Corporate sustainability performance and corporate financial performance in the industrials good sector

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Corporate sustainability performance and corporate financial performance in the

industrials good sector

‘Can business meet new social, environmental, and financial expectations and still win?’ (Business Week August 21, 1999)

University of Amsterdam

Amsterdam Business School

Bsc Economics & Business

Major Economics and Finance

Author:

L.M. Kennepohl

Student number:

10772758

Thesis supervisor: Dr. J.J.G. Lemmen

Finish date:

31 January 2018

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Statement of orginality

This document is written by Student, Léonie Kennepohl, 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.

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ABSTRACT

This Study examines whether Corporate Sustainability Performance affects Corporate Financial Performance in the Industrials Goods Sector. A sample of 54 companies during the period 2002-2015 have been used, all based in countries that are part of the European Union. In this study Thomson Reuters ASSET4 ESG is used as a proxy for the Corporate Sustainability Performance and the ROA is used as a proxy for the Corporate Financial Performance. To examine whether CSP affects CFP several OLS regressions have been made. Pooled regressions and fixed model regressions both show a significant linear positive relation between CSP and CFP after correcting for heteroscedasticity. Furthermore this study concludes, in line with previous studies, that CSP is even more related to CFP in times of crisis. This means that in times of uncertainty stakeholders attach value to social responsible companies and therefore companies with high corporate sustainability performance generated a competitive advantage and faced less negative effects during the financial crisis in 2008. Nevertheless, the increased positive significant relation turns out to be temporarily.

Keywords:

Corporate Sustainability Performance, Corporate Financial Performance, Competitive Advantage, Financial Crisis

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CHAPTER 1 Introduction

More and more people are paying interest to sustainability. People get more aware of the environmental damage firms cause. As Lichtenstein et al. (2004) mentioned Corporate Social Responsibility (CSR) has moved from ideology to reality. Firms get forced to define their roles in society and implement social and ethical standards into their business. Ruf et al. (2001) concluded that firms must at some level satisfy stakeholder demands as an unavoidable cost of doing business. They investigated the need of CSR from a stakeholder perspective, where CSR is assessed in terms of a company meeting the demands of multiple stakeholders. Because of the increasing need for social responsibility, CSR activities are increasingly used to position a firm’s corporate brand. Firms use annual reports and their websites to make stakeholders aware of their social responsible activities.

Besides the stakeholder and society perspective, there is a fundamental belief that CSR pays-off for the firm in general (Burk and Logsdon, 1996). Implementing a CSR strategy is an expensive investment. Neo-classic economics state that a CSR strategy fits with a sum trade-off. A zero-sum trade-off occurs when the benefits equals the costs, so the net change in accounting variables is equal to zero.

Overtime there have been many researches according to whether CSR pays-off on a financial level. The classic economic theory about CSR is that the costs in the short term should be

outperformed by the created long-term value. According to Lopez et al. (2007) it is thought that competitive advantages are often linked to the adoption of social responsible behaviour. Competitive advantages should be positively related to a firm’s financial performance. Besides competitive advantage, CSR measures as ethical codes, better environmental practices and human capital

development are considered a good strategy that leads to better corporate management, what therefore leads to better performance (Orlitzky et al., 2003).

Different researches concluded different things according to whether CSR, and therefore CSP, is positive or negative related to Corporate Financial Performance (CFP). Also, many found a positive relation, but not significant. They aimed that the main reason for this finding was that their research relied on a short amount of time. To find a significant correlation this research is based on a period from 2002 until 2015, which is a timeframe of fourteen years. In this timeframe we have to take the crisis in 2008 into account and check whether this positively or negatively influences the correlation between CSP and CFP and therefore the opportunities for firms to invest in CSP during a period of crisis.

This study focuses only on the industrial good sector, therefore the following research question will be answered:

Does Corporate Sustainability Performance affect the firm’s Financial Performance in the industrial goods sector?

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The remainder of this thesis is organised as follows. Chapter 2 contains the existing literature on CSR and CFP. Chapter 3 lists the different hypothesis. Chapter 4 explains the data chosen and methodology used in this research. Finally, Chapter 5 shows the results and conclusion.

CHAPTER 2 Literature Review

The main problem when investigating the relation between CSP and CFP is how to interpreter them and how to measure them. There is no common accepted way to measure Corporate Sustainable Performance and there are lot of measures used for Corporate Financial Performance. In this chapter we compare different researches and argue the choices they made according to 1) measure Corporate Sustainable Performance 2) measure Corporate Financial Performance. Furthermore, we discuss the different results they found divided in positive correlation and negative correlation founded.

2.1 Corporate Sustainability Performance

There are different ways to define Corporate Sustainability Performance. Social Responsible Investing (SRI), Corporate Social Responsibility (CSR) and Corporate Sustainability Performance are often used in the same sentence and all look at risk and investment opportunities due to Environmental, Social and Economic developments. Marrewijk (2003) used the illustration (figure 1) from the Erasmus university to explain the relationship between Corporate Sustainability (CS) and Corporate Social Responsibility (CSR). The main difference is that CS is the long-term effect of a firm being Corporate Social Responsible. But in practice CSR is defined as a synonym to CS (Marrewijk, 2003).

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The regulations according to sustainability and corporate social responsibility differ per country. In 2010 the European Union launched he Enterprise 2020, where they included three strategic priorities, including stimulating companies’ sustainability and social responsibility. They believe corporate social responsible companies taking responsibility for their impact on society is important for the sustainability, competiveness and innovation of European based firms and the European economy. In this research we use a sample of European firms, assuming that each firm has the same philosophy according to sustainability. In Europe, sustainable development focuses on proactive policies related to the environment and human resources. However, in the U.S., sustainability policies focus on the control of issues like tobacco, alcohol, gambling, environmental impact, and human rights (Lopez et al., 2005).

2.1.1. Measuring Sustainability Performance

Besides that here are different ways to define Corporate Sustainability Performance, there are also many ways to measure CSP, but after all those years there is still no commonly accepted way of measuring sustainability. Orlitzky et al. (2003) found, using a Meta-Analysis, that the construct of CSP is in most studies associated with four broad measures: CSP disclosure, CSP reputation ratings, Social audits/CSP processes and outcomes, Managerial CSP principles and values. Especially the third measurement category, the objective measure of third parties, is used in many researches. For example The Dow Jones Sustainability Index, the corporate knight index, the asset4 ESG and the KLD, now the MSCI KLD index are all indexes that are used in researches that investigate relations between CSP and other variables.

In 2007, M. Victoria López et al. investigated whether business performance is affected by the adoption of Corporate Social Responsibility. This study is based on the Dow Jones Sustainability Index (DJSI). The Dow Jones Sustainability index contains 10% of the firms of the Dow Jones Global Index. In cooperation with RobecoSAM who annually evaluate companies’ sustainability practice, Dow Jones listed the firms that meet the sustainable requirements in the DJSI. The concepts selected to measure CSR in the DJSI are similar to those proposed by the most frequently used CSR guides and are used by a large number of firms to develop and disclose their sustainability report (López et al., 2007). Some indicators used by the DJSI are the evaluation of intangible assets, development of human capital, organizational issues, strategic plans, corporate governance and investor relations.

López et al. (2007) compared firms listed in the DJSI to firms not listed in the DJSI using a sample of 110 firms, of which 55 were included in the DJSI. In their study they used a dummy

variable for whether the firm is sustainable or not. A dummy variable takes either 1 or 0, in this case 1 if the firm is listed in the DJSI and 0 if not. Even though the DJSI is overall accepted, it is hard to use it as a measure for sustainability in a research. They list the most sustainable firms in their index, but don’t publish their specific findings. Therefore it is only possible to use a dummy variable in the

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regressions, which is not reliable since all firms in the DJSI are not equally sustainable and the same counts for firms in the DJGI.

Stanwick (1998) investigated the Relationship between Corporate Social Performance, and Organizational Size, Financial Performance, and Environmental Performance. In this study they used the corporate reputation index as measure of CSP. They found a positive correlation between CSP and profits and CSP and sales. However, Fryxell and Wang (1994) stated that the Fortune corporate reputation index isn’t a valid measure of CSP, since the index is highly correlated to the financial position of the firm.

Another measure of CSP is the KLD, now known as the MSCI KLD. Ruf et al. (2001) used the KLD to investigate the relationship between CSP and CFP. The KLD is a commonly used index as measure for CSP. Ruf et al. mentioned in their paper that KLD is appropriate since companies are evaluated on different social dimensions by their strengths and concerns and firms are rated over time, so researchers can asses change in social performance. To find the overall CSP score they used an approach found by Ruf et al. (1998). In this approach, the dimensions of social performance are identified. A questionnaire is then administered to a group of respondents to evaluate the relative importance of the dimensions and add a weight to each dimension. Then, the CSP is the sum of all dimensions scores and their specific weight. This formula is only easy to use when you have the needed weights, since we don’t have them and have insufficient time to get them this method can’t be used. Besides that, KLD only rates U.S. firms and therefore can’t be used since this research is based on European firms.

After finding these indexes, that all couldn’t be used for this research, I found the Thomson Reuters ESG index, also called ASSET4, used in the research “Corporate Social Responsibility and the access to Finance”(Cheng et al., 2013). Thomson Reuters rates transparently and objectively over 6000 global firms on three different pillars: Social, Environmental and Corporate Governance

performance. They base there score on data from company reports, company websites, NGO websites, newspapers, journals and trade publications but their biggest sources are their own CSR reports, collected by their own analysts. The database is available in the University Library Amsterdam, you can find it in excel. Using the function Sample Sheet and chose the ASSET$ ESG template you can easily look up the needed average ASSET4 scores, this is the average score of all three pillars and is considered a good measure for the Corporate Sustainability Performance in this research.

2.2 Measuring Corporate Financial Performance

There are different ways to measure Corporate Financial Performance of a firm. There are either market-based indicators, such as stock return and accounting based indicators, such as ROA, ROE, EBIT etcetera. Both were used in investigating the correlation between CSP and CFP. In the Meta-Analysis of Orlitzky et al. (2003) they found that accounting based measures are more correlated to CSP than market based measures. A reason for this can be that market indicators not necessarily

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indicate financial fluctuations within the firm. Other macroeconomic factors such as speculations, control of the government and natural or man-made disasters may also have influence. A firm’s financial performance could be explained by using market indicators, but accounting indicators are considered less noisy (Lopez et al., 2007).

2.3 Corporate Sustainability Performance and Corporate Financial Performance A lot of researches investigated the relationship between CSP and CFP. The results found are divided and sometimes even controversial. Different studies found either negative or positive relations.

2.3.1. Negative relation

Although it is not found often, some studies found a negative relation between CSP and CFP. The study of Lopez et al. (2007), who investigated the relation between sustainable development and corporate performance, using the Dow Jones Sustainability Index, found a negative Beta of -0.171. This can be due to the weak measure of sustainability, since they used a dummy variable. Or, as stated in the limitations, the timeframe wasn’t big enough and therefor the firm’s sustainable development did not manage to produce new strategic resources, improve the quality of existing ones, construct others or exploit existing resources for other uses. Their findings were confirm their expectations, insufficient time has passed and they assumed short-term cost savings were not made, so the costs outperformed the benefits in short term.

2.3.2. Positive relation

Stanwick (1998) investigated the relationship between CSP and organizational Size, Financial Performance and Environmental Performance. They used profit as a measure for CFP and controlled for size. They found a positive relationship with all three variables, but these findings where only significant in two out of six years.

Orlitzky et al. (2003) investigated if corporate social performance (CSP) and corporate financial performance (CFP) are related using a Meta-analysis, assuming that current evidence is too fractured or too variable to draw any generalizable conclusions. They concluded that there is a positive relation between CSP and CFP. But they also concluded that a firm’s size, financial performance and environmental performance impact the firm’s level of CSP. This means that not only CSP affects CFP, but also that the level of CFP affects CSP.

In the paper Corporate Social Responsibility and financial performance et al. (Van der Velde et al., 2006) they found a positive, but not significant relation. In this paper they used the Fama and French model to compare different portfolios and see if the one outperforms the other. In this model the financial performance is the return on the portfolio and they used SMB, market capitalization, and HML, whether it is a value or growth portfolio, as control variables. The insignificant finding is

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consistent with the finding that market based indicators are less correlated with CSP than accounting based indicators (Orlitzky et al, 2003).

Wagner (2010) also found an insignificant relation between corporate sustainability and economic performance. They used Tobin’s q as dependent variable, which is a mix of a market based and accounting based measure for the firm’s value. They included firm age, firm size, R&D

expenditure and industry as control variables. Insignificant coefficients were found using Tobin’s q. What they did find is that there is a potential trade-off between corporate sustainability and economic performance, but stakeholders have to be aware of the socially related activities of the firm to generate positive net benefits.

Ruf et al. (2001) investigated the relationship between changes in CSP and changes in CFP using KLD as measure for CSP. They used ROE, ROA and growth in sales as a dependent variable and they controlled for industry type, firm size and prior year’s financial performance. They found that change in CSP was positively associated with growth in sales for the current and subsequent year. This indicates that there are short-term benefits from improving CSP. Return on sales was significantly positively related to change in CSP for the third financial period, indicating that long-term financial benefits may exist when CSP is improved.

Cheng et al. (2013) concluded in their research on “ CSR and access to finance” that CSR performance is negatively related to capital constrains and therefore improves a firm’s financial situation. As arguments for this conclusion they mention that CSR performance is associated with superior stakeholder engagement. This leads to better trust and higher quality relations with customers, business partners and among employees, that in turn increases the potential to generate revenue or profit. Further, they mention that firms with better CSR performance are more likely to be transparent. Transparency reduces informational asymmetry and again creates better trust.

2.4 CSP and CFP in times of crisis

Since this research investigates the CSP CFP relationship between 2002 and 2015, we have to be aware of the financial crisis in 2008. Several studies investigated the CSP opportunities in times of crisis and whether this can positively or negatively influence companies’ financial performance.

Schnietz & Epstein (2005) concluded that a good reputation according to social responsibility protects a firm in times of financial crisis. They even found that firms in industries that faced the greatest crisis, benefitted most from their reputation. In these industries, firms without a social responsible reputation faced a 3 per cent decline in shareholder value, compared to firms in the same industry that did have a good reputation.

Ducassy (2012), investigated whether CSR pays off in times of crisis. She found a significant positive relation between CSP and CFP in the beginning of the financial crisis, but this turned out to be temporarily. These findings show that firms with high CSP suffer less from the negative effects of the crisis overall; this confirms the importance for investors that a firm invests in social responsibility

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and sustainability. Ducassy concludes that in times of uncertainty CSR positively influences a firm’s competitive advantage.

2.5 Linearity

Researchers that study the relationship between CFP and CSP are still criticized for assuming linearity without valid testing (Callen & Thomas, 2009). Theories in management research, to maximize the organizational outcome, are often based on the assumption that more is always better (Trumpp, 2015). This means that an increase in the CSP score always results in an increase in CFP. Thus the

relationship between CFP and CSP is linear.

The ‘too-much-of-a-good-thing’ (TMGT) meta-theory argues that there is no such linear relation, they assume that each relationship has a context-specific maximum (Trumpp, 2015). At some point the additional costs exceed the additional benefits (Pierce and Aguinis, 2013). According to the TMGT theory there is an optimal CSP score, where the firm’s CFP is at its maximum and therefore the relationship between CSP and CFP follows an inverted U-shaped association.

In contrast, the ‘too-little-of-a-good-thing’ (TLTG) meta-theory assumes that each relationship has a context-specific minimum (Trumpp, 2015). This means that CSP and CFP are negatively

correlated until CSP achieves a certain ‘minimum level’ where CFP is at its minimum. The

relationship between CSP and CFP becomes positive when the CSP score exceeds this minimum. This means that the negative coefficient of CSP at some point converts to a positive coefficient, therefore the relationship between CSP and CFP follows a U-shaped association.

In summary the relationship between CFP and CSP can either be linear or non-linear. The non-linear relationship can either be U-shaped or inverted U-shaped.

CHAPTER 3 Hypothesis

After analysing the literature in chapter 2, the following hypotheses can be made according to the research question:

Does Corporate Sustainability Performance affect the firm’s Financial Performance in the industrial goods sector?

According to the literature found, the overall finding is that there is a positive relation between CFP and CSP and therefore CSP positively affects CFP. Even though in the short-term the expenses of acting Social Responsible are high and the firm will only be able to apply existing resources to

sustainability practices. In the long-term planning, the resources needed to carry out CSR strategies can be predicted and financed obtained to achieve them(López et al., 2007). At the end CSP creates value and a competitive advantage. Therefore corporate sustainable companies are suspected to

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outperform non-corporate sustainable companies, assuming there is a linear relationship between CFP and CSP.

Hypothesis 1: Corporate Sustainability Performance has a positive effect on the firm’s Financial Performance in the period 2002-2015.

The timeframe of this study includes the financial crisis of 2008. The two analysed studies both found that CSP is not a threat, but an opportunity during a crisis. A good reputation is in times of uncertainty an important factor for companies. There is little to spend and invest and choices have to be made. Social responsible behaviour is in this case a factor that can cause a competitive advantage in times of crisis. So firms that score high on CSP are expected to face less negative effects of the

financial crisis, compared to firms that score low on CSP.

Hypothesis 2: Corporate Sustainability Performance has an increasingly positive effect on firm’s Financial Performance during the financial crisis of 2008.

After the financial crisis the increased positive relation is expected to diminish. As

Ducassy(2012) found, the effect is temporarily. But there is still expected to find a positive relation. Hypothesis 3: Corporate Sustainability Performance has a positive effect on firm’s Financial

Performance in the period 2010-2015, but the effect is less compared to the previous years of financial distress.

CHAPTER 4 Data and Methodology

4.1 Sample selection

This study will investigate the relation between CSP and CFP using a sample of firms based in Europe in a country which is part of the European Union. As mentioned before we assume that each firm, based in a country that is part of the EU, has the same philosophy according to sustainability. I will especially focus on the industrials goods sector that contains: Aerospace & Defence, Building products, Construction & Engineering, Electric Equipment, Industrial Conglomerates, Machinery, Trading Companies & Distributors, Commercial & Professional Services and Transportation. The choice for this sector is based on the available data in Datastream, the database used. Datastream covers a lot of European firms participating in the industrial goods sector.

The selection of the firms, depends on the availability of the needed data for this research. In this study the ASSET4 template has been used as measure for the Corporate Sustainability

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Performance. This template, that is a source for environmental, social and governance (ESG) data, can be easily found in excel using Thomson Reuters Datastream.

First of all there is a selection made of firms in the Industrial Goods Sector that are based in Europe, using the ASSET4 company level template. The total number of firms found was 129. Using their ISIN code to list the firms is an easy way to find the rest of the data needed in Datastream. Since the total timespan of this research is 2002-2015, the firms have to be rated in ASSET4 since the beginning of 2002 till the beginning of 2016. If there are any missing values, the firm is excluded from the sample. After correcting for CSP data, there are only 59 firms listed in the sample.

Second there has to be checked for available data on the dependent variable ROA. This data is also obtained from Datastream using the ISIN codes of the remaining 59 firms. Again if there are any missing values in the timespan of 2002-2015, the firm is excluded. This leads to an additional decrease of 5 firms in the sample.

Third there has to be checked for the available data of the control variables; firm size and risk. There were no missing data found in the control variables, so the remaining sample consist of 54 firms.

4.2 Variables

The variables used in this research consist of one dependent variable, namely the Corporate Financial Performance, the independent variable, Corporate Sustainability Performance and some control variables.

4.2.1 Dependent variable

The corporate financial performance of a firm can be measured through accounting-based variables and market-based variables. According to previous research the use of accounting-based variables is preferred when looking at the relation between CSP and CFP. In this study the return on assets will be used to measure the corporate financial performance. The return on assets measures the profitability of a firm according to its total assets. The following formula is used to calculate the ROA:

ROA= (Net Income/Total Assets) *100%

4.2.2 Independent Variable

The corporate sustainability performance of a firm depends on different social responsible activities. ASSET4 rates firms on three pillars; environmental, social and corporate governance performance. These pillars examines different factors:

The environmental pillar: includes resource usage and reduction; emissions and emissions reductions; environmental activism and initiative and product or process innovation.

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The social pillar: includes employment quality, health and safety issues, training, diversity, human rights, community involvement and product responsibility.

The corporate governance pillar: includes board structure, compensation policy, board functions, financial and operational transparency, shareholder rights and vision and strategy.

ASSET4 ESG, rates each firm on these three pillars with a 0 to 100 score. Each firm is ranked against a benchmark within their industry and therefore ASSET4 is a good measure of Corporate Sustainability Performance when comparing companies within a particular industry. Scoring good on these three pillars results in a higher corporate sustainability performance. The corporate sustainability performance is calculated as the overall score on the three pillars. Datastream automatically generates the overall score on the three pillars, using the datatype ‘equal weighted rating’. So in this research there is assumed that each pillar is equally important to the corporate sustainability of a firm.

4.2.3. Control Variables

Previous studies used several control variables. All studies included in this research controlled for firm’s size. Not only does size affect the level of CFP, but it also affects the level of CSP. Stanwick (1998) and Orlitzky et al.(2003) both found a positive relation between CSP and firm’s size. There are different ways to measure firm size. The two common used measures for firm size in investigating the relation between CFP and CSP are total assets and market capitalization. To see which measure is most relevant, one can check with the goodness of fit of the variable that is measured with the R-squared. The R-squared varies with different firm size measures (Dang & Li, 2015). In this study the natural logarithm of the total assets is used, since previous studies has shown a significant relation between ROA and the natural logarithm of the total assets and DataStream provides more data according to the firm’s total assets than firm’s market capitalization.

Furthermore the control variables risk, industry and R&D expenditures are used in previous researches. Since this study only focuses on one industry, there is no need to control for industries. R&D expenditures are hard to obtain when using European firms and there is no database found that provides R&D data from 2002 to 2015. So R&D expenditures are also not included in this research. This research does control for risk. The formula used is total debt divided by total assets.

In summary, this study controls for size and risk using the following formulas: SIZE = log total assets

RISK = total debt/total assets

4.3 Methodology

This study uses panel data, consisting of 54 companies in a period of 14 years. Panel data is mostly used when observing the behaviour of, in this case, different companies across time. After finding all the data in DataStream and listing all the data in one excel sheet, the excel sheet is imported into

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STATA15. This statistical program is used to do the needed regressions for this study. Using the reshape command, the data is easily converted to panel data.

To see if there is a relation between CFP and CSP and whether this relation is positive or negative, the following linear equation is used:

𝐶𝐹𝑃!" = 𝛽0!+ 𝛽1𝐶𝑆𝑃!"+ 𝛽2𝑅𝐼𝑆𝐾!"+ 𝛽3𝑆𝐼𝑍𝐸!"+ 𝜀

i=firm(1...54), t=time(2002…2015)

Where CFP is the return on assets, CSP is measured by ASSET4, RISK is the total debt divided by total assets and SIZE is the natural logarithm of total assets.

Pooles OLS

In this study the ordinary least square method (OLS) is used to determine the unknown parameters in the model. First the pooled OLS estimation is used, but in this case the firm’s specific effects are ignored.

Random and fixed effects

If you assume the variation across companies is random and not correlated with the independent variable, there has to be controlled for random effects using the random effects model.

𝐶𝐹𝑃_!" = 𝛽0_!+ 𝛽1𝐶𝑆𝑃_!"+ 𝛽2𝑅𝐼𝑆𝐾_!"+ 𝛽3𝑆𝐼𝑍𝐸_!"+ 𝜀_!+ 𝜇_!"

i=firm(1...54), t=time(2002…2015)

In Stata you can simply use the function re, to control for random effects. If you assume the variation across companies is fixed and thus correlated with the independent variable, you have to control for fixed effects. When controlling for fixed effects in an OLS regression one can use the least square dummy variable (LSDV). 𝐶𝐹𝑃!" = 𝛽0 + 𝛽1𝐶𝑆𝑃!"+ 𝛽2𝑅𝐼𝑆𝐾!"+ 𝛽3𝑆𝐼𝑍𝐸!" + 𝛾! 𝑓𝑖𝑟𝑚! ! !!! + 𝜇!" i=firm(1...54), t=time(2002…2015)

To test whether to control for random or fixed effects the Hausman test is used. Testing the chi squared against a significance level of 5%, the null hypothesis that the model has random effect is either accepted or rejected.

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Heteroscedasticity

Furthermore there has to be tested for heteroscedasticity, since OLS estimators assume that error terms are uncorrelated and identically distributed and thus homoscedastic. If the error terms seem to be heteroskedastic, robust standard errors have to be used. To test for heteroscedasticity the likelihood ratio test is used. Testing against a significance level of 5% the null hypothesis that the error terms are homoscedastic is either rejected or accepted. If the null hypothesis is rejected and the error term is assumed to be heteroskedastic, robust standard errors have to be used.

Linearity

As discussed in the literature review, this study also tests for linearity. The relationship between CFP and CSP can either be linear or non-linear. The non-linear relationship can either be U-shaped or inverted U-shaped. To test for linearity we add an extra variable, the squared of the variable CSP.

𝐶𝐹𝑃!" = 𝛽0 + 𝛽1𝐶𝑆𝑃!"+ 𝛽2𝐶𝑆𝑃2!"+ 𝛽3𝑅𝐼𝑆𝐾!"+ 𝛽4𝑆𝐼𝑍𝐸 + 𝜀

i=firm(1...54), t=time(2002…2015)

The results of Beta 1 and Beta 2 show if there is a linear or nonlinear relation between CSP and CFP. If the signs of the two Betas are the same, there can be concluded that there is a linear relation. If the signs differ, there is a nonlinear relation. The nonlinear relation can either be shaped or inverted U-shaped. If Beta 1 is positive and B2 is negative, the relation is inverted U-shaped where there is a maximum CSP score where a firms’ CFP is at its maximum. If Beta 1 is negative and Beta 2 is positive, the relation is U-shaped. This means that CSP only pays-off when the firm meets the minimum CSP score required.

OLS regressions

After it is clear whether random or fixed effects have to be used and whether there has to be a

correction for heteroscedasticity, the correct OLS regressions can be made. In this study that includes the period 2002-2015, the financial crisis of 2008 is included. The subprime mortgage crisis started in 2007 in the US, but since the global financial crisis started in September 2008 the years 2008 and 2009 are considered as the years of the financial crisis. Therefore, three regressions are made. One

regression that contains the period 2002-2007, one that contains the period 2008-2009 and one that contains the period 2010-2015.

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CHAPTER 5 Results

This chapter includes the results of the Hausman test, test for heteroscedasticity and the results of the different regressions. All results are tested against a 5% significance level. After analysing the different results, conclusions for the hypotheses are made.

Table 5.1: Summary of the variables CFP, CSP, RISK and SIZE, with 54*14=756 observations.

Obs Mean Std. Dev. Min

Max

CFP

756 5.518

6.643 -53.220 75.090

CSP

756 73.943 24.213

2.620

97.640 RISK

756 27.609 15.074

0

90.030 lnSIZE

756 15.981 1.585

12.026

19.721

CFP = Corporate Financial Performance

CSP = Corporate Sustainability Performance RISK = Riskiness of the firm, total debt/total assets lnSIZE = Logarithm of the total assets

As can be seen in table 5.1, there is a high variation across the 54 companies included in this study when it comes to the CFP – CSP relationship and riskiness of the firm. The natural logarithm of the firm’s size varies between 12.026 and 19.721, so there can be said that there are no huge

differences across companies when it comes to size. What you can see is that there are firms that perform really badly on CSP, with a minimum value of 2.62 on a scale from 0 to 100. And there are firms that score really high on CSP, with a maximum value of 97.64. The mean of the corporate sustainability performance in a sample of 54 companies in 14 years is 73.943, which is assumed to be high. So, on average the companies perform well on corporate sustainability.

Table 5.2: The correlation between the different variables

CFP

CSP

RISK lnSIZE

CFP

1.000 CSP

0.008

1.000 RISK

0.048 0.080 1.000

lnSIZE -0.231 0.390 0.031 1.000

The correlation between variables is assumed to be high when it is above 0.5 or below -0.5. Since this is not the case, there can be concluded that the correlation between the variables is low. The table shows that there is a positive relation between firm’s size and the CSP. This finding is in line with Stanwick (1998), Orlitzky (2003) and Ruf et al. (2001) who all found a positive relation between firm’s size and the level of CSP. Furthermore, we see a positive relation between the logarithm of firm’s size and the firm’s risk, where risk is the debt-to-total assets ratio. Empirically findings show

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that firm size is strongly positively related to capital structure (Kurshev and Strebulaev, 2005). The presence of fixed costs in large firms is considered to be the driving force that creates the wedge between small and large firms (Kurshev and Strebulaev, 2005). In the correlation between the logarithm of firm’s size and CFP, we see a negative sign. This means that the ROA is negatively related to the logarithm of the firm’s total sales. Furthermore, we see that the riskiness of the firm is positively related to CFP and CSP.

Table 5.3: Results of the pooled OLS regression of the total period

CFP

Coef.

Std. Err. z

P>z

95% Conf. Interval

CSP

0.030 0.013

2.28 0.023 0.004

.056

RISK

- 0.039 0.020

-1.87 0.061 -0.080

.001

lnSIZE -1.320 0.267

-4.95 0.000 -1.847

-.799

Cons

25.518 4.015

6.36 0.000 17.648

33.387

R2= 0.119 Adjusted R2= 0.066

The pooled OLS regression shows that CSP is positively related to CFP. The coefficient of

.030

is significant with a significance level of 0.023. The riskiness of the firm and the firm’s size are negatively related to CFP. But where the result of RISK is insignificant, SIZE is significant.

Table 5.4: Results of the Likelihood-ratio test

Likelihood-ratio test

LR chi2(58)

618.80 (Assumption: homosk nested in

hetero)

Prob > chi2

0.000

The Likelihood test shows us that there need to be controlled for heteroscedasticity. Therefore the regressions in table 5.5 till 5.11 use robust standard errors

Table 5.5: Results of the pooled OLS regression with robust standard errors

CFP

Coef.

Robust Std. Err. z

P>z

95% Conf. Interval

CSP

0.030 0.0116

2.59 0.010 0.007

0.053 RISK

-0.039 0.0297

-1.32 0.188 -0.097

0.019 lnSIZE -1.323 0.3731

-3.55 0.000 -2.055

-0.592

Cons

25.518 5.7836

4.41 0.000 14.182

36.853

R2= 0.119 Adjusted R2= 0.066

After correcting for heteroscedasticity the coefficients remain the same, but the probability values of z changes. The significance level of CSP changes from 0.023 to 0.010 and that of the variable RISK increases to 0.188. Therefore after correcting for heteroscedasticity, the coefficient of RISK becomes insignificant.

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Whether to use the fixed or random variable model, the Hausman test is used. The results show that with a significance level of 0.0001 the null hypothesis that the model contains random effects is rejected. The OLS regressions have to be corrected for fixed effects using the least square dummy variable (LSDV).

Table 5.6: Results of the cross-sectional fixed effects estimation using LSDV with robust standard errors for the total period

CFP

Coef.

Robust Std. Err. t

P>t

95% Conf. Interval

CSP

0.031

0.016 1.94 0.053 -0.000

0.064 RISK

-0.099 0.027

-3.64 0.000 -0.153

-0.045

lnSIZE -1.880 0.596

-3.15 0.002 -3.052

-0.709

Cons

35.285 9.652

3.66 0.000 16.334

54.237

R2= 0.309 Adjusted R2= 0.253

Using the fixed effects OLS regression, the coefficient of CSP stays roughly the same. There is a tiny increase from

.030

to 0.031. However, the relation does not seem to be significant. Where we test against a significance level of 5%, it is said that CSP has no significant effect on CFP. The negative coefficient of the variable RISK decreases and becomes significant. Size is also significant and negatively related to CFP with a coefficient of -1.88. The R-squared improved compared to the pooled regression, therefore using the fixed effects model may indicate a better fit.

Heteroscedasticity in the pooled OLS regression doesn’t mean that there is also

heteroscedasticity in the fixed effect model, but since there is no compelling reason to believe that there is homoscedasticity we assume that there is heteroskedasticity in the fixed effect model. But the conventional robust standard errors estimator is inconsistent for a fixed effects panel data regression (Stock, Watson, 2008). Therefore, to control for heteroscedasticity we need to use a bias-adjusted heteroscedasticity robust estimator. Using clustered standard errors helps us to get the following table: Table 5.7: Results of the cross-sectional fixed effects estimation using LSDV and cluster(id)

CFP

Coef.

Robust Std. Err. t

P>t

95% Conf. Interval

CSP

0.031

0.013 2.43 0.015 0.006

0.057 RISK

-0.099 0.029

-3.43 0.001 -0.156

-0.042

lnSIZE -1.880 0.514

-3.66 0.000 -2.890

-0.871

Cons

35.285 8.141

4.33 0.000 19.301

51.269

R2= 0.309 Adjusted R2= 0.253

Controlling for heteroscedasticity in the fixed effect model only changes the probabilities. All variables are now significantly related to the dependent variable CFP.

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To see if there are differences in the effect of CSP on CFP before, during and after the financial crisis the following three regressions were made. These regressions are controlled for fixed effects and heteroscedasticity.

Table 5.8: Results of the cross-sectional fixed effects estimation for the period 2002-2007 using LSDV and cluster(id)

CFP

Coef.

Robust Std. Err. t

P>t

95% Conf. Interval

CSP

0.036

0.015 2.44 0.015 0.007

0.066 RISK

-0.149

0.047 -3.14 0.002 -0.243

-0.055

lnSIZE 1.330

0.825 1.61 0.108 -0.294

2.955 Cons

-16.792 13.774

-1.22 0.224 -43.913

10.328

R2= 0.502 Adjusted R2=0.472

CFP

Coef.

Robust Std. Err. t

P>t

95% Conf. Interval

CSP

0.358

0.117 3.04 0.004 0.121

0.595 RISK

0.540

0.451 1.20 0.237 -0.365

1.446 lnSIZE -0.751

12.771 -0.06 0.953 -26.391

24.889 Cons

-27.257 215.045

-0.13 0.900 -458.979

404.464

R2 = 0.670 Adjusted R2= 0.65

CFP

Coef.

Robust Std. Err. t

P>t

95% Conf. Interval

CSP

0.013

0.063 0.21 0.832 -0.111

0.137 RISK

-0.304 0.093

-3.27 0.001 -0.487

-0.120

lnSIZE -0.886 2.265

-0.39 0.696 -5.346

3.573 Cons

21.328 40.705

0.52 0.601 -58.816

101.474

R2= 0.495 Adjusted R2= 0.464

The three regressions show different results when it comes to the relation between CSP and CFP. In the period 2002-2007, the pre-crisis period, we observe a 0.036 positive coefficient that is highly significant. However the positive coefficient is really small, there is a significant effect of CSP on CFP found in the period of 2002-2007.

In table 5.7, the coefficient of CSP in the period 2008-2009 is found to be highly increased compared to the coefficient in the period 2002-2007. There is a positive coefficient found of 0.358 that is even more significant than the previous coefficient found of 0.0369. This means that during the

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financial crisis of 2008 the companies’ Corporate Sustainability Performance has a positive effect on the Corporate Financial Performance. These results support the findings of Schniets & Epstein (2005) and Ducassy (2012). In times of financial crisis it seems to be important for stakeholders that firms’ activities are social responsible and sustainable and therefore firms with a high CSP face a competitive advantage compared to the firms with a lower CSP. Furthermore, the R2 increased with approximately 17%, which means that the goodness-of-fit, of the model used, increased in the period 2008-2009 compared to 2002-2007.

Table 5.7 provides us with the results of the regression in the period after the financial crisis, 2010-2015. The coefficient is still positive with 0.013, but drastically decreased compared to the coefficient in the period 2008-2009. Furthermore the positive coefficient is highly insignificant. This result is in line with the results of Ducassy (2012), she found a significant positive relation between CSP and CFP in the years of the financial crisis, but this was just temporarily. Comparing the results of 2010-2015 to the results of 2002-2007, we see that the effect of corporate sustainability

performance on corporate financial performance decreased. Before the crisis the effect of CFP was positive significant, where after the crisis the effect is positive insignificant and therefore corporate sustainability is said to have no effect on corporate financial performance in the period 2010-2015.

To test for linearity, the control variable CSP2 is added. This variable is the squared of the variable CSP. Table 5.10 contains the results of the regression made included the variable CSP2. Table 5.11: Test for linearity using fixed effects and cluster(id)

CFP

Coef.

Robust Std. Err. t

P>t

95% Conf. Interval

CSP

0.055

0.047

1.18 0.239 -0.037

0.149 CSP2

-0.000 0.000

-0.49 0.622 -0.001

0.000 RISK

-0.099 0.029

-3.43 0.001 -0.156

-0.042

lnSIZE -1.874 0.512

-3.65 0.000 -2.881

-0.867

Cons

34.732 8.122

4.28 0.000 18.783

50.680

As we can see, the coefficient of CSP is positive and the coefficient of CSP2 is negative, this would say the relation between CSP and CFP is nonlinear and is inverted U-shaped. But the t-test tells that the coefficients are both non significant, so that the null hypotheses is not rejected and we assume both coefficients are zero. Another way to check for this is to calculate the point where the curve bends. The following formula is used, where X1 is the point where the relation changes sign:

𝑋1 = − 𝛽1 2𝛽2

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The outcome is approximately 137.4, since this number is outside the range of 0-100 the relationship appears monotonic. This means that CFP always increases as X increases. Concluding the relationship between CFP and CSP is linear.

CHAPTER 6 Conclusion

Summarizing the results found, we could answer the research question: Does Corporate Sustainability Performance affect the firm’s Financial Performance in the industrial goods sector? The overall finding is that there is a significant positive relation between CSP and CFP and therefore Corporate Sustainability Performance affects the firm’s Financial Performance in the industrials goods sector. After testing for linearity, we found that a higher CSP score always results in a higher CFP.

The pooled OLS regression and the cross-sectional fixed effects estimation using LSDV found nearly the same results according to the relation between CSP and CFP. For the total sample period 2002-2015 we can conclude that corporate sustainability performance has a positive effect on the firm’s financial performance. The first Hypothesis: Corporate Sustainability Performance has a positive effect on the firm’s Financial Performance in the period 2002-2015 is therefore accepted. Looking at the period before, during and after the financial crisis we found that corporate sustainable firms face less negative effects in times of crisis and CSP can be seen as an opportunity rather than a threat during the financial crisis of 2008. The coefficient increased from 0.036 to 0.358 and therefore the second hypothesis: Corporate Sustainability Performance has an increasingly positive effect on firm’s Financial Performance during the financial crisis of 2008 is also accepted.

But in line with Ducassy (2012) this opportunity seems to be temporarily, since the coefficient after the financial crisis turns out to be positive but insignificant and therefore there can be concluded that CSP has no longer effect on the firm’s financial performance. The third hypothesis: Corporate Sustainability Performance has a positive effect on firm’s Financial Performance in the period 2010-2015, but the effect is less compared to the previous years of financial distress is rejected. There is no relation found between CSP and CFP in the period 2010-2015.

6.1 Limitations and suggestions for future research

This study faces several limitations. First of all, there were a significant amount of missing data in the period 2002-2015, whereby a lot of companies had to be excluded and the sample stayed rather small. Furthermore there still is no common way to measure Corporate Sustainability Performance. In this study Thomson Reuters ASSET4 ESG is used, but it is still unclear whether this database provides all the information according to environmental, social and corporate governance performance. Using different databases and doing some self-research may help to solve this problem. Another limitation is that this study only uses the overall average score of the three pillars Environmental, Social and

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Corporate governance as measure for CSP. For further research different regressions can be made for the Environmental, Social and Corporate Governance score, to see which pillar affects CFP the most or which pillar might be negatively correlated to CFP.

Because this study only focuses on the Industrials Goods sector, it can’t be said that there is a positive relation between CSP and CFP in general. Since ASSET4 rates all companies against a benchmark within their sector, each sector has to be evaluated separately when using this database as a measure for CSP. So further research has to be done according to the relation between CSP and CFP in different industries and in general.

In this research the ROA is used as measure for the firm’s financial performance. This measure is used because previous studies showed a significant relation between the firm’s ROA and their CFP. Several studies using market based measured for CFP found an insignificant relation between CFP and CSP. However accounting measures such as ROA, ROE and ROS only focus on the past performance, whereas market shareholder value focus on future performance and Tobin’s q on both past and future performance. For further research more measures for the variable CFP can be used.

The control variables used in this study are company’s size and risk. Due to limited data availability on European firms control variables such as R&D expenditures and advertising costs couldn’t be included.

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Corporate sustainability performance and corporate financial performance in the industrials good sector