The effect of firm risk on the relationship between corporate social
performance and corporate financial performance in industries that
influence and depend on the environment.
Abstract
The main goal of this study was to investigate if corporate social performance(CSP) increases corporate financial performance(CFP), if CSP influences firm risk and in particular if firm risk mediates the relationship between CSP and CFP. Datasets from Compustat and KLD Stats were used to test the hypotheses. Only industries that have a large influence and at the same time are largely dependent on the environment were selected, which resulted in a total sample of 66 companies. The selected industries are the mining,
agriculture, food, textile, paper, lumber, rubber, stone, clay, glass and concrete sectors. The hypotheses were tested with hierarchical regression analysis and the results show that CSP increases market value, lowers firm risk and companies with low firm risks experience higher return on assets. However, environmental CSP lowers the return on assets. Unfortunately, there was no mediation found but the results can still help organizations in the researched industries to reduce the uncertainties of company performance or to know more about the effects of CSP on CFP.
Statement of Originality
This document is written by student Pieter Zuiderveld, 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 the sources other than those mentioned in the text and 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.
Introduction
Corporate Social Responsibility(CSR) is one of few concepts which integrates business activities with social consequences and gives companies the opportunity to implement responsible behaviour. A project is socially responsible if it enhances the social good, exceeds the economic goals of the firm and transcend the requirements of the law (McWilliams & Siegel, 2001). In recent years’ companies are devoting more resources to CSR because they are encouraged to do so by society and their stakeholders (McWilliams, 2000). According to Galema, Plantinga and Scholtens (2008), more than half of the Fortune 1,000 companies in the U.S. regularly issue CSR reports and almost 10% of all U.S. investments are screened to assure that certain CSR-related criteria are met. 93% of 766 chief executive officers (CEO’s) from different countries believe that CSR-related issues are critical to future success (Lacy et al., 2010). Recently, environmental concerns and changing customer
expectations have a large influence on business strategy (Prahalad and Hamel, 1994). These relatively new influences on business strategy are the effect of different stakeholder expectations, and how a company interacts with its stakeholders can add up to its overall corporate social performance (CSP) (Freeman & Reed, 1983). Some companies even adopt a CSR strategy to gain a competitive
advantage (Porter and Kramer, 2007).
The relationship between corporate social performance (CSP) and corporate financial performance (CFP) has been largely analysed in existing literature and has produced different results (Jiao, 2010; El Ghoul, Guedhami, Kwok & Mishra, 2011). Orlitzky, Schmidt and Rynes (2003) conducted a meta-analysis of 52 prior studies on this relationship and found that CSP is positively correlated with CFP, but also stated that still a lot of research has to be done to further explain this relationship.
McWilliams and Siegel (2000) found a neutral relationship and argue that a relationship between CSP and CFP exists by chance because there are many variables which influence the underlying
relationship and that the misspecification of econometric models is the main reason behind these inconsistent findings. One of the problems with the current literature according to Allouche and Laroche (2005) is that there are large differences in methodological approach, sampling,
measurements of CSP and measurements of CFP between papers, therefore it is inevitable that they have different outcomes).
One of the variables that influences the relationship between CSP and CFP is the cost of capital, this variable determines at what cost companies can raise capital. Recent studies have researched the relationship between CSR and cost of capital and also found different results. Sharfman and Fernando (2008) found a reduction in cost of capital for companies that engage in environmental CSR. El Ghoul et al. (2011) analysed the relationship between CSR and cost of equity capital and found that firms with higher CSR scores can raise equity at a lower price. Goss and Roberts (2011) analysed the influence of CSR on the cost of debt and found that banks do not view CSR as value
enhancing or risk reducing. According to Sharfman and Fernando (2008), companies that implement certain forms of environmental CSR into their strategy can benefit from a lower cost of capital mainly because they are exposed to less risks. Several papers have analysed the effect of CSP on firm risk and they showed that an important mechanism through which CSP affects CFP is the effect of CSP on firm risk (McGuire, Sundgren & Schneeweis, 1988; Starks, 2009; El Ghoul et al., 2011). The basic theory in the papers about firm risk is that investors base their rate of return on the expected return and the expected risk of a company (Modigliani & Miller, 1958; Sharpe, 1964). CSR activities lower the risk of a company, because those companies are better equipped against changes in the market and environment (Feldman, Soyka, & Ameer, 1997). Investors price the risk related to environmental performance because of the unpredictability of the future cash flow effects of the consequences of poor performance such as lawsuits and regulatory exposure (Connors & Silva-Gao, 2008). The paper of Lee and Faff (2009) shows that firms with high CSR scores have lower idiosyncratic risk, while Goss (2009) found that firms with low CSR scores are more likely to encounter financial distress (Cheng, Ioannou & Serafeim, 2014). If CSR influences the riskiness of a firm, then socially responsible firms should benefit from lower risks or cost of capital, which could enhance financial performance (Ghoul et al., 2011).
Another important variable related to the relationship between CSP and CFP is the industry of the company and this is because different industries face different CSP challenges. Firms in the energy industry might focus on pollution for example, while clothing companies see human rights as their largest problem. Until now, the amount of CSP has mostly been investigated at a cross-industry level. According to Peloza (2009), more than 77% of his sample data is not industry specific. The results for measuring CSP and CFP can hide individual differences due to the specific situation of an industry (Griffin & Mahon, 1997). Between industries there can be different CSR activities, some industries are considered more polluting than others, such as the mining or chemical industry. Some industries may be growing while others are declining, stakeholders can change the amount of regulation for
different industries. Therefore, the level of CSR activities may vary for different industries (Waddock & Graves, 1997; McWilliams & Siegel, 2001). Due to the fact that CSR activities influence firm risk and the fact that CSR activities may vary across industries, some industries could be more exposed to risks that others. Accordingly, it is assumed that the industry plays a large role on the effect of CSP on firm risk and CFP (Sharfman & Fernando, 2008). Because most studies are not industry specific, while it plays a large role on the relationship between CSP and CFP, it would contribute the literature to conduct an industry specific analyses.
CSR is highly relevant for industries that have a strong influence and a high reliance on the economy, the environment and on society, for instance the food sector (Hartmann, 2011). There are several reasons why the food sector encounters challenges in the context of CSR. The food industry has a high impact on natural, human and physical resources, while at the same time depending on them (Genier, Stamp & Pfitzer, 2009). Because food fulfils a basic human need people tend to have strong opinions about what they eat. This leads to basic requirements for the food sector as to animal welfare, energy and water use, pollution, waste and social conditions along the whole value chain of the company. Also for the quality, healthiness and safety of products (Maloni and Brown, 2006). Even though sectors such as mining have a stronger impact on the environment, there are few sectors so dependent on natural resources as the food sector (Jones, Comfort, Hillier, & Eastwood, 2005; Maloni and Brown, 2006; Hartmann, 2011). Although every sector has its own special characteristics, just as the food industry, there are other sectors which face similar challenges,
because they all have a high impact on natural resources, while at the same time depending on them. Although scientific research has given the environmental impact, safety and quality issues of these sectors lots of attention, so far, industry specific research on CSR is rare. Nevertheless, due to the special characteristics of these sectors, the increasing importance of CSR and the fact that the outcomes could help these companies, these studies are highly relevant.
Existing literature has neglected to look at the interaction of CSP, firm risk and CFP in industries that influence and are highly dependent on the environment. This paper will address the effects of CSP on firm risk and CFP for the following industries, companies that manufacture or process foods and beverages for human consumption, companies in the mining, agricultural, textile, paper, lumber rubber, stone, clay, glass and concrete sector. In the interest of better understanding the underlying relationship between CSP and CFP in these industries, the effect of firm risk will be analysed. The outcomes could help build a better understanding of the effects of the implementation of CSR and could give scholars and managers new insights on the consequences of CSR strategies. In order to fulfil these objectives, the following research questions were formulated;
Research Question and Sub Questions:
What is the effect of corporate social performance on firm risk and corporate financial
performance?
What is the effect of CSP on CFP? What is the effect of CSP on firm risk? What is the effect of firm risk on CFP?
Does firm risk mediate the relationship between CSP and CFP?
Theoretical framework
Corporate Financial Performance
According to Orlitzky et al. (2003), the performance of business organizations is affected by their strategies and operations in markets and non-markets. When looking at the existing literature, there is a large variety of firm performance definitions. Margolis & Walsh (2003) found that 70 measures of financial performance had been used in 122 different studies.
Orlitzky et al. (2003) studied both accounting definitions and market definitions. They explain three different measures of CFP namely, market-based, accounting-based, and perceptual measures. The market-based measures of CFP are the share price and market value of a firm. Accounting-based measures on the other hand are the return on assets, return on equity, or earnings per share of a firm. Perceptual measures of CFP are surveys which provide subjective estimates about firm performance.
Allouche and Laroche (2005) studied both measures and found that accounting-based measures are less highly correlated with CSP than market-based and subjective CFP measures. Still, the use of accounting-based measures, such as return on sales, return on assets, and return on equity leads to greater reported effects. Other studies have found that accounting measures tend to show a larger
correlation between CSP and corporate financial performance (Margolis, Elfenbein & Walsh, 2009; Orlitzky et al., 2003). Therefore, the way in which financial performance is measured does influence the CSP-CFP relationship.
Proponents of accounting-based measures argue that market-based measures are influenced by several factors unrelated to the activity of the firm and it requires a relatively high number of financial variables, which makes it susceptible to missing values and uncertainties. On the other hand, supporters of market-based measures are uncertain about the objectivity and informational value of accounting data. One of the reasons for this is the fact that accounting-based measures are influenced by choices of managers and therefore indicate managerial performance rather than external market responses. (Brammer & Millington, 2008; Margolis & Walsh, 2003). Margolis and Walsh (2003) stated that the most reasonable approach is to use both measures and let the empirical evidence advice our understanding.
In the context of the research questions, the perceptual measures do not seem appropriate because the objective of this paper is not to find subjective estimates. Both accounting-based and market-based measures have their strengths and weaknesses, in this paper both measures will be used in order to answer the research questions because it will provide more information and the differences between the two measures can eventually be compared.
Corporate Social Performance
According to Wood (1991), CSP can be defined as ‘a business organization’s configuration of principles of social responsibility, processes of social responsiveness, and policies, programs, and observable outcomes as they relate to the firm’s societal relationships’. There are theories which predict a positive relationship between CSP and CFP. The stakeholder theory developed by Freeman (1984) suggests that CSP is positively associated with CFP because it improves the satisfaction of different stakeholders and therefore its reputation, which leads to better financial performance. According to the resource-based view (RBV) developed by Barney (1991), if the resources of a company are valuable, rare, inimitable and non-substitutable, they will be the cause of competitive advantage. CSP may be a resource for a firm that provides internal or external benefits. Investments in CSP can help firms develop new competencies, resources, and capabilities which are incorporated in a firm’s culture and structure (Barney, 1991). When the environment of a firm is dynamic or complex, CSP can help build managerial competencies (Shrivastava, 1995). According to Fombrun and Shanley (1990), CSP can also have effects on reputation, when a firm communicates its level of CSP to other organizations, it can help build a positive image with customers, investors, bankers, and suppliers. Firms high in CSP may also attract better employees (Turban & Greening, 1997). Another theory is that firms who try to lower their costs by socially irresponsible actions could eventually incur higher costs, which will result in a competitive disadvantage (Waddock & Graves, 1997). There are also theories which predict a negative relationship between CSP and CFP. Some academics see shareholder wealth maximization as the only social responsibility of a company, everything else destroys value. Social responsibility could drain off capital and resources from the firm, which gives the company a relative competitive disadvantage compared to other firms that are less socially active (Friedman, 1970). McWilliams and Siegel (2001) found no reason to observe any relationship
Their results indicate that the link between CSP and CFP disappears when more variables are introduced into their models.
Several studies have researched the influence of CSP on CFP. Orlitzky et al. (2003) found that CSP is positively correlated with CFP, King and Lenox (2002) found that companies that had lower than average TRI emissions had higher return on assets and Tobin’s q in the following year. According to Malik (2015), socially responsible firms perform better then less socially responsible firms in terms accounting measures such as, return on investment (ROI), return on assets (ROA), and return on sales (ROS). Margolis et al. (2009) conducted a meta-analysis of 251 studies and found that the overall effect is positive but small. Therefore, by analysing the results of these papers it is likely that CSP relates to CFP and the first hypothesis is that H1: Corporate social performance positively affects
corporate financial performance.
Firm Risk
According to Modigliani and Miller (1958), The cost of capital is the expected rate of return demanded by investors for investing in a firm. If investors demand a higher rate of return for the capital they provide to a firm, it will be more expensive for the firm to finance itself. The cost of capital is also the rate that investors use to discount a firm’s future cash flows. The higher the cost of capital, the lower the present value of the future cash flows of a firm. Therefore, ceteris paribus, firms with a lower cost of capital will probably perform better financially than firms with a higher cost of capital. True economic performance, results in both high financial return and low financial risk. Investors calculate the cost of capital by looking at the returns and riskiness of its cash flows compared with other investment possibilities.
Because the riskiness of a firm or investment is an important variable in order to determine its cost of capital or financial performance, several studies have analysed the effect of CSP on firm risk. Spicer (1978) was one of the first to examine the relationship between CSR and risk and he found that companies with better pollution control tended to have higher profits and lower risks. From the perspective of stakeholder theory or good management theory CSP is expected to decrease firm financial risk (Waddock & Graves, 1997). McGuire et al. (1988) showed that risk is closely connected with social responsibility and that high levels of CSP can be related to low financial risk because of lower probabilities of having legal prosecutions and fines, less regulatory controls, more stable relations with the government and the financial community and more customer loyalty. Herremans, Akathaporn and McInnes (1993) also investigated the relationship between CSR and firm risk and found that large U.S manufacturing companies with better financial performance provided investors better stock market returns and lower risks. Orlitzky and Benjamin (2001) analysed the effect of CSP on firm risk and found that high corporate social performance relates to low financial risk. El Ghoul et al. (2011) found that firms who adopt a more environmentally pro-active attitude can encounter a reduction in perceived riskiness. According to Feldman et al. (1997), investors identify socially irresponsible firms as having more risk. Oikonomou et al. (2012) showed that CSR is negatively but weakly related to systematic risk and that corporate social irresponsibility is positively and strongly related to systematic risk. Badly managed social and environmental risks could create significant financial risk (Porter & Kramer, 2007). The opposite can therefore reduce risks and lower risks make the expectations of the future cash flows of a firm more certain and reliable, which can increase the value of the firm (Orlitzky & Benjamin, 2001). Starks (2009) reported that CSR activities not only
reduce social risks but also operational, litigation, product, and technology-related risks. Due to risk management, CSP can function as a buffer against losses and therefore guard the assets of a firm (Fombrun, Gardberg & Barnett, 2000).
Looking at the results of the literature, it can be assumed that CSP reduces the riskiness of a company and therefore enhances CFP. Hence, it is hypothesized that H2: Corporate social
performance negatively affects firm risk and H3: Firm risk negatively affects corporate financial performance. Consequently, it is thought that firm risk might mediate the relationship between CSP
and CFP. CSP will negatively influence firm risk, which will then result in a positive effect on CFP. Therefore, the last hypothesis is that H4: The positive relationship between corporate social
performance and corporate financial performance is mediated by firm risk.
Conceptual model
Methods
Sample
The sample contains 66 US-listed firms, which have been analysed for a period of 6 years, namely between 1-1-2005 and 31-12-2010. This time period was chosen because the financial crisis in 2008 should make it easier to see which companies move along with the market and which companies do not. In this study, the market is the Standard & Poor’s 500 (S&P 500), which was used together with the realized returns of the companies within the chosen time period to measure firm risk. Due to some missing financial variables the final sample consists of 324 observations. The selection criteria for the companies was their major sic group, which gave the possibility to only select industries that have a strong influence and a high reliance on the environment and on society. This includes all industries from the agriculture, forestry, fishing and mining division. From the manufacturing division only the food and kindred, textile mill, lumber and wood, paper and allied, rubber and miscellaneous
plastics, stone, clay, glass and concrete industries were selected. The corresponding major sic groups are 1-14, 20, 22, 24, 26, 30 and 32.
The necessary data was provided by Wharton Research Data Services (WRDS), which is a research platform and business intelligence tool. WRDS is composed of independent sources that specialize in specific historical data, some of these sources are CRSP, S&P Global Market Intelligence, Compustat and the KLD database.
Measurements
Dependent variable Corporate Financial Performance
Accounting and market data for the firms were obtained from Standard and Poor’s Compustat, which includes accounting information of public firms reported to the Securities and Exchange Commission (SEC). Compustat provides data about all the financial variables which are used in this research to measure CFP, these variables are; return on assets (ROA) and market value (MV). The return on assets is the net income divided by the total assets and the market value is the product of the annual closing price times the shares outstanding. With these variables it is possible to give an indication of CFP, ROA and market value will be used as measurements of CFP in order to answer the research questions.
Independent variable Corporate Social Performance
In this paper the level of CSP will be based on data provided by the Kinder, Lydenberg, Domini & Co., Inc. (KLD) social performance dataset. KLD evaluates companies along a wide range of social
performance indicators and is a social investment and screening firm. KLD evaluates the members of the S&P 500 on several social performance indicators and these evaluations are widely used in the financial industry. The social performance indicators are organized into two categories, qualitative issue areas and controversial business issues. The controversial business issues are related to nuclear power, tobacco, alcohol, gambling and military concerns. This paper does not focus on controversial industries, so controversial business issues will not be taken into account. KLD uses seven qualitative issue areas, which are split into two components: strengths and concerns. These areas are: the environment (pollution, recycling, etc.), the community (charities, community engagement, etc.), the product (product quality and safety, etc.), diversity (women and minority contracting, gay and lesbian policies, etc.), employee relations (union relations, health and safety, etc.), human rights (human rights policies, etc.), and governance (governance structure, business ethics, etc.). The KLD database also provides a count for the total number of concerns and the total number of strengths for a specific firm in a particular qualitative issue area each year. These total scores will be used in this research.
Graves and Waddock (1994) stated that the KLD data is the best single source of social and
environmental performance data because the people who rate are well-informed and not connected to any of the rated companies or to researchers carrying out studies. Therefore, KLD provides
exclusive access to a vast range of consistently rated firms over several social performance indicators.
In past literature, authors created a new variable in which they subtracted the average concerns from the average strengths. Unfortunately, the assumption that each strength category and each
concern category are equal is not correct. It is not empirically verifiable that one is adding or subtracting equals (Mattingly & Berman, 2006).
To calculate an annual KLD score, the total strengths of the seven qualitative issue areas are added together. The total number of strengths of all seven areas and the total environmental strength scores will both be used as a measure of CFP in order to answer the research questions.
Mediating variable Firm Risk
Highly leveraged firms and financial stocks tend to be less protected against negative economic conditions, while for example supermarkets are relatively better protected. In contrast to systematic risk, firm-specific risk is particular to a firm. Because an investor can diversify away firm-specific risk, it is only the systematic risk that is a variable of the required rate of return, and therefore the cost of capital in the Capital Asset Pricing Model (CAPM) developed by Sharpe (1964). The relationship between systematic risk and the cost of capital is a function of the risk free rate, the expected return of the whole market and the beta of the stock. Beta stands for the volatility of the stock in relation to the market and thereby indicates the amount of exposure to systematic risk. Re = rf + β (rm − rf ) (Sharpe, 1964). Re stands for the cost of capital, rf for the risk-free rate, β for the beta of the stock and rm for the expected return of the whole market. Beta (β) is the covariance of the return of the market with the individual common stock return of a company divided by the variance of the market (Sharpe, 1964).
According to Feldman et al. (1997) a reduction of the cost of equity by a reduction of firm risk is established by a lower beta. The firm can achieve this by implementing changes that increase the flexibility of a company to handle economic dips. A company could for example change its operations is such a way that there are less toxic inputs required. If there is an economic dip and the firm can no longer change its operations, the firm would be less affected by price increases due to its reduced inputs. By doing so, the fluctuation of financial performance of the company would be reduced, which would likely reduce its beta, lower the cost of equity capital and therefore possibly enhance financial performance.
Different studies have tried to assess the relationship between CSP and beta as indicator of firm risk. Orlitzky and Benjamin (2001) found an overall negative correlation. McGuire et al. (1988) also found a negative, although weak relationship between CSR and beta. Feldman et al. (1997) found a positive relationship between measures of environmental activities and TRI emissions on firm beta and stock price
In order to calculate the annual beta for each company, realized returns and stock market returns were needed. The daily realized returns and the daily stock market returns were obtained from Standard and Poor’s Compustat. The calculated annual betas are used as measure of firm risk in the analyses. With this measure, it is possible to compare firm risk with CSP and CFP and answer the research questions.
Control variables
Regarding control variables, the literature suggests that there are three variables most likely to influence cost of capital and thereby firm risk. These variables are financial leverage, industry and firm size (Gebhardt, Lee & Swaminathan, 2001; Sharfman & Fernando, 2008; Bansal, 2005). Different
industries could have contrasting levels of firm risk and CSP, which would result in a false correlation. In order to prevent this false correlation, it is important to control for industry (Sharfman &
Fernando, 2008). According to Bansal (2005) larger firms will probably be more engaged in CSR activities because they attract more stakeholder attention and generally have more resources. In this study these three variables will also be used as control variable and the same measures are taken to calculate them. Firm size is calculated by LOG (amount of employees) and financial leverage is the total debt divided by the stockholder’s equity. The information necessary to calculate the control variables was also obtained from Compustat. The industry effects can be investigated in different ways. Authors regularly use the Standard Industrial Classification (SIC) code, which classifies the industry as a categorical variable. The two-digit SIC codes were also found on Compustat and there are 11 different SIC codes in the sample. With the use of SPSS Statistics, it was possible recode the codes into a categorical variable of eleven categories, which could then be used in the analyses.
Analytical method
First the social performance data from KLD and financial data from Compustat, including net income, total assets, amount of employees, annual closing price, shares outstanding, total debt, stockholder’s equity and sic groups was merged on the basis of available ticker and firm name. Hereafter, the annual company betas were separately calculated with the use of the realized returns of the
companies in the sample and the realized returns of the S&P 500. This was included into the merged file, which then had all the information needed to analyse the hypotheses. In order to analyse the data SPSS statistics was used. The next step was to create new variables in SPSS with the use of the financial data. The new variables were; return on assets, market value, total KLD strengths, firm size, financial leverage and industry. After this, it was possible to run the different analyses.
According to Baron and Kenny (1986), to test for mediation, three regression equations will have to be estimated;
1. Regression of the mediator on the independent variable
2. Regression of the dependent variable on the independent variable
3. Regression of the dependent variable on both the independent variable and on the mediator.
Because the independent variable is assumed to cause the mediator, these two variables should be correlated. Variables function as a mediator when variations in levels of the independent variable significantly account for variations in the dependant variable, variations in levels of the independent variable significantly account for variations in the mediator, variations in the mediator significantly account for variations in the dependent variable and when these paths are controlled, a previously significant relation between the independent and dependent variables is no longer significant, with the strongest mediation occurring when this relation is zero. If this is the case, there is evidence for a single mediator. If it is not zero, there are probably more mediating factors.
In order to answer the first hypothesis, the relationship between CSP and CFP will be tested with a regression analysis. Companies who score high on CSP are expected to perform better financially then companies who score low on CSP. With a second regression analyses it is possible to investigate the relationship between CSP and firm risk, which answers the second hypothesis. The prediction is that there is a negative relation between CSP and firm risk, so companies that score high on CSP will
face relatively less firm risk. In order to answer the third hypothesis, a third regression analyses will examine the relationship between firm risk and CFP. Companies with low risk are expected to perform better financially then companies with high risk. A fourth regression analyses answers the last hypothesis and investigates if the mediating effect of firm risk on the relationship between CSP and CFP describes a more significant relationship compared to the relationship between CSP and CFP when there is no mediator. The prediction is that the effect of CSP on CFP is greater when it goes through firm risk then when it goes directly from CSP to CFP. This paper assumes that firm risk acts as a mediator, but it does not assume that firm risk is the only mediating factor, therefore it is expected that firm risk will significantly decrease the relationship between the independent and dependent variable, but it will not be zero.
Results
Descriptives & Correlations
The means, standard deviations and the relevant correlations between the different variables used to answer the hypotheses are presented in table 1. Although there was no reason to think that the results could be affected by linear dependencies across the independent variables, it was a
possibility, therefore a collinearity diagnostic was calculated for each equation. The VIF statistics for each independent variable were all between 1.0 and 1.8 and shows that there is no variable that has an influence on the results due to multicollinearity. Most variables behaved as expected, there was a positive relationship found between total strengths and ROA, r (324) = 0.162, p = .003, also between total strengths and market value, r (324) = 0.584, p = .000. Between total strengths and beta there was indeed a negative relationship found, r (324) = -0.377, p = 0.000 as well between beta and ROA, r (324) = -0.197, p = .000. Between beta and market value there was also a negative relationship r (324) = -0.257, p = .000. With total environmental strengths as measure of CSP instead of total strengths the effects were slightly lower except for the industry effect which is slightly higher. The relationship between total environmental strengths and market value is significant, r (324) = 0.410, p = .000, as is the negative relationship between total environmental strengths and beta, r (324) = -0.137, p = .013. It was expected to find stronger effect with the variable total strengths, because it is based on several qualitative issue areas that can potentially influence CFP and firm risk, whereas total environmental strengths is only based on the environment. Unexpectedly, there was an
insignificant relationship found between total environmental strengths and ROA, r (324) = -0.006, p = .917. These correlations show that the effects of the independent variables on market value will probably be larger than the effects on ROA. This conforms with the research of Allouche and Laroche (2005) where accounting-based measures are found to be less highly correlated with CSP than market-based measures of CFP.
Looking at the control variables, firm size has significant correlations with all variables used in this study. For the variable market value this is not strange since larger firms typically make greater profits, r (324) = 0.542, p = .000. Firm size has the highest significant correlations with total strengths,
r (324) = 0.604, p = .000 and total environmental strengths, r (324) = 0.480, p = .000, suggesting that
larger firms have higher CSP scores. This seems logical, since larger firms generally have more capital and resources to invest in CSR activities and therefore CSP. Unexpectedly, firm size significantly correlates with ROA, r (324) = 0.245, p = .000, which should not necessarily be higher for larger firms. On the other hand, market value and ROA also have a significant correlation, r (324) = 0.360, p =
.000, suggesting that firms with high market values also have high ROA and it is shown that firm size does affect market value. Leverage is only significantly correlated with firm size, r (324) = 0.113, p = .043 and industry, r (324) = 0.114, p = .039. The industry variable is positively correlated with total strengths, r (324) = 0.184, p = .001, total environmental strengths, r (324) = 0.218, p = .000 and firm size, r (324) = 0.327, p = .000, suggesting that industry does influence the level of CSP and firm size. The correlations above indicate whether something will be found in the main analyses, which follows next. The data was analysed using hierarchical regression in order to test the improvement of the theoretical variables over the control variables. First there will be two regression models, one with market value as dependant variable and total strengths as independent variable and one with market value as dependent variable and total environmental strengths as independent variable. Hereafter, there will be two more regression models with in both ROA as dependant variable and again one with total strengths as independent variable and one with total environmental strengths as independent variable.
Table 1. Descriptives and correlations between the variables.
M SD 1 2 3 4 5 6 7 1. Market Value 12909.62 25000.37 2. ROA 0.0606 0.07100 .360** 3. Total Strengths 2.5864 3.48041 .584** .162** 4. Tot. Environ. Strength 0.546 1.0082 .410** -.006 .815** 5. Beta 1.165694 0.517346 -.257** -.197** -.377** -.137* 6. Firm Size 0.8211 0.70674 .542** .245** .604** .480** -.370** 7. Leverage 0.9537 4.12959 -.048 -.077 .011 .046 -.011 .113* 8. Industry 18.614 6.50 -.103 -.085 .184** .218** -.087 .327** .114* Note. N=234, *p<.05. **p<.01.
1. Market Value as CFP measure and Total Strengths as CSP measure
As predicted, the first regression with an explained variance of forty-eight percent, revealed that CSP does affect CFP (β= 0.391, p = 0.000, R²= 0.486). This is 9.7 percent more than the variance explained by the control variables (R²= 0.389) and shows that companies who have high total strength scores have a higher market value. (Baron and Kenny step 1).
As expected, the second regression with an explained variance of seventeen percent demonstrated that CSP does affect firm risk (β= -0.240, p = 0.000, R²= 0.175). This is 3.6 percent more than the variance explained by the control variables (R²= 0.139) and indicates that companies with high total KLD strength scores generally have a lower beta (Baron and Kenny step 2).
Surprisingly, the negative effect of firm risk on CFP (β= -0.050, p = 0.291, R2 = 0.384) is weak and
insignificant. This means that companies with low beta’s do not have a higher market value then companies with a high beta. Therefore, firm risk does not negatively affect corporate financial performance (Baron and Kenny Step 3).
Because the effect of firm risk on market value was insignificant, there is no need to conduct the fourth analyses that tests for mediation. This demonstrates that firm risk does not mediate the relationship between CSP and CFP, because one of the theoretical assumptions does not hold. All models can be found in table 2 (Baron and Kenny step 4).
Table 2: Regression results
CFP measured in Market Value Model 1
Model 2 Model 3 Dependant variable CFP Firm risk CFP 1 Independant
variable Coefficient SE Beta Coefficient SE Beta Coefficient SE Beta
Constant 13108.520** 2905.810 1.348** 0.071 13108.520** 2905.810 Firm size 23071.733** 1640.301 0.652 -0.282** 0.040 -0.385 23071.733** 1640.301 0.652 Leverage -522.098 267.054 -0.086 0.004 0.007 0.028 -522.098 267.054 -0.086 Industry -3194.573** 483.669 -0.306 0.008 0.012 0.036 -3194.573** 483.669 -0.306 R² 0.389 0.139 0.389 2 Constant 12453.595** 2671.086 1.357** 0.070 16349.666** 4224.453 Firm size 14582.337** 1862.938 0.412 -0.174** 0.049 -0.238 22394.428** 1760.774 0.633 Leverage -387.652 245.972 -0.064 0.002 0.006 0.014 -513.671 267.125 -0.085 Industry -3155.625** 444.405 -0.303 0.007 0.012 0.034 3175.900** 483.903 -0.305 Total Strengths 2810.804** 362.599 0.391 -0.036** 0.010 -0.240 Beta -2403.748 2274.458 -0.050 R² 0.486 0.175 0.392 Note: N =234, *p<.05. **p<.01.
2. Market Value as CFP measure and Total Environmental Strengths as CSP measure
As predicted, the first regression with an explained variance of forty-two percent, revealed that CSP does affect CFP, even with only total environmental strengths scores as indicator (β= 0.219, p =
0.000, R²= 0.426). This is 3.7 percent more than the variance explained by the control variables (R²= 0.389) and shows that companies who have high total environmental strengths scores have a higher
market value. This also indicates that total strengths scores are a better predictor of market value then total environmental strengths scores.
Unexpectedly, the second regression was insignificant and demonstrated that if total environmental strength acts as CSP indicator, it does not affect firm risk, (β= 0.050, p = 0.398, R²= 0.141). This means that companies with high total environmental strengths scores do not generally have a lower beta and demonstrates that total strengths scores are a better predictor of beta then total environmental scores.
The third regression here is the same as in the last regression model. Because the effect of total environmental strengths on firm risk and the effect of firm risk on market value were insignificant, there is no need to conduct the fourth analyses that tests for mediation. Firm risk does not mediate the relationship between CSP and market value as measurement of CFP, because two of the
Table 3: Regression results
CFP measured in Market Value Model 1
Model 2 Model 3 Dependant variable CFP Firm risk CFP 1 Independant
variable Coefficient SE Beta Coefficient SE Beta Coefficient SE Beta
Constant 13108.520** 2905.810 1.348** 0.071 13108.520** 2905.810 Firm size 23071.733** 1640.301 0.652 -0.282** 0.040 -0.385 23071.733** 1640.301 0.652 Leverage -522.098 267.054 -0.086 0.004 0.007 0.028 -522.098 267.054 -0.086 Industry -3194.573** 483.669 -0.306 0.008 0.012 0.036 -3194.573** 483.669 -0.306 R² 0.389 0.139 0.389 2 Constant 13965.436** 2828.329 1.352** 0.072 16349.666** 4224.453 Firm size 19521.511** 1777.129 0.552 -0.299** 0.045 -0.408 22394.428** 1760.774 0.633 Leverage -504.373 259.375 -0.083 0.004 0.007 0.029 -513.671 267.125 -0.085 Industry -3352.115** 471.007 -0.321 0.007 0.012 0.033 3175.900** 483.903 -0.305 Total Environmental Strengths 5419.592** 1202.679 0.219 0.026 0.030 0.050 Beta -2403.748 2274.458 -0.050 R² 0.426 0.141 0.392 Note: N =234 *p<.05. **p<.01.
3. ROA as CFP measure and Total Strengths as CSP measure
Surprisingly, the first regression was insignificant and revealed that CSP does not significantly affect CFP with ROA as CFP measure (β= 0.010, p = 0.877, R²= 0.099). This means that companies with high total strengths scores do not experience higher return on assets.
The effect of total strengths on firm risk has already been discussed in the first regression model and showed that companies with high total strengths have a lower beta. As anticipated, the third
regression with a variance of eleven percent showed a negative effect of firm risk on CFP (β= -0.113,
p = 0.048, R2 = 0.110). This is 1.1 percent more than the variance explained by the control variables
(R²= 0.099) and indicates that companies with low beta’s have a higher return on assets then companies with a high beta. Therefore, firm risk negatively affects corporate financial performance. Because the effect of total strengths on ROA was insignificant, there is again no need to conduct the fourth analyses that tests for mediation. All models can be found in table 4.
Table 4: Regression results
CFP measured in ROA Model 1
Model 2 Model 3 Dependant variable CFP Firm risk CFP 1 Independant
variable Coefficient SE Beta Coefficient SE Beta Coefficient SE Beta
Constant 0.067** 0.010 1.348** 0.071 0.067** 0.010 Firm size 0.031** 0.006 0.313 -0.282** 0.040 -0.385 0.031** 0.006 0.313 Leverage -0.002 0.001 -0.092 0.004 0.007 0.028 -0.002 0.001 -0.092 Industry -0.005** 0.002 -0.177 0.008 0.012 0.036 -0.005** 0.002 -0.177 R² 0.099 0.139 0.099 2 Constant 0.067** 0.010 1.357** 0.070 0.088** 0.015 Firm size 0.031** 0.007 0.307 -0.174** 0.049 -0.238 0.027** 0.006 0.270 Leverage -0.002 0.001 -0.091 0.002 0.006 0.014 -0.002 0.001 -0.088 Industry -0.005** 0.002 -0.177 0.007 0.012 0.034 -0.005** 0.002 -0.173 Total Strengths 0.000 0.001 0.010 -0.036** 0.010 -0.240 Beta -0.016* 0.008 -0.113 R² 0.099 0.175 0.110 Note: N =234 *p<.05. **p<.01.
4. ROA as CFP measure and Total Environmental Strengths as CSP measure
Unexpectedly, the first regression with an explained variance of eleven percent, revealed that CSP negatively affects CFP (β= -0.149, p = 0.014, R²= 0.116). This is 1.7 percent more than the variance explained by the control variables (R²= 0.099) and demonstrates that companies with low total environmental strength generally have a higher return on assets.
The effect of total environmental strengths on beta has already been discussed in the second regression model. The third model here is the same as in the last regression model, so it also needs no further explanation.Because the effect of total environmental strengths on beta was insignificant, there is no need to conduct the fourth analyses that tests for mediation. All models can be found in table 5.
Table 5: Regression results
CFP measured in ROA Model 1
Model 2 Model 3 Dependant variable CFP Firm risk CFP 1 Independant
variable Coefficient SE Beta Coefficient SE Beta Coefficient SE Beta
Constant 0.067** 0.010 1.348** 0.071 0.067** 0.010 Firm size 0.031** 0.006 0.313 -0.282** 0.040 -0.385 0.031** 0.006 0.313 Leverage -0.002 0.001 -0.092 0.004 0.007 0.028 -0.002 0.001 -0.092 Industry -0.005** 0.002 -0.177 0.008 0.012 0.036 -0.005** 0.002 -0.177 R² 0.099 0.139 0.099 2 Constant 0.065** 0.010 1.352** 0.072 0.088** 0.015 Firm size 0.038** 0.006 0.382 -0.299** 0.045 -0.408 0.027** 0.006 0.270 Leverage -0.002 0.001 -0.094 0.004 0.007 0.029 -0.002 0.001 -0.088 Industry -0.005** 0.002 -0.166 0.007 0.012 0.033 -0.005** 0.002 -0.173 Total Environmental Strengths -0.010 0.004 -0.149 0.026 0.072 0.050 Beta -0.016* 0.008 -0.113 R² 0.116 0.141 0.110 Note: N =234 *p<.05. **p<.01.
Discussion
Summary, key findings and unexpected results
The main goal of this study was to investigate if CSP will increase CFP, if CSP influences firm risk and in particular if firm risk mediates the relationship between CSP and CFP. With the results of all four regression models the hypotheses can be answered. The first hypothesis, which stated that CSP positively affects CFP can only be supported if market value is used as CFP measure. Because
companies that invest in CSR activities are generally larger companies with more available capital and therefore a higher market value, it is understandable that the effects are clearer with market value as CFP measure. This is supported by recent studies of Orlitzky et al. (2003), Margolis et al. (2009) and Bansal (2005).Still, it was unexpected to find no significant result between CSP and ROA as CFP measure. Even more unexpected was the result of the relationship between total environmental strengths and ROA, which is significantly negative, although the explained variance is only 1.7 percent more than the variance explained by the control variables. The results are not in line with the results of studies by Fombrun et al. (2000), King and Lenox (2002) and Malik (2015) where CSP enhances accounting measures of CFP and CSP can function as a buffer against losses and therefore guard the assets of a firm. The results in this study suggest that companies with low environmental strengths have higher returns on assets. A reason could be that companies low in total
environmental strengths do not use capital from their net income to improve their environmental performance, if companies do so then their return on assets will probably decrease. This is in line with the theory developed by Friedman (1970), who stated that everything besides shareholder wealth maximization destroys value and leads to a competitive disadvantage. He predicted a
negative relationship between CSP and CFP, which confirms these results. The results of the first hypothesis reveal that CSP positively affects market value, CSP does not affect return on assets but environmental CSP negatively affects return on assets.
The second hypothesis stated that CSP negatively affects firm risk, the results indicate that this hypothesis can only be supported if total strengths is used as CSP measure. When total
environmental strengths are used this relationship becomes insignificant. This was an unexpected result and suggests that not environmental strengths but another qualitative issue area of the KLD data has a significant relationship with firm risk. This is different than the results of Sharfman and Fernando (2008), who found that environmental CSR reduces cost of capital and because firm risk is one of the underlying variables of cost of capital it should also reduce firm risk. Apparently not environmental CSR but another form of CSR activities influences firm risk. One way to solve this problem is to analyse the qualitative issue areas of the KLD data separately instead of combining them into a single variable, in this study the variable total strengths. Analysing the issue areas separately makes it able to determine what the effect is of each issue area on firm risk. The outcomes with total strengths as CFP measure match the findings of Feldman et al. (1997), who reported that CSR activities should lower the risk of a company, because those companies are better equipped against changes in the market and environment. Orlitzky and Benjamin (2001) found that high corporate social performance relates to low financial risk. It also corresponds with other papers who analysed the effect of CSP on firm risk and found that an important mechanism through which CSP affects CFP is the effect of CSP on firm risk (McGuire et., 1988; Starks, 2009; El Ghoul et al., 2011). The stakeholder theory is also supported because CSP decreases firm risk (Freeman, 1984; Waddock & Graves, 1997). The results of the second hypothesis are in line with the literature and demonstrate that CSP negatively affects firm risk, but environmental CSP does not affect firm risk. The third hypothesis, which stated that firm risk negatively affects CFP is also only partly supported. With ROA as CFP measure the hypothesis can be supported, although the effect is barely significant at a five percent level and only explains 1.1 percent more than the variance explained by the control variables. With market value as CFP measure the hypothesis has to be rejected because the
relationship becomes insignificant. This is different than the results of Orlitzky and Benjamin (2001) who found that CSP can reduce risks and lower risks make the expectations of the future cash flows of a firm more certain and reliable, which can increase the value of the firm. Because the
expectations of future cash flows are embedded in the stock price, the effect on market value was expected to be significant. Allouche and Laroche (2005) stated that the use of accounting-based measures leads to greater reported effects, but in this study the market-based measure is not
smaller but insignificant. The results of the third hypothesis partly differ from the literature and show that firm risk negatively affects return on assets but it does not affect market value.
The last hypothesis stated that firm risk mediates the relationship between CSP and CFP. This hypothesis clearly has to be rejected, because none of the four regression models meet the necessary requirements for mediation. These necessary requirements are that the first three hypothesis have to be significant before the last hypothesis can be tested. The lack of finding a mediation effect could be because of a methodological choice or because of the chosen industries. With a different sample, timeline, measurement of firm risk and measurement of CFP it could still be possible to find a significant mediating effect. The chosen industries could also play a role, maybe the chosen industries differ too much, which will have a negative influence on the results. Another
possibility is that for the industries in the sample firm risk just does not influence the relationship between CSP and CFP, but this is in contrast with the literature. Because the results show large differences between measurements, it is believed that the lack of finding a mediating effect is because of the methodological choices made earlier in this study.
As expected, the total strengths measure of CSP functions as a better predictor then total environmental strengths, because it holds more qualitative issue areas that influence CFP. This is shown in the results by a higher explained variance and larger significant effect. The regression models with ROA as CFP measure all demonstrated lower explained variances then the models where market value acted as CFP measure. Reviews of Margolis et al. (2009) and Orlitzky et al. (2003) reported that accounting measures tend to show larger correlations between CSP and CFP then market measures. In this study the reported effects and the correlations of the market-based measures are larger, which is different than the results of the studies mentioned above.
Limitations
The largest point of critique is that studies use many different approaches to determine CSP and CFP, which makes them difficult to compare, especially with the CFP measures there is a large variety of possible measurements. Many studies have used accounting-based measures such as return on assets or return on equity and although such measures are helpful, they look backwards and their objectivity and informational value can be questioned. Stock market measures on the other hand are forward looking with expectations of future cash flows embedded within the stock price, and they are more relevant for considering the implications of CSR for investors. Another argument in favour of using expected returns rather then realized returns is the fact that environmental performance probably affects future cash flows and the risk of these cash flows. The downside however is that expected returns are prone to uncertainties. Although this paper used both methods, a universal method to measure CFP would make the results of different papers more comparable (Orlitzky et al., 2003; Margolis et al., 2009).
Another point of critique is that there are different ways to determine firm risk, such as the Fama-French three factor (1993) model, the Carhart (1997) four factor model and Arbitrage Pricing Theory models. The CAPM model assumes that there is only one systematic risk factor, which is the risk that is captured by beta (β). Even though the other models are different, they all have the same
underlying theoretical assumption that with diversified portfolios, only systematic risk affects expected returns, which indicates that markets are not influenced by firm-specific risk. Firm-specific risks are not reflected in the expected cost of capital; they are carried out in expected future cash flows. Therefore, the firm-specific risk of the impact of any CSR activity will appear as positive or negative impacts in the expected cash flows, which does not influence the expected cost of equity capital. In future risk models the measure used to indicate firm risk should take firm-specific risk into account and use expected cash flows as a measure in order to give a better overview of the
consequences of CSR activities.
According to Griffin and Mahon (1997), the results for measuring CSP and CFP can hide individual differences due to the specific situation of an industry. Therefore, it is possible that the
methodological choice to include different industries in the sample just because they all depend and influence the environment was incorrect. There could still be large differences between these industries which are now difficult to see.
Positive points
While papers such as Sharfman and Fernando (2008) focus on one qualitative issue area of KLD, the environment, this paper has a more overall approach and examines the combination of all qualitative issue areas provided by KLD. These seven dimensions are community, diversity, employee relations, the environment, human rights, product characteristics and corporate governance.
Another positive point is that most papers have a cross-industry design, while this paper really focusses on industries that are connected. Future investigations must consider the negative effects of a cross-industry design, because there are large differences between industries, which influence the results.
Practical implications
The relationship between CSP and financial risk is potentially important for managers and investors. Mainly for managers and executives who want to reduce the uncertainty of the performance of their business, it might be useful to know if improving the social performance of the company will increase or decrease the uncertainties of future firm performance.
Further research
In order to improve this research, it would be helpful to find more realized returns of the companies in these industries, which could enlarge the sample. This could be achieved by including more industries and by changing the timeline, which should increase the amount of companies and observations. Another possibility would be to find a different database, which has more realized returns of companies within certain industries. The results of the second hypothesis show that analysing the qualitative issue areas of the KLD data separately might give helpful information about which activities lower firm risk. It was against expectations to see that the total environmental strengths did not have any significant effect on firm risk and it would be interesting to see which other qualitative issue areas of the KLD data have an influence on firm risk and financial
performance. For business practices this could be of high value and should therefore be considered in future research. Another improvement would be the use of different measurements of firm risk, more measurements of firm risk would strengthen this study. Because there could also be industry specific characteristics, it would be valuable to really look at one particular industry, the only complication would then be the probably small sample size. If it is possible to find a respectable sample size of just one industry, it could also enrich this research.
The correlation and regression results have shown that firm size has a large influence on all variables used in this study, in the future it would be interesting to analyse the influence of firm size on the relationship between corporate social performance and corporate financial performance.
For most companies attracting good employees is critical for their financial performance. According to Turban and Greening (1997), firms high in CSP may attract better employees. For future research it would be interesting to investigate the importance of CSP for employee recruitment and to look at the differences across industries.
Although there has been extensive literature on the relationship between CSP and CFP, there is still a large gap between the literature and the actual ways in which managers or executives can assess the
impact of CSP of their own firm. In order to do so practitioners and academics need to work together and more research is necessary to provide companies with practical information about this subject.
Conclusion
The assumption was that companies high on CSP would experience higher CFP, because it improves the satisfaction of different stakeholders, which leads to better financial performance. The results back the stakeholder theory developed by Freeman (1984) and reveal that CSP positively affects market value. However, CSP does not seem to affect return on assets and environmental CSP negatively affects return on assets, supporting the shareholder approach of Friedman (1970).
Regarding firm risk, it is negatively affected by CSP, but not by environmental CSP. This reinforces the theories of McGuire et al. (1988) and Orlitzky and Benjamin (2001), where CSP lowers firm risk. Firm risk negatively affects return on assets, however it does not affect market value. This does not conform with the study of Orlitzky and Benjamin (2001) where lower risks make the expectations of the future cash flows of a firm more certain and reliable, which increase the value of the firm. Some of the results contradict and at the same time agree with the findings of Allouche and Laroche (2005), who reported that by using different measurements of CSP and CFP it is inevitable to find different outcomes, still accounting-based measures should report greater effects. There was no mediation effect found, but because the results show large differences between measurements, it is believed that the lack of finding a mediating effect is because of the methodological choices made. More research has to be done to fully understand the relationship between CSP and CFP, the inconsistent findings could be the effect of too many influential variables on this relationship (Orlitzky et al., 2003; McWilliams & Siegel, 2000). Although the results were not uniform, scholars can build upon this industry specific analyses of consequences of CSP on CFP in an industry where environmental concerns and changing customer expectations have a large influence on business strategy. Furthermore, for managers trying to reduce the uncertainty of company performance it is helpful to know the consequences of CSP.
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