to SRI strategies, their presence lowers total investment in the economy but is not enough to induce firms to change their technology to a CSR-approved one. The third chapter further explores the role of socially responsible investors in a much richer framework by assuming that some investors gain direct utility from owning firms that practice CSR. We show how this concern impacts investors' risk-sharing opportunities, equilibrium prices and value-maximizing firms' decisions about practicing CSR. The major finding of this chapter is that policy variables, such as tax rates imposed on individuals and corporations and the limit on net income that can be used for C S R spending and qualify for a tax rebate, influence the Social Surplus (defined as total individual donations plus corporate C S R spending less the tax rebates given for such spending) in important ways. First, the social surplus is 96  monotonically decreasing in the tax rebate given to individual donations. Because changing the individual tax rebate rate does not influence corporate C S R spending, raising the rebate rate generates less new individual donations than the additional tax rebates given, causing social surplus to be lower. On the other hand, social surplus is non-monotonic in the corporate tax rebate. That is, there is a social-surplus-maximizing level for the corporate tax rebate rate, for any given set of parameters. Another important parameter that we analyze is the limit on net income that can be used for C S R spending and qualify for a tax rebate (any C S R spending beyond the limit generates no additional tax rebate). We take the rebate limit as given. This limit may exist as a political compromise between groups favoring C S R tax rebates and those that feel such spending is outside the area of corporate responsibility. Alternatively, some may view CSR spending as an agency problem, benefiting management at the expense of shareholders. Whatever the reason for the tax rebate limit, its level influences the social surplus-maximizing level of the corporate tax rebate rate. Raising the tax rebate limit leads to higher optimal tax rebate rates, up to a maximum, past which the optimal tax rebate rate is constant. While socially responsible investing seems to have only a marginal impact on firms' behavior if the proportion of socially responsible investors is about 1 1 % , it appears that the dramatic change in stakeholders' preferences and its effect on profitability is what makes C S R so visible. The optimal level of C S R expenditure with respect to firm value is simply much higher than it used to be only a few years ago and firms are responding to it by spending more and advertising their social records. But is the actual amount that firms spend on C S R optimal? Under the umbrella of C S R there are many corporate activities; among them are employer-employee relations, community involvement, environmental issues, product safety and many more. It is probably impossible both for managers and 97  for shareholders to identify the exact level of CSR expenditure which is consistent with maximizing firm value. The hypothesis of the fourth chapter is that this "grey" area can allow insiders (affiliated shareholders) to over-invest in C S R for their private benefit in cases in which there are looser monitoring mechanisms since C S R spending improves their reputation as being good citizens. We test this hypothesis by investigating the relation between firms' C S R ratings and their ownership and capital structure. We employ a unique data set that categorizes the 3,000 largest US corporations to being either socially responsible or socially irresponsible. We find that insiders' ownership and leverage are negatively related to the social rating of firms, while institutional ownership is uncorrelated with it. These results support the hypothesis that C S R is indeed a source of a conflict between different shareholders. Corporate social responsibility is all about doing good. Therefore, it is probably hard even for the toughest shareholders' representative to object allocating resources to a good cause even in cases in which the contribution to firm value is questionable. For example it is probably much easier for an outside director to oppose allocating golden parachutes for managers than to vote against donations to the tsunami victims in Asia. This can help explaining our empirical finding that in some cases firms deviate from the optimal level of C S R expenditure and simply spend too much on these issues.  98  

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