The relationship between
Corporate Social Responsibility
and Financial Performance for
firms in The United States
Name: Tanguy Wagenaar Student Number: 10243690 Date: 15-7-2014
Study: BSc Economics & Finance Supervisor: F. Gomez
Abstract
This research tried to investigate the relationship between corporate social responsibility and financial performance for companies from the United States.
Regression analyses are used to check the relationship. The dependant variables were the return on assets and return on equity. The Dow Jones Sustainability Index North America is used as a measure of CSR. The regressions were used for the years 2010, 2011 and 2012. From the results of these regressions it can be concluded that CSR has no effect on financial performance.
Index:
1: Introduction 2: Literature Review
2.1: Defining Corporate Social Responsibility
2.2 How is Corporate Social Responsibility measured? 2.3: How is Corporate Financial Performance measured? 2.4: The control variables
3: Business benefits of Corporate Social Responsibility 4: Research Method 4.1: Hypothesis 4.2: Data 4.3: Variables 4.4 Regressions 5: Empirical analyses 5.1: Correlations
5.2: The regression analysis 6: Conclusion
Introduction
Corporate social responsibility has become a lot more important over the last few years. There are an increasing number of companies that report their corporate social
responsibility (CSR). Companies try to integrate CSR into the businesses it participates in. The demand by stakeholders, like customers, employees, suppliers, community groups, governments, and some stockholder, to account for the CSR problems is becoming more profound (McWilliams & Siegel, 2001). This is because it is now more obvious that the world needs to change, in order to stay sustainable and survive. Therefore there is also an increasing demand for companies to be transparent and to have good measurements and reports to show how it is accounting for CSR. This will help to see if companies are improving their environmental, social and economic performance.
Corporate social responsibility has a lot of different definitions. One definition of CSR is that it is a duty of every corporate body to protect the interest of the society at large. Even though the main motive of business is to earn profit, corporate should take initiative for welfare of the society and should perform its activities within the
framework of environmental norms (Holme, 2013). “CSR is seen as a comprehensive set of policies, practices, and programs that are integrated into business operations, supply chains, and decision-making processes throughout the company and usually include issues related to business ethics, community investment, environmental concerns, governance, human rights, the marketplace as well as the workplace’’ (Tsoutsoura, 2004). A more extensive review on the definitions of CSR will be given in the literature review.
Companies apply CSR in a different way. It depends on several factors such as the company’s size, the industry the company is in, the demand of the stakeholders, the business culture of the firm and the progressiveness the company is engaging CSR (Tsoutsoura, 2004). For a firm to have a sustainable plan that is successful, the CSR principles should be integrated in the strategic planning and the values of the firm. “Companies should choose which concept and definition is the best option, matching the company’s aims and intentions and aligned with the company’s strategy, as a response to the circumstances in which it operates” (Van Marrewijk, 2003).
Ben and Jerry’s ice cream is a good example of CSR. The company uses only fair trade ingredients, and developed a dairy farm sustainability program in their home state of Vermont. Starbucks is also an example of a company that integrates CSR in their business plan. Starbucks created its C.A.F.E Practices guidelines, which are designed to ensure the company sources sustainably grown and processed coffee by evaluating the economic, social and environmental aspects of coffee production (Business News Daily, 2013)
But why would companies adopt CSR? For companies to adopt CSR there should be either financial benefits or companies do it because they feel moral obligated.
Therefore there is an economic perspective and an ethical perspective.
With regard to the relationship between firms CSR and the economic perspective there have been made several arguments. One view is that companies face a trade-off between CSR and financial performance. Economists who hold this view assume that the costs of CSR outweigh the benefits and therefore give the firm an economic disadvantage (Mcguire, Sundgren, Schneeweis, 1988). Another perception is that CSR entails a zero-sum trade-off when looking at corporate economic interests. A lot of defenders of CSR accept that there could be a zero-sum trade-off, while also embracing the social
obligations of business. The zero-sum perception is highly identified with neo-classical economics. Classical economics however, claimed that CSR could induce short-term costs, but that it would pay off for firms in the long run (Burke & Logsdon, 1996). Classical economics asserted that a better society was better for the long-term profitability. Yet another perspective, that has the same conclusion as the classical economics, is the modern corporate stakeholder theory. This theory states that a company’s value depends not only on the cost of explicit claims but also of implicit claims. Claimants on the resources of a company are not only the stockholders and debtors but also the stakeholders. If a company does not act in a way that is social responsible, parties with implicit contracts will try to make the contracts explicit, which could cost more. If for example a company acts environmentally irresponsible, the government can make stricter regulations for the company, which could be costly. When a company is socially responsible it will thus improve the image with a good CSR, and could therefore have lower costs of contracts. Lower costs of contracts will lead to better financial performances (Cornell & Shapiro, 1987).
In this thesis there will be a more extensive look to the relationship between corporate social responsibility and financial performances. Because of limited available information this research will look at companies from the United States. The research question that is going to be answered is: Does corporate social responsibility leads to better financial performances in North America. To answer this question I will first calculate the correlation between CSR and financial performance. But to know which direction it goes, I will use a regression analysis. The variables used will be the Return on Assets, Return on Equity, some control variables and an index that determines the level of sustainability of the firm. The method and the variables will be more extensive explained later in this thesis.
The remainder of this thesis is structured as follows. The second paragraph will contain a literature review. In the third paragraph a more extensive view on the
business benefits and costs of CSR will be given. In the fourth paragraph, the research method will be explained, and the results of this research will be given in paragraph 5. Paragraph 6 will contain the conclusion of this thesis, and paragraph 7 will be the appendix.
2 Literature Review
2.1 Defining Corporate Social Responsibility
The discussion about what corporate social responsibility exactly contains, is present for already five decades. In this chapter I will go through the evolution of the definition and discussion of Corporate Social Responsibility.
Bowen set the foundation for corporate social responsibility in 1953. His book ‘Social Responsibility of the Businessman’ discussed the social responsibility that businesses had. A citation in this book about the social responsibility of entrepreneurs is; “CSR refers to the obligations of businessman to pursue those policies, to make those decisions, or to follow those lines of action which are desirable in terms of the objectives and values of our society” (Bowen, 1953).
After the 1960s the literature written about CSR increased notably (Carrol, 1999). One of the most important writers in the 1960s was Davis. The definition of CSR given by Davis was; “businessman’s decisions and actions taken for reasons at least partially beyond the firm’s direct economic or technical interest” (Davis, 1960, Boonstoppel, 2011).
In the 70s Friedman defined the most discussed view on CSR. Friedman stated that; “There is one and only one social responsibility of business- to use its resources and engage in activities designed to increase its profits so long as it stays within the rules of the game, which is to say, engage in open and free competition, without deception or fraud” (Friedman, 1970). This definition is nowadays still a definition of CSR that is discussed. There were also other new views about CSR. The Committee for Economic Development (CED) created one important view. They stated: “Business is being asked to assume broader responsibilities to society than ever before and to serve a wider range of human values. Business enterprises, in effect are being asked to
contribute more to the quality of American Life than just supplying quantities of goods and services. In as much as business exists to serve society, its future will depend on the quality of management’s response to the changing expectations of the public” (CED, 1971, Boonstoppel, 2011). Near the end of the 70s, Carrol stated another definition of CSR. Carrol stated that CSR is “The social responsibility of business encompasses the economic, legal, ethical, and discretionary expectations that society has of organizations at a given point in time” (Carrol, 1979).
In the 80s there was less focus on developing the definition of CSR. Drucker however stated an important perspective. His perspective was that business should convert its social responsibilities into business opportunities (Carrol, 1979,
Boonstoppel, 2011).
In the 90s a lot of topics related to CSR, such as Corporate Social Performance, the stakeholder theory, the business ethics theory, and corporate citizenship are discussed (Carrol, 1999). In 1999 Carrol stated ”the CSR concept will remain as an essential part of the business language and practice, because it is a vital underpinning to many of the other theories and is continually consistent with what the public expects of the business community today” (Carrol, 1999, Boonstoppel, 2011).
As stated in the introduction, in the last few years the concept of CSR has become increasingly important. There are several important new definitions formulated. One
definition was given by The World Business Council for Sustainable Development. They formulated CSR as follows; “the continuing commitment by business to behave ethically and contribute to economic development while improving the quality of life of the workforce and their families as well as the local community and society at large” (WBCSD, 2007, Boonstoppel, 2011). McWilliams and Siegel gave another often-used definition of CSR. McWilliams and Siegel stated that “Actions that appear to further some social good, beyond the interest of the firm and that which is required by law”
(McWilliams & Siegel, 2001). This definition states that corporate social responsibility means more than following the law only (Boonstoppel, 2011)
2.2 How is CSR measured?
CSR can be measured in different ways. In this paragraph some of the most
widely used measurements will be discussed. Commonly there are two methods that are accepted in order to measure CSR. The first method is content analysis, and the second way to measure CSR is a reputation index (Cochran and Wood, 1984). First the content analysis will be discussed, and later in this paragraph the reputation index will be discussed.
The content analysis is a technique that is widely used in the field of CSR research analysing non-financial reports (Adler & Milne 1999). As stated by Giannarakis,
Sariannidis and Garefalakis, the content analysis is;’’ a process which gathers and codifies both qualitative and quantitative information into pre-defined categories. The quantative approach transforms observations into quantative statistical data while the qualitative one summarizes and classifies elements or parts of the text material and focuses on intentionality and its implications’’. Content analysis is the easiest way to find out if a company is adopting CSR (Cho et al, 2004). Content analysis has the advantage that it is quite objective and it’s easier to obtain large sample sizes (Cochran and Woods, 1984). A disadvantage however is that content analysis looks at what firms say or pretend they are doing, and not at how the firms is actually performing on CSR.
The reputation index is a method that rates how social responsible a firm is performing. The firms are rated by observers who look at how the firm is performing on several dimensions of CSR. One advantage of this measurement is that is tends to be internally consistent. This is because an evaluator will apply the same criteria to each firm. A second advantage is that it makes no pretence of applying a rigorous objective measure to a dimension that may be innately subjective. A third advantage of this measurement is that it can summarize the perceptions of a key constituency of different firms (Boonstoppel, 2011). However, the reputation index has also disadvantages. The disadvantage that is the most important is that a ranking can be subjective, and
therefore can very significantly from one evaluator to another. A second problem can be the sample size. Sometimes, reputation indexes are generated by only covering a small number of firms (Cochran and Woods, 1984).
As the importance of CSR practices has grown in the last decade, investors try to include portfolios with sustainability criteria and indices. For this reason indexes need to be linked with financial markets (Lopez et al, 2007). The Dow Jones Sustainability Index, also known as the DJSI is a good example. The most important reason why these indexes are created is that sustainability could result in long-term benefits. CSR can lead to less environmental, social and economic risk. More on this will be explained in the next paragraph.
The DJSI is an index that is based on environmental, social and economic indicators. The DJSI is identified as the most widely recognized sustainability rating (DJSI, 2014). Because this thesis focusses on The United States, the DJSI North America (DJSINA) will be used.
For a firm to be accepted in the DJSINA, the firm has to meet several criteria. Industries such as the alcohol or gambling industry are not included. The DJSI and the DJSINA are used as reference points and as investment universes for financial portfolios etc. that apply CSR. Firms can only be accepted in the DJSI and the DJSINA when the firm is included in the Dow Jones Global Total Stock Market Index, also known as the
DJGTSM. Firms should also be in the top ten percent of the biggest firms (Boonstoppel, 2011). To assess the firm’s level of sustainability, the criteria from RobecoSam are used (DJSI, 2014). The criteria used by RobecoSam include criteria that are used for all companies and criteria that are industry specific. The industry specific criteria accounts for 60% of the total assessment. The industry specific criteria consist the performance in
environmental, social and economic issues. The information used to assess a company’s performance in those areas is gathered by among others; submitted documents, publicly available information and direct interaction between RobecoSam analysts and firms. The other 40% of the total assessment is accounted by the general criteria. The general criteria include i.a. ; management practices and performance measures, like risk and crisis management and corporate governance. In order to be sure that the quality and objectivity is acceptable, an external check is done to control and maintain the precision of the input data, assessment procedures and results (DJSI, 2014).
When firms are included in the DJSI world, the firms will be monitored continuously. This is done so that it can be seen how firms have dealt with environmental, social and economic issues (DJSI, 2014, Boonstoppel, 2011).
2.3 How is financial performance measured?
Financial performance can be measured in a lot of different ways. There are two classes in which you can derive the measures, namely; investor returns and accounting-based returns.
The basic idea of investor returns is that the returns should be measured with regard to the shareholders. Investor returns were used in several researches. One of the first to use investor returns were Moskowitz (1972) and Vance (1975). These studies used the changes in the price per share as the index for investor returns. The measure of the change in price per share is however not complete. To measure investor returns the dividend income should also be included (Cochran, Wood, 1984). Other measures that were used to calculate the investor returns were; market value-to-book value ratio and the appreciation or depreciation of the share price. One advantage of investor returns as measurement of financial performance is that it depends less on accounting policies of companies. Therefore investor returns as a measurement takes into account what investors think that will be the future gain on their investment and not the past performance of the company. A major shortcoming of this measurement of financial performance is that the observation of the investor could not be sufficient to measure the financial performance of companies (Ullman, 1985, Boonstoppel, 2011).
The basic idea behind the usage of accounting returns as a measure of financial performance is to focus how companies react to different managerial policies.
Accounting returns also show the efficiency of a firm (Cochran, Wood, 1984). The most used measures are earning per share (EPS) or price/earnings (P/E), return on assets (RoA), return on equity (ROE), return on revenue (RoR) and debt ratios. Using these ratios also has its shortcomings. Most of these ratios such as EPS and P/E are influenced a lot by the growth rate of companies (Beaver & Morse, 1978). Another shortcoming of these ratios is that they are not comparable across companies, without taking into account the risk and financial leverage differences. Despite its shortcomings, accounting returns are the best approximation as measurements of financial performance (Cochran, Wood, 1984).
The variables that will be used in this research are the return on equity and the return on assets. Those were variables that were also used in prior research
(Boonstoppel, 2011, Waddock & Graves, 1997).
2.4 The control variables
Control variables should be included in order to make an unbiased regression analysis. Control variables that should be included are the industry, size and risk (Ruf et al, 2001).
Industry is an important control variable because the economics of scale and the competition can be different among industries. Therefore firms have different financial performances across industries (McWilliams and Siegel, 2001). It is also evident that the practices and actions to be social responsible are different across industries (Roberts, 1992). In this regression analysis the industry is controlled by looking at the Standard Industrial Classification (SIC) Code. The SIC Code is a number that shows in what
industry a company is in. The first digit of the SIC Code shows what the main industry is. There are 10 different main industries. For every main industry there will be a dummy variable.
Company Size is also a control variable. Larger companies have more CSR
attributes than smaller companies (McWilliams, Siegel, 2001). One reason for this is that larger companies will have more scrutiny from the stakeholders than smaller
companies, and therefore will be more engaged in CSR practices (Burke & Logsdon, 1996). The larger the company the more plausible it is that the company will be able to get the financial, technical and managerial expertise to adopt CSR (Ulmann, 1985). Research done by Wu in 2006, concluded that there was a small correlation between the size of a company and CSR but that it was not significant. For this regression analysis the control variable company size will be calculated by the natural logarithms of total
revenue (Boonstoppel, 2011).
Research done by Barbosa and Louri in 2005 came to the conclusion that the tolerance for risk is correlated with the financial performance of a firm. It is also concluded by prior research that companies with lower risk often participate more in CSR (Cochran & Wood, 1984). A model that was used by Waddok and Graves (1997), to find the relationship between CSR and financial performance, used the debt to assets ratio as a measure for the risk of a firm.
Investment in Research and Development has a positive relation with
improvements in the long-run economic performance of a firm (Grilichesm, 1979). R&D could lead to an increase in economic performance because investment in technical capital will lead to product and process innovation. This can lead to an increase in productivity and thus a better economic performance (McWilliams & Siegel, 2000). The R&D investments/ expenses to sales ratio is the most used measure of R&D. The data for investment is not complete, so in this research it will not be included. Other previous research also excluded the control variable investment in R&D (Lopez et al. 2007, Boonstoppel, 2011).
3.1: Business Benefits of CSR
Companies will have benefits when engaging CSR, in this paragraph I will look into the benefits obtained from CSR and discuss them.
First, firms that engage CSR often can get tax credits for their efforts in being sustainable. For example, the president of the US, Obama, introduced tax credits for the wind and solar industry (Grunwald, 2012). Companies can also receive tax credits for
using “green” materials and participating in the renovation of sustainable construction of buildings.
A second benefit for companies is that they can have free advertising and improve the image of the company. When being social responsible, in general a company will be a subject in the news, and receive coverage about its deeds. The cost that are normally made to advertise in newspapers and television is now gone and can therefore be seen as a benefit. A company that engages CSR improves its image and therefore might expect higher demand. The improvement in its image can also reduce the price sensitivity a company is facing (Navorro, 1988).
Third, social responsibility can lead to savings in the costs and efficiency of the value chain, and the operating costs. For example, if a company reduces the materials used for packaging, or by investing in a manufacturing building that is energy efficient, the company is not only reducing environmental costs but also reduces the operating costs. Recently TNT Express of the Netherlands moved to a new headquarter which was energy positive, it generates more energy than it uses (OVG, 2011 ). This off course will lead to less energy expenses and will be good for the environment. The engaging of CSR will therefore motivate the managers to create an efficient and social responsible operating strategy (Weber, 2008).
A fourth benefit is that a strong CSR commitment leads to the improved ability to attract, motivate and retain talent (Turban & Greening, 1997). This will lead to less turnover, recruitment and training costs. There has been research that pointed out that the costs of employee turnover can range from 30% of the base salary for entry-level positions, to 150% of middle level employees and to a 400% of the base salary for
specialized high level employees (Blake, 2006). So for example, a firms pays middle level employees on average 40,000$ per year, than multiply this by .125%. This means that it will cost the firm 50,000$ to replace a middle level employee. These replacement costs will be less because of CSR. A strong CSR commitment will also lead to a higher
productivity (Moskowitz, 1972). Corporate social responsibility makes sure that employees can work under appropriate conditions and that the wage rates are good. Higher wages and better production facilities controls may be expensive, but it will lead to a higher productivity and better quality. These benefits can be higher than the costs and therefore increase the financial performances of the firm.
Companies that engage social responsibility have less risk to be involved negative events. There are three categories of risk related to CSR namely, environmental, social and corporate governance risk. When engaging CSR, a company will have more
environmental controls, which will result in less risk of for example producing too much pollution and therefore facing a fine. A company will also have less risk of being related to negative social events. A good example is the clothing industry, where a lot of child-labour happens. When engaging CSR a company will not be involved in child-child-labour, and therefore won’t be named in those scandals. Socially responsible companies will thus see less downside volatility. When having less downside risk, the discount rate for the company could be lower and could result in an increase in the value of the company (Weber, 2008)
Finally if CSR is motivated by altruism, the increase in social welfare is an
important benefit for the society as a whole. Altruism is the principle and/or practice of concern for the welfare of other people.
3.2 Arguments against CSR
Arguments against CSR often begin with the idea that management has one responsibility and that is to maximize the profits of the owners of the firm or the shareholders. This idea was formulated by Friedman in 1962. Friedman argued that social problems should not be the concern of business people but that these problems should be resolved by the free market mechanism. When the social problems cannot be resolved by the free market, Friedman argued that the problems should be resolved by the government (Caroll & Shabana, 2010). A second argument against CSR is that managers are directed towards finance and organization. Managers often don’t have skills to make social decisions (Davis, 1973, Caroll & Shabana, 2010). Thirdly, it is argued that business controls already a lot of power and giving business another power such as social power may not be wise (Davis, 1973, Carrol & Shabana, 2010). However, the arguments against CSR given by Carrol & Shabana were arguments introduced mostly at the beginning of the concept of CSR.
4 Research Method 4.1 Hypothesis
Most companies would only adopt CSR if it won’t hurt the financial performance. The business benefits given in the previous paragraph suggests that CSR can improve the financial performance of a company. The business benefits in short were; tax credits, free advertising, lower costs and less business risk. Burke and Logsdon (1996) were convinced that CSR would have a positive effect for the stakeholders of the company and the society. Because of the benefits given above it is expected that CSR will have a
positive relationship on financial performance. In this research I will look at the financial performance of the companies included in the S&P 500, where CSR is measured by the DJSI North America, this will be further explained in the next paragraph. The hypothesis of this research will be:
H1: There is a positive relationship between CSR and financial performance for companies included in the DJSI North America and the S&P500
4.2 Data
In order to make a regression analysis an indicator is needed to measure the level of CSR. The indicator that will be used in this research is the Dow Jones Sustainability Index of North America (DJSINA). The DJSINA contains the top 20% of the 600 largest United States and Canadian companies in the S&P Global Market Index that lead the field in terms of sustainability (DJSI, 2014). A total of 140 companies are included in the DJSINA.
The companies that are used in this research are all the companies included in the S&P 500, all the US companies included in the DJSINA are also included in the S&P 500. The S&P 500 is a stock index that includes the 500 largest companies having common stock listed on the NYSE or NASDAQ.
The period that is used for this research is 2010-2012. The financial
performances of all the American companies included in the DJSINA and the S&P 500 are analysed during the years 2010, 2011 and 2012.
The data that I used is gathered by using the program Compustat and the
database from Warthon Research Data Services. By using the program Compustat I was able to collect the following information from the companies listed on the S&P 500: the total assets, total debt, shareholders equity, net income, total revenue and the sic codes.
4.3 Variables
This paragraph will describe the variables that are included in the regression analysis.
The Dependent variables: RoA (return on assets)
The return on assets ratio shows the amount of net income that can be earned for every dollar of assets the company controls. The return on assets is measured by
dividing net income by total assets.
RoE (return on equity)
The Return on equity ratio shows how much profit a company makes with the amount of money that shareholders have invested. The RoE is calculated by dividing the net income by the total shareholder’s equity.
The independent variables:
CSR (corporate social responsibility)
The Dow Jones Sustainability index North America is an index that contains 140 companies that are the leaders in sustainability in North America. The DJSINA will be used as a dummy variable. When a company is included in the DJSINA and the S&P 500 it will score a 1 for CSR, and when a company is only listed on the S&P 500, it will score a 0 for CSR.
Control Variables: Risk
The risk of a company is measured by total debt divided by total assets (debt to assets ratio). The more debt compared to assets a company has, the more risky the company will be. The debt to assets ratio measures the amount of debt that is used to obtain the assets.
Size (size of the company)
In order to measure the size of a company, the natural logarithm of total revenue is used. The higher total revenue the bigger the size of the company.
Industry
To control for the industry a company is in, 9 dummy variables are used. One dummy variable is used for every main industry. The industry Agriculture is excluded because in the data there was no company in this industry . One industry will be used as the reference variable.
4.4 The regressions
To test the Hypothesis, I made use of the following regressions. Each regression is tested for the years: 2010,2011 and 2012. The industry Manufacturing 1 (Man1) will be used as the reference variable.
ROAi=B+B1*CSRi+B2*LnSIZEi+B3*RISK(td/ta)i+B4*Min+B5*Man2+B6*Trans+B7*W hole+B8*Fin+B9*Ser+B10*Ser2+B11*Pub+ εi
ROEi=B+B1*CSRi+B2*LnSIZEi+B3*RISK(td/ta)i+B4*Min+B5*Man2+B6*Trans+B7*W hole+B8*Fin+B9*Ser+B10*Ser2+B11*Pub + εi
5 Empirical analyses
This paragraph will present the empirical results of this research. In paragraph 5.1 the correlations will be discussed. And finally in paragraph 5.2 the results of the regression analyses will be given. On the basis of the results, the hypothesis will be accepted or rejected.
5.1 Correlations
The tables of the correlations for each year can be found in the appendix (Table 2,6 and 10). From the results you can see that CSR had a very small positive correlation with RoA in 2010 but a small negative correlation with RoA in the years 2011 and 2012. CSR also had a small negative correlation with RoE in the years 2010,2011 and 2012. These results could suggest that firms included in the DJSINA have lower RoA and RoE than firms excluded from the DJSINA. The correlation is however very small and not significant. So no conclusions can be based on these results. One results that is significant is the positive correlation of between the size of a company and the CSR. The correlation between CSR and the size is in the years 2010,2011 and 2012 around 0.3. This is also what Ullman suggested in 1985. From the results it can also be suggested that risk has a negative correlation with the RoA. In every year the correlation was around -0.3 and -.35.
5.2 The regression analyses
5.2.1 2010
The first regression analysis for the year 2010 and with RoA as dependant variable, shows that there is no effect of CSR on RoA (Table 3). Research done by McWilliams and Siegel in 2000 came to the same conclusion. One variable that is significant is the control variable Risk (TDTA). Risk has a negative effect of -0.069 on RoA. This effect is significant based on a 5% significance level because the P value is 0.000. Another significant effect on RoA is dummy variable Fin. This means that companies in the industry Finance and Real estate have a slightly, but significant, higher RoA. The regression analysis is given in the table in the appendix. The R-squared is 0.219 of the model; this means that the model can explain 21.9% of the variances in the results.
The second regression analysis for the year 2010 has the RoE as dependant variable. This model has a very low R-squared of 0.0179 and a high F of 0.6529, from this it can be concluded that the model is not able to predict the relation between CSR and RoE with the size, risk and industry as control variable (Table 4).
5.2.2 2011
In 2011 the coefficient of CSR was -.002045 (Table 7). From this it can be concluded that CSR had no effect on financial performance in 2011. Just like in 2010, the level of risk has a significant negative effect on RoA. The coefficient of risk was -0.072 in 2011. The industries Mineral construction, Whole sale and Retail and Finance and Real estate all had a significant negative effect on RoA, this can be seen in table 7. The R-squared for the model in 2011 was 0.217. This result is very close to the one founded in 2010.
The regression analysis with the RoE as dependent variable has just like in 2010 a very low R-squared of 0.0154 and a high F of 0.75. Therefore it can be concluded that in 2011 the regression model with RoE as dependent variable cannot predict a relation between CSR and financial performance (Table 8)
5.2.3 2012
The coefficient of CSR in 2012 was -.0052 (Table 11), which is very close to the coefficient found in 2011. The results are as in 2010 and 2011 not significant. So again it can be
concluded that in 2012 CSR had no effect on financial performance. Other research also found that there was no significant relationship between CSR and financial performance (McWilliams & Siegel, 2000). Again it can be said that risk has a negative effect on RoA. The coefficient in 2012 was -0.0724 with a P of 0.000, and therefore the coefficient is significant. The R-squared was 0.1781 in 2012, this result is a bit lower than in 2010 and 2011, but still explains 17.8% of the variances in the results.
The model with the RoE as dependant variable is like in 2010 and 2011 not able to predict a relationship between CSR and RoE (Table 12). With an R-squared of 0.0223 and a F of 0.43 it can be concluded that the model doesn’t work.
6 Conclusion
This research tried to test the relationship between CSR and financial performance. In order to test this relationship, regression analyses were made. The hypothesis was that a positive effect of CSR on financial performance existed for the companies that were used in this research. The model was used in the years 2010, 2011 and 2012. With the control variables risk, size and industry, the regression model was not able to predict a significant relationship between CSR and financial performance. Therefore the hypothesis of this research can be rejected. The results of this research suggest that CSR has is no effect on financial performance. Research done by McWilliams and Siegel (2000) and Boonstoppel (2011) came to the same conclusion. What could be concluded from the correlations was that the size of a firm positively correlates with CSR, and that the level of risk of companies has a negative relationship with RoA. From the regressions with RoE as dependant variable it is concluded that the model doesn’t work, so no conclusions can be made.
7 Appendix
2010
Table 1 Table 2 Table 3 CSR 487 .1991786 .3997933 0 1 TDTA 487 .6062792 .2088828 .0744136 1.712266 LNSales 487 8.998683 1.214399 5.887001 12.91436 ROE 487 .1234781 .9257881 -11.3299 9.082343 ROA 487 .0645188 .0582102 -.1424439 .340002 Variable Obs Mean Std. Dev. Min MaxCSR 0.0309 -0.0242 0.3407 0.0103 1.0000 TDTA -0.3472 -0.0824 0.2281 1.0000 LNSales -0.0782 -0.0740 1.0000 ROE 0.1249 1.0000 ROA 1.0000 ROA ROE LNSales TDTA CSR
Total 1.64677661 486 .003388429 Root MSE = .05203 Adj R-squared = 0.2012 Residual 1.2856527 475 .002706637 R-squared = 0.2193 Model .361123915 11 .032829447 Prob > F = 0.0000 F( 11, 475) = 12.13 Source SS df MS Number of obs = 487
_cons .1300366 .0196728 6.61 0.000 .09138 .1686931 Publ -.0421582 .0375777 -1.12 0.262 -.1159973 .031681 Ser2 .0182412 .0238069 0.77 0.444 -.0285387 .065021 Ser .0088658 .0096178 0.92 0.357 -.0100328 .0277644 Fin -.0397683 .0076968 -5.17 0.000 -.0548923 -.0246443 Whol .0043742 .0094419 0.46 0.643 -.0141789 .0229272 Trans -.0316832 .0081736 -3.88 0.000 -.0477441 -.0156223 Man2 .0003792 .0071995 0.05 0.958 -.0137675 .014526 Min -.0340412 .0100993 -3.37 0.001 -.053886 -.0141964 TDTA -.0710707 .0126505 -5.62 0.000 -.0959285 -.0462129 LNSales -.0012547 .0022347 -0.56 0.575 -.0056458 .0031364 CSR .0051998 .0063232 0.82 0.411 -.007225 .0176246 ROA Coef. Std. Err. t P>|t| [95% Conf. Interval]
Table 4
2011
Table 5Table 6
Total 416.542612 486 .857083564 Root MSE = .92802 Adj R-squared = -0.0048 Residual 409.083931 475 .861229329 R-squared = 0.0179 Model 7.45868094 11 .678061903 Prob > F = 0.6529 F( 11, 475) = 0.79 Source SS df MS Number of obs = 487
_cons .8015608 .3509226 2.28 0.023 .1120082 1.491113 Publ .0413187 .670309 0.06 0.951 -1.275819 1.358456 Ser2 .1105286 .4246656 0.26 0.795 -.7239269 .9449841 Ser -.1069423 .1715607 -0.62 0.533 -.4440541 .2301695 Fin -.0692161 .1372949 -0.50 0.614 -.3389966 .2005643 Whol -.0304678 .1684238 -0.18 0.857 -.3614157 .30048 Trans -.2542244 .1458 -1.74 0.082 -.5407171 .0322683 Man2 -.1058016 .1284237 -0.82 0.410 -.3581505 .1465472 Min -.1595454 .1801505 -0.89 0.376 -.513536 .1944451 TDTA -.2882695 .225658 -1.28 0.202 -.7316809 .155142 LNSales -.0460422 .0398618 -1.16 0.249 -.1243695 .0322851 CSR -.0039994 .112792 -0.04 0.972 -.2256324 .2176335 ROE Coef. Std. Err. t P>|t| [95% Conf. Interval]
CSR 495 .2141414 .4106404 0 1 TDTA 495 .6198314 .2110664 .0721353 1.780569 LNSales 495 9.114306 1.179967 6.456869 12.97971 ROE 495 .2090777 2.000476 -15.83851 37.51528 ROA 495 .0682403 .0603732 -.2738133 .3710106 Variable Obs Mean Std. Dev. Min Max
CSR -0.0130 -0.0053 0.3167 0.0040 1.0000 TDTA -0.3516 0.0267 0.2053 1.0000 LNSales -0.0963 0.0741 1.0000 ROE 0.0544 1.0000 ROA 1.0000 ROA ROE LNSales TDTA CSR
Table 7
Table 8
Total 1.80059312 494 .003644925 Root MSE = .05403 Adj R-squared = 0.1989 Residual 1.41025177 483 .002919776 R-squared = 0.2168 Model .390341354 11 .035485578 Prob > F = 0.0000 F( 11, 483) = 12.15 Source SS df MS Number of obs = 495
_cons .1501771 .0213267 7.04 0.000 .1082725 .1920816 Publ -.0408848 .0389799 -1.05 0.295 -.1174759 .0357062 Ser2 .0006218 .0227235 0.03 0.978 -.0440273 .0452708 Ser .0032951 .0100388 0.33 0.743 -.01643 .0230201 Fin -.04053 .0080164 -5.06 0.000 -.0562814 -.0247786 Whol .014489 .0095561 1.52 0.130 -.0042877 .0332657 Trans -.028662 .0085292 -3.36 0.001 -.045421 -.011903 Man2 .0038941 .0074358 0.52 0.601 -.0107165 .0185047 Min -.0285824 .0105834 -2.70 0.007 -.0493776 -.0077872 TDTA -.0723664 .0127574 -5.67 0.000 -.0974332 -.0472997 LNSales -.0029062 .0023323 -1.25 0.213 -.0074889 .0016765 CSR -.0011578 .0062807 -0.18 0.854 -.0134988 .0111832 ROA Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 1976.94081 494 4.00190448 Root MSE = 2.0075 Adj R-squared = -0.0071 Residual 1946.55489 483 4.03013434 R-squared = 0.0154 Model 30.3859272 11 2.76235702 Prob > F = 0.7529 F( 11, 483) = 0.69 Source SS df MS Number of obs = 495
_cons -.7143546 .7923348 -0.90 0.368 -2.271203 .8424943 Publ -.8019533 1.448189 -0.55 0.580 -3.647482 2.043575 Ser2 -.258379 .8442271 -0.31 0.760 -1.91719 1.400432 Ser -.4254694 .3729629 -1.14 0.255 -1.1583 .3073609 Fin -.45072 .2978277 -1.51 0.131 -1.035918 .134478 Whol -.4281827 .3550312 -1.21 0.228 -1.125779 .2694136 Trans -.4619714 .3168797 -1.46 0.146 -1.084604 .1606617 Man2 -.4614465 .2762583 -1.67 0.095 -1.004263 .08137 Min -.4058941 .3931972 -1.03 0.302 -1.178482 .3666941 TDTA .1089997 .4739644 0.23 0.818 -.8222872 1.040287 LNSales .1354801 .0866501 1.56 0.119 -.0347777 .3057378 CSR -.153806 .2333437 -0.66 0.510 -.6123002 .3046883 ROE Coef. Std. Err. t P>|t| [95% Conf. Interval]
2012
Table 9 Table 10 Table 11 CSR 498 .2148594 .4111378 0 1 TDTA 498 .6237152 .2139819 .079565 1.778221 LNSales 498 9.154889 1.163372 6.637213 13.00571 ROE 498 .2838216 3.821213 -34.32715 70.38462 ROA 498 .0617622 .0672626 -.3791224 .3346658 Variable Obs Mean Std. Dev. Min MaxCSR -0.0232 -0.0163 0.3138 0.0395 1.0000 TDTA -0.2937 0.0552 0.1977 1.0000 LNSales -0.0713 0.0770 1.0000 ROE 0.0488 1.0000 ROA 1.0000 ROA ROE LNSales TDTA CSR
Total 2.24855315 497 .004524252 Root MSE = .06167 Adj R-squared = 0.1595 Residual 1.84814419 486 .003802766 R-squared = 0.1781 Model .400408955 11 .036400814 Prob > F = 0.0000 F( 11, 486) = 9.57 Source SS df MS Number of obs = 498
_cons .1547128 .0249511 6.20 0.000 .1056874 .2037382 Publ -.0417304 .0445291 -0.94 0.349 -.1292238 .045763 Ser2 -.0036805 .0259882 -0.14 0.887 -.0547436 .0473826 Ser -.0062343 .0115233 -0.54 0.589 -.0288759 .0164073 Fin -.0448119 .009341 -4.80 0.000 -.0631656 -.0264582 Whol .0063432 .0108971 0.58 0.561 -.015068 .0277545 Trans -.0418163 .009877 -4.23 0.000 -.0612232 -.0224094 Man2 -.0165639 .0085956 -1.93 0.055 -.0334531 .0003253 Min -.055577 .0120514 -4.61 0.000 -.0792563 -.0318976 TDTA -.0744491 .0141841 -5.25 0.000 -.1023188 -.0465794 LNSales -.0026506 .0026844 -0.99 0.324 -.0079251 .0026239 CSR -.0052331 .0071559 -0.73 0.465 -.0192934 .0088273 ROA Coef. Std. Err. t P>|t| [95% Conf. Interval]
Table 12
Total 7257.02991 497 14.6016698 Root MSE = 3.8209 Adj R-squared = 0.0002 Residual 7095.22121 486 14.5992206 R-squared = 0.0223 Model 161.808703 11 14.7098821 Prob > F = 0.4383 F( 11, 486) = 1.01 Source SS df MS Number of obs = 498
_cons -2.355877 1.545986 -1.52 0.128 -5.393518 .6817646 Publ -1.053934 2.759048 -0.38 0.703 -6.47507 4.367201 Ser2 -.250714 1.610243 -0.16 0.876 -3.414611 2.913183 Ser -1.048984 .7139881 -1.47 0.142 -2.451868 .3539007 Fin -.5270203 .5787732 -0.91 0.363 -1.664227 .6101862 Whol -.4263623 .6751904 -0.63 0.528 -1.753015 .9002903 Trans -.5425775 .6119845 -0.89 0.376 -1.74504 .6598845 Man2 .4222642 .5325901 0.79 0.428 -.6241992 1.468728 Min -.3078603 .7467129 -0.41 0.680 -1.775045 1.159324 TDTA 1.138536 .8788531 1.30 0.196 -.588285 2.865356 LNSales .2459612 .166329 1.48 0.140 -.0808516 .572774 CSR -.4369511 .4433839 -0.99 0.325 -1.308137 .4342349 ROE Coef. Std. Err. t P>|t| [95% Conf. Interval]
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