The effect of age and incentives on CSR-quality

(1)

1

The effect of age and incentives on CSR-quality

Name: Jan Douwe Box Student number: 11123257

Thesis supervisor: Georgios Georgakopoulos Date: 26 June 2017

Word count: 13,955

MSc Accountancy & Control, specialization Control

(2)

2

Statement of Originality

This document is written by student Jan Douwe Box who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

(3)

3

Abstract

This study examines the effect of age and different kinds of incentives on the quality of Corporate Social Responsibility (CSR). More specifically, this study focus on the influence of the average age of the board of directors and the different kind of incentives for the board of directors on the quality of CSR. The influence of both factors is assumed to be equal. The sample is drawn from the S&P 500 over a timeframe that extends from 2008-2013. This sample contains 6837 observations over 1624 unique companies. The results show that a higher average age of the board of directors has a little negative influence on the CSR-Score. Then the results show that short-term incentives have a negative influence on the CSR-Score. The combination of short- and long-term have a positive influence on the Score. There is no combined effect of age and different kinds of incentives towards the CSR-Score, this is excluded by the multicollinearity test. The results of this study are gathered through mostly multiple linear regression an independent sample t-test. Bottom-line, age is not significantly influencing the CSR, whereas incentives do. This study contributes to research on CSR, short-term incentives, long-term incentives, and age.

Keywords: Corporate Social Responsibility, age, short-term incentives, long-term incentives, Board of

(4)

4

Acknowledgement

I would like to express my special thanks to my supervisor Georgios Georgakopolous, who provide me excellent and understandable feedback in a fast way. During the process of this study, he helped me to structure the core elements of this study and write a thesis on this level. My supervisor was easily accessible and approachable, which benefits the communication and the quality of my thesis.

(5)

5

1 Introduction

How valuable are the age of directors and different incentives on a board of directors on the subject of CSR? This research will contribute to prior literature because this study will investigate the discussion about the influence of different variables (age and incentives) on CRS. Specifically, I investigate the relationship between the age of directors on a board and the use of different incentives for the board of directors on the quality of CSR.

Corporate Social Responsibility has developed throughout the last few decades, with a great majority of firms in Europe and the USA finding sustainability important for their future. There has been done research regarding the quality of CSR. These research were done to measure the quality of CSR influenced by, for example: gender (variation in the board of male and female), high/low education members of the board, stakeholder pressure, small, medium and large organizations, different kind of industries and different performance measures rewarding (Giddings et al.,2002; Post et al.,2011).This makes clear that the literature has dealt with the effect of different compositions of the board of directors related to the quality of CSR.

The study of Fernandez-Feijoo, Romero, and Ruiz-Blanco (2014) examine the relationship between sustainability reporting and the existence of at least three women on the board of directors. Their results show that in countries with a higher proportion of boards of directors with at least three women, the quality of CSR is higher. This shows that the gender has an influence on the quality of CSR and this makes it interesting to examine whether other differences in the composition of the board has an influence on the quality of CSR.

The aim of the paper of Perrini, Russo, and Tencati (2007) is to make a comparison of SME and large firm CSR strategies. Furthermore, the size of the firm is analyzed and determined as a factor that influences specific choices related to CSR. The analysis of Perrini et al. (2007) provides evidence that large firms are more likely to identify relevant stakeholders and meet their requirement trough specific and formal CSR strategies.

It’s commonly known that larger firms adopt CSR principles more often than SMEs (Ullman, 1985). Ullman (1985) also implies just like Perrini et al. (2007) that large firms have to deal with greater interest of their stakeholders. This entails a certain amount of pressure for the board of directors to continue to perform in the long run because the stakeholders are the firm and they act in best interest of the firm.

These above papers are examples of how the quality of CSR is being influenced. These research made me curious about the influence of the average age and different kind of incentives for

(8)

8

directors on a board regarding the quality of CSR. On forehand, I do have a suspicion or age and differences in incentives will influence the quality of CSR. This suspicion is based on the papers of Perrini et al. (2007); Gallén and Peraita 2017); Fernandez-Feijoo et al. (2014); Post et al. (2011); Dechow and Sloan (1991); McGuire et al. (2003); Deckop et al. (2006). This will be obvious in the created hypotheses. This leads to the following research question: what is the effect of age and incentives on the quality of CSR?

This research extends the existing literature on CSR by looking at differences caused by differences in age of directors on a board and different kinds of incentives. This research is important, because of the rising importance of the term CSR and what are possible factors that influence the quality of CSR. The motivation for this study is strengthened because of the call for further research by i.e. Perrini et al. (2007). They think there is much more research needed related to CSR and the differences among companies that can influence the quality of CSR. This further research will improve the knowledge of this important issue. The paper of Fernandez-Feijoo et al. (2014) also implicates that there is need for further research because they want to include more countries.

This study is structured as follow. The next part is the literature review, which elucidates the underlying theory and literature. The third chapter is about how the data is compiled and reduced. In the same chapter as the data, the methodology that is used to test the data has been displayed. The results are reported in the fourth chapter. The conclusion and discussion are demonstrated in the fifth chapter. References and the appendix are located in respectively chapter six and seven.

(9)

9

2 Theory and literature review

In the literature review, I will discuss and introduce the most important subjects in this thesis geared in order to develop the hypotheses. The most important subjects are Corporate social responsibility, the age of the board of directors and incentives. The most important theories in connection with this subjects are ethical stewardship theory and stakeholder theory. After collecting all the relevant information, the hypotheses will be formulated.

2.1 Corporation Social Responsibility

In this section of the literature review, the subject Corporate Social Responsibility (CSR) will be defined in detail, explanation why organizations use CSR and what effect CSR has on the performance of an organization.

2.1.2 Elucidation of Corporate Social Responsibility In the beginning of 2003, McAdams and Leonard introduced a good definition of CSR, namely: “that

CSR policy works as a self-regulatory mechanism whereby a business monitors and ensures its active compliance with the law, ethical standards, and social norms”. CSR refers to many subjects like sustainable development, environmental protection, social equity and this all in combination with economic growth. During the 1990s until now CSR is an emergent discourse within organizational research and praxis, because of the rising importance. Some organizations consider CSR to be a peripheral and sector specific issue, but it is becoming mainstream, and not maintained but supported by legislation. CSR’s purpose is to embrace responsibility for corporate actions and to encourage a positive impact on the environment and stakeholders. Stakeholders include all interested parties like i.e. consumers, employees, investors, communities, and others (McAdams & Leonard, 2003).

Shauki (2011) elaborate CSR almost the same as McAdams & Leonard (2003), but then in slightly different words, namely: “ to fulfil CSR, an organization considers the interests of society by taking responsibility for the impact of their operational activities on customers, suppliers, employees, shareholders, communities, and other stakeholders, including social and environmental (S&E) advocates, and regulators”. I will make the assumption for this study that the purpose and meaning of CSR will not change in the near future because it did not change for the last decade. Nowadays, it is

(10)

10

not only important to make profit, but organizations are facing increasing pressure to behave in socially responsible ways” (Shauki, 2011).

The researchers are defining CSR in a slightly different way (McAdams and Leonard, 2003; Shauki, 2011), but they all do share the same opinion that CSR is a voluntary activity that an organization is doing for the society as a whole and for their stakeholders and employees.

2.1.3 Reasoning for using CSR

A sustainable way of thinking by organizations and thus manage business social responsibility can make the world a better place. CSR is an opportunity for companies to benefit multiple players, like the organization itself and all their stakeholders, i.e. their suppliers and the society as a whole.1_There

are a couple reasons for using CSR in order to create benefits:

 Innovation: An example of innovation related to CSR is that Unilever was able to develop a new product with using less water. Without caring about sustainability, Unilever would never develop an advanced product like this.

 Cost savings: Embrace Sustainability is a manner to reduce costs i.e. using less plastic, less energy, less water or more efficient use of packaging materials. Comment is that environmentally friendly packaging instead of plastic often is more expensive for the company, so sustainability could also increase instead of saving cost.

 Brand differentiation: If a company can add their one values (sustainability) into their business model and into their products, the products are one of a kind and therefore unique. This is related to the Innovation process.

 Long-term thinking: CSR is a tool that served the interest of the company for the long-term future.

 Customer/employee engagement: If the company established itself as a leader from an environmental point of view (CSR), it is about doing a good job and this would most likely make it easier to engage with the customer and their employees.1

(11)

11 2.1.4 Effect of using CSR

According to Horrigan (2010): “CSR is one of the greatest global challenges of this century. Our ancestor has bequeathed to us ways of conceiving, running and regulating corporations the core elements of which are tested more in 21st_{-century conditions than ever before. They need revisiting}

and even recasting for the sake of our generation, descendants, and the planet's future". The book of Horrigan has focused mainly on governmental, legal and business frameworks for CSR, to bring corporate responsibility into the 21st_{-century business environment.}

With the findings of Horrigan (2010), I can determine the importance of CSR at this current moment. The question that is rising: is acting CSR an advantage or a disadvantage for an organization? Table 1 provides an overview of advantages and disadvantages of using CSR:

Table 1. Advantages and disadvantages CSR

Advantages CSR Disadvantages CSR

Good image of the organization Focus shift from profit making to global welfare Easier recruiting and retain employees Cost production increase

Authorities become less antagonistic Possible negative perception of shareholders

Good publicity CSR is valued differently all over the world. So for large companies, it is hard to maintain a high quality of CSR.

Horrigan (2010)

This advantages and disadvantages indicate that CSR is not only creating value for a company, but there are also downsides. It is up to the companies to weigh this against each other.

2.2 Corporate Social Performance

Deckop, Merriman, and Gupta (2006) noticed that Corporate social performance (CSP) is increasingly viewed as an important business outcome by researchers, investors, and society as a whole. Deckop et al. (2006) introduced the CSP definition in this way: “the social responsibility of business encompasses the economic, legal, ethical, and discretionary expectations that society has of organizations at a given point in time”. This definition shows that CSP is more a less similar to CSR.

The ideal combination of an organization's objectives is to be both profitable and socially responsible. Important to know for this research is that there is increasing pressure by i.e. the United Nations for organizations to embrace acting social responsibility. This is because of the emerging standards related to social performance. Furthermore, empirical researcher Orlitzky, Schmidt, &

(12)

12

Rynes (2003) claim that overall seen CSP is positively related to corporate financial performance (CFP). This means that when your CSP is improving/increasing, the CFP is also increased, and of course the other way around with a negative development. This gives reasoning for organizations to improve their policy towards CSR, because of the rising importance of acting socially responsible.

2.3 Ethical Stewardship theory

Next to all the definitions of CSR, Caldwell, Hayes, Bernal et al. (2007) talked about ethical stewardship. According to them, ethical stewardship is in line with CSR, because they define it in a similar way: ”ethical stewardship as the honoring of duties owed to employees, stakeholders, and society in the pursuit of long-term wealth creation”.

The ethical stewardship theory helps explain why the board of directors will choose a set of activities in the interest of the organizations to align with CSR. Based on the previous paragraphs and the paper of Caldwell et al. (2007) I can infer that ethical stewardship and CSR has the same main objectives, namely: pursuit of long-term wealth creation and to embrace responsibility for corporate actions and to encourage a positive impact on the environment and stakeholders to include all interested parties. Thus ethical stewardship and CSR are more or less the same with comparable objectives.

2.4 Stakeholder theory

The stakeholder theory has emerged as an important part of the business case for CSR by pointing out the importance of adopting a stakeholder view in order to have a better understanding of the performance consequences and therefore the CSR efforts (Perrini et al., 2011, p.62). For a good understanding of the term Stakeholder theory, I will provide two different descriptions:

(1). Freeman’s theory (2010) elaborates that a company’s real success will be achieved when the company is satisfying all its stakeholders and not just those who might profit from its stock.

(2). Jones (1995) describes the stakeholder theory like this: “Strive to what managers actually do with respect to stakeholder relationships, what would happen if managers adhered to stakeholder management principles, and what managers should do vis-a-vis dealing with firm stakeholders” (Jones, 1995, p. 406)

The Stakeholder theory is about the interests of one stakeholder does not overriding/affect the interests of the other stakeholders, but it guarantees that all interested parties will be considered. The

(13)

13

Stakeholder theory will help to understand what impact the quality of CSR has on an organization. The stakeholder theory and CSR have the same main objectives like already mentioned in the previous paragraph about ethical stewardship (Freeman, 2010).

2.5 Performance Measurement Rewarding

The next subject of this study is Performance measurement. This is the process of collecting, analyzing and/or reporting information regarding the performance of an individual, group, organization, system or component and to see whether output is in line with what should have been achieved (Oakland, 2017).

The paper of Dechow and Sloan (1991) introduces a study which examines whether those earnings-based performance measures provide executives with incentives to focus on short-term performance. This is also known as the horizon problem. The results of this paper suggest that executives who are in their final years as CEO spend less on R&D. On the other hand, there is a different way of rewarding employees that mitigate the incentives of executives to reduce R&D expenditures. This different rewarding system is incentives based on stock and options, better known as long-term incentives (LTI). The conclusion that can be drawn from this paper is that the more stock and options executives own in their firm, the less likely it is that executives reduce discretionary R&D expenditures prior to their departure (Dechow et al., 1991, p. 52).

An often heard criticism of incentives based on the short-term is that they encourage management to focus on short-term performance rather than long-term value creation. This criticism has been made by all kinds of professionals, like business journalists, consultants, research and development directors, top executives and also by academics (Dechow et al., 1991, p.52). This means there is doubt whether short-term incentives create value for the organizations on the long-term. This is interesting to investigate in relation with CSR because CSR is focused on the long-term value creation.

On the other hand, there are stock-priced-based incentives that encourage management to focus on the long-term value creation. Dechow and Sloan (1991) find for example that the more stock and options executives own, the less likely they are going to reduce R&D expenditure prior to their departure. Expenditure in R&D shows that the firm is willing to invest in future possibilities and sustainability to create long-term value and in this way increasing the CSR quality.

(14)

14

McGuire, Dow, and Argheyd (2003) have done research to the relationship between CEO incentives and the quality of corporate social performance. The study of McGuire et al. (2003) is built based on two different kinds of research.

First of all the authors draw the conclusion that compensation is an important incentive through which the board of directors could achieve objectives for both financial and social purposes. Financial incentives may provide the commitment of the organization's towards social performance and may improve corporate social policies. Secondly, McGuire et al. (2003) examine the quality of social performance (both weak, or poor). They are looking for de difference between poor social performance: socially dubious or risky behavior, and strong social performance: willingness to exceed expectations for social performance (McGuire et al, 2003, pp. 341-343). Strong social performance approximately the same as CSR.

Based on the gathered data and statistical analysis the findings of McGuire et al. (2003) claim that incentives have no significant relationship with strong social performance. On the other hand salary and long-term incentives have a positive relationship with weak social performance (McGuire et al, 2003, pp. 341-349). The conclusion of this research is that these findings are congruent with arguments that high levels of executive compensation are indicative of a less socially responsible orientation. (McGuire et al, 2003, pp. 341-352).

According to Deckop, Merriman, and Gupta (2006) the importance of Corporate Social Performance grows and this leads to the next question: do pay packages that contain financial incentives (i.e. annual- or stock-based) for CEOs, lead to an improvement of the firm’s CSP, and if so, how? The conclusion based on this gathered data is that a short-term CEO pay focus (annual-based) was negatively related to CSP, whereas a long-term focus (stock-(annual-based) was positively related to CSP (Deckop et al., 2006, pp. 329-337). This conclusion of Deckop et al. (2006) demonstrates the importance of the manner an organization provides incentives for the board of directors.

The findings of Dechow and Sloan (1991); Deckop et al. (2006) are contrary to findings of McGuire et al. (2003) and therefore an interesting development for this research. This study will examine whether different kinds of incentives influence the quality of CSR. The performance measurement plan is divided into two kinds of rewarding, namely (1) short-term incentives, like annual bonuses, and (2) long-term incentives, like stock or options. The methodology part of this study introduces a more detailed elucidation over short- and long-term incentives and how it is used during the statistical analysis.

(15)

15 2.6 Effect of composition of the board directors

In this part of the literature review, I will show what occurs in previous research that investigates the effect of composition of the board directors on CSR related objectives/subjects, like i.e. Social Responsible Investing (SRI).

First of all the next question raises: Does composition of the board directors has significant influence on CSR related subjects? The meaning of composition of the board of directors varies from differences in average age, size, gender, to proportion of outside board members. This research will especially focus on the variable age of the board directors and different kinds of incentives. I will use previous research about CSR related subjects in combination with the effect of the composition of board directors to demonstrate the gap in the literature (i.e. Fernandez-Feijoo et al., 2014; Gallén and Peraita, 2017; Perrini et al., 2007; Post et al., 2011). In this way, I want to indicate there is reasoning to think that the age of board directors and different kinds of incentives has an effect on the quality of CSR.

The study of Fernandez-Feijoo et al. (2014) explores the relationship between sustainability reporting and the existence of at least three women on the board of directors. This research shows the effect of the composition of the board of directors on CSR business policies. The results of Fernandez-Feijoo (2014) shows that in countries with a higher attendance of women on the board of directors (at least three women), the quality of CSR is higher. Thereafter this researcher also ﬁnd that countries with a higher gender similarity have more organizations with at least three women on the boards of directors.

Their findings contribute to the literature by studying the relationship between board gender composition and CSR reporting. Thus, this paper extends the existing literature on CSR by looking at differences in reporting produced by including women on the board of directors. This demonstrates that composition of the board matters regarding the quality of CSR, but still it is vague the extent to which different kind of composition of the board influence the CSR-quality (Fernandez-Feijoo et al., 2014, p.351).

Gallén and Peraita (2017) noticed that other researcher on the quality of CSR and stakeholder engagement focused solely on the internal aspects of the organizations, and not taking into account external factors as culture, industry, regulation and economic context of the country where it is operating. The study of Gallén and Peraita (2017) examine: “the influence of femininity in the disclosure of sustainability information based on the Global Reporting Initiative (GRI) guidelines”.

(16)

16

The main conclusion from this study is that countries with higher percentage of femininity provide a higher quantity of sustainability reports, but do not provide higher quality sustainability reports (Gallén and Peraita, 2017, p. 1). This is a contrary conclusion relative to the study of Feijoo et al. (2014) and that seems to be strange because both are about gender differences and the influence on CSR-quality.

A remark is that both studies are in a different setting, namely, the first one is at least three woman on the board of directors and the second is searching for the influence of femininity. So this difference in result can be explained by the different approach in researching and analyzing. They used the same variable (gender woman), but in different circumstances (woman on the board vs. proportion of femininity in a country) regarding CSR quality.

Perrini, Russo, and Tencati (2007) introduces CSR as becoming a mainstream issue for many organizations. Most of the studies of this moment address CSR in large businesses rather than in small- and medium-sized organizations, because it is too often considered a privilege only for large businesses. The study of Perrini et al. (2007) introduces the differences in strategy regarding CSR of SME (small- and medium enterprises) in comparison to large organizations strategies. This study provides evidence that large firms are more likely to identify relevant stakeholders and meet their requirements through specific and formal CSR strategies (Perrini et al. 2007). So generally seen large organizations has a better CSR strategy to satisfy their stakeholders than SME.

Post, Rahman, and Rubow (2011) did research that examines the relationship between the composition of the board of directors and environmental corporate social responsibility (ECSR). ESCR is comparable to CSR because these two terms have the same main objectives and the quality is determined based on similar indicators (see Chapter methodology). Post et al. (2011) find that a higher proportion of outside board directors is related to a higher level of ECSR and higher KLD strengths score.

Next, to that conclusion of Post et al. (2011) they came to the conclusion that organizations with boards composed of three or more female directors receive higher KLD strengths scores. The third and fourth conclusion in this study is that boards whose directors average is closer to 56 years of ageand those with a higher proportion of Western European directors are more likely to implement environmental governance structures. This implicates that they had a higher KLD strength score. The results of Post et al. (2011) evaluates multiple facets related to the composition of the board, namely proportion of outside board directors, age, gender and proportion of Western European directors on

(17)

17

the board of directors. This paper demonstrates how important the composition of the board is related to the quality of CSR.

Like mentioned in this paragraph, at least three woman on the board of directors, size, age, % outside directors, origin executives influence the quality of CSR This also indicates that composition of the board matters regarding the quality of CSR and related subjects.

2.7 The variables and hypotheses development

The three main variables used in this research are the quality of CSR, the age of directors on a board and the different variety of incentives. The quality of CSR is the dependent variable. The definition of CSR has already been described in previous parts of this study. In this research, I will investigate whether the average age of directors on a board and different incentives have influence on the quality of CSR. The quality of CSR is based on the KLD-Index and can be interpreted as how sustainable the board of directors is working with their resources and with their internal and external environment.

The age of directors on a board is used as independent variable for this study. With the variable age, I am going to investigate whether a higher or lower age of the directors on the board influence the quality of CSR. This variable is divided into different groups: age between 40-50, age between 50-60 and age between 60-70. The focus in this research will be in the group with the age between 50-60 and mostly on the group with an average age between 60-70, because this is the most interesting group to examine (Dechow and Sloan, 1991). The paper of Dechow and Sloan (1991) support this assumption that the group with the age between 60-70 is the most interesting because they investigate the hypothesis that CEOs in their final years of their working period decrease the discretionary investment expenditures to improve their achievements towards short-term incentives, like annual bonuses. The results of the study of Dechow and Sloan (1991) suggest that CEOs spend less on R&D during their final years in office. This given, it is reasonable to think that the behavior of directors of the board negatively change when they get older (Dechow and Sloan, 1991, p.51).

Therefore it is interesting to do a comparable research in the field of the quality of CSR and average age of the board of directors. This study will outline whether varying average age of the board and different incentives of and for directors demonstrates differences in behavior towards the term CSR. Next, to that in the first part of the literature review, prior research demonstrates that the composition of the board of directors has varied influence on the quality of CSR (Perrini et al., 2007; Gallén and Peraita, 2017; Fernandez-Feijoo et al. 2014; Post et al.,2011). These studies show divergent

(18)

18

results, which makes it interesting to investigate whether age influences the quality of CSR. With this previous studies in mind, the following hypotheses are developed:

H1: A higher average age of directors on a board has a negative relationship with the quality of CSR H1a: A lower average age of directors on a board has a positive relationship with the quality of CSR This hypothesis claimed that if the board of directors has a higher average age, the quality of CSR will decline. In the methodology part, the methods will demonstrate how this hypothesis is tested and elaborated in more detail.

The influence of average age is hypothesized above and the influence of different performance management rewarding will also be examined. This is because of the indicated influence on CSR (Dechow and Sloan, 1991) and therefore it is important for this study. Therefore we will determine the effect of Performance measurement rewarding (PMR) and this variable is also used as independent variable. This study will assess two different manners of using PMR and their influence on the quality of CSR: (1) short-term incentives and (2) and a combination of short- and long-term incentives. The influence of PMR toward CSR-quality will be determined solely and in combination with de variable age. First, the influence of only PMR will be assessed and this lead to the development of the next hypotheses:

H2: Short-term incentives have a negative relation with CSR-Quality

H2a: Combination of Short-term and Long-term incentives has a positive relationship with CSR-quality These two hypotheses are testing the relationship between different manners of PMR policies and the quality of CSR. Different methods of PMR affects the business policy regarding CSR (Dechow & Sloan 1991; McGuire et al. 2003; Deckop et al. 2006). Consistent with these findings, I predict that there will be a negative relation between board directors measured which are based on short-term incentives and the quality of CSR. The relation between the combination of both and CSR quality will be exactly the other way around, namely positive.

Finally, I will test whether the combination of average age of the board of directors and policy regarding different manners of PMR has a positive or negative relationship with the quality of CSR. I will formulate a prediction, namely: there will be a positive relation between board directors with a lower age * long-term performance incentives and the CSR quality. Based on this prediction I developed the final hypothesis that will be answered in this study.

H3: The combination of low average age and long-term incentives has a positive relationship with the quality of CSR These five hypotheses are formulated based on prior research in combination with my predictions.

(19)

19

In the next chapter, I will subscribe the methodology used in this study. This methodology is needed to answer the research question and the developed hypotheses. Next to that, I introduce a regression model to examine if the mentioned hypotheses are true or false. Furthermore, I will explain which sample is used and in which timeframe. Table 2 provides an overview of the key papers used in this study.

Table 2. Summary table key papers

Author Publicatio

n

Topic examined Sample _years Sample _Country Caldwell, Hayes,

Bernal & Bus 2008 Ethical Stewardship *** U.S.A.

Dechow, P., and R.

Sloan 1991 Executive incentives and the horizon problem 1974 - 1988 U.S.A. Deckop, Merriman &

Gupta 2006

The effects of CEO pay structure on

CSP 2001 U.S.A.

Fernandez-Feijoo,

Romero & Ruiz 2014 Women on Boards 2008 22 Countries

Hill, Ainnscough,

Shank & Manullang 2007 CSR and SRI

1995 - 2005

U.S.A., Europe, Asia Kang 2015 Effectiveness of KLD Social Ratings 1996 - ₂₀₀₈ U.S.A. Leonard and McAdam 2003 Corporate Social Responsibility *** U.S.A. McGuire, Dow, &

Argheyd 2003 CEO incentives and corporate social performance. 1999-2000 U.S.A. María L. Gallén,

Carlos Peraita, 2017 Femininity and Sustainability Reporting 2007- 2012 30 Countries Orlitzky, Schmidt &

Rynes 2003 Corporate social and financial performance *** *** Perrini, Russo &

Tencati 2007 CSR strategies of SMEs and large ﬁrms 2000-2003 Italy Post, Rahman &

Rubow 2011 Composition and Environmental CSR 2011 U.S.A. RiskMetrics group 2010 How to use the KLD-Stats *** U.S.A. Shauki 2011 Corporate social responsibility 2011 Indonesia

(20)

20

3 Data & Research Methodology

In the third chapter, the research method that has been used in this study to answer my research question will be elucidated. This means that I explain the choices I made during the processes, collecting data, measurement of variables, elaboration control variables. Next to that, the model that is used for judging the influence of AVERA and PMR on the QCSR will be introduced. Finally, this chapter will show the regression model that has been used to regress the dependent variable QCSR with the independent variables AVERA, PMR, and AVERA* PMR. The control variables SensitIndus, Regulation, BoardS, and Gen will be showed and explained in more detail.

3.1 Sample size & Timeframe

The data for this research are collected through multiple databases within the umbrella of the Wharton Research Data Services (WRDS) database. For this study different data is needed. Data about the quality of CSR is obtained through the KLD dataset. The data about the age of board directors is acquired from the ISS database. The ISS database contains information on the nature of directors on US boards. Furthermore this research contains data about performance measurement, and this data is collected through the Compustat Executive Compensation – Annual Compensation database.

The sample that is used for this study consist all firms listed in the Standard & Poor 500 Index (S&P 500). The companies that are listed in the S&P 500, are selected by a group of analyst, economics, and the S&P Index Committee. Initially this research had the purpose of a timeframe of eleven years (2005-2015), but the lack of data from multiple variables (age & CSR) shortened this horizon to six years. The final timeframe for the sample of this study extends from 2008 to 2013. This period is chosen because of the absence of ratings after 2013 for the quality of CSR and the absence of information about the age of the board of directors over the years 2005-2007. Down here I will elucidate in more detail how the reduction of data occurred.

At the start of this study, the dataset contains 111,509 age of directors observations. After calculating the average age per year per board of directors the remained observations was 31,935. The average year is calculated annually per company and this means that the average age per company is changing every year. This step also shows that there was a lack of information about the age of board directors for the years 2005-2007 and therefore this year are eliminated from this study, and thus a reason for the reduction of observations.

(21)

21

The second step was merging, the quality of CSR with the average age of a board of directors in one database. This action reduced the amount of observation from 31,935 to 10,833. This reduction occurs, because of the fact that firms didn't make use of the CSR-rating. This 10,833 observation were spread out over a timeframe of eight years (2008-2015). The KLD-database gives no valid ratings about the CSR-score over the years 2014 and 2015. With reducing the number of years, because of the lack of information, the number of observations declined to 7,956.

The next reduction is accomplished by merging the variable PMR with the variables average age of directors and quality of CSR over the timeframe of six years. This reduced the 7,956 observations with 1,086 (no available data), so that remains an amount of 6,870 observations. The final reduction occurs with labeling all the companies to their industry group, based on their SIC-code. Because of the lack of information about a view firms, the data reduced with 33 observations. The final sample for this study contains 6,837 observations over a timeframe of six years. These 6,837 observations are based on 1624 unique firms. The Control variables Gender and Board size did not reduce the number of observations, because all information needed, was available. The meaning of outliers in this study is also tested. The test with excluding outliers was not changing the results. This indicates that all observation are part of the results and gives the best validity and reliability for answering the hypotheses. Table 3 provides a summary of the sample determination

Table 3. Sample determination

Observation age of board directors 111,509

Calculation average age of board directors per company per year + no available data

trough year 2005-2007 (79,574)

Companies do not participate in CSR-score rating provided by the KLD-database (21,102)

No available data CSR-score 2014-2015 (2,877)

Companies with no available data about PMR (1,086)

Labeling all firms to their industry (33)

Final sample observation 6,837

Number of unique firms in the sample 1624

3.2 Data variable CSR-Score

For the determination of the CSR-quality, the KLD-Index is used. KLD-Index is a tool for statically analyzing trends in social and environmental performance and it helps organizations to evaluate their

(22)

22

ethical commitments. The KLD Index examines the social performance of approximately 4,000 firms (Hartman and Sharman, 2015). The rating of the KLD Scores are based on 5 key Environmental, Social and Governance (ESG) factors (Lauren Turner, 2013)2_:

1. Environment

2. Community & Society 3. Employees & Supply Chain 4. Customers

5. Governance & Ethics

The Scores of the KLD rating are only awarded to organizations with demonstrable commitment to social and environmental issues, and organizations who carry out socially responsible investing.2_Social

Responsible Investing (SRI) is defined as: "investments enabling investors to combine financial objectives with their social values” (Munoz-Torres et al., 2004, p. 200). These investors seem to be younger, higher educated, and more concerned about environment and labor relations than their less socially conscious counterparts. Bottom line, the objectives of Social Responsible investors is to receive a fair return while simultaneously accomplish CSR goals (Hill et al.,2007, p.167). This means that SRI is part of acting CSR.

Organizations whose business operations are negative or unethical (i.e. no SRI) are excluded from getting scored by the KLD rating. Organizations who are excluded are for example

organizations who work in areas such as alcohol, tobacco, military weapons gambling and nuclear weapons (RiskMetrics Group, 2010). These organizations are therefore out of the scope of this study.

The KLD expanded the coverage to the largest 3000 US companies and like already mentioned in the beginning of this paragraph the coverage is already more expanded to 4,000 companies (Hartman and Sharman, 2015). Table 4 provides an overview of data about which organizations are awarded by KLD-Index.

2_{Http://nbs.net/knowledge/kld-scores/}

(23)

23

Table 4. Organizations awarded by the KLD-Index

Coverage Universe 1991-2000 2001 2002 2003-Present

S&P 500 Index X X X X

Domini 400 Social Index X X X X

1000 Largest US Companies X X X

Large Cap Social Index X X

2000 Small Cap US Companies X

Broad Market Social Index X

Total Number of Companies 650 1100 1100 3100

RiskMetrics Group (2010)

The study of Kang (2015) show that the KLD ratings effectively measure (past) and predict (future) social performance in both categories. The results also suggest that the KLD ratings may identify differences in the quality of management and firm which can affect future social performance and is not entirely explained by past social performance. This result provides support for empirical studies relying on the KLD-ratings to determine the quality of CSR.

Hart and Sharman (2015) support the findings of Kang (2015) because he draws the conclusion that the new version KLD shows strong concurrent validity with the original KLD data set, thus there is concurrent validity of the KLD with previously validated measures (Hart & Sharfman, 2015, pp. 575-579). Thus, the main conclusion of Kang (2015); Hart and Sharman (2015) is that the KLD dataset is a valid index to value the quality of CSR.

During this study, the KLD-Index will be used as a measure for CSR. The data will be gathered through US organizations who are evaluated by the KLD-Index and these organizations will be ranked based on the ratings given by the Index. The KLD-Index evaluates (1) Corporate Social Performance (CSP), (2) Social Responsible Investing and (3) Environmental, Social and Governance based measures. In my opinion these three subjects are covering all the components of CSR, that is used as the dependent variable in this thesis. Based on this three components in combination with the evaluation of the KLD-Index, the quality of CSR can be determined

This part will show in more detail how the quality of CSR is determined based on multiple indicators and their Strengths (+) and Concerns (-). Table 5 provides an overview of the seven main indicators/categories which compose the CSR-Score (Community, Corporate Governance, Diversity, Employment Relations, Environment, Human Rights and Product). These indicators are divided over multiple strengths and concerns. At this moment the KLD dataset looks at the strengths and concerns of every category. The coding is being simplified to give the number 1 or 0. The presence of a strength

(24)

24

or concern is indicated with (=1) and the absence of a strength or concern is indicated with (=0). Easier said I will add up the positive items (strengths) and subtract the negative items (concerns) to calculate an overall CSR-score per organization (Post et al., 2011).

Table 5 gives an overview of a binary summary of positive and negative ratings of all the seven indicators to determine the quality of CSR. These indicators are obtained through the RiskMetric Group. For this study, all the possible indicators are used to create a valid and reliable research regarding the quality of CSR

Table 5. Indicators for determining CSR-Score

Indicator Strength (+) Concerns (-)

Community Charitable Giving, Innovative Giving, Non-US charitable giving, Support for Housing, Support for education, Indigenous peoples relations and volunteer programs

Investment Controversies, Negative economic impact, Indigenous people Relations and Tax disputes

Corporate

Governance Limited compensation, Ownership strength, Transparency strength and Political accountability strength

High Compensation, Ownership concern, Accounting concern, Transparency concern and Political Accountability Concern

Diversity CEO, Promotion, Board of Directors, Work/life benefits, Woman & Minority Contracting, Employment of the disabled and Gay & Lesbian policies

Controversies and

Non-representation

Employee

Relations Union relations, No-layoff policy, Cash profit sharing, Employee involvement, Retirement benefit strength and Health and Safety strength

Union Relations, Health and safety concern, Workforce reduction and Retirement benefit concern

Environment Beneficial products and services, Pollution Prevention, Recycling, Clean Energy, Communications, Property plant and equipment and management systems

Hazardous waste, Regulatory problems, Ozone depleting chemicals, Substantial emissions, Agricultural Chemicals and Climate change

Human

rights Positive record in South Africa, Indigenous peoples relations strength and labor rights strength

South Africa, Northern Ireland, Burma concern, Mexico, Labor rights concern and Indigenous peoples relations concern

Products Quality, R&D/innovation, and benefits to

economically disadvantaged. Product contracting concern, and Antitrust safety, Marketing/

(25)

25

In this study, in order to measure the quality of CSR, I use the KLD data for the companies in the S&P 500. For the measurement, I convert the KLD scores calculated as mentioned above to scale, with zero as a base. Every score higher than zero shows that the CSR strengths about the company are more than its CSR concerns. A score lower than zero shows that the CSR concerns about the company are more than its CSR strengths (Waddock and Graves, 1997).

3.3 Data variable age of the board directors

The data about the age of the directors on the board is collected through the ISS database on WRDS. The ISS database contains information on the nature of directors on US boards. This research is focusing only on average age of the directors of US boards because US organization are mandatory to publish the characteristics of the board of directors. This given, it is possible to gather the data needed for this research. The objective is to use as many observations as possible within the scope of the S&P 500. After collecting all the data about the age of members of the board of directors the average age of every board of directors is calculated per year. The average age of every board will be associated with the CSR-score, in order to determine what the effect is.

3.4 Data variable Performance Measurement Rewarding (PMR)

This study contains data about PMR, and this data is collected through the Compustat Executive Compensation – Annual Compensation database. Another name for PMR is an employee compensation system.3_{This system is made to provide competitive wage and to reward employees for}

achieving their objectives that create value for the company. Part of that compensation system are annually changing salaries and bonuses, this means the encouragement of employees to behave in order to create valuable results for the company within a year. For the best interest of the company, the board of directors needs to make long-term objectives in combination with a suitable strategy. Therefore most of all the companies make compensation plans that reward executives for the results over multiple years (i.e. 5 years).3

The compensation plan can be divided into two different parts: (1) salary and bonuses (the annual process) and (2) Long-Term Incentives.3_{The first of the compensation plan is about the fact}

that companies adjust salaries and bonuses annually. This process repeats itself every year and

(26)

26

determines every year a new set of performance measures related to the salary and bonuses This part is divided into two parts, namely:

 Salary: the compensation for an employee because of performing daily duties and taking responsibilities for their job.

 Bonus: achieving objectives or accomplish task outside task package. Bonus are optional for the employer to pay because the employer is unsure whether an employee will achieve these objectives (there is risk involved).4

The second part is about the long-term incentives (LTI) and this decisions and actions have no effect on the current year activities, but there might be a positive effect on the future performances of the company.4_{The LTI plan immediately demonstrates the negative part of the annual bonus plan,}

because that plan is not focusing on making good decisions in order to create long-term value because this could negatively affect their current year bonus. This is the most important reason that most of the companies are including an executive compensation plan for the long-term. This LTI plan encourages executives to behave in best interest of the company for the future years (Narayanan, 1985).

Long-term incentives are paid with stock or equity of the company instead of cash. This increasing executive's ownership of the company will be in favor of the company because the executives also benefit long-term growth and this will be more important than short-term gains. There is one more benefit of the LTI plan and that is that it contains the function of a retention tool, because these rewards are paid in the future and if an employee leaves early there is a possibility of missing the long-term incentive. With all these reasons in mind, it's likely to assume that the LTI plan increase the CSR-score.4

According to Park and Sturman (2016): “ the pay plan (short-term) is usually based on an individual’s performance assessed by an employee performance appraisal”. They give the following definition for short-term incentives: “bonus pay in the form of cash reward given in addition to the employee’s salary”. The biggest reason for companies to hand out bonuses is to motivate their employees and in this way increasing their efficiency and quality of delivered work (Park and Sturman, 2016, pp. 699-700).

(27)

27

Long-term incentives (LTI) are rewards related to a company's long-term growth and employee retention. These rewards are in general expressed in in the form of stock. These rewards are not immediately valuable for the employee, they must wait until awards are vested before they can be used. Park and Sturman (2016) tell that the value of rewards related to LTI depends on market performance of the company.

There are three important difference between bonuses and LTI, because LTI is an one-time payment, while bonuses are possible multiple payments. Bonuses are immediate payments and LTI is the opposite. LTI's requires a vesting period and are not immediately valuable (i.e. stock awards). The value of stocks is riskier because it can fluctuate with the time and even become worthless. The employee prefers immediately available rewards, thus short-term incentives (Park and Sturman, 2016, pp. 699-702).

This study investigates whether these different styles of compensation affect the CSR-quality. Per company, there will be determined which kind of compensation is used and the companies are divided over two groups (1) uses short-term incentives, (2) a combination of short- and long-term incentives. To divide the companies over the groups the following queries are determined for short-term incentives: Salary and annual bonuses and for long-short-term incentives are the queries stock and options. Based on this queries a distinction is made between companies that use only short-term incentives and a company that is using short- and long-term incentives. Based on the collected data and determined queries I conclude that every company uses short-term incentives because all the companies distracted from the dataset are handing out salary towards their employees. This is the reason for only making the comparison between the effect of short-term incentives relative to a combination of both on the CSR-Score

This fact makes it impossible to find out the different effect of short-term and long-term incentives because every company that is using long-term incentives also is using short-term incentives. To make a comparison between the differences I will instigate which form of PMR is better, related to the CSR-Score (short-term incentives or the combination of both).

3.5 Control variables

In previous parts of this study, the independent variable (Age & PMR) and the dependent variable (CSR-quality) are already mentioned and elaborated explicitly. This paragraph will focus on the control variables used in the regression analysis.

(28)

28

The study of Ullman (1985) said: “ when the pollution control variable is forced into the regression there is a sharp decline in the coefficient and significance of the size variable in the

regression equation. Statistically, this is due to the fact that these two variables are highly correlated”. Based on the study of Ullman (1985) I will add the control variable board size to this regression analysis because the size of the firm affect CSR. It's commonly known that larger firms adopt CSR principles more often than small- and medium firms. This also implies that large firms have to deal with greater interest of their stakeholders (Perrini et al., 2007). This entails a certain amount of pressure for the board of directors to continue to perform in the long run because the stakeholders are the firm and they are forced to act in best interest of the firm. The size of the board in this study is determined by the numbers of members of the board of directors. This is similar to the method of Duchin, Matsusuaka, and Ozbas (2010); Post et al. (2011). This two studies also used the board size as a control variable. To use board size as a control variable, I have to calculate the board size by counting the number of board members per company. The number of directors per board in this study is varying between 3 and 34 in the selected sample. This means that the number of members on the board is the proxy for determining the board size and this does not give a clear view of the overall company size. For company size, there is another proxy, namely all the employees added together. Based on the study of Duchin et al., 2010; Post et al. (2011) I assume that the board size gives a representative view of the size of the company.

Secondly the industry in which the company operates has influence on CSR. This means that industry is the second control variable. The authors Waddock and Graves (1997) used the method which controls differences between industries. This study will contain a slightly different approach towards the distinctions between the classified industries. The original SIC-Code contains four numbers and describes the industry group classification. This study will divide the industry groups based on the first two numbers of the SIC-code because these two numbers indicate the name of the major group. Table 6 represents the distinctions between all industry groups based on

(29)

29

Table 6. Industries

SIC codes Industry

01-09 Agric1ulture. Forestry, Fishing

10-14 Mining

15-17 Construction

20-39 Manufacturing

40-49 Transportation & Public Utilities

50-51 Wholesale Trade

52-59 Retail trade

60-67 Finance, Insurance, & Real Estate

70-89 Services

91-98 Public Administration

99-99 Non-classifiable Establishments

The NC State University5

The variable regulation/enforcement will be not used to control because it is outside the scope of this study because all the companies that are part of this study are located in the U.S. Next to that mostly all firms in the US realize the importance of CSR and therefore they need to embrace it. In my opinion regulation don't even play a role in this, because firms become socially obligatory to behave responsibility to the society and environment. So when companies don't act socially responsible they disadvantage themselves and this means that they don’t need a strict regulation for acting socially responsible. In this study, the assumption is made that regulation/enforcement related to CSR the same is for the whole U.S and that means that there is no control variable added.

With the use of Gender as a control variable, I can determine whether gender difference is playing a role of meaning with regard to the policy towards the CSR-score. Therefore there will be three control variables added to the equations.

3.6 Methodology

To test the hypotheses, I use linear regression as statistical analyses to establish the relationship between the dependent variable (CSR-Score) and the independent variable (age of the board directors and PMR) as presented in the formulation of developed hypotheses.

(30)

30

Table 7 down present all the variables used in this study. The control variables have been processed into the regression equations in the same way as the independent variables. For this research, I am not particularly interested in the control variables, but they are related to the used dependent variable. In the statistic tests, I will use the control variables, because I want to remove their impact from the equation. For this study, a cross-sectional regression is used which is a type of regression analyses wherein the explained and explanatory variables are associated with a point of period in time. Table 7 provides an overview of the independent-, dependent- and control variables/Dummy variables which are part of the equations which examine all developed hypotheses.

Table 7. Variables

Variable Measurement Database

QualityCSR (QCSR) Quality of CSR based on multiple Indexes _{(dependent variable)} KLD

Average Age (AVERA) Average age of Board of Directors ISS/RiskMetrics Short-Term Incentives

(SHORTTI) Annual incentives, like bonuses Compustat

Long-Term Incentives

(LONGTI) Incentives over multiple years, like stock Compustat Long + Short term incentives

(BOTH) Combination of long- and short-term incentives Compustat SensitIndus (SINDUS) Classification industries based on SIC-_{codes (Control variable)} Compustat

BoardSize (BOARDS) Board size by counting the amount of _{board members per company(Control}

variable) ISS/RiskMetrics

Gender (Gen) Difference in policy towards CSR based on _{Gender, (Control variable)} ISS/RiskMetrics

3.7 Hypothesis 1

The hypotheses that are formulated in the previous chapter will be tested and answered with help of equations. These equations help to elaborate how the hypotheses are tested and examined. The first hypothesis will be examined by the multiple linear regression analysis on the independent variable average age and three control variables. The three control variables are industry, board size, and Gender. The equations also contain a random error component, which makes the relationship

(31)

31

stochastic. This equation is to examine whether a high average age is negatively related to the quality of CSR:

I. QCSR= B0 + B1 * AVERA + B2 * SINDUS + B3 * BOARDS + B4 * Gen + εi .

The control variables are included in every model. The Quality of CSR is the dependent variable and is examined through multiple linear regression analysis, based on this empirical equation. Hypothesis 1a is examined based on the same equation.

This second hypothesis will be examined based on two equations. The first equations examine the influence of short-term incentives on the quality of CSR. Short-term incentives are responsible for changes in behavior, but does it create long-term value for the company in a sustainable way.

I. QCSR= B0 + B1 * SHORTTI + B2 * SINDUS+ B3 * BOARDS+ B4 * Gen + εi .

The second equations is examining the influence of a combination of long-term incentives and short-term incentives on the quality of CSR. Based on prior literature, I can assume that a combination of both incentives is in favor of the long-term wealth and therefore in favor of the CSR-Score

II. QCSR= B0 + B1 * BOTH + B2 * SINDUS+B3 * BOARDS + B4 * Gen + εi

This two equations for this two hypotheses are both tested through multiple linear regression and an independent sample t-test. With this test, I can see which group perform better regarding CSR-score.

The equation for Hypothesis three test whether the combination of average age of the board of directors and policy regarding different manners of PMR has a positive or negative relationship with the quality of CSR

II. QCSR= B0 + B1 * AVERA +B2 * LONGTTI + B3 * SINDUS + B4 ** BOARDS+ B5 *

Gen + εi

This equation is tested trough the multiple linear regression and by a multicollinearity test. The multicollinearity test helps to understand the results of the multiple linear regression analysis.

The next chapter will demonstrate the results of this study. The results are based on the data methods explained in this chapter.

(32)

32

4 Results

In this section, I will explain and describe the statistic test this study contain to examine the hypotheses and the research question. A total of 1624 companies remains after missing information and therefore data is eliminated from this study.

4.1 Descriptive statistics

Table 8 Shows the descriptive statistic for this sample used in this study. The amount of observations (6837) is divided over 1.624 unique companies. The mean value of the board size in this study is 9.38. This indicates that the average amount of board members is between 9 and 10 directors. In comparison with the paper of Post et al. (2011), my results show a slightly lower average, because they report an average board size of 9.50. The reasoning for this small difference could be, that their study focused on a timeframe that extends from 1996-2005 and that is earlier than the timeframe of this study. The study of Post et al. (2011) reports an average age of 60.66 vs. an average age of 62.54 in this study. This small difference could be explained trough the different and short timeframe (2006-2007) used by Post et al. (2011) and they used a smaller (89 firms) sample, namely from the Fortune 1000 companies list. They also report an average ESCR-score of -0.24. ESCR is a small subset of the total CSR score used in this study. This study shows an average CSR-score 0.31. The difference between this two averages is because of that ESCR is just a small subset of the total CSR score used in this study. ESCR is only focusing on the Environmental part whereas CSR is rated over seven indicators, mentioned in chapter three.

Table 8. Descriptive statistic

Observations Minimum Maximum Mean Std. Deviation

CSR-score 6837 -11 19 .31 3.234

Age 6837 47.67 78.20 62.54 3.01

Short term incentives 6837 0 1 1.00 .03

Long-term incentives 6837 0 1 .17 .37

Both 6837 0 1 .17 .37

Size 6837 3.00 34.00 9.38 2.35

(33)

33

Table 9 shows the descriptive statistics for the control variable industry. Since the CSR-score were scaled with a base of 0, any score higher than zero means the industry has more CSR strengths than concerns. It is interesting to see that every score is near to the base of zero. This implicit that there are possibilities for improvement in every industry. This study finds similar results with Waddock and Graves (1997) about the industry Mining and Construction because in both studies this is the worst two industries performing related to the CSR-Score. The remark about this comparison is that the CSR-score determination is slightly different and based on another scale. Next to that, the time of research was different so with the rising importance of CSR was expected a higher CSR-score with the years. The sample of this study is also much bigger than the sample of Waddock and Graves (1997).

Table 9. Industry descriptive statistic

SIC codes Industry N Average CSR-Score

01-09 Agriculture. Forestry, Fishing 0

10-14 Mining 323 -0.80

15-17 Construction 106 -1.59

20-39 Manufacturing 2719 0.58

40-49 Transportation & Public Utilities 662 0.44

50-51 Wholesale Trade 226 -0.16

52-59 Retail trade 477 0.18

60-67 Finance, Insurance, & Real Estate 1365 0.41

70-89 Services 947 0.06

91-98 Public Administration 0

99-99 Non-classifiable Establishments 12 1.25

Table 10 shows the averages and differences distracted from the dataset over the years 2008-2013. Interesting is to see that the CSR-score over the years rises. This is in line with the expectations because CSR has developed throughout the last few decades, with great majority of firms in Europe and the USA finding sustainability important for their future. Interesting in combination with the rising

(34)

CSR-34

score is that the Board size also increases and the % men on the board of directors is decreasing. This implicates that a higher Board size is positively related with the CSR-score and that fewer men on the board also is positively related to the CSR-score. These findings are consistent with the findings of Fernandez-Feijoo et al. (2014); Perrini et al. (2007); Post et al. (2011). The effect of the average age of the board of directors on CSR will be determined in the next part with other statistical analysis.

The normality, linearity, and homoscedasticity are checked trough SPSS. All the results which are shown in Appendix 1-4 are indicating that there is a qualitative regression model and there are no problems regarding the distribution.

Table 10. Averages over the years

Year N CSR-Score Average _age Short term Both Size %Gender _Male

2008 1048 -0.56 61.73 1 0.17 9.343 0.888 2009 1090 -0.59 62.06 1 0.17 9.328 0.886 2010 1101 -0.08 62.43 1 0.17 9.312 0.884 2011 ₁₀₉₇ _-0.17 _62.73 ₁ _0.17 _9.362 _0.878 2012 1200 1.48 62.93 1 0.17 9.482 0.869 2013 1301 1.43 63.17 1 0.17 9.440 0.860 4.2 Correlation

Table 11 contains the Pearson correlation matrix for the sample used in this study. With correlation, the strength and direction of a relationship between two variables are displayed. The Pearson correlation matrix is a measure of the linear relationship between two interval/ratio variables. The values in the correlation matrix with two asterisk are significant at the 1% level and the values with one asterisk are significant at the 5% level. The independent variable age is significantly negatively correlated with the dependent variable CSR, which is expected since research shown that age has influence on the behavior of executives and therefore on CSR. This negative correlation means that when the average age increases, the CSR-score decreases. The correlation between the dependent variable CSR and independent variable combination of both incentives is significantly positively correlated. This was also expected because the literature review has shown that a combination of incentives is creating long-term values for a company and therefore act socially responsible. This positive correlation means that when the amount of a combination both incentives increases, the

The effect of age and incentives on CSR-quality