Business Finance - Management Business Finance - Management ASSIGNMENT (APA, NO PLAGARISM, GREAT WORK, ON TIME)
Pelicans!!322
Week6The_impact_of_a_firms_ESG_sco.pdf
The impact of a firm’s ESG score on its cost of capital: can a high
ESG score serve as a substitute for a weaker legal environment
Randy Priem and Andrea Gabellone UBI Business School, Brussel, Belgium
Abstract Purpose – This article aims to analyse the relationship between the environmental, social and governance (ESG) score and the cost of capital of 600 large, mid and small capitalization companies across 17 countries that are component of the EURO STOXX 600 Index. By examining whether ESG has an impact on the cost of capital, this article contributes to the solutions to improve the impact of organizations and societies on sustainable development. The article further examines whether the effect is because of the environmental, social and/or governance components. In addition, the article analyses which WACC component (i.e. the cost of equity, the cost of debt, the beta or the leverage ratio) is affected. Furthermore, this article analyses whether a high ESG score can substitute for a weaker legal environment. Design/methodology/approach – The results were obtained by using ordinary least squares panel data modelling to analyse the relationship between the ESG score and the cost of capital. The sample consists of companies that are part of the STOXX Europe 600 Index over the period 2018–2021, which is composed of 600 companies, including large, mid and small capitalization firms listed across 17 countries. The sample finally includes 1,960 firm-year observations. Findings – Companies with a higher ESG score tend to have a lower cost of capital, but this relationship holds only for firms domiciled in countries with a weaker legal environment. In addition, these firms should not only increase their ESG score to create a more sustainable environment but also to reduce their cost of debt. Environmental and social factors have a significantly negative impact on the cost of capital only in countries with a weaker legal environment, while the governance component positively impacts the cost of capital by allowing firms to borrowmore. Research limitations/implications – There is not yet a standardized taxonomy to define ESG, making the study dependent on commercial data providers. Practical implications – The new insights can be used by companies domiciled in countrieswithweaker legal environments to reduce their cost of capital. The results also allow us to know onwhich components of the ESG score to focus. It can also help policymakers, specifically those in countries with a weaker legal environment, to provide incentives to further stimulate ESG investments and disclosure, thereby contributing to amore sustainable society. Social implications – To achieve the sustainable development goals put forward by the United Nations, it is important for firms to invest in ESG projects. It is nevertheless insightful to know whether these ESG investments, which are currently observed as a cost, also provide benefits to firms and in which countries. If firms clearly see the advantages of investing in ESG projects, they are likely to proactively engage in them. Originality/value – This article is the first, to the best of the authors’ knowledge, to focus on 17 European countries, thereby capturing divergent legal environments. This setting allows us to answer the main novel research question, namely, whether the ESG score can act as a substitute for the legal environment in which the company is
JEL classification – G3, G31, Q5 The authors like to thank Giuseppe Bellia, Gaston Fornez, Maria Altamira, Alvaro Mendez, Ro
van den broeck, S�ebastien Wolf, S�ebastien Martino, An De Pauw, Joachim Van Wymmeersch and Sofie Verweire for their useful comments on an earlier version of this article.
SAMPJ 15,3
676
Received 1May 2023 Revised 13 September 2023 21 November 2023 Accepted 1 January 2024
Sustainability Accounting, Management and Policy Journal Vol. 15 No. 3, 2024 pp. 676-703 © EmeraldPublishingLimited 2040-8021 DOI 10.1108/SAMPJ-05-2023-0254
The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/2040-8021.htm
domiciled. The article also goes further than previous articles by examining whether the effect is because of the environmental, social and/or governance component and whether these impact the components of the weighted cost of capital, namely, the cost of equity, the cost of debt, the beta or the leverage ratio of the companies.
Keywords ESG, Cost of capital, Sustainable finance, Capital structures
Paper type Research paper
1. Introduction On 25 September 2015, the United Nations adopted the 2030 Agenda for Sustainable Development. The 2030 Agenda contains the 17 sustainable development goals (SDGs) [1] and covers the three dimensions of sustainability: environmental, social and governance (ESG) [2]. These goals recognize that ending poverty must go hand-in-hand with strategies that improve health and education, spur economic growth and reduce inequality while also tackling climate change. The objective is to reach these goals by 2030.
In addition to the SDGs, the European Union approved on 5 October 2016, the Paris Agreement adopted under the United Nations Framework Convention on Climate Change. One of the goals is to strengthen the response to climate change by making financial flows consistent with a pathway towards low greenhouse gas emissions and climate-resilient development. As a result, the Commission mandated in December 2016 a high-level expert group to develop a Union strategy on sustainable finance, which reported on 31 January 2018, that a technically robust classification system should be created to establish clarity on which activities quality as “green” or “sustainable”.
The European Commission published on 8 March 2018, its action plan on financing sustainable growth, launching a comprehensive and ambitious strategy for sustainable finance. One objective of this action plan is to reorient capital flows towards sustainable investments to achieve inclusive and sustainable growth. This work finally resulted in the Sustainable Finance Disclosure Regulation (SFDR) [3] and the Taxonomy Regulation [4]. While SFDR focuses on disclosure by financial participants (e.g. investment firms and credit institutions), the Taxonomy Regulation has a broader scope and contains a classification system, thereby establishing a list of environmentally sustainable economic activities and providing companies, policymakers and investors with appropriate definitions for which economic activities can be considered environmentally sustainable. On 10 December 2021, a delegated act supplementing the Taxonomy Regulation was published in the Official Journal of the European Union, specifying the content, methodology and presentation of information to be disclosed concerning the proportion of environmentally sustainable economic activities in their investments, lending or business activities. Further regulatory standards are currently under development.
On 21 April 2021, the European Commission proposed a Corporate Sustainability Reporting Directive [5], amending the existing reporting requirements of the non-financial reporting directive (NFRD) [6]. Where the NFRD set rules for large public-interest companies (i.e. companies with more than 500 employees, including listed entities, banks and insurance companies) containing the rules on the disclosure of non-financial and diversity information, the new directive would apply to listed companies, banks, insurance companies and other companies designated by national authorities as public-interest entities. These entities would have to publish information related to environmental matters, social matters, treatment of employees, respect for human rights, anti-corruption and bribery and diversity on company boards. The proposal would not only apply to EU-based companies but also to non-EU-based companies that have a subsidiary in the European Union.
Because of the aforementioned global and European rules and incentives, sustainable investing has set records (see, e.g. de Zwaan, 2015).While definitions of ESGmight vary between
The impact of a firm’s ESG
score
677
Europe and other parts of the world, ESG investments are expected to rise to $50tn by 2025 [7]. According to Bloomberg, Europe and the USA are currently the market leaders with a total of $30tn in assets under management, followed by Japan, Canada and Australia. In a survey conducted by PwC (2021) [8], nearly 80% of investors responded that ESG was an important factor in their investment decision-making. Even more, 50% of the investors indicated that they are willing to divest companies from their portfolios that do not have clear and measurable ESG targets. These figures illustrate that corporates should not only contribute to the current social and environmental sustainability challenge by increasing their ESG score but should also do so if they wish to continue attracting investors’ funds in the future, especially at a low cost. Although some scholars find evidence that firms with high ESG ratings are found to enjoy better financial and market performance (Aboud and Diab, 2019), the question for many corporates also arises whether the additional costs to increase the ESG score are compensated by other financial advantages, such as the ability to have a lower cost of capital.
This article is the first to analyse the relationship between the ESG score and the cost of capital of 600 large, mid and small capitalization companies across 17 countries that are component of the EURO STOXX 600 Index. The article further examines whether the effect is because of the environmental, social and/or governance components. In addition, we analyse whether all components of the weighted cost of capital (WACC), such as the cost of equity, the cost of debt, the beta or the leverage ratio of the companies, are impacted. In this way, we can examine whether, e.g. creditors or shareholders have a different perception of the benefits of ESG activities. This article focuses on the impact on the cost of capital, as this represents an important factor for the viability and growth of a business given that it impacts the decision whether to take on specific projects, carry on investments or raise further capital.
By examining whether corporates with a higher ESG score obtain a lower cost of capital, we contribute to the sustainability literature on the relationship between non-financial disclosures and the cost of capital. Previous literature on the impact of ESG on the cost of capital is currently scarce, which focuses mainly on the cost of debt (e.g. Goss and Roberts, 2011; Oikonomou et al., 2012), the cost of equity (e.g. Sharfman and Fernando, 2008; El Ghoul et al., 2011), both (e.g. Gonçales et al., 2022; Yilmaz, 2022) or leverage (e.g. Adeneye et al., 2022) without focusing on other aspects of the weighted cost of capital as dependent variables, such as beta. These studies often find contradictory or inclusive results, most likely because they focus on particular countries, such as the USA (e.g. Sharfman and Fernando, 2008; Dhaliwal et al., 2011), Canada (Richardson and Welker, 2001), South Africa (e.g. Johnson, 2020), Malaysia (e.g. Atan et al., 2018), Australia (e.g. Bhuiyan and Nguyen, 2020), China (e.g. Liu et al., 2023; Chen et al., 2023), Japan (e.g. Suto and Takehara, 2017), emerging countries, such as Kuwait, the Philippines, Qatar and Indonesia (e.g. Mohammad et al., 2023), and Latin America (e.g. Ramirez et al., 2022). Besides, the European continent seems to be largely ignored. For European corporations that need to adhere to all new types of sustainable regulation, it is not yet sufficiently clear whether their cost of capital can be decreased by investing more heavily in ESG projects. The results of previous studies might also not be generalized to the European region given that the stringency of regulations and the associated level of litigation risk are different between continents (see e.g. Dhaliwal et al., 2011).
As the European continent, including the UK, is diverse in terms of countries’ legal ecosystems (i.e. common vs civil law countries), examining Europe offers the opportunity to be the first to examine whether the impact of a firm’s ESG score on its cost of capital differs between countries with divergent institutional settings. If a country indeed has a weaker legal environment, it might be expected that corporations domiciled in that country try to compensate to convince financiers to provide funds at a lower rate by improving their ESG rating and disclosure. To test this assumption, this article is the first, to the best of the authors’
SAMPJ 15,3
678
knowledge, to explore whether the World Bank’s Governance Indicators (i.e. voice and accountability, political stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law and control of corruption) moderate the relationship between the firms’ ESG score and their cost of capital. In this way, this article brings together research from a range of disciplinary approaches to address social and environmental sustainability challenges by improving the understanding of the mechanisms by which ESG affects a firm’s cost of capital and the interplay between firm-level and country-level governance.
This article further contributes to the literature by not only examining whether the ESG score has an impact on its cost of capital but also whether the individual dimensions of ESG have an impact. Until now, it has indeed not been examined whether the impact of ESG factors on the cost of capital is different, and financiers thus attach more importance to one dimension over the other. Compared to previous literature (e.g. Dhaliwal et al., 2011; Ng and Rezaee, 2015), we also examine the impact on the cost of capital components, which are the cost of debt, the cost of equity, beta and the leverage ratio of the firm. Compared to previous literature focusing on a single component of the cost of capital, this article thus provides a more holistic view on whether ESG positively or negatively impacts a firm’s cost of capital and the underlying reasons why this is the case.
We find significant evidence that companies with a higher ESG score have a lower cost of capital, but this relationship holds only for firms domiciled in countries with a weaker legal environment, thereby providing evidence for the substitution effect. The ESG score does not seem to have a significant impact on the cost of equity and the beta, although the ESG score has a significant negative impact on the cost of debt for firms located in a country with a weaker legal environment. In these countries, creditors have fewer rights andmight feel more protected in case a firm has a higher ESG score, thereby signalling their high-quality firm-specific governance (see, e.g. Shevelena, 2022). Credible disclosures could thus reduce an information asymmetry between a firm and its creditors (see, e.g. Zhu, 2014). In countries with a higher legal environment, the cost of debt is generally already lower (see, e.g. Djankov et al., 2003; Qi et al., 2010) so an ESG score could matter more for those firms having a higher cost of debt because they are located in a country with a weaker legal environment. In countries with a higher legal environment, investors are willing to fund debt marks at a lower cost because the control mechanisms of laws are in place to mitigate agency conflicts at firms by facilitating corporate governance practices (see, e.g. Ozer and Cam, 2022). Thus, it is in countries with a lower legal environment that the ESG rating is still of particular relevance. We further see that firms with a high ESG score can significantly obtain more leverage. In terms of the ESG components, especially the environmental and social factors, they have a significantly negative impact on the cost of capital, mainly in countries with a weaker legal environment, suggesting that investments in ecological and social projects can serve as a substitute for weaker country-level governance. The environment and social scores also have a significant negative impact on the cost of equity and the cost of debt in countries with a weak legal environment, while firms with a high environmental and/or social score can obtain more leverage in countries with weaker legal protection. In contrast, the governance score seems to have a significant positive impact on theWACC, the cost of equity, the cost of debt and leverage. The impact on the cost of equity and the cost of debt is, however, significantly negative for firms in aweaker level environment.
The remainder of this paper is organized as follows. Section 2 provides a detailed literature review and outlines our hypotheses, while Section 3 outlines our research design and methodology, including a discussion of the sample and the variables. Section 4 provides summary statistics, while Section 5 entails a detailed review of our regression outcomes. Section 6 discusses our performedsensitivity checks, while Section 7 concludes and provides future research topics and policy advice.
The impact of a firm’s ESG
score
679
2. Literature review and hypotheses In this section of the article, we provide arguments supporting our claim that firms with a higher ESG score have a lower cost of capital. First, a higher ESG score could reduce information asymmetries, as firms can use this score to signal to external financiers that they are a high-quality firm (see, e.g. Dhaliwal et al., 2011). If investors believe that they are better informed, they are likely to reduce their expected return. That is, investors and financial analysts typically take improved ESG factors into account when granting funds or providing positive recommendations, and the more likely that the firm is behaving decently from an ESG perspective, the more eager financiers could be to provide financing at a lower cost (see, e.g. Sharfman and Fernando, 2008). According to Bansal (2005), firms engaging in better environmental risk management are also more visible and are publicly mentioned in the media, thereby again attracting more investors at a lower cost.
Second, companies that have a higher ESG score mitigate the risk of litigation (see, e.g. King and Shaver, 2001). Investors indeed have more information to identify whether certain risks, such as oil spills, product recalls, accounting fraud or radiation, are lower in cases of a higher ESG score. For high-ESG firms, potential investors might be more certain that the profit of the company will be directed strategically to dividends, debt payments or internal investments rather than to undesirable litigation costs. Because of the reduced risk perception, investors might also be less likely to quickly sell these stocks in case of an economic downturn, leading to reduced volatility of the firm’s stock as measured by its beta. In addition to fewer adverse selection problems, companies with strong ESG disclosure typically also have strong corporate governance in place, leading to a reduction in perceived risk for the firm with a negative impact on the company’s cost of capital (see also Ashbaugh et al., 2004; Pham et al., 2020).
Sharfman and Fernando (2008) argue that the relationship between the cost of capital and environmental risk management is negative because of the types of investors that green firms attract. Green investors might only be willing to invest in firms with higher ESG scores. This results in companies having a higher ESG score to be capable of attracting more investors at a lower cost (see also Mackey et al., 2007; Ramirez et al., 2022; Hong and Kacperczyk, 2009). Petersen and Vredenburg (2009) document that the majority of institutional investors now prefer high ESG firms, illustrating that high ESG scores can help firms obtain a wider range of investors. Also, lenders are increasingly incorporating environmental issues into their lending decisions. Based on the aforementioned arguments, we formulate the following hypothesis:
H1. The coefficient offirms’ESG score on their cost of capital will be significantly negative.
In this article, we also hypothesize that the negative impact of the ESG score on the cost of capital prevails mainly in countries with a weaker legal environment, suggesting a substitution effect. That is, in countries unable to protect the accuracy of disclosed information or where the quality of political institutions is low, financiers might be more concerned with a firm’s downside risk (see, e.g. Ge et al., 2012; Zhu, 2014). According to institutional theory (e.g. DiMaggio and Powell, 1983; Mizruchi and Fein, 1999), organizations must incorporate institutional rules to achieve legitimacy and their survival. In cases where the institutional rules are thus of weaker quality, their internal controls have to increase, which is costly. To attract financing at a lower cost, firms domiciled in these countries might compensate by investing heavily in ESG projects and disclosure to convince financiers (e.g. Klapper and Love, 2004; Durnev and Kim, 2005). In countries with weaker legal institutions, ESG laws could be less enforced, but financiers might still be concerned that when the company faces claims because of social or environmental violations, they will be less
SAMPJ 15,3
680
protected in countries with weaker legal systems (see e.g. Durnev and Kim, 2005). Shareholders are also heavily concerned with the quality of firm-level governance to constrain the moral hazard problems of insider management. In countries with weaker legal institutions associated with less independent judicial systems, firms could find it optimal to invest more in ESG to increase their creditability (see, e.g. Aggarwal et al., 2009). Creditors are also concerned by shareholders exchanging low-risk assets for high-risk investments, which could be more prevalent in cases of poor legal institutions. To attract equity financing at a lower cost, strong firm-level governance mechanisms can be put in place to restrict insider expropriation (John et al., 2008).
Not only is it worthwhile to increase the governance and/or social component of the ESG score, but also the environmental score in countries with lower investor protection. That is, a firm taking care of the environment could signal its superior quality and engagement, which is especially relevant when overall investor protection is limited. Investor preferences may have shifted in recent years, with them worrying more about climate-related financial hazards, fueling an increase in the importance placed on sustainability risk when evaluating a company (Eccles and Klimenko, 2019). Firm-level disclosures on ESG could reduce information asymmetries between the firm and its investors. If creditors or shareholders can verify that the firm is ecological, they might be less concerned about ecological violations, which is of more relevance in countries where the rule of law is less strong. Based on the aforementioned arguments, we postulate the following hypothesis:
H2. A firm’s ESG score negatively impacts its cost of capital, especially in countries with a weaker legal environment.
3. Sample, variables and model Our sample consists of companies that are part of the STOXX Europe 600 Index over the period 2018–2021. Our sample is thus composed of 600 companies, including large, mid and small capitalization firms listed across 17 countries of the European continent: Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Luxembourg, The Netherlands, Norway, Poland, Portugal, Spain, Sweden, Switzerland and the UK.We thus entail common law aswell as civil law countries in our sample. This STOXX Europe 600 Index is globally recognized by institutional investors and provides the broadest proxy for the European economy. In line with previous research, such as Johnson (2020), we exclude companies operating in the financial sector from the sample set, as these issuers are subject to a different EU regulatory framework compared to other firms. Our sample finally includes 1,960 firm-year observations.
To test whether the ESG score has a negative impact on the cost of capital of European firms, we follow Sharman and Fernando (2008), Khanchel and Lassoued (2022) and Johnson (2020) and retrieve from Bloomberg the WACC, the cost of equity, the cost of debt, the beta and the leverage of the firm as dependent variables. Bloomberg calculates the WACC by applying the following formula:
WACC ¼ EQUITY LEVERAGE þ EQUITY
� � COSTOFEQUITY
þ LEVERAGE LEVERAGE þ EQUITY
COSTOFDEBT 1� Tð Þ
where EQUITY represents the market value of the firm’s equity and LEVERAGE represents the market value of the firm’s debt. EQUITY is found by Bloomberg by using the
The impact of a firm’s ESG
score
681
total market capitalization divided by the debt plus market capitalization. LEVERAGE is taken from its last financial reporting and is calculated as the ratio of long-term outstanding debt divided by total assets reported by the firm. COSTOFEQUITY equals the firm’s cost of equity capital, while COSTOFDEBT is the firm’s cost of debt capital. T stands for the firm’s rate of corporate taxation. The cost of equity capital is estimated by Bloomberg using the CAPM, which equals the cost of equity of a firm to the risk-free interest rate plus the firm’s beta times themarket risk premium:
COSTOFEQUITY ¼ rf þ BETA RM � rf � �
where rf is the risk-free rate, RM is the return on the market portfolio and BETA measures the firm’s systematic risk and is calculated on a weekly basis by Bloomberg as the covariance between the return on equity of the firm and the market return divided by the variance of the market return. Bloomberg uses the local country’s 10-year government bond yield as a proxy for the current risk-free rate (Rf). BETA is estimated by Bloomberg using the market model and regression analysis versus the country’s blue-chip index, over a period of two years using weekly returns data. The cost of debt is the firm’s marginal cost of borrowing, calculated as the interest paid during a given financial year and expressed as a percentage of the total interest-bearing debt.
The main independent variables, namely, the ESG scores, are provided by Refinitiv, following many academic studies, such as Albuquerque et al. (2020), Bae et al. (2020), Demers et al. (2021), Mahmut et al. (2022), Dyck et al. (2019), Gonçales et al. (2022) and Ramirez et al. (2022). Refinitiv offers one of the most comprehensive ESG databases, covering over 85% of the global market across more than 630 different ESGmetrics. That is, ESG metrics like the usage of resources, emissions and innovations are included to calculate the environmental score, while metrics on the workforce, human rights, community and product responsibility are used to develop the social score. Metrics on management, shareholders and corporate social responsibility serve as input for the governance score. The environmental (ENVIRON), social (SOCIAL) and governance (GOVER) scores are then aggregated into an ESG score. The input for4 all ESG metrics comes from the firms’ annual reports, company websites, NGO websites, stock exchange filings, CSR reports and news sources. Refinitiv also performs around 400 error checks in the data collection tool and runs around 300 automated quality checks on the outcome together with independent audits to ensure a high-quality ESG score. We take the natural logarithm of the various ESG scores.
A potential endogeneity effect might be present given that companies that increase their leverage might also start disclosing more ESG information because of the increased scrutiny from financial institutions and an increase in debt covenants (Atan et al., 2018). Also, any cost of capital might be a driver of the ESG score because companies with a high cost of capital might be more eager to have it reduced by investing in ESG projects. To address this endogeneity effect, we follow Sharfman and Fernando (2008), Dhaliwal et al. (2011) and Ng and Rezaee (2015) by lagging the ESG factors and the control variables by one year in our panel dataset in addition to various robustness checks (see infra) [9].
To take the quality of the legal system of the country into consideration, we rely on the Worldwide Governance Indicators (WGI) of the World Bank. These indicators focus on six dimensions of governance: voice of accountability, political stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law and control of corruption. These six aggregate indicators combine the views of a large number of enterprise, expert and citizen survey respondents. They are based on over 30 individual
SAMPJ 15,3
682
data sources produced by a variety of survey institutions, NGOs, think tanks, private sector firms and international organizations. The WGIs were selected for this article given that they do not only focus on investor rights in a narrow sense but are also related to topics like human rights, freedom of association, quality of bureaucracy, political stability, investment freedom, fairness of the judicial process, property rights and corruption. Hence, the indicators are also related to social and environmental topics and not only to governance issues. The average value of the six WGIs is used in our regression model (LEGALENV).
In line with previous research, our study controls for several variables. Bloomberg was used for the data retrieval process, together with a manual screening of the companies’ annual accounts where the data provided by Bloomberg was incomplete. First, we control for the size (SIZE) of the firm, as larger firms may be under greater scrutiny by the public (Durnev and Kim, 2005). SIZE is calculated as the natural logarithm of the market capitalization of the firm, which is the number of shares outstanding multiplied by the current share price. Second, we control for the free float of a firm (FREE FLOAT), calculated as the percentage of the outstanding shares not held by insiders. As documented by Huo et al. (2021), the absence of large controlling shareholders might lead to more agency problems, potentially resulting in a higher cost of capital. Third, we control for a firm’s financial leverage (LEVERAGE), calculated as long-term debt divided by total assets when leverage is not the dependent variable. The reason is that companies with a higher leverage ratio might face more bankruptcy risks, leading to a higher cost of capital. Fourth, we include the return on assets (ROA) as a proxy for a firm’s profitability, given that more profitable companies are more likely to repay their debt or provide dividends, resulting in a lower cost of capital. Fifth, we control for the firms’ market-to-book (MTB) value as a positive relationship exists between the MTB ratio of a company and its expected return (see, e.g. Fama and French, 1992). Finally, we include year dummies as fixed effects (i.e. Y2019, Y2020 and Y2021) in our base panel regression model, where Y2018 is the reference category:
WACC ¼ b0 þ b1ESGþ b2LEGALENV þ b3SIZE þ b4FREE FLOAT
þb5LEVERAGE þ b6ROAþ b7MTBþ b8Y2019þ b92020þ b102021þ «
A panel data approach has the advantage over a cross-sectional analysis in that it gives more information with less collinearity amongst the variables, can control for individual heterogeneity, has more degrees of freedom and is more efficienct. To analyse whether the ESG score matters mainly for firms being domiciled in a country with a weaker legal environment, we create a dummy variable based on LEGALENV (i.e. LEGAL) for interpretation reasons, having a value of one in case LEGALENV is larger than the median and zero otherwise, and create an interaction term with ESG:
WACC ¼ b0 þ b1ESGþ b2LEGALþ b3ESG *LEGALþ b4SIZE þ b5FREE FLOAT þ b6LEVERAGE þ b7ROAþ b8MTBþ b9Y2019þ b102020þ b112021þ «
Table 1 displays the geographical distribution of the sample together with their average WGI score. Most of the firms in our sample are domiciled in the UK, followed by France, Germany and Sweden. In terms of the legal environment, Finland scores best, followed by Norway, Switzerland and Denmark. The countries having the lowest WGI scores are Italy, Poland and Luxembourg.
The impact of a firm’s ESG
score
683
4. Summary statistics Table 2 reports summary statistics on the dependent and independent variables. To limit the influence of outliers, we winsorized variables at 5%–95%. To facilitate the reading of the table, Table 2 displays the results in absolute values (i.e. before the logarithmic transformation).
We observe that the average value of WACC equals 8.065. The average cost of equity equals 10.523, while the cost of debt averages 0.421. The average BETA equals 0.933, and the average firm in our sample has a total debt to total assets ratio (LEVERAGE) of 22.40%. As for our main variables of interest, the average ESG score equals 67.871 with the ESG scores being of similar values (i.e. 70.504, 71.504 and 64.771, respectively). As for the control variables, the average WGI sore (LEGALENV) equals 1.381 and SIZE averages 9,248,760,000 EUR. The average free float of firms in our sample equals 77.893%, and firms have a return on assets of 6.333. TheMTB variable averages 4.203.
5. Multivariate results Table 3 displays pairwise correlations among the various continuous explanatory variables. As expected, the correlations between the various ESG indicators are large, and these variables will therefore not be included in the same regression models. The other correlation coefficients are smaller than 0.60, which allows us to assume that there are no further multicollinearity issues when including these explanatory variables together in the regressionmodels.
Table 4 reports the outcome of the multivariate panel regression models. Column 1 displays the results of our baseline model. Columns 3, 5, 7 and 9 report the results of the same explanatory variables on the components of the WACC. In Columns 2, 4, 6, 8 and 10, LEGALENV is replaced by its dummy LEGAL, and the interaction term with LEGALENV is included to detect whether the influence of the ESG score on the cost of capital matters
Table 1. Geographical distribution of the sample
Country N Aggregated WGI score
Austria 24 1.4333 Belgium 48 1.1917 Denmark 80 1.7042 Finland 64 1.7792 France 260 1.0875 Germany 244 1.4417 Ireland 40 1.3917 Italy 76 0.5333 Luxembourg 24 1.6958 The Netherlands 116 1.6250 Norway 52 1.7583 Poland 20 0.5958 Portugal 12 1.0250 Spain 80 0.8083 Sweden 224 1.6458 Switzerland 172 1.7208 UK 424 1.3292 Total 1960
Note: This table displays the distribution of the firm-year observations over the period 2018–2021 Source:Authors’ own work
SAMPJ 15,3
684
more in countries with a weaker legal environment. A dummy variable representing the legal environment of the country in which the firm is domiciled is preferred over a continuous variable for ease of interpretation.
The results in Table 4 reveal that the ESG score has a significant negative impact on the WACC. This effect seems to matter only for countries with a LEGALENV score below the mean, suggesting that the ESG score of a firm and its legal environment can act as substitutes. This effect is also economically significant given that a one standard deviation change in the ESG score results in a decrease of the cost of capital by 4.79% [10]. The ESG score does not seem to have a significant impact on the cost of equity, the cost of debt and the beta. Table 4 documents that for countries having weaker legal institutions, the impact of the ESG score on the cost of debt is significantly negative.
Concerning the control variables, LEGAL seems to have a significant positive impact on the WACC, a significant negative impact on the cost of debt and leverage, and a significant negative impact on leverage. We also see that LEGAL positively impacts beta. In addition, SIZE has a significant negative impact on the WACC and the cost of equity. Qualitatively similar results are obtained when the natural logarithm of the number of employees is used as a proxy for the size of the firm or the natural logarithm of total assets. FREE FLOAT has a significant positive impact on the cost of capital, the cost of equity, the cost of debt, beta and leverage. It thus seems that firms with a more dispersed shareholder structure can obtain more leverage but also contain more systematic risk, resulting in a higher cost of capital. Furthermore, ROA has a significant positive impact on the WACC and the cost of debt, while having a significant negative impact on the cost of equity, beta and leverage.
Table 2. Univariate analysis of the exploratory
variables
Variable Mean Median SD Minimum Maximum
WACC 8.065 7.820 2.727 3.581 13.738 COSTOFEQUITY 10.523 10.130 2.829 6.205 16.745 COSTOFDEBT 0.421 0.240 0.593 �0.132 1.742 BETA 0.933 0.920 0.204 0.584 1.335 LEVERAGE 0.224 0.211 0.123 0.021 0.478 ESG 67.871 71.006 0.789 9.442 95.638 ENVIRON 70.504 74.889 2.651 1.347 97.294 SOCIAL 71.504 75.889 1.652 2.347 98.294 GOVER 64.771 68.238 0.981 4.527 98.589 LEGALENV 1.381 1.417 0.313 0.483 1.817 SIZE 9,248,760,000 8,121,294,000 2,955,000 159,532,000 331,785,754,000 FREE FLOAT 77.893 84.110 21.748 1.874 100.000 ROA 6.333 5.310 4.737 �0.475 18.092 MTB 4.203 2.850 3.537 0.782 14.089
Notes: This table reports summary statistics and univariate results for the dependent and independent variables. All explanatory variables are winsorized at 5%�95% to remove extreme values in either tail of the distribution. WACC represents the weighted average cost of capital. COSTOFEQUITY represents the cost of equity capital based on the CAPM. COSTOFDEBT indicates the firm’s cost of debt capital. BETA measures the firm’s systematic risk. LEVERAGE is the ratio of long-term outstanding debt divided by total assets. ESG is the natural logarithm of the ESG score. ENVIRON is the natural logarithm of the environmental score. SOCIAL is the natural logarithm of the social score. GOVER is the natural logarithm of the governance score. LEGALENV is the average value of the six WGIs. SIZE represents the natural logarithm of market capitalization. In this table, the results of the variables before the log transformation are displayed to facilitate interpretation. FREE FLOAT is the percentage of total outstanding shares not held by insiders. ROA is the return on assets. MTB is the market-to-book value Source:Authors’ own work
The impact of a firm’s ESG
score
685
1. E SG
2. E N V IR O N
3. SO
CI A L
4. G O V E R
5. LE
G A LE
N V
1 1. 00 00
2 0. 87
27 ** * (<
0. 00
01 )
1. 00 00
3 0. 87
77 ** * (<
0. 00
01 )
0. 99
92 ** * (<
0. 00
01 )
1. 00 00
4 0. 63
06 ** * (<
0. 00
01 )
0. 34
60 ** * (<
0. 00
01 )
0. 34
91 ** * (<
0. 00
01 )
1. 00 00
5 �0
.0 92
6* **
(< 0. 00
01 )
�0 .0 90
8* **
(< 0. 00
01 )
�0 .0 91
4* **
(< 0. 00
01 )
0. 01 86
(0 .4 15 5)
1. 00 00
6 0. 43
90 ** * (<
0. 00
01 )
0. 39
38 ** * (<
0. 00
01 )
0. 40
12 ** * (<
0. 00
01 )
0. 21
44 ** * (<
0. 00
01 )
�0 .0 74
5* **
(< 0. 00
01 )
7 0. 09
66 ** * (<
0. 00
01 )
0. 03 71
(0 .1 04 5)
0. 03
84 * (0 .0 92
4) 0. 28
57 ** * (<
0. 00
01 )
0. 14
99 ** * (<
0. 00
01 )
8 �0
.1 74
1* **
(< 0. 00
01 )
�0 .1 46
1* **
(< 0. 00
01 )
�0 .1 47
6* **
(< 0. 00
01 )
�0 .0 86
7* **
(0 .0 00
1) 0. 18
02 ** * (<
0. 00
01 )
9 �0
.2 01
6* **
(< 0. 00
01 )
�0 .1 42
6* **
(< 0. 00
01 )
�0 .1 44
1* **
(< 0. 00
01 )
�0 .1 06
5* **
(< 0. 00
01 )
0. 14
78 ** * (<
0. 00
01 )
10 0. 11
41 ** * (<
0. 00
01 )
0. 07
91 ** * (0 .0 00
6) 0. 07
83 ** * (0 .0 00
6) 0. 16
75 ** * (<
0. 00
01 )
�0 .1 86
2* **
(< 0. 00
01 )
N ot es
: T hi s ta bl e di sp la ys
pa ir w is e co rr el at io ns
am on g th e co nt in uo us
va ri ab le s. E SG
is th e na tu ra l lo ga ri th m
of th e E SG
sc or e. E N V IR O N
is th e na tu ra l
lo ga ri th m
of th e en vi ro nm
en ta ls co re .S O CI A L is th e na tu ra ll og ar ith
m of
th e so ci al sc or e. G O V E R is th e na tu ra ll og ar ith
m of
th e go ve rn an ce
sc or e. LE
G A LE
N V
is th e av er ag e va lu e of
th e si x W G I’s .S
IZ E re pr es en ts
th e na tu ra ll og ar ith
m of
th e m ar ke t ca pi ta liz at io n.
FR E E FL
O A T is th e pe rc en ta ge
of to ta lo
ut st an di ng
sh ar es
no t he ld
by in si de rs .R
O A
is th e re tu rn
on as se ts .M
T B is
th e m ar ke t-t o- bo ok
va lu e. A ll ex pl an at or y va ri ab le s ar e w in so ri ze d at
5% – 95 %
to re m ov e
ex tr em
e va lu es
in ei th er ta il of th e di st ri bu
tio n. p- va lu es
ar e re po rt ed
be tw
ee n pa re nt he se s. *p
< 0. 10 ;* *p
< 0. 05 ; ** *p
< 0. 01
S ou
rc e:
A ut ho rs ’o w n w or k
(c on tin
ue d)
Table 3. Correlation matrix
SAMPJ 15,3
686
6. SI ZE
7. FR
E E FL
O A T
8. R O A
9. M T B
10 .L
E V E R A G E
1 2 3 4 5 6 1. 00 00
7 �0
.1 08
6* **
(< 0. 00
01 )
1. 00 00
8 0. 00 12
(0 .9 58 9)
�0 .1 08
6* **
(< 0. 00
01 )
1. 00 00
9 0. 06
42 ** * (0 .0 04
3) �0
.0 54
6* * (0 .0 15
0) 0. 58
80 ** * (<
0. 00
01 )
1. 00 00
10 0. 04
86 **
(0 .0 30
7) 0. 08
63 ** * (0 .0 00
1) 0. 04
86 **
(0 .0 30
7) �0
.0 43
6* (0 .0 52
4) 1. 00 00
Table 3.
The impact of a firm’s ESG
score
687
B as el in e m od el (1 )
M od el (2 )
M od el (3 )
M od el (4 )
M od el (5 )
M od el (6 )
D ep en de nt
va ri ab le
W A CC
W A CC
CO ST
O FE
Q U IT Y
CO ST
O FE
Q U IT Y
CO ST
O FD
E B T
CO ST
O FD
E B T
In te rc ep t
7. 80
17 ** * (<
0. 00
01 )
6. 04
56 ** * (<
0. 00
01 )
10 .2 13
6* **
(< 0. 00
01 )
9. 53
84 ** * (<
0. 00
01 )
1. 15
17 ** * (<
0. 00
01 )
�0 .1 95 6 (0 .5 16 7)
E SG
�0 .4 28
6* * (0 .0 38
1) 0. 11 65
(0 .6 70 6)
0. 01 23
(0 .9 58 5)
0. 17 09
(0 .5 87 5)
0. 00 24
(0 .7 75 1)
0. 16
63 ** * (0 .0 06
7) LE
G A LE
N V /L E G A L
0. 51
83 ** * (0 .0 03
6) 4. 46
79 ** * (0 .0 02
4) �0
.0 48 9 (0 .8 10 9)
1. 18 83
(0 .4 82 3)
�0 .6 55
9* **
(< 0. 00
01 )
1. 43
47 ** * (<
0. 00
01 )
LE G A L � E SG
�1 .1 18
5* **
(0 .0 01
5) �0
.3 09 1 (0 .4 44 7)
�0 .2 42
5* **
(0 .0 02
2) SI ZE
�0 .1 18
1* * (0 .0 39
1) �0
.1 12
5* * (0 .0 49
5) �0
.2 07
7* **
(0 .0 01
6) �0
.2 03
9* **
(0 .0 01
9) �0
.0 03 7 (0 .7 75 1)
�0 .0 06 8 (0 .5 97 9)
FR E E FL
O A T
0. 83
02 ** * (<
0. 00
01 )
0. 88
29 ** * (<
0. 00
01 )
0. 88
69 ** * (<
0. 00
01 )
0. 87
23 ** * (<
0. 00
01 )
0. 09
81 ** * (0 .0 02
9) 0. 00 03
(0 .9 92 8)
R O A
0. 07
01 ** * (<
0. 00
01 )
0. 06
84 ** * (<
0. 00
01 )
�0 .0 40
2* * (0 .0 17
2) �0
.0 41
6* * (0 .0 13
8) 0. 00
83 **
(0 .0 12
0) 0. 00
76 **
(0 .0 21
8) M T B
0. 12
23 ** * (<
0. 00
01 )
0. 12
57 ** * (<
0. 00
01 )
�0 .0 45
8* * (0 .0 40
7) �0
.0 47
7* * (0 .0 33
2) �0
.0 13
7* **
(0 .0 01
8) �0
.0 12
1* **
(0 .0 05
8) LE
V E R A G E
�0 .0 68
6* **
(< 0. 00
01 )
�0 .0 69
5* **
(< 0. 00
01 )
�0 .0 12
6* * (0 .0 18
1) �0
.0 11
65 **
(0 .0 27
6) 0. 00
53 ** * (<
0. 00
01 )
0. 00
59 ** * (<
0. 00
01 )
Y ea rd
um m ie s
Y E S
Y E S
Y E S
Y E S
Y E S
Y E S
A dj us te d R -s qu
ar e
0. 27 42
0. 27 56
0. 10 84
0. 10 84
0. 22 59
0. 23 66
N um
be ro
fo bs er va tio
ns 1, 90 5
1, 90 4
1, 90 5
1, 90 4
1, 90 5
1, 90 4
N ot es
:T hi s ta bl e di sp la ys
th e re su lts
of th e m ul tiv
ar ia te pa ne lr eg re ss io ns .W
A CC
re pr es en ts th e w ei gh
te d av er ag e co st of
ca pi ta l. CO
ST O FE
Q U IT Y re pr es en ts
th e co st of
eq ui ty
ca pi ta lb
as ed
on th e CA
PM .C
O ST
O FD
E B T in di ca te s th e fi rm
’s co st of
de bt
ca pi ta l. B E T A m ea su re s th e fi rm
’s sy st em
at ic ri sk .L
E V E R A G E is
th e ra tio
of lo ng
-te rm
ou ts ta nd
in g de bt
di vi de d by
to ta l as se ts . E SG
is th e na tu ra l lo ga ri th m
of th e E SG
sc or e.
E N V IR O N
is th e na tu ra l lo ga ri th m
of th e
en vi ro nm
en ta ls co re .S
O CI A L is th e na tu ra ll og ar ith
m of
th e so ci al
sc or e. G O V E R is th e na tu ra ll og ar ith
m of
th e go ve rn an ce
sc or e. LE
G A LE
N V is th e av er ag e
va lu e of
th e si x W G Is .S IZ E re pr es en ts th e na tu ra ll og ar ith
m of
th e m ar ke tc ap ita
liz at io n. FR
E E FL
O A T is th e pe rc en ta ge
of to ta lo ut st an di ng
sh ar es
no th
el d by
in si de rs .R
O A is th e re tu rn
on as se ts .M
T B is th e m ar ke t-t o- bo ok
va lu e. A ll ex pl an at or y va ri ab le s ar e w in so ri ze d at
5% – 95 %
to re m ov e ex tr em
e va lu es
in ei th er
ta il of
th e di st ri bu
tio n. p- V al ue s ar e re po rt ed
be tw
ee n pa re nt he se s. *p
< 0. 10 ;* *p
< 0. 05 ;* ** p < 0. 01
S ou
rc e:
A ut ho rs ’o w n w or k
(c on tin
ue d)
Table 4. Multivariate regression analyses: the impact of ESG
SAMPJ 15,3
688
M od el (7 )
M od el (8 )
M od el (9 )
M od el (1 0)
D ep en de nt
va ri ab le
B E T A
B E T A
LE V E R A G E
LE V E R A G E
In te rc ep t
0. 44
26 ** * (<
0. 00
01 )
0. 49
77 ** * (<
0. 00
01 )
1. 98 29
(0 .7 24 0)
�1 .9 11 6 (0 .7 75 0)
E SG
0. 02 17
(0 .2 15 8)
0. 02 04
(0 .3 80 0)
2. 60
05 **
(0 .0 11
1) 1. 94 43
(0 .1 55 0)
LE G A LE
N V /L E G A L
0. 04
66 ** * (0 .0 02
1) �0
.0 25 3 (0 .8 39 0)
�6 .7 65
0* **
(< 0. 00
01 )
�5 .3 59 7 (0 .4 65 0)
LE G A L � E SG
�0 .0 03 3 (0 .9 13 0)
2. 09 61
(0 .2 32 0)
SI ZE
0. 00 19
(0 .6 82 1)
0. 00 29
(0 .6 09 0)
0. 04 18
(0 .8 82 9)
0. 00 99
(0 .9 72 0)
FR E E FL
O A T
0. 07
52 ** * (<
0. 00
01 )
0. 08
17 ** * (<
0. 00
01 )
4. 62
63 ** * (<
0. 00
01 )
3. 73
78 ** * (<
0. 00
01 )
R O A
�0 .0 05
2* **
(< 0. 00
01 )
�0 .0 05
3* **
(< 0. 00
01 )
�0 .8 66
5* **
(< 0. 00
01 )
�0 .8 78
6* **
(< 0. 00
01 )
M T B
�0 .0 00
8 (0 .6 21
5) �0
.0 01 07
(0 .5 18 0)
0. 72
14 ** * (<
0. 00
01 )
0. 71
98 ** * (<
0. 00
01 )
LE V E R A G E
�0 .0 01
94 ** * (<
0. 00
01 )
�0 .0 01
9* **
(< 0. 00
01 )
Y ea rd
um m ie s
Y E S
Y E S
Y E S
Y E S
A dj us te d R -s qu
ar e
0. 07 75
0. 08 06
0. 12 86
0. 11 86
N um
be r of ob se rv at io ns
1, 90 5
1, 90 4
1, 90 6
1, 90 5
Table 4.
The impact of a firm’s ESG
score
689
These results are somewhat counterintuitive, as we would expect that more profitable firms have a lower default risk and can thus obtain more debt at a cheaper price (e.g. Myers and Majluf, 1984), while they can also easily provide dividends and should thus obtain equity financing easier. We examined the interaction effect between ROA and the ESG score to see whether the presence of both financial and non-financial disclosure strengthens the impact on the cost of capital, but we could not find any significant effect. TheMTB has a significant positive impact on the WACC, which is because of the significant positive impact on leverage, as the MTB has a significant negative impact on the cost of equity, the cost of debt and the beta. Finally, LEVERAGE negatively impacts the WACC, the cost of equity and the beta, while positively impacting the cost of debt. When leverage increases, agency problems of equity could be reduced because of the disciplinary effect of debt (Jensen, 1986), leading to a lower cost of equity, while an increase in leverage would increase default risk, thereby positively impacting the cost of debt.
Tables 5–7 focus on the impact of the individual ESG components, namely, the environment score, the social score and the governance score. Examining these three tables together, one can see that the ENVIRON and SOCIAL have a significantly negative impact on the WACC, but only in countries with a weaker legal environment, suggesting once more that investments in ecological and social projects can serve as a substitute for country-level governance. The environment and social scores also have a significant negative impact on the cost of equity and the cost of debt in countries with a weak legal environment. Firms with a high environmental and/or social score can obtain more leverage in countries offering weaker legal protection. In contrast, the governance score seems to have a significant positive impact on the WACC, the cost of equity, the cost of debt and leverage. The impact on the cost of equity and the cost of debt is, however, significantly negative for firms with a weaker legal environment.
6. Sensitivity tests As a first sensitivity check, we clustered the standard errors based on the year, industry and/or country of the firm instead of running pooled OLS regression models with year-fixed effects. The results are qualitatively similar. Also, random effects generalized least squares (GLS) models with standard errors that account for intra-group correlations were executed. The results allow us to draw similar conclusions [11].
Second, we replace LEGALENV with a dummy variable indicating whether the firm is located in a common law vs a civil law system, which is equivalent to comparing the UK and non-UK firms in our sample. According to La Porta and Lopez-de-Silanes (1998), Djankov et al. (2002) and Mulligan and Shleifer (2005), legal rules protecting investors vary fundamentally among legal traditions or origins. Common-law countries (originally called English law countries) afford the best legal protection to shareholders with lower formalism of judicial procedures and greater judicial independence compared to civil-law countries having greater corruption, a larger unofficial economy and higher unemployment. Our dummy variable captures many underling institutions and outcomes such as procedural formalism, judicial independence, property rights, level of corruption, labor laws, company laws, securities laws, stock market developments, ownership structures, bankruptcy laws and government ownership of banks (see La Porta et al., 2008). Yet, we do not find a significant impact of this variable on our dependent variable, most likely because we only have one common-law country (i.e. the UK) in our sample. Also, when splitting the sample into common law vs civil law countries, we did not seem to find significantly different results between the two subsamples. Also, whether the economy of the corporation is bank- oriented or market-oriented does not significantly matter.
SAMPJ 15,3
690
B as el in e m od el (1 )
M od el (2 )
M od el (3 )
M od el (4 )
M od el (5 )
M od el (6 )
D ep en de nt
va ri ab le
W A CC
W A CC
CO ST
O FE
Q U IT Y
CO ST
O FE
Q U IT Y
CO ST
O FD
E B T
CO ST
O FD
E B T
In te rc ep t
7. 50
26 ** * (<
0. 00
01 )
5. 94
89 ** * (<
0. 00
01 )
10 .3 07
1* **
(< 0. 00
01 )
9. 02
49 ** * (<
0. 00
01 )
1. 16
93 ** * (<
0. 00
01 )
0. 02 22
(0 .9 36 8)
E N V IR O N
�0 .2 87
6* (0 .0 59
9) 0. 23 20
(0 .2 77 7)
�0 .0 69 0 (0 .6 88 0)
0. 24 38
(0 .3 21 5)
�0 .0 11 7 (0 .7 30 1)
0. 11
31 **
(0 .0 18
6) LE
G A LE
N V /L E G A L
0. 51
51 ** * (0 .0 03
8) 3. 90
18 ** * (0 .0 00
7) �0
.0 57 2 (0 .7 79 7)
2. 27
97 * (0 .0 85
3) �0
.6 57
1* **
(< 0. 00
01 )
0. 99
66 ** * (0 .0 00
1) LE
G A L � E N V IR O N
�0 .9 78
6* **
(< 0. 00
01 )
�0 .5 67 8*
(0 .0 71 2)
�0 .1 36 6* * (0 .0 26 6)
SI ZE
�0 .1 32
2* * (0 .0 16
8) �0
.1 26
7* * (0 .0 22
3) �0
.1 96
7* **
(0 .0 02
0) �0
.1 91
1* **
(0 .0 02
7) �0
.0 01 7 (0 .5 91 4)
�0 .0 07 5 (0 .5 49 6)
FR E E FL
O A T
0. 81
47 ** * (<
0. 00
01 )
0. 83
96 ** * (<
0. 00
01 )
0. 90
57 ** * (<
0. 00
01 )
0. 86
86 ** * (<
0. 00
01 )
0. 10
08 ** * (0 .0 01
9) 0. 00 16
(0 .9 59 1)
R O A
0. 06
96 ** * (<
0. 00
01 )
0. 06
79 ** * (<
0. 00
01 )
�0 .0 40
6* * (0 .0 16
4) �0
.0 42
7* * (0 .0 11
6) 0. 00
83 **
(0 .0 12
6) 0. 00
79 **
(0 01
69 )
M T B
0. 12
59 ** * (<
0. 00
01 )
0. 13
09 ** * (<
0. 00
01 )
�0 .0 46
7* * (0 .0 33
7) �0
.0 47
5* * (0 .0 31
9) �0
.0 13
9* **
(0 .0 01
4) �0
.0 12
1* **
(0 .0 05
1) LE
V E R A G E
�0 .0 69
0* **
(< 0. 00
01 )
�0 .0 69
2* **
(< 0. 00
01 )
�0 .0 12
6* * (0 .0 18
04 )
�0 .0 11
14 **
(0 .0 34
9) 0. 00
53 ** * (<
0. 00
01 )
0. 00
59 ** * (<
0. 00
01 )
Y ea r du
m m ie s
Y E S
Y E S
Y E S
Y E S
Y E S
Y E S
A dj us te d R -s qu
ar e
0. 27 42
0. 27 68
0. 10 92
0. 11 05
0. 22 59
0. 23 48
N um
be r of ob se rv at io ns
19 07
19 06
19 07
19 06
19 07
19 06
N ot es
:T hi s ta bl e di sp la ys
th e re su lts
of th e m ul tiv
ar ia te pa ne lr eg re ss io ns .W
A CC
re pr es en ts th e w ei gh
te d av er ag e co st of
ca pi ta l. CO
ST O FE
Q U IT Y re pr es en ts
th e co st of
eq ui ty
ca pi ta lb
as ed
on th e CA
PM .C
O ST
O FD
E B T in di ca te s th e fi rm
’s co st of
de bt
ca pi ta l. B E T A m ea su re s th e fi rm
’s sy st em
at ic ri sk .L
E V E R A G E is
th e ra tio
of lo ng
-te rm
ou ts ta nd
in g de bt
di vi de d by
to ta l as se ts . E SG
is th e na tu ra l lo ga ri th m
of th e E SG
sc or e.
E N V IR O N
is th e na tu ra l lo ga ri th m
of th e
en vi ro nm
en ta ls co re .S
O CI A L is th e na tu ra ll og ar ith
m of
th e so ci al
sc or e. G O V E R is th e na tu ra ll og ar ith
m of
th e go ve rn an ce
sc or e. LE
G A LE
N V is th e av er ag e
va lu e of
th e si x W G Is .S IZ E re pr es en ts th e na tu ra ll og ar ith
m of
th e m ar ke tc ap ita
liz at io n. FR
E E FL
O A T is th e pe rc en ta ge
of to ta lo ut st an di ng
sh ar es
no th
el d by
in si de rs .R
O A is th e re tu rn
on as se ts .M
T B is th e m ar ke t-t o- bo ok
va lu e. A ll ex pl an at or y va ri ab le s ar e w in so ri ze d at
5% – 95 %
to re m ov e ex tr em
e va lu es
in ei th er
ta il of th e di st ri bu
tio n. p- va lu es
ar e re po rt ed
be tw
ee n pa re nt he se s. *p
< 0. 10 ;* *p
< 0. 05 ; ** *p
< 0. 01
S ou
rc e:
A ut ho rs ’o w n w or k
(c on tin
ue d)
Table 5. Multivariate
regression analyses: the impact of the environment score
The impact of a firm’s ESG
score
691
M od el (7 )
M od el (8 )
M od el (9 )
M od el (1 0)
D ep en de nt
va ri ab le
B E T A
B E T A
LE V E R A G E
LE V E R A G E
In te rc ep t
0. 45
42 ** * (<
0. 00
01 )
0. 46
86 ** * (<
0. 00
01 )
5. 17 65
(0 .3 44 0)
4. 64 67
(0 .4 53 2)
E N V IR O N
0. 01 41
(0 .2 71 2)
0. 02 22
(0 .2 20 0)
0. 82 49
(0 .2 68 6)
�0 .7 09 0 (0 .5 10 3)
LE G A LE
N V /L E G A L
0. 04
63 ** * (0 .0 02
2) 0. 05 29
(0 .5 89 0)
�6 .8 16
7* **
(< 0. 00
01 )
�1 1. 54
05 **
(0 .0 44
6) LE
G A L � E N V IR O N
�0 .0 21 7 (0 .3 48 0)
3. 56
29 ** * (0 .0 09
1) SI ZE
0. 00 26
(0 .5 74 1)
0. 00 03 5 (0 .4 69 0)
0. 26 13
(0 .3 41 1)
0. 20 82
(0 .4 50 8)
FR E E FL
O A T
0. 07
74 ** * (<
0. 00
01 )
0. 08
27 ** * (<
0. 00
01 )
4. 81
58 ** * (<
0. 00
01 )
4. 05
87 ** * (<
0. 00
01 )
R O A
�0 .0 05
2* **
(< 0. 00
01 )
�0 .0 05
3* **
(< 0. 00
01 )
�0 .8 69
9* **
(< 0. 00
01 )
�0 .8 74
5* **
(< 0. 00
01 )
M T B
�0 .0 00 9 (0 .5 43 8)
�0 .0 01 8 (0 .4 72 0)
0. 68
86 ** * (<
0. 00
01 )
0. 67
53 ** * (<
0. 00
01 )
LE V E R A G E
�0 .0 01
9* **
(< 0. 00
01 )
�0 .0 01
9* **
(< 0. 00
01 )
Y ea rd
um m ie s
Y E S
Y E S
Y E S
Y E S
A dj us te d R -s qu
ar e
0. 07 83
0. 08 17
0. 12 61
0. 11 84
N um
be ro
fo bs er va tio
ns 19 07
19 06
19 08
19 07
Table 5.
SAMPJ 15,3
692
B as el in e m od el (1 )
M od el (2 )
M od el (3 )
M od el (4 )
M od el (5 )
M od el (6 )
D ep en de nt
va ri ab le
W A CC
W A CC
CO ST
O FE
Q U IT Y
CO ST
O FE
Q U IT Y
CO ST
O FD
E B T
CO ST
O FD
E B T
In te rc ep t
7. 54
71 ** * (<
0. 00
01 )
5. 88
57 ** * (<
0. 00
01 )
10 .3 10
6* **
(< 0. 00
01 )
8. 96
79 ** * (<
0. 00
01 )
1. 17
37 ** * (<
0. 00
01 )
�0 .0 11 8 (0 .9 66 9)
SO CI A L
�0 .2 97
4* (0 .0 58
8) 0. 24 18
(0 .2 82 6)
�0 .0 68 3 (0 .7 05 7)
0. 25 86
(0 .3 16 9)
�0 .0 13 9 (0 .6 95 5)
0. 12
11 **
(0 .0 16
6) LE
G A LE
N V /L E G A L
0. 51
48 ** * (0 .0 03
9) �0
.1 25
1* * (0 .0 24
7) �0
.0 57 1 (0 .7 80 3)
2. 37
45 * (0 .0 87
2) �0
.6 57
2* **
(< 0. 00
01 )
1. 04
78 ** * (0 .0 00
1) LE
G A L � SO
CI A L
�1 .0 16
7* **
(< 0. 00
01 )
�0 .5 87
9* (0 .0 73
5) �0
.1 48
2* * (0 .0 21
4) SI ZE
�0 .1 31
1* * (0 .0 18
3) �0
.1 25
1* * (0 .0 24
7) �0
.1 96
7* **
(0 .0 02
1) �0
.1 91
6* **
(0 .0 02
7) �0
.0 01 4 (0 .9 09 8)
�0 .0 07 4 (0 .5 51 8)
FR E E FL
O A T
0. 81
57 ** * (<
0. 00
01 )
0. 83
97 ** * (<
0. 00
01 )
0. 90
56 ** * (<
0. 00
01 )
0. 86
81 ** * (<
0. 00
01 )
0. 10
09 ** * (0 .0 01
9) 0. 00 12
(0 .9 70 6)
R O A
0. 06
91 ** * (<
0. 00
01 )
0. 06
80 ** * (<
0. 00
01 )
�0 .0 40
6* * (0 .0 16
4) �0
.0 42
6* * (0 .0 11
6) 0. 00
83 **
(0 .0 12
7) 0. 00
79 **
(0 .0 17
0) M T B
0. 12
59 ** * (<
0. 00
01 )
0. 13
06 ** * (<
0. 00
01 )
�0 .0 46
8) **
(0 .0 33
9) �0
.0 47
5* * (0 .0 31
8) �0
.0 13
9* **
(0 .0 01
4) �0
.0 12
1* **
(0 .0 05
1) LE
V E R A G E
�0 .0 69
1* **
(< 0. 00
01 )
�0 .0 69
2* **
(< 0. 00
01 )
�0 .0 12
6* * (0 .0 17
9) �0
.0 11
1* * (0 .0 34
8) 0. 00
53 ** * (<
0. 00
01 )
0. 00
59 ** * (<
0. 00
01 )
Y ea rd
um m ie s
Y E S
Y E S
Y E S
Y E S
Y E S
Y E S
A dj us te d R -s qu
ar e
0. 27 43
0. 27 67
0. 10 92
0. 11 05
0. 22 59
0. 23 50
N um
be ro
fo bs er va tio
ns 1, 90 7
1, 90 6
1, 90 7
1, 90 6
1, 90 7
1, 90 6
N ot es
:T hi s ta bl e di sp la ys
th e re su lts
of th e m ul tiv
ar ia te pa ne lr eg re ss io ns .W
A CC
re pr es en ts th e w ei gh
te d av er ag e co st of
ca pi ta l. CO
ST O FE
Q U IT Y re pr es en ts
th e co st of
eq ui ty
ca pi ta lb
as ed
on th e CA
PM .C
O ST
O FD
E B T in di ca te s th e fi rm
’s co st of
de bt
ca pi ta l. B E T A m ea su re s th e fi rm
’s sy st em
at ic ri sk .L
E V E R A G E is
th e ra tio
of lo ng
-te rm
ou ts ta nd
in g de bt
di vi de d by
to ta l as se ts . E SG
is th e na tu ra l lo ga ri th m
of th e E SG
sc or e.
E N V IR O N
is th e na tu ra l lo ga ri th m
of th e
en vi ro nm
en ta ls co re .S
O CI A L is th e na tu ra ll og ar ith
m of
th e so ci al
sc or e. G O V E R is th e na tu ra ll og ar ith
m of
th e go ve rn an ce
sc or e. LE
G A LE
N V is th e av er ag e
va lu e of
th e si x W G Is .S IZ E re pr es en ts th e na tu ra ll og ar ith
m of
th e m ar ke tc ap ita
liz at io n. FR
E E FL
O A T is th e pe rc en ta ge
of to ta lo ut st an di ng
sh ar es
no th
el d by
in si de rs .R
O A is th e re tu rn
on as se ts .M
T B is th e m ar ke t-t o- bo ok
va lu e. A ll ex pl an at or y va ri ab le s ar e w in so ri ze d at
5% – 95 %
to re m ov e ex tr em
e va lu es
in ei th er
ta il of th e di st ri bu
tio n. p- va lu es
ar e re po rt ed
be tw
ee n pa re nt he se s. *p
< 0. 10 ;* *p
< 0. 05 ;* ** p < 0. 01
S ou
rc e:
A ut ho rs ’o w n w or k
(c on tin
ue d)
Table 6. Multivariate
regression analyses: the impact of the
social score
The impact of a firm’s ESG
score
693
M od el (7 )
M od el (8 )
M od el (9 )
M od el (1 0)
D ep en de nt
va ri ab le
B E T A
B E T A
LE V E R A G E
LE V E R A G E
In te rc ep t
0. 45
13 ** * (<
0. 00
01 )
0. 46
97 ** * (<
0. 00
01 )
5. 15 21
(0 .3 48 5)
5. 18 13
(0 .4 11 8)
SO CI A L
0. 01 52
(0 .2 55 5)
0. 02 34
(0 .2 18 0)
0. 80 24
(0 .3 04 3)
�0 .8 47 1 (0 .4 49 7)
LE G A LE
N V /L E G A L
0. 04
63 ** * (0 .0 02
2) 0. 05 47
(0 .5 94 0)
�6 .8 19
8* **
(< 0. 00
01 )
�1 2. 60
14 **
(0 .0 36
4) LE
G A L � SO
CI A L
�0 .0 22 1 (0 .3 62 0)
3. 80
02 ** * (0 .0 07
6) SI ZE
0. 00 25
(0 .5 93 3)
0. 00 33
(0 .4 84 0)
0. 26 75
(0 .3 31 9)
0. 21 18
(0 .4 44 9)
FR E E FL
O A T
0. 07
73 ** * (<
0. 00
01 )
0. 08
27 ** * (<
0. 00
01 )
4. 81
90 ** * (<
0. 00
01 )
�0 .8 74
7* **
(< 0. 00
01 )
R O A
�0 .0 05
2* **
(< 0. 00
01 )
�0 .0 05
3* **
(< 0. 00
01 )
�0 .8 70
2* **
(< 0. 00
01 )
0. 21 18
(0 .4 44 9)
M T B
�0 .0 00 9 (0 .5 47 1)
�0 .0 01 1 (0 .4 74 0)
0. 68
79 ** * (<
0. 00
01 )
0. 67
49 ** * (<
0. 00
01 )
LE V E R A G E
�0 .0 01
9* **
(< 0. 00
01 )
�0 .0 01
8* **
(< 0. 00
01 )
Y ea rd
um m ie s
Y E S
Y E S
Y E S
Y E S
A dj us te d R -s qu
ar e
0. 07 83
0. 08 17
0. 12 60
0. 11 84
N um
be ro
fo bs er va tio
ns 1, 90 7
1, 90 6
1, 90 8
1, 90 7
Table 6.
SAMPJ 15,3
694
B as el in e
M od el (1 )
M od el (2 )
M od el (3 )
M od el (4 )
M od el (5 )
M od el (6 )
D ep en de nt
va ri ab le
W A CC
W A CC
CO ST
O FE
Q U IT Y
CO ST
O FE
Q U IT Y
CO ST
O FD
E B T
CO ST
O FD
E B T
In te rc ep t
6. 76
38 ** * (<
0. 00
01 )
8. 10
73 ** * (<
0. 00
01 )
9. 78
79 ** * (<
0. 00
01 )
11 .3 33
1* **
(< 0. 00
01 )
1. 06
55 ** * (<
0. 00
01 )
0. 05 70
(0 .8 39 7)
G O V E R
0. 25
50 * (0 .0 89
7) 0. 10 44
(0 .6 02 2)
0. 34
33 **
(0 .0 46
7) 0. 01 12
(0 .9 60 9)
0. 07
14 **
(0 .0 35
7) 0. 10
86 **
(0 .0 15
8) LE
G A LE
N V /L E G A L
0. 51
92 ** * (0 .0 03
4) �1
.5 70 2 (0 .1 60 7)
�0 .0 68 3 (0 .7 38 1)
�2 .8 61
7* * (0 .0 26
7) �0
.6 59
4* **
(< 0. 00
01 )
0. 86
48 ** * (<
0. 00
01 )
LE G A L � G O V E R
0. 33 71
(0 .2 14 8)
�0 .6 74
8* * (0 .0 30
2) �0
.1 07
8* (0 .0 77
6) SI ZE
�0 .1 97
5* **
(0 .0 00
2) 0. 20
30 ** * (0 .0 00
1) �0
.2 37
7* **
(< 0. 00
01 )
�0 .2 36
7* **
(< 0. 00
01 )
�0 .0 09 8 (0 .4 04 4)
�0 .0 07 1 (0 .5 42 8)
FR E E FL
O A T
0. 71
51 ** * (<
0. 00
01 )
0. 75
78 ** * (<
0. 00
01 )
0. 79
81 ** * (<
0. 00
01 )
0. 73
89 ** * (<
0. 00
01 )
0. 07
87 **
(0 .0 20
3) 0. 00 22
(0 .9 47 4)
R O A
0. 07
06 ** * (<
0. 00
01 )
0. 07
19 ** * (<
0. 00
01 )
�0 .0 40
6* * (0 .0 16
7) �0
.0 40
6* * (0 .0 16
0) 0. 00
83 **
(0 .0 12
7) 0. 00
78 **
(0 .0 17
1) M T B
0. 13
35 ** * (<
0. 00
01 )
0. 13
59 ** * (<
0. 00
01 )
�0 .0 41
2* (0 .0 61
7) �0
.0 43
7* * (0 .0 47
5) �0
.0 12
8* **
(0 .0 03
2) �0
.0 12
4* **
(0 .0 03
9) LE
V E R A G E
�0 .0 70
3* **
(< 0. 00
01 )
�0 .0 71
6* **
(< 0. 00
01 )
�0 .0 13
9* **
(0 .0 08
9) �0
.0 13
1* * (0 .0 13
3) 0. 00
49 ** * (<
0. 00
01 )
0. 00
56 ** * (<
0. 00
01 )
Y ea rd
um m ie s
Y E S
Y E S
Y E S
Y E S
Y E S
Y E S
A dj us te d R -s qu
ar e
0. 27 40
0. 27 21
0. 11 10
0. 11 29
0. 22 76
0. 23 47
N um
be ro
fo bs er va tio
ns 1, 90 7
1, 90 6
1, 90 7
1, 90 6
1, 90 7
1, 90 6
N ot es
:T hi s ta bl e di sp la ys
th e re su lts
of th e m ul tiv
ar ia te pa ne lr eg re ss io ns .W
A CC
re pr es en ts th e w ei gh
te d av er ag e co st of
ca pi ta l. CO
ST O FE
Q U IT Y re pr es en ts
th e co st of
eq ui ty
ca pi ta lb
as ed
on th e CA
PM .C
O ST
O FD
E B T in di ca te s th e fi rm
’s co st of
de bt
ca pi ta l. B E T A m ea su re s th e fi rm
’s sy st em
at ic ri sk .L
E V E R A G E is
th e ra tio
of lo ng
-te rm
ou ts ta nd
in g de bt
di vi de d by
to ta l as se ts . E SG
is th e na tu ra l lo ga ri th m
of th e E SG
sc or e.
E N V IR O N
is th e na tu ra l lo ga ri th m
of th e
en vi ro nm
en ta ls co re .S
O CI A L is th e na tu ra ll og ar ith
m of
th e so ci al
sc or e. G O V E R is th e na tu ra ll og ar ith
m of
th e go ve rn an ce
sc or e. LE
G A LE
N V is th e av er ag e
va lu e of
th e si x W G Is .S IZ E re pr es en ts th e na tu ra ll og ar ith
m of
th e m ar ke tc ap ita
liz at io n. FR
E E FL
O A T is th e pe rc en ta ge
of to ta lo ut st an di ng
sh ar es
no th
el d by
in si de rs .R
O A is th e re tu rn
on as se ts .M
T B is th e m ar ke t-t o- bo ok
va lu e. A ll ex pl an at or y va ri ab le s ar e w in so ri ze d at
5% – 95 %
to re m ov e ex tr em
e va lu es
in ei th er
ta il of
th e di st ri bu
tio n. p- va lu es
ar e re po rt ed
be tw
ee n pa re nt he se s. *p
< 0. 10 ;* *p
< 0. 05 ;* ** p < 0. 01
S ou
rc e:
A ut ho rs ’o w n w or k
(c on tin
ue d)
Table 7. Multivariate
regression analyses: the impact of the governance score
The impact of a firm’s ESG
score
695
M od el (7 )
M od el (8 )
M od el (9 )
M od el (1 0)
D ep en de nt
va ri ab le
B E T A
B E T A
LE V E R A G E
LE V E R A G E
In te rc ep t
0. 46
43 ** * (<
0. 00
01 )
0. 55
67 ** * (<
0. 00
01 )
1. 36 37
(0 .8 00 0)
�5 .8 05 0 (0 .3 50 5)
G O V E R
0. 00 95
(0 .4 57 8)
0. 00 25
(0 .8 81 0)
4. 13
16 ** * (<
0. 00
01 )
3. 90
39 ** * (<
0. 00
01 )
LE G A LE
N V /L E G A L
0. 04
51 ** * (0 .0 02
9) �0
.1 04 8 (0 .2 69 0)
�6 .9 31
3* **
(< 0. 00
01 )
2. 42 45
(0 .6 61 9)
LE G A L � G O V E R
0. 01 61
(0 .4 83 0)
0. 22 44
(0 .8 67 5)
SI ZE
0. 00 39
(0 .3 79 1)
0. 00 38
(0 .3 68 2)
0. 01 00 6 (0 .9 69 0)
0. 05 67
(0 .8 27 1)
FR E E FL
O A T
0. 07
58 ** * (<
0. 00
01 )
0. 08
03 ** * (<
0. 00
01 )
3. 58
67 ** * (<
0. 00
01 )
2. 71
29 ** * (<
0. 00
01 )
R O A
�0 .0 05
3* **
(< 0. 00
01 )
�0 .0 05
3* **
(< 0. 00
01 )
�0 .8 64
1* **
(< 0. 00
01 )
�0 .8 44
7* **
(< 0. 00
01 )
M T B
�0 .0 01 1 (0 .5 13 5)
�0 .0 01 7 (0 .4 36 0)
0. 72
27 ** * (<
0. 00
01 )
0. 71
48 ** * (<
0. 00
1) LE
V E R A G E
�0 .0 01
9* **
(< 0. 00
01 )
�0 .0 01
9* **
(< 0. 00
01 )
Y ea rd
um m ie s
Y E S
Y E S
Y E S
Y E S
A dj us te d R -s qu
ar e
0. 07 79
0. 08 15
0. 13 98
0. 12 74
N um
be ro
fo bs er va tio
ns 1, 90 7
1, 90 6
1, 90 8
1, 90 7
Table 7.
SAMPJ 15,3
696
Finally, a potential endogeneity effect might be present given that companies that increase their leverage might also start disclosing more ESG information because of the increased scrutiny from financial institutions (Atan et al., 2018). Also, any cost of capital might be a driver of the ESG score because companies with a high cost of capital might be more eager to have it reduced by investing in ESG projects. To address this endogeneity effect, we already followed Sharfman and Fernando (2008), Dhaliwal et al. (2011) and Ng and Rezaee (2015) by lagging the ESG factor and the control variables by one year. To further address this endogeneity effect, we also examined whether including the lagged dependent variable changed our main conclusions. Qualitatively similar results can be found, but by including the lagged dependent variable, we lose all observations from 2018, leading to a lower power of our statistical tests. Furthermore, we followed Xu et al. (2015) by running a two-stage least squares (2SLS) model where, in a first step, we regressed the ESG factors on the lagged ESG factor and the control variables. In a second step, we then regressed the cost of capital on the ESG factor found in step 1, the lagged ESG factor and the control variables. Although p-values are somewhat larger (most likely because of lower power as the number of observations from 2018 was used to calculate the lagged ESG score), the same conclusions can be drawn. As alternatives, we executed a panel generalized methods of moments estimation using the same instruments (see also Naffa and Fain, 2022) and a pool mean group (PMG) estimation (see Pesaran and Shin, 1999, where the lagged ESG score is included as a regressor given that the PMG estimator is made for dynamic panel data models). Qualitatively similar conclusions can be drawn.
Finally, as stated by Berg et al. (2022) and Svanberg et al. (2022), most data providers report their ESG score without following a mandatory framework. As a consequence, the methodologies of various data providers are somewhat different, as are the data sources that they use. In turn, their provided ESG ratings diverge, and the methodologies are not always completely transparent (see Llanos et al., 2023). In order not to depend on a single data provider, we follow, e.g. Demers et al. (2021) and Albuquerque et al. (2020) and use an alternative ESG score (i.e. the Bloomberg ESG rate) as a sensitivity check. We found qualitatively similar results, although the Refinitiv scores seem to have a larger impact on the cost of capital.
Furthermore, Refinitiv changed their methodology on 15 April 2020, in consultation with market participants through discussions about sustainable investing and what is required to encourage and accurately reflect the integration of ESG data into investment strategies. The three key enhancements of the methodology were as follows: the development of a materiality magnitude matrix where magnitude values are automatically and dynamically adjusted as ESG corporate disclosure evolves and matures; assigning a score of zero to companies who do not report on metrics relevant to the industry; and taking into account company size where a market cap factor is introduced to put more weight on small companies than large companies. There has been criticism by Berg et al. (2020) that ESG ratings calculated before the methodological change were retroactively modified, leading to potential errors when time series analyses are performed. To examine whether our conclusions still hold, we have split the sample into the periods 2018–2019 and 2020–2021, respectively. The first period contains ESG data that was retroactively modified after the methodological change, while the second time period contains end-of-year accounting data that only existed after the change. For the period 2020–2021, investors were thus aware of the methodological change when determining their expected return. Although p-values are somewhat larger because of a smaller sample size, our conclusions remain robust for the two samples.
The impact of a firm’s ESG
score
697
5. Conclusions and discussion This article is the first, to the best of the authors’ knowledge, to analyse the relationship between the ESG score and the cost of capital of 600 large, mid and small capitalization companies across 17 countries in the European region, which is a component of the EURO STOXX 600 Index. The article further examines whether the effect is because of the environmental, social and/or governance components and whether these specifically impact the cost of equity, the cost of debt, the beta or the leverage ratio. As the European continent is also diverse in terms of countries’ legal ecosystems (i.e. common vs civil law countries), examining Europe offers the opportunity to be the first to examine whether the impact of a firm’s ESG score on its cost of capital differs between countries with divergent institutional settings. If a country indeed has a lower legal environment, it might be expected that corporations domiciled in that country try to compensate this by improving their ESG rate and disclosure to convince financiers to provide funds at a lower rate.
We find significant evidence that companies with a higher ESG score have a lower cost of capital, but this relationship holds only for countries with a weaker legal environment, thereby providing evidence for the substitution effect. The ESG score does not seem to have a significant impact on the cost of equity, the cost of debt and the beta. Yet, in countries with weaker legal institutions, the impact of the ESG score on the cost of debt is significantly negative. In terms of the ESG component, especially environmental and social factors have a significantly negative impact on the cost of capital, mainly in countries with a weaker legal environment, suggesting once more that investments in ecological and social projects can serve as a substitute for country-level governance. The environment and social scores also have a significant negative impact on the cost of equity and the cost of debt in countries with a weak legal environment, while firms with a high environmental and/or social score can obtain more leverage in countries with weaker legal protection. In contrast, the governance score seems to have a significant positive impact on theWACC, the cost of equity, the cost of debt and leverage.
The results of this article are of particular relevance to companies as well as policymakers focusing on how to stimulate firms to become more sustainable, as it documents that investing in ESG projects does matter as it can lead to a lower cost of capital, which positively impacts a firm’s valuations, and the possibility to invest even in further projects having a positive net present value. The Sustainability Institute [12] documented indeed in 2023 that companies are facing increasingly time-consuming ESG projects and do not always immediately see the benefit. Some respondents to the survey by the Sustainability Institute even indicated that it becomes difficult to justify the costs associated with ESG ratings, analyses and data as it means a considerable increase in human resources, consulting support and IT tools. The average expenditure for such services ranged between $210,000 and $480,000 per year. Our results now clearly show that investing in ESG can lead to a lower cost of capital and that there are also benefits involved. The article also illustrates that firms domiciled in a weaker legal environment can use a positive ESG score as a substitute. Firms being domiciled in a country with a weaker legal environment might thus be able to attract funding at a cheaper rate in spite of their institutional environment but because of the ESG investments. This does, of course, not need to be an argument for policymakers to neglect the institutional environment of their countries, as the strength of country institutions does also matter for a firm’s cost of capital and the protection of shareholders and creditors in general. It is thus suggested for policymakers to both improve country institutions as well as stimulate firms to invest in ESG projects. This article also illustrates the necessity for regulators to screen for possible greenwashing practices (see also Bernini and La Rosa, 2023). If firms know that a higher
SAMPJ 15,3
698
ESG score leads to a lower cost of capital, they do not only have incentives to invest in ESG projects but also to unethically claim that they are green. Whether firms have greenwashed in our sample was not possible to examine, but future research could further examine whether “real” high ESG scores matter compared to those scores that are the result of greenwashing.
Although this article examined the impact of the individual ESG components (i.e. environmental, social and governance), future research could dig even deeper and examine which particular environmental, social and governance topics do matter, especially because we found evidence that the governance component seems to impact other cost-of-capital components more than the environmental and social components. Also, future research could investigate whether the level of greenness of the country in which the firm is domiciled, rather than its legal environment, has a moderating effect. For this, the Environmental Performance Index (EPI) could be used, as in Arat et al. (2023). In addition, we found evidence that the additional costs of more stringent and comprehensive reporting requirements on ESG are compensated by obtaining a lower cost of capital or the ability to take on more debt, but future research should examine whether the compensation is only partly or fully. That is, the ESG costs could lead to lower future free cash flows, while the discount factor also decreases. The net effect is thus, until now, not yet known. In addition, a caveat of our study is that we only have four years of data. Future research with more years available could examine whether a higher ESG becomes “the new normal” in the future, not leading to a lower cost of debt anymore. A further future research topic is to validate the arguments of Sharfman and Fernando (2008) that firms having a higher ESG score also attract other types of financiers, namely, those focusing on sustainable aspects. In this study, we did not have access to data on the financiers and therefore left this as a future research question.
Notes
1. See www.un.org/sustainabledevelopment/for the 17 SDGs.
2. Environmental issues include the reduction of energy, reduction of waste, natural resource conservation and decent treatment of animals. Social issues are related to a company’s relationships with stakeholders and answers questions such as whether a company donates to the local community and whether workplace conditions take employees’ health and safety into account. The governance component includes issues such as whether accounting methods are accurate and transparent, conflicts of interests are avoided, and the company has a good corporate governance.
3. Regulation (EU) 2019/2088 of the European Parliament and of the Council of 27 November 2019 on sustainability-related disclosures in the financial services sector.
4. Regulation (EU) 2020/852 of the European Parliament and of the Council of 18 June 2020 on the establishment of a framework to facilitate sustainable investment, and amending Regulation (EU) 2019/2088.
5. https://finance.ec.europa.eu/capital-markets-union-and-financial-markets/company-reporting- and-auditing/company-reporting/corporate-sustainability-reporting_en
6. Directive 2014/95/EU of the European Parliament and of the Council of 22 October 2014 amending Directive 2013/34/EU as regards disclosure of non-financial and diversity information by certain large undertakings and groups.
7. www.bloomberg.com/news/articles/2022-02-03/esg-by-the-numbers-sustainable-investing- set-records-in-2021#:�:text¼ESG%20was%20born%20as%20an,exceeding%20%241.6% 20trillion%20in%202021.
The impact of a firm’s ESG
score
699
8. www.pwc.com/gx/en/services/audit-assurance/corporate-reporting/2021-esg-investor-survey.html
9. An ideal approach to completely handle the endogeneity effect is to identify an exogenous stock, which would allow to use a difference-in-difference approach. Yet, this research examines in detail whether the legal environment has a material impact that is more stable and does not change frequently.
10. Not-reported analyses are available upon request.
11. There are no results reported with firm fixed effects. The reason is that we have 600 different firms in our sample (which would lead to 599 dummy variables) while only having four years (i.e. from 2018 to 2021) of data. Also, the level of variation of the main dependent variables (i.e. the ESG scores and legal environment) is rather limited over time. (Hill et al. 2020) and Clark and Linzer (2015) stress that fixed-effects coefficients are less reliable when the number of time periods is limited, while Nickell (1981) explains that a set of panel data with a larger number of individuals from firms and a rather small number of time periods could lead to biases of the Hurwicz type. The problem is that fixed-effects coefficients are biased in a conservative fashion when the data are characterized by a small number of panels, and this downward bias can be reduced as the number of time periods increases.
12. See www.sustainability.com/thinking/rate-the-raters-2023/
References Aboud, A. and Diab, A. (2019), “The financial and market consequences of environmental, social, and
governance ratings: the implications of recent political volatility in Egypt”, Sustainability Accounting,Management and Policy Journal, Vol. 10 No. 3, pp. 498-520.
Adeneye, Y.B., Kammoun, I. and Ab Wahab, S. (2022), “Capital structure and speed of adjustment: the impact of environmental, social and governance (ESG) performance”, Sustainability Accounting, Management and Policy Journal, Vol. 14 No. 5, pp. 945-977.
Aggarwal, R., Erel, I., Stulz, R. and Williamson, R. (2009), “Differences in governance practices between US and foreign firms: measurement, causes, and consequences”, Review of Financial Studies, Vol. 22 No. 8, pp. 3131-3169.
Albuquerque, R., Koskinen, Y., Yang, S. and Zhang, C. (2020), “Resiliency of environmental and social stocks: an analysis of the exogenous covid-19 market crash”, The Review of Corporate Finance Studies, Vol. 9 No. 3, pp. 593-621.
Arat, E., Hachenberg, B., Kiesel, F.L. and Schiereck, D. (2023), “Greenium, credit rating, and the covid- 19 pandemic”, Journal of Asset Management, Vol. 24 No. 7, pp. 547-557.
Ashbaugh, H., Collins, D. and LaFond, R. (2004), Corporate Governance and the Cost of Equity Capital, NYU Stern, New York, NY.
Atan, R., Alam, M., Said, J. and Zamri, M. (2018), “The impacts of environmental, social, and governance factors on firm performance: panel study on malaysian companies”,Management of Environmental Quality: An International Journal, Vol. 29 No. 2, pp. 182-194.
Bae, K., El Ghoul, S., Guedhami, O. and Zheng, X. (2020), “Board reforms and dividend policy: international evidence”, Journal of Financial and Quantitative Analysis, Vol. 56 No. 4, pp. 1296-1320.
Bansal, P. (2005), “Evolving sustainably: a longitudinal study of corporate sustainable development”, Strategic Management Journal, Vol. 26 No. 3, pp. 197-218.
Berg, F., Fabisik, K. and Sautner, Z. (2020), Is History Repeating Itself? The (un)Predictable past of ESG Ratings, SSRNWorking Paper.
Berg, F., Kölbel, J.F. and Rigobon, R. (2022), “Aggregate confusion: the divergence of ESG ratings”, Review of Finance, Vol. 26 No. 6, pp. 1315-1344.
SAMPJ 15,3
700
Bernini, F. and La Rosa, F. (2023), “Research in the greenwashing field: concepts, theories, and potential impacts on economic and social value”, Journal of Management and Governance, pp. 1-40.
Bhuiyan, M.B.U. and Nguyen, T.H.N. (2020), “Impact of CSDR on cost of debt and cost of equity capital: Australian evidence”, Social Responsibility Journal, Vol. 16 No. 3, pp. 419-430.
Chen, Y., Li, T., Zeng, Q. and Zhu, B. (2023), “Effect of ESG performance on the cost of equity capital/ evidence from China”, International Review of Economics and Finance, Vol. 83, pp. 348-364.
Clark, T.S. and Linzer, D.A. (2015), “Should I use fixed or random effects?”, Political Science Research andMethods, Vol. 3 No. 2, pp. 399-408.
de Zwaan, L., Brimble, M. and Stewart, J. (2015), “Member perceptions of ESG investing through superannuation”, Sustainability Accounting,Management and Policy Journal, Vol. 6 No. 1, pp. 79-102.
Demers, E., Hendrikse, J., Joos, P. and Lev, B. (2021), “ESG did not immunize stocks during the covid-19 crisis, but investments in intangible assets did”, Journal of Business Finance and Accounting, Vol. 48 Nos 3/4, pp. 433-462.
Dhaliwal, D., Zhen Li, O., Tsang, A. and Yang, Y. (2011), “Voluntary nonfinancial disclosure and the cost of equity capital: the initiation of corporate social responsibility reporting”, The Accounting Review, Vol. 86 No. 1, pp. 59-100.
DiMaggio, P.J. and Powell, W.W. (1983), “The iron cage revisited: institutional isomorphism and collective rationality in organizational fields”,American Sociological Review, Vol. 48 No. 2, pp. 147-160.
Djankov, S., Glaeser, E., La Porta, R., Lopez-de-Silanez, F. and Shleifer, A. (2003), “The new comparative economics”, Journal of Comparative Economics, Vol. 31 No. 4, pp. 595-619.
Djankov, S., La Porta, R., Lopez-de-Silans, F. and Shleifer, A. (2002), “The regulation of entry”, The Quarterly Journal of Economics, Vol. 118 No. 2, pp. 453-517.
Durnev, A. and Kim, E.H. (2005), “To steal or not to steal: firm attributes, legal environment, and valuation”,The Journal of Finance, Vol. 60 No. 3, pp. 1461-1493.
Dyck, A., Lins, K.V., Roth, L. and Wagner, H.F. (2019), “Do institutional investors drive corporate social responsibility? International evidence”, Journal of Financial Economics, Vol. 131 No. 3, pp. 693-714.
Eccles, R. and Klimenko, S. (2019), “The investor revolution”,Harvard Business Review, pp. 106-116. El Ghoul, S.E., Guedhami, O., Kwok, C.C.Y. and Mishra, D.R. (2011), “Does corporate social responsibility
affect the cost of capital?”, Journal of Banking and Finance, Vol. 35 No. 9, pp. 2388-2406. Fama, E. and French, K. (1992), “The cross-section of expected stock returns”, The Journal of Finance,
Vol. 47 No. 2, pp. 427-465. Ge, W., Kim, J. and Song, B.Y. (2012), “Internal governance, legal institutions, and bank loan
contracting around the world”, Journal of Corporate Finance, Vol. 18 No. 3, pp. 413-432. Gonçales, T.C., Dias, J. and Barras, V. (2022), “Sustainability performance and the cost of capital”,
International Journal of Financial Studies, Vol. 10 No. 3, pp. 63-95. Goss, A. and Roberts, G.S. (2011), “The impact of corporate social responsibility and the cost of bank
loans”, Journal of Banking and Finance, Vol. 35 No. 7, pp. 1794-1810. Hill, T.D., Davis, A.P., Roos, J.M. and French, M.T. (2020), “Limitations of fixed-effects models for panel
data”, Sociological Perspectives, Vol. 63 No. 3, pp. 357-369. Hong, A. and Kacperczyk, M. (2009), “The price of sin: the effects of social norms on markets”, Journal
of Financial Economics, Vol. 93 No. 1, pp. 15-36. Huo, X., Lin, H., Meng, Y. and Woodq, P. (2021), “Institutional investors and cost of capital: the
moderating effect of ownership structure”, Plos One, Vol. 16 No. 4, pp. 1-40. John, K., Litov, L. and Yeung, B. (2008), “Corporate governance and risk-taking”, Journal of Finance,
Vol. 63 No. 4, pp. 1689-1728. Johnson, R. (2020), “The link between environmental, social, and corporate governance disclosure and the
cost of capital in SouthAfrica”, Journal of Economic and Financial Sciences, Vol. 13No. 1, pp. 543-555.
The impact of a firm’s ESG
score
701
Khanchel, I. and Lassoued, N. (2022), “ESG disclosure and the cost of capital. Is there a ratcheting effect over time?”, Sustainability, Vol. 14 No. 15, pp. 1-19.
King, A.A. and Shaver, J.M. (2001), “Are aliens green? Assessing foreign establishments’ environmental conduct in the United States”, StrategicManagement Journal, Vol. 22 No. 11, pp. 1069-1085.
Klapper, L.F. and Love, I. (2004), “Corporate governance, investor protection, and performance in emerging markets”, Journal of Corporate Finance, Vol. 10 No. 5, pp. 703-728.
La Porta, R. and Lopez-de-Silanes, F. (1998), “Law and finance”, Journal of Political Economy, Vol. 106 No. 6, pp. 1113-1155.
La Porta, R., Lopez-de-Silanes, F. and Shleifer, A. (2008), “The economic consequences of legal origins”, Journal of Economic Literature, Vol. 46 No. 2, pp. 285-332.
Liu, D., Gu, K. and Hu, W. (2023), “ESG performance and stock idiosyncratic volatility”, Finance Research Letters, Vol. 58.
Llanos, A., Vijaya, A. and Wicaksono, H. (2023), Rating ESG key performance indicators in the airline industry, Environment, Development and Sustainability, Forthcoming.
Mackey, A., Mackey, T. and Barney, J. (2007), “Corporate social responsibility and firm performance: investor preferences and corporate strategies”, Academy of Management Review, Vol. 32 No. 3, pp. 817-835.
Mahmut, A., Güzhan, G. and Korkmaz, E. (2022), “Impact of ESG performance on firm value and profitability”, Borsa Instanbul Review, Vol. 22 No. 2, pp. 119-127.
Mizruchi, M.S. and Fein, L.C. (1999), “The social construction of organizational knowledge: a study of the uses of coercive, mimetic, and normal isomorphism”, Administrative Science Quarterly, Vol. 44 No. 4, pp. 653-683.
Mohammad, W.M.W., Osman, M. and Rani, M.S.A. (2023), “Corporate governance and environmental, social, and governance (ESG) disclosure and its effect on the cost of capital in emerging markets”,Asian Journal of Business Ethics, Vol. 12 No. 2, pp. 175-191.
Mulligan, C.B. and Shleifer, A. (2005), “The extent of the market and the supply of regulation”, The Quarterly Journal of Economics, Vol. 120 No. 4, pp. 1445-1473.
Myers, S.C. and Majluf, N.S. (1984), “Corporate financing and investment decisions when firms have information that investors do not have”, Journal of Financial Economics, Vol. 13 No. 2, pp. 187-221.
Naffa, H. and Fain, M. (2022), “A factor approach to the performance of ESG leaders and laggards”, Financial Research Letters, Vol. 44, pp. 1-8.
Ng, A. and Rezaee, Z. (2015), “Business sustainability performance and cost of equity capital”, Journal of Corporate Finance, Vol. 34, pp. 128-149.
Nickell, S. (1981), “Biases in dynamicmodels with fixed effects”,Econometrica, Vol. 49 No. 6, pp. 1417-1426. Oikonomou, I., Brooks, C. and Pavelin, S. (2012), “The effects of corporate social performance on
financial risk and utility: a longitudinal study”, Financial Management, Vol. 41 No. 2, pp. 483-515. Ozer, G. and Cam, I. (2022), “The influence of country governance on the capital structure and
investment financing decisions of firms: an international investigation”, Borsa Istanbul Review, Vol. 22 No. 2, pp. 257-271.
Pesaran, M.H. and Shin, Y. (1999),AnAutoregressive Distributed LagModelling Approach to Cointegration Analysis, in Strom S., Holly, A., and Diamond, P. (Eds), Cambridge University Press.
Petersen, H. and Vredenburg, H. (2009), “Morals or economics? Institutional investor preferences for corporate social responsibility”, Journal of Business Ethics, Vol. 90 No. 1, pp. 1-14.
Pham, H., Sutton, B., Brown, P. and Brown, D. (2020), “Moving towards sustainability: a theoretical design of environmental performancemeasurement systems”, Journal of Cleaner Production, Vol. 269, pp. 1-40.
Qi, Y., Roth, L. and Wald, J.K. (2010), “Political rights and the cost of debt”, Journal of Financial Economics, Vol. 95 No. 2, pp. 202-226.
SAMPJ 15,3
702
Ramirez, A., Monslave, J., Gonz�alez-Ruiz, J., Almonacid, P. and Peña, A. (2022), “Relationship between the cost of capital and environmental, social, and governance scores: evidence from Latin America”, Sustainability, Vol. 14 No. 9, pp. 1-40.
Richardson, A. and Welker, M. (2001), “Social disclosure, financial disclosure, and the cost of equity capital”,Accounting, Organizations and Society, Vol. 26 Nos 7/8, pp. 597-616.
Sharfman, M. and Fernando, C. (2008), “Environmental risk management and the cost of capital”, Strategic Management Journal, Vol. 29 No. 6, pp. 569-592.
Shevelena, G.I. (2022), “Corporate governance in generating companies of the russian electric power industry in the context of ESG agenda”,Global Energy Interconnection, Vol. 5 No. 5, pp. 512-523.
Suto, M. and Takehara, H. (2017), “CSR and cost of capital: evidence from Japan”, Social Responsibility Journal, Vol. 13 No. 4, pp. 798-816.
Svanberg, J., Ardeshiri, T., Samsten, I., Öhman, P., Neidermeyer, P.E., Rana, T., Maisano, F. and Danielson, M. (2022), “Must social performance ratings be idiosyncratic? An exploration of social performance ratings with predictive validity”, Sustainability Accounting, Management and Policy Journal, Vol. 14 No. 7, pp. 313-348.
Xu, S., Liu, D. and Huang, J. (2015), “Corporate social responsbility, the cost of equity capital and ownership structure: an analysis of Chinese firms”, Australian Journal of Management, Vol. 40 No. 2, pp. 245-276.
Yilmaz, I. (2022), “ESG-based sustainability performance and its impact on cost of capital: International evidence from the energy sector”, International Journal of Applied Economics, Finance and Accounting, Vol. 12 No. 2, pp. 21-30.
Zhu, F. (2014), “Corporate governance and the cost of capital: an international study”, International Review of Finance, Vol. 14 No. 3, pp. 393-429.
Further reading Chen, L. and Zhao, X. (2006), “On the relation between the market-to-book ratio, growth opportunity,
and leverage ratio”, Finance Research Letters, Vol. 3 No. 4, pp. 253-266. Du, X., Weng, J., Zeng, Q., Chang, Y. and Pei, H. (2017), “Do lenders applaud corporate environmental
performance? Evidence from Chinese private-owned firms”, Journal of Business Ethics, Vol. 143 No. 1, pp. 179-207.
Ellili, N.O.D. (2020), “Environmental, social, and governance disclosure, ownership structure and cost of capital: evidence from the UAE”, Sustainability, Vol. 12 No. 18, pp. 7706-7734.
Liu, H. and Ruan, L. (2021), “Environmental, social, governance activities and firm performance: evidence from China”, Sustainability, Vol. 13 No. 2, pp. 767-780.
Meyers, J. and Rowan, B. (1997), “Institutionalized organizations: formal structure as myth and ceremony”,American Journal of Sociology, Vol. 83 No. 2, pp. 340-363.
Surroca, J., Tribo, J. and Waddock, S. (2010), “Corporate responsibility and financial performance: the role of intangible resources”, Strategic Management Journal, Vol. 31 No. 5, pp. 463-490.
Corresponding author Randy Priem can be contacted at: [email protected]
For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: [email protected]
The impact of a firm’s ESG
score
703
Reproduced with permission of copyright owner. Further reproduction prohibited without permission.
- The impact of a firm’s ESG score on its cost of capital: can a high ESG score serve as a substitute for a weaker legal environment
- Introduction
- Literature review and hypotheses
- Sample, variables and model
- Summary statistics
- Multivariate results
- Sensitivity tests
- Conclusions and discussion
- References
