The effect of corporate social responsibility on
the financial performance in the financial sector
of the S&P 500.
A post-crisis empirical research
Abstract
This paper studies the effect of corporate social responsibility (CSR) on the financial performance (FP) of a company within the financial sector of the S&P 500 between 2012 and 2018. The Governance & Accountability Institute (G&A) shows that 86% of the S&P 500 companies published a sustainability report in 2018. In 2011 this was only roughly 20%. Despite the growing importance of CSR, the effect of CSR on FP remains yet unclear. The findings of this empirical study imply a positive correlation between the financial performances of a firm and the CSR score. This is examined and found statistically significant, based on the return on equity (ROE), return on assets (ROA) and Tobin’s Q.
Keywords: Corporate social responsibility, financial performances, S&P 500, financial sector, ROE, ROA, Tobin’s Q
Name Joeri Schrauwen
Student number 11339004
Program Economie en Bedrijfskunde
Track Finance and Organization
Field Finance
Number of credits thesis 12
Supervisor Richard Evers
Statement of Originality
This document is written by Joeri Schrauwen who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Inhoudsopgave
1 Introduction ... 4
2 Literature review ... 5
2.1 Defining corporate social responsibility ... 5
2.2 Measurement of corporate social responsibility ... 6
2.3 Measurement of Financial Performance ... 7
2.4 Research on the CSR-FP relationship ... 8
2.4.1 Theoretical research on the CSR-FP relationship ... 8
2.4.2 Empirical research on the CSR-FP relationship ... 10
2.5. Hypothesis ... 10
3 Methodology ... 11
3.1 CSR-score database ... 11
3.2 Financial performance measure ... 12
3.3 Model ... 13 3.4 Control variables ... 13 3.5 Data ... 14 3.6 Reliability of results ... 14 4. Data analysis ... 15 4.1 Descriptive statistics ... 15 4.2 Data results ... 16 4.3 Regression results. ... 17 4.4 Robustness check ... 19
5. Conclusion & discussion ... 20
5.1 Conclusion ... 20
5.2 Limitations and additional research ... 20
Reference list ... 22
1 Introduction
The Governance & Accountability Institute (G&A) shows that 86% of the S&P 500 companies published a sustainability report in 2018. In 2011 this was only roughly 20%. This shows growth in importance and interest of corporate social responsibility (further on mentioned CSR) within companies. This is one of the signs that CSR is becoming increasingly relevant over the years and with global warming or for example that we are running out of fossil fuels, it will become one of the more important aspects of a company in the nearby future (Ehrgott, Reimann, Kaufmann, & Carter, 2011).
Although there is an importance of CSR for companies, it is still not sure whether a good CSR-score has a positive outcome on the corporate financial performance (FP) of a company. The growing importance of CSR is consistent with the growing literature about CSR. Despite this growing literature, there are different outcomes and therefore it is still controversial whether there is a positive or negative relationship. Lopez et al. (2007) found a negative relationship between CSR and FP, as did Hassel, Nilsson & Nyquist (2011). Peters and Mullen (2009), Waddock and Graves (1997) and Tsoutsoura (2004) on the other hand show a positive relationship between CSR and FP.
With the yet uncertain effect of CSR on the financial performance of a company and the upcoming importance of CSR this is a relevant topic for research. To contribute to existing literature this research focusses on the study of this relationship within the financial sector of the S&P 500, existing of 66 companies, because there is limited to no research within this sector (Wu and Shen, 2013). There are other studies to CSR within the finance sector but they do not focus on the relationship between CSR and FP. Simpson and Kohers (2002) do present a research with data from the finance sector to CSR but do not pursue the relationship with FP. The study of Chih et al. (2010) concentrates on which firms within this sector implement CSR policies and Cuesta-González et al. (2006) focus on the social performances of Spanish companies within this sector but again do not examine the relationship with the financial performances. While multiple studies have been conducted regarding this relationship, empirical studies within this sector are rare (Wu and Shen, 2013). Therefore, the research question is: “What is the effect of corporate social responsibility on the corporate financial performance within the financial sector of the S&P 500 between 2012 and 2018?”
The CSR-score is subtracted from the ASSET4 database by Thomson Reuters. The effect on the financial performances of a firm is measured with an accounting-based measure and with a market-based measure: the return on assets and return on equity are used as accounting-based measures and as market-based measure Tobin’s Q is used. The financial data
is subtracted from COMPUSTAT. Both databases are in line with the research of Inoue and Lee (2011), who studied the effect of CSR on FP within the tourism industry.
In the following section the existing literature on the relationship between CSR and FP are discussed. The third section includes the methodology of this research and contains the used database, the used model and its control variables. In the subsequent section the data is analyzed. Finally, in the last section the conclusion is provided together with the limitations and suggestions for follow-up studies.
2 Literature review
With an increasing number of existing literatures on the relationship between CSR and FP, there is still uncertainty regarding definitions and outcomes. First different ways of measuring and defining CSR and FP are discussed in the literature review. Subsequently, existing theories and empirical research are shown. The hypothesis is the last paragraph in the literature review.
2.1 Defining corporate social responsibility
Even though CSR has been studied for years and has a growing database of literature, no general definition for this term has been made yet (Matten & Moon, 2008). According to Matten and Moon (2008), CSR varies widely varies in definitions of its underlying meanings and how these terms are being used within context. One of the causes of not having a similar outcome in the different studies could be the due to the absence of a general definition for CSR. As a result Dahlsrud (2008) has illustrated all the definitions of CSR being used in existing literature. This research resulted in 37 different definitions of CSR.
According to Van Marrewijk (2003), a successful method is to define CSR by making it context specific for each business, however, this is less useful for a general definition. But Van Marrewijk (2003) and Kim and Ramos (2018) produced a concept of CSR which include three major perspectives; shareholders, stakeholders and the societal approach.
The shareholders approach, according to Friedman (1962) and Zenisek (1979), emphasizes that the responsibility of a corporation should be narrowed down to only maximizing its firms profit. Hence, this theory is referred to as shareholders approach. They state that investing the shareholders profits in protecting or improving society will not be fair to them. In addition to this, Van Marrewijk (2003) claims that socially responsible activities should not be the responsibility of corporations, but it should be the responsibility of the government.
According to the stakeholders approach, Freeman (1984) says that corporations also have an obligation to the stakeholders who are involved within the actions of the corporation, instead of just to the shareholders. This includes investors, customers, employees, communities, political groups, suppliers, trade associations and governments (Donaldson and Preston, 1995). The correct way of operating a business, according to Benn et al. (2010), is by resolving their concerns and meeting their ethical needs together with the stakeholders to create value for the company. The stakeholders approach is the most used theory to explain CSR (Rodgers et al., 2013).
The societal approach, also known as the broader view on CSR, is a contradiction of the shareholder approach. Companies have a responsibility to the society as a whole. Companies operate by public consent and therefore they need to positively serve the needs of the society (Van Marrewijk, 2003). Laan et al. (2008) suggest moral principles have the upper hand within the decision-making process to meet the needs of society.
As mentioned, a general definition for CSR has not been set yet. Therefore, this research uses a certain approach to be the guideline for this research. Since the stakeholders approach is a fair compromise between of the societal and shareholders approach and because, according to multiple studies (e.g Platonova et al., 2018; Kakabadse et al. 2005), the stakeholders theory results in better financial performances it is used as guidance for a definition of CSR in this research.
2.2 Measurement of corporate social responsibility
Another result of the variety of definitions for CSR is the lack of a general measurement for CSR. As discussed by Graves and Waddock (1994) there has been multiple measurements used in existing literature and all methods have their own concerns, which gives room for discussion when it comes to which method is the best to measure CSR. According to Igalens and Gond (2005) studies show that on average five different measurement methods are used.
The first measurement is based on evaluation of the contents of annual reports (Igalens and Gond, 2005). These measurements are often used within accountancy studies that want to measure the social dimension of a specific discourse. According to Ullman (1985) this method focusses more on the social disclosure and not on CSR in particular. This measurement is performed by the company itself and therefore the measurement is subjective and easily prone to manipulation. (Igalens and Gond, 2005).
Pollution indices is the second method of measurement according to Igalens and Gond (2005). In contradiction to the first measurement this is an objective measurement because it is
performed by State entities who are independent of the company in question. However, this measurement method is limited by the fact that it only measures one of the dimensions of CSR, namely the environmental aspect. Furthermore, this method is only applicable and relevant to certain industries (Igalens and Gond, 2005).
Another measurement method is a perceptual measurement which is derived from questionnaire-based surveys done by an independent researcher who wants to gather information directly from the company (Igalens and Gond, 2005). In contrast to the pollution indices this method measures the multiple dimensions of CSR. However, the researcher’s perception plays a big part in the evaluation and this method can be manipulated depending on how the surveys are administered.
The fourth measurement method according to Igalens and Gond (2005) is the Corporate Reputation Indicators. The Corporate Reputation Indicators is the least used measurement of the five most used. This measurement is purely perceptual resulting from evaluations of people outside the firm (e.g financial analyst).
The last measurement method is from data produced by independent measurement organizations. This method measures the multiple dimensions of CSR with the extent of certain theoretical models which can be adjusted to each company because it depends on operation models and benchmarks for every industry (Igalens and Gond, 2005). However, Igalens and Gond (2005) state that a limitation of this method can be depending on the agencies operational halo effect. With a halo effect there is a tendency for an impression created in one area to influence the opinion in another effect.
With the most used method discussed above, Igalens and Gond (2005) conclude that the method with data produces by independent measurement organizations has the least limitations. Therefore, this measurement method is used in this research as well with the database ASSET4 by Thomson Reuters which is explained in more detail in paragraph 3.1.
2.3 Measurement of Financial Performance
There are two types of financial performance (FP) measures used in the researches on the Corporate Social Responsibility – Financial Performance relationship: accounting based (e.g Bragdon and Marlin, 1972; Heinze, 1976) and market-based measures (e.g Alexander and Buchholz, 1978; Anderson and Frankle, 1980). (Griffin and Mahon, 1997). Within these two types of FP measures, there is a wide variety.
With the accounting-based measures the idea is to concentrate on how company earnings respond to different management strategies like CSR (Cochran & Wood, 1984). The
accounting method uses historical performances to calculate the financial performances. Because the accounting-based method is focused on the earnings of a company, earning ratio’s like return on equity or return on assets are used to measure the financial performance (Cochran & Wood, 1984). According to Benston (1982) the used data is interpreted differently to the outsiders for each firm and therefore difficult to compare to each other. This questions the validity of the data and therefore market-based measures are more relevant and therefore a better method to calculate the FP.
For the market-based measures the idea is that the financial performance should be calculated from the perspective of the shareholders (Cochran & Wood, 1984). The market performance method often uses changes in the share price and the dividend income. According to Margolis et al. (2007) an event study should be used with most of the market-based methods, because these studies show a significant bigger impact on the CSR-FP relationship than other type of studies. According to Rodgers, Choy and Guiral (2007), Tobin’s Q is also an often-used market-based measure to calculate the financial performance. Tobin’s Q measures the growth of a company estimated by the market (Rodgers et al., 2007).
2.4 Research on the CSR-FP relationship
2.4.1 Theoretical research on the CSR-FP relationship
Despite an increasing number of researches on the relationship between CSR and FP of a firm, no clear relationship has been found yet. Several researches show a positive relationship between CSR and FP (Kohers and Simpson, 2002; Lee and Park, 2010; Peters and Mullen, 2009), negative relationship (Lopez et al., 2007; Hassel, Nilsson & Nyquist, 2011) or a non-linear relationship (McWilliam and Siegel, 2000; Aupperle et al. 1985).
As previously discussed in this research, the stakeholders approach is used to define CSR. This approach is also known as a strategy, where the company meets the concerns and demands of all stakeholders. With this strategy, a company will create essential assets with, for example, stronger relationship with customers. Creating stronger relationships via CSR can improve the corporation’s relationship amid customers, regulators, employee and suppliers (Carmeli et al. 2007; Brammer and Pavalin, 2006). Eventually these assets will lead to a better position compared to competitors, which can ultimately result in improved financial performances (Barney, 1991).
Some studies have found a positive relation between CSR and FP. Positive social performances and especially donations to good causes can reduce costs or improve revenues, which leads to greater financial performances (Navarro, 1988; Brammer and Millington, 2008).
These positive social performances may take some of the activities of promoting and advertisements away by reducing price sensitivity and increasing the demand for the products of companies (Sen and Bhattacharya, 2001). Positive social performances can reduce costs by improving productivity by employees (Moskowitz, 1972) or by reducing waste during processes (Konar and Cohen, 2001; Brammer and Millington, 2008).
On the other hand, several researches have found a negative relationship between CSR and FP (eg: Lopez et al., 2007; Hassel, Nilsson & Nyquist, 2011). In contradiction to the argument that Navarro (1988) states in favor of the CSR-FP relationship, neoclassical economics state that firms who are not actively with social performances have fewer costs and therefore, ceteris paribus, have higher profits in comparison to companies who do actively work on their social performances (Aupperle et al. 1985). The most critical argument for a negative relationship between CSR and FP is the principle-agent model (Jensen and Meckling, 1976). In this situation the owners or shareholders of the company are linked with the principal, and the senior managers are linked with the agent. While shareholders may want a good social performance, the managers want to maximizes their own utility. With little to no control from the shareholders over the managers, the managers will maximize their utility by actions which will not provide significant returns to companies (Navarro, 1988). Therefore, the principal-agent model predicts either good social performances, or good financial performances. This model predicts a negative relationship between social performances and financial performances.
Finally, non-linear relationships have also been found between CSR and FP (Brammer and Millington, 2008). Hillman and Keim (2001) state that financial implications with positive social performances “are contingent upon the scope or extent of social responsibility that a firm accepts.” They argue that positive social performances have a positive influence on the financial benefits of a company, but that this can cause social actions which are beyond the bounds of the firm’s interest and therefore the incline of good social performances can cause a decline in financial performances (Hillman and Keim, 2001). According to Brammer and Millington (2008), good financial performances are usually related to a very high or very low CSR score and consequently result in a non-linear relationship. This relationship is in line with the theory of Porter and Kramer (2006). This insinuates that competitive advantage usually comes with low cost or a good differentiation approach. By not pursuing good social performances and therefore not having a growth in the costs, a company may have a competitive advantage.
2.4.2 Empirical research on the CSR-FP relationship
As indicated previously in this research, there is no clear relationship yet between CSR and FP of a firm despite the number of studies which have been done. There have been a few meta-analysis to studies regarding this subject and these analyses gives a small but significant positive relationship between corporate social responsibility and the financial performance of a firm (e.g Margolis et al. 2007; Orlitsky et al, 2003).
According to Ruf et al. (2001) there are five causes why there are conflicting outcomes in the CSR-FP relationships studies. Four of these causes are due to methodological issues: there is no comprehensive measure of CSR, there is a lack of methodological consistency, there is a mismatch with the control variables and the sample size gives limitations. The fifth reason for conflicting outcomes is theoretical, where there is a lack of a theoretical foundation. Ruf et al. (2001) claim that by applying one of the three theories as discussed in paragraph 2.1, this problem is solved.
In the meta-analysis of Margolis et al. (2007) of 192 studies, a small positive effect has been found on the CSR-FP relationship across different industries. With 13% of the sample size not being valid to draw conclusions Margolis et al. (2007) found that 57% have, nevertheless, an insignificant outcome, compared to 2% that have a negative relationship and therefore 28% of these studies have a positive relationship. Another outcome of this meta-analysis is that market-based performance measures have a smaller effect on the relationship than accounting-based measures.
The meta-analysis of Orlitsky et al. (2003), which has been performed on more than 30 years of studies, gives the same outcome as Margolis et al. (2007), a positive CSR-FP relationship. In addition to this outcome, the meta-analysis of Orlitsky et al. (2003) shows that errors in the sample size, errors in the measuring of variables and stakeholder mismatching can explain 15 out of 100 percent of the different outcomes in the CSR-FP correlation. More important is that this analysis also shows that there is a bidirectional and simultaneous relationship.
2.5. Hypothesis
The literature review does not give a clear answer on the question what the effect of CSR on CFP is. However, with the meta-analyses from paragraph 2.4 and the rising popularity of CSR for companies (McPherson, 2017) the expectation of this research is that CSR has a positive effect on financial performance.
𝐻" : There is no positive relationship between CSR and CFP. 𝐻% : There is a positive relationship between CSR and CFP.
3 Methodology
This section gives the methodology that is used to analyze the relationship between CSR and FP of a firm. The used techniques within this study are all found in existing studies. With the amount of research done on this topic, utilizing these techniques are deemed appropriate. The instruments and statistics that are used in this research are shown in the next paragraphs. At first the database of the CSR-score is explained. After which the methods that are used to measure the financial performance are shown. Following that, the model that is used to test the relationship is shown and the control variables are explained. Finally, the given data is explained.
3.1 CSR-score database
As discussed before, this research uses the database of Thomson Reuters, ASSET4. This is in line with multiple studies regarding the CSR-FP relationship (e.g., Cheng et al., 2014; Eccles et al., 2014; Ioannou and Serafeim., 2012; Mackenzie et al., 2013). ASSET4 uses more than 750 data points, to measure the non-financial performance of a firm based on three pillars: Environmental, social and corporate governance performance. This databank includes the data of more than 4,000 companies all over the world. The analysts of ASSET4 use public available resources as annual reports, key news providers, non-governmental organizations and more for the database (Sassen, Hinze, & Hardeck, 2016).
With the first pillar, the environmental pillar (ENS), ASSET4 measures the effect of the firm on its non-living and natural living background. This is based on three classifications: Reducing emission, supporting research of eco-friendly products and achieving an efficient use of natural resources (Sassen, Hinze, & Hardeck, 2016). Secondly, the social pillar (SOS) represents a company’s ability to create trust and reliability with its staff, customers and society. This will be measured within seven classifications: employment quality, health and safety issues, training, diversity, human rights, community involvement and product
responsibility (Thomson Reuters Corporate Responsibility Methodology, 2013). The third and last pillar is the corporate governance pillar (CGS). This pillar measures the way board members and executives follow the corporate governance principles.
Each pillar has the same weight and the sum of the outcome of every pillar will result in a number between 0 and 100, where 0 will be the lowest point and where 100 will be the ultimate number. (Thomson Reuters Corporate Responsibility Methodology, 2013).
3.2 Financial performance measure
As already discussed in this research, there are two methods to calculate the financial performance of a firm: accounting-based and market-based measures. Since both have been used in multiple studies, there is a combination of both in this research. This gives the effect of CSR on FP for the short term and for the long term. This way of measuring has been done by Inoue and Lee (2011) and Rodgerts et al. (2013) as well. The accounting-based measures are the return on assets (ROA) and return on equity (ROE), as used in multiple studies (e.g Inoue & Lee, 2011; Makni, Francoeur, and Bellavance, 2009). For the market-based measure this research uses Tobin’s Q as Inoue and Lee (2011) and Rodgers et al. (2013) did. According to Margolis et al. (2007) ROE, ROA and Tobin’s Q are the most used measures to calculate the financial performance.
ROE is used as a measure for short-term profitability and is described as the net income divided by the shareholders equity (Inoue, Y., & Lee, S., 2011). The return on equity provides a measure of the return a firm has earned on its past investments. A higher ROE may suggest that a company is capable to find rewarding investment opportunities (Berk & DeMarzo, 2014).
ROA is also used as a measure for short-term profitability and is described as the net income plus interest expenses divided by the book value of the assets. ROA shows how resource allocations can lead to a firm’s profits (Inoue, Y., & Lee, S., 2011). Compared to ROE, ROA has the advantage that it is less sensitive to leverage. (Berk & DeMarzo, 2014).
With Tobin’s Q this research uses a market-based measure to calculate the financial performance. Tobin’s Q reveals how investors estimate the firm’s abilities to generate potential profits (Inoue, Y., & Lee, S., 2011). When potential investors see CSR as a positive investment for the company, this should have a positive effect on Tobin’s Q (Rodgers et al., 2013). Tobin’s Q is calculated as the sum of the market value of equity and liabilities divided by the book value of assets (Rodgers et al., 2013). With the assumption that S&P 500 companies can pay off the liabilities for the foreseeable future, the market value of the liabilities is approximately the same as the book value of the liabilities. As shown in part A of the appendix, the credit ratings of the companies are all above B (Standard & Poor’s ratings services, 2014). The credit rating of a firm gives information about the firm’s credit quality according to Kisgen (2006). They state
that firms with a higher credit rating are more able to pay off the debt and therefore this research assumes that shocks on the market do not affect the debt position of these firms.
3.3 Model
To test the effect of CSR on the FP of a firm, this study uses multiple regression analyses, as Inoue and Lee (2011) did. This effect is tested on, as previously discussed in this research, two short-term profitability measures and on a market-based measure. ROA and ROE tests the short-term profitability and Tobin’s Q tests the markets estimation of potential profitability.
𝑅𝑂𝐸),+: 𝛽"+ 𝛽%𝐶𝑆𝑅),++ 𝛽0𝑆𝑖𝑧𝑒),++ 𝛽4𝑅𝑖𝑠𝑘),++ 𝛽7𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝑅𝑎𝑡𝑖𝑜),++ 𝜀) 𝑅𝑂𝐴),+: 𝛽"+ 𝛽%𝐶𝑆𝑅),+ + 𝛽0𝑆𝑖𝑧𝑒),++ 𝛽4𝑅𝑖𝑠𝑘),++ 𝛽7𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝑅𝑎𝑡𝑖𝑜),+ + 𝜀)
𝑇𝑜𝑏𝑖𝑛B𝑠 𝑄
),+: 𝛽"+ 𝛽%𝐶𝑆𝑅),++ 𝛽0𝑆𝑖𝑧𝑒),++ 𝛽4𝑅𝑖𝑠𝑘),++ 𝛽7𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝑅𝑎𝑡𝑖𝑜),++ 𝜀)
3.4 Control variables
Previous research has shown multiple variables with an effect on the CSR-FP relationship. The meta-analysis on the CSR-FP relationship of Van Beurden and Gössling (2008) showed four variables that appeared to be an important factor in different studies. These are size, risk, industry and the intensity of research & development. The variable for industry is not used for this research since there is only one industry to be studied. This study uses the size and risk as control variables, because R&D is not accessible in the used database. Instead, this research uses the capital ratio to show the effect of CSR on the FP of a firm.
Size is the first control variable within this model. According to Dowell et al. (2000) and Waddock and Graves (1994) bigger firms apply CSR faster than smaller firms due to the high pressure from stakeholders and because these firms have the financial resources to accomplish this. According to numerous studies (e.g Trump and Guenther, 2015; Hillman and Keim, 2001) the size of the firm influences the financial performance and therefore this variable is relevant for this research. The size can be calculated in multiple ways, by the logarithm of the total assets, number of employees and total sales. The logarithm of the total assets in US dollars is however the best proxy to represent the size and is in line with previous research (McWilliams & Siegel, 2000; Simpson & Kohers, 2002) and is therefore used in this research. The logarithm is used because the distribution is more expected to be normal and hence provides a better variable for the regression analyses. This data is received from COMPUSTAT.
As second variable in this research Risk is used. Leverage is often used as a proxy for risk. Studies shown that risk is related to CSR and its impact on the financial performance of a
firm (e.g Herremans et al., 1993; Orlitsky and Benjamin, 2001). Firms with a high-risk acceptance and therefore with high leverage, might undertake different activities regarding CSR in comparison to firms which have little to no leverage (Waddock and Graves, 1994). Waddock and Graves (1994) and Dowell et al. (2000) also show that a higher leverage usually has a negative effect on the financial performance. As different studies, (i.e Inoue & Lee, 2011; Waddock and Graves, 1994) this research measures the risk or leverage by the total debt divided by the total assets. This data is received from COMPUSTAT.
The last control variable is the capital ratio. According to Platonova et al. (2018) the capital ratio is a main internal element of financial companies. With the capital ratio, there is an indicator that firms have an adequate cushion relative to the hypothetical shocks and risks. According to Kosmidou (2008) financial firms who have a high capital ratio assume to have a higher profitability because they need fewer external funds. This study measures the capital ratio by dividing the shareholders equity with the total assets, like Simpson and Kohen (2002) did in their research,
3.5 Data
This study collects its data from two sources. For the CSR scores ASSET4 by Thomson Reuters is used. For the financial data COMPUSTAT is used, as used by Inoue and Lee (2011) in their study. In this research the most recent relationship between CSR and FP is shown. Platonova et al. (2018) concludes that the crisis has a negative impact on the financial numbers and recommends to study the period after the crisis if the most recent relationship is the focus of the research. Therefore, this research studies the timeframe between 2012 and 2018. The financial numbers that are used, are every three months to be as precise as possible. However, the CSR scores are available on a yearly basis. Therefore, this study uses the same CSR score for every three months per year. This in contrast to other studies, where the financial numbers are used for every year instead of every three months (e.g Inoue and Lee, 2011; Platonova et al., 2018).
3.6 Reliability of results
Before and after the regression analysis, multiple assumptions are checked via different tests. This has been done in other studies regarding this relationship (e,g (Inoue, Y., & Lee, S., 2011; Platonova et al., 2018; Dhaliwal et al. (2012). The data is tested before the regression analysis for the normal distribution of the data and multicollinearity between the variables. After the
main regression analysis, the data is tested with different regression analysis including fixed effects and a check for robustness.
For the normal distribution test, the skewness and kurtosis standards are tested. If the skewness score is above 1.96 and the kurtosis score is above 3, the data is not normal distributed. If this is the case, the data should be winsorized (Haniffa and Hudaib, 2006).
The second test before the regression analysis is the multicollinearity check via the Pearson correlation matrix. Multicollinearity gives a problem for the regression analysis because it weakens the significance of an independent variable in the model. There is multicollinearity between two variables if the correlation value is above 0.8 (Jing et al., 2008).
There is a new regression analysis including fixed effects after the main regression analysis. Fixed effects estimators are used to limit selection bias. This is done by eliminating parts of the variation to contain confounding causes (Mummolo and Peterson, 2018). Within this research the selection bias is limited with fixed effects for years and for firms. The fixed effects for years controlled the changes through the years. If a certain event happens in a certain year, this is taken into account for the financial performances. The fixed effects for firms note the changes within a firm. For example, if a firm goes bankrupt because of a scandal which has nothing to do with engaging in CSR, fixed effects limits the effects on the financial performances.
The last test on the data is done with the robustness check. This test examines the behavior of the regression coefficients by adding or removing regressors. In this study the CSR score database is changed. The CSR score from ASSET4 is replaced with the CSR score from Sustainalytics. If the coefficients are plausible and robust, this is interpreted as a validate regression (Lu and White, 2014).
4. Data analysis
4.1 Descriptive statistics
In the financial sector of the S&P 500 there are 66 companies. After matching these companies with the complete CSR scores and financial numbers there are 57 companies left. The companies can be seen in section A of the appendix. Therefore, with 7 years of data and 4 measure moments per year there is a N of 1,596. Table 1 shows the summary of the descriptive statistics. This includes number of observations, the mean, the standard deviation and the minimum and maximum value.
Variables N mean sd min max ROE 1,596 0.031 0.185 -2.531 5.508 ROA 1,596 0.008 0.016 -0.08 0.170 Tobins Q 1,596 1.389 1.334 0.855 14.29 CSR score 1,596 50.708 15.08 12.20 87.29 Size(log) 1,596 11.42 1.662 5.826 14.78 Risk 1,596 0.104 0.108 0 0.760 Capital Ratio 1,596 0.197 0.173 -0.193 0.957
Table 1 Descriptive statistics
4.2 Data results
In line with the study of Platonova et al. (2018) and Dhaliwal et al. (2012) the skewness and kurtosis standards are tested to see if the financial performances are normally distributed. As the results show in section B of the Appendix, the financial performances are not normally distributed and therefore will be winsorized at a 2.5% level at both ends. Based on the normal distributed financial performances, the variables are tested on multicollinearity with a Pearson correlation matrix as shown in table 2. According to Platonova et al. (2018) and Jing et al. (2008) there is multicollinearity if the Pearson correlation matrix computes a correlation value higher than 0.8. Therefore, ROA and Tobin’s Q have multicollinearity. This is not a problem for the regression because these are both financial performances and are both only used as dependent variable, so they will not affect each other.
Variables ROE ROA TobinsQ CSRscor
e SizeLog Risk CapitalRatio
ROE 1.000 ROA 0.622*** 1.000 Tobins Q 0.562*** 0.884*** 1.000 CSR score -0.076*** -0.186*** -0.170*** 1.000 Size(log) -0.386*** -0.628*** -0.578*** 0.466*** 1.000 Risk 0.371*** 0.253*** 0.269*** -0.045* -0.251*** 1.000 Capital Ratio 0.134*** 0.597*** 0.412*** -0.282*** -0.565*** -0.017 1.000 *** p<0.01, ** p<0.05, * p<0.1
4.3 Regression results.
Table 3 shows the regression results of ROE, ROA and Tobin’s Q on CSR and three control variables. The CSR score has a positive effect on every financial performance measure. A higher CSR score has a positive effect on the return on assets, and this is in line with previous research from Lee and Park (2010). The positive effect of the CSR score on Tobin’s Q is also in line with previous research (Inoue, Y., & Lee, S., 2011).
As shown in table 3, the CSR score does not only have a positive effect on the financial performance measures, but it is also a significant positive effect for a 1% level. The results show that every control variable in every model, except for the Capital Ratio in the ROE regression, to be significant at 0.01. With the same amount of significant control variables as the study of Platanova et al. (2018), the same conclusion as theirs can be withdrawn from the regression results, namely that this indicates that the equation is reliable.
The regression results illustrate that the size of a firm in the financial sector has a negative effect on the financial performance of this firm. It also shows that risk increases the profitability of a firm on average. Capital ratio is the only control variable that does not show the same results for each of the regression results and the explanation for this outcome is unclear.
(1) (2) (3)
Variables ROE ROA TobinsQ
CSR score 0.000158*** 8.43e-05*** 0.00577*** (3.93e-05) (1.15e-05) (0.000815) Size(log) -0.00728*** -0.00244*** -0.221*** (0.000835) (0.000229) (0.0170) Risk 0.0504*** 0.0265*** 2.617*** (0.0131) (0.00324) (0.227) Capital Ratio 0.00240 0.0318*** 0.926*** (0.00580) (0.00239) (0.166) Constant 0.101*** 0.0221*** 3.085*** (0.00937) (0.00263) (0.200) Observations 1,596 1,596 1,596 R-squared 0.250 0.625 0.564
Table 3 Regression coefficents and statistics
As discussed in paragraph 3.6 Platonova et al. (2018) indicate that using fixed effects is the most appropriate way to examine the data regarding the relationship of CSR and FP. Table 4 shows the extended regression model which include year fixed effects and firm fixed effects. Table 4 shows positive significant effects of the CSR score on every performance measure as well for both the fixed effects models. The size of a firm has a negative impact of firms within the financial sector of S&P 500, which is the same outcome as the original regression as shown in table 3. The risk of a firm shows little difference between the three regressions. The capital ratio shows a different outcome as well for the regression with the added fixed effects for firms compared to the first regression. It shows a negative significant effect on the ROA. A possible explanation can be the fact that the first regression shows different changes through the years, which may be solved with the fixed effects. With little differences within the different regressions, the CSR score remains constant in terms of a positive significant effect.
(1) (2) (3) (4) (5) (6)
Variables ROE ROA TobinsQ ROE ROA TobinsQ
CSR score 0.000131*** 8.67e-05*** 0.00556*** 0.000243*** 4.63e-05*** 0.00312*** (4.91e-05) (1.43e-05) (0.00104) (7.35e-05) (1.47e-05) (0.000682) Size(log) -0.00719*** -0.00245*** -0.221*** -0.0255*** -0.00800*** -0.543*** (0.000569) (0.000166) (0.0121) (0.00227) (0.000453) (0.0211) Risk 0.0501*** 0.0265*** 2.604*** -0.0630*** 0.00287 1.292*** (0.00586) (0.00171) (0.124) (0.0162) (0.00324) (0.151) Capital Ratio 0.00268 0.0318*** 0.932*** -0.0805*** -0.00389 -2.299*** (0.00456) (0.00133) (0.0967) (0.0154) (0.00308) (0.143) Constant 0.101*** 0.0221*** 3.095*** 0.333*** 0.0971*** 7.668*** (0.00651) (0.00190) (0.138) (0.0256) (0.00511) (0.237) Fixed effects yearly Fixed effects firms Yes No Yes No Yes No No Yes No Yes No Yes Observations 1,596 1,596 1,596 1,596 1,596 1,596 R-squared 0.256 0.626 0.566 0.558 0.896 0.951
Table 4 Regression coefficents and statstics including fixed effects for years and firms. Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
4.4 Robustness check
To test the robustness of the results of this study, one additional test is applied. Instead of the CSR score of Thomson Reuters, the CSR score of Sustainalytics is used. Table 5 shows the results of the robustness check. The results of this test validate the results of the second and third regression, which include the fixed effects. Table 5 shows significant positive effects of CSR on the financial performance measures, as shown in the original regression. The robustness check also shows a negative significant effect of the size of a firm on every financial performance. As presented in the original regression analyses as well, risk has a significant positive effect except with firm fixed effects. Capital ratio has a negative non-significant effect on the return on equity with yearly fixed effects and on the return on assets with firm fixed effects. With all the results to have a similar effect on the financial performances, the results of the fixed effect regression are validated.
(1) (2) (3) (4) (5) (6)
Variables ROE ROA TobinsQ ROE ROA TobinsQ
CSRscore
sustainalytics 0.000999*** 0.000331*** 0.0303*** 0.000518*** 6.79e-05** 0.00852*** (8.64e-05) (2.52e-05) (0.00177) (0.000143) (2.86e-05) (0.00132) Size(log) -0.00855*** -0.00264*** -0.253*** -0.0229*** -0.00754*** -0.507*** (0.000502) (0.000146) (0.0103) (0.00219) (0.000438) (0.0202) Risk 0.0380*** 0.0231*** 2.256*** -0.0539*** 0.00423 1.432*** (0.00573) (0.00167) (0.117) (0.0163) (0.00326) (0.150) Capital Ratio -0.00537 0.0297*** 0.710*** -0.0852*** -0.00481 -2.359*** (0.00442) (0.00129) (0.0902) (0.0153) (0.00307) (0.142) Constant 0.0702*** 0.0109*** 2.128*** 0.287*** 0.0904*** 6.946*** (0.00661) (0.00193) (0.135) (0.0273) (0.00545) (0.252) Fixed effects yearly Fixed effects firms Yes No Yes No Yes No No Yes No Yes No Yes Observations 1,596 1,596 1,596 1,596 1,596 1,596 R-squared 0.311 0.655 0.628 0.558 0.896 0.951
Table 5 Robustness regression coefficents and statstics including fixed effects for years and firms.
5. Conclusion & discussion
5.1 Conclusion
This research studies the relationship between the CSR score and the financial performances of S&P 500 companies within the financial sector. It answers the research question: What is the effect of corporate social responsibility on the corporate financial performance within the financial sector of the S&P 500 between 2012 and 2018? This study contains data of 57 companies over 7 years, which results in 1,596 data observations. The financial performance measures are quantified by the return on assets, the return on equity and Tobin’s Q. The findings of this study show a significant positive effect of CSR on all measures. Therefore, the hypotheses can be rejected at a 0.01% level. Hence, the conclusion is that financial firms within the S&P 500 will be rewarded financially if they invest in CSR-activities.
The findings of this study regarding the significant positive effect of CSR on the financial performance are in line with the findings of the meta-analysis of Orlitsky et al. (2003) and Margolis et al. (2007). Nevertheless, one of the conclusions from these meta-analyses is that market-based performance measures are less influenced by the CSR score in comparison to accounting-based performance measures. This research, however, shows a bigger effect of CSR on Tobin’s Q.
The positive effect of CSR on the financial performances can possibly be explained by the theory, as discussed before, that positive social performances may reduce costs in multiple ways. A theory that was discussed is for example the improvement of productivity by the employees. Positive social performances can also lead to improved revenues, hence better financial performances (Brammer and Millington, 2008).
5.2 Limitations and additional research
One of the main issues with CSR and FP is the possible existence of endogeneity. This issue is more common within studies regarding CSR (Simpson, W., & Kohers, T. 2002). As done by Platonova et al. (2018), an instrumental variable regression can be a possible solution for this limitation. A possible causal relationship can be estimated with an instrumental variable regression. However, using the right instrumental variable for CSR stays unclear in this study. Therefore, further research regarding reverse causality in the CSR-FP relationship is recommended. This can also be done with an event study in response to, for example, a change in the law. An example is the change in the law in Denmark, where big companies are required to report on corporate social responsibility since 2009 (Vallentin, 2015).
Acquisitions are a common event within big companies in the S&P 500, which can have a possible effect on the outcome of this study. Despite the fact that acquisitions are not part of this research because it was not the goal to study the link with acquisitions, it should be taken into account for an ideal data regression. Therefore, this should be acknowledged as a limitation and can be recommended for future researches regarding this relationship.
Another limitation within this research is the use of a yearly CSR score for every three months of the concerning year. As already mentioned, there are almost no other studies regarding the relationship between CSR and FP who use this method. All other studies use yearly scores, because the number of observations is big enough to do so. To make the study more reliable with more observations and by using the same method as other studies, this study could have used more years to do so.
This study focusses on the relationship between CSR and FP of financial firms within the S&P 500. Interesting additional research to the relationship between CSR and FP can be done to financial firms who are not as big as these companies. There could be a different relationship between CSR and FP for smaller financial firms.
Further research to the relationship of CSR-FP is also an option, in terms of testing why this relationship exists. A few theoretical explanations have been reviewed in this research, but these have diverse implications, where multiple studies see these theoretical explanations differently. Therefore, a recommendation for further research is to do empirical tests to explain why there is a positive relationship.
Despite the limitations of this research and the encouragement to do further research regarding this relationship, the results of this research are promising for companies within the financial sector of the S&P 500, hence these companies can be financially successful and be publicly responsible.
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Appendix
A. Firms within the financial sector of the S&P 500 and the additional data available.
Firms Data available Creditrating
Aflac Incorporated
American International Group Assurant Inc
Arthur J. Gallagher & Allstate Corp
Ameriprise Financial Services AON Plc
American Express Company Bank of America Corp Franklin Resources
Bank of New York Mellon Corp Blackrock
Berkshire Hathaway Cl B Citigroup Inc
Chubb Ltd
CBOE Global Markets Inc Citizens Financial Group Inc/Ri Cincinnati Financial
Comerica Inc CME Group Inc
Capital One Financial Corp Discover Financial Services E*Trade Finl Corp
Fifth Third Bncp First Republic Bank Globe Life Inc
Goldman Sachs Group Huntington Bcshs
Hartford Financial Services Intercontinental Exchange Invesco Plc
JP Morgan Chase & Company Keycorp
Loews Corp
Lincoln National Corp Moody's Corp Metlife Inc Marketaxess Holdings YES A- YES BBB+ YES BBB YES BBB YES A- YES A YES A- YES BBB+ YES A- YES A YES A YES AA- NO AA YES BBB+ YES A YES A- NO A- YES BBB+ YES A- YES AA- YES BBB YES BBB- YES BBB YES BBB+ YES A- YES A YES A+ YES BBB+ YES BBB+ YES A YES BBB+ YES - YES BBB+ YES A YES A- YES BBB+ YES A- NO -
B. Skewness and Kurtosis
Description ROE ROA Tobins Q
Skewness 13.360 4.50 6.48
Kurtosis 520.67 30.517 52.832
Marsh & Mclennan Companies Morgan Stanley
MSCI Inc
M&T Bank Corp Nasdaq Inc
Northern Trust Corp People's United Finl
Principal Financial Group Inc Progressive Corp
PNC Bank
Prudential Financial Inc Everest Re Group Regions Financial Corp Raymond James Financial The Charles Schwab Corp Svb Financial Group S&P Global Inc State Street Corp Synchrony Financial Truist Financial Corp. T Rowe Price Group
The Travelers Companies Inc Unumprovident Corp
U.S. Bancorp
Wells Fargo & Company Willis Towers WT W.R. Berkley Corp Zions Bancorp YES A- YES A+ YES BB+ YES A- YES BBB YES A+ YES BBB+ YES A- YES A YES A YES A YES A- YES BBB+ YES BBB+ YES A NO BBB NO B- YES A NO BBB NO A- YES - YES A YES BBB YES A+ YES A- NO BBB YES BBB+ YES BBB+
