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Article

ESG Scores and Performance in Brazilian Public Companies

by
Edna Aparecida Greggio Possebon
1,*,
Felippe Aparecido Cippiciani
1,
José Roberto Ferreira Savoia
1 and
Frédéric de Mariz
2
1
Faculty of Economics, Business and Accountancy, University of São Paulo, São Paulo 05508-010, Brazil
2
School of International and Public Affairs, Columbia University, New York, NY 10027, USA
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(13), 5650; https://doi.org/10.3390/su16135650
Submission received: 3 June 2024 / Revised: 22 June 2024 / Accepted: 27 June 2024 / Published: 2 July 2024
(This article belongs to the Section Economic and Business Aspects of Sustainability)
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Abstract

Environmental, social, and corporate governance (ESG) practices are gaining prominence globally and in Brazil, as it is home to invaluable environmental assets. This article presents new evidence on the impact of ESG scores on publicly traded Brazilian companies, contributing to the growing body of literature that examines the relationship between ESG practices and corporate financial performance, while addressing a gap in the analysis of the Brazilian market, the eighth-largest economy globally. By testing two main hypotheses—that ESG scores are negatively associated with the cost of capital and positively associated with return on assets—this study aimed to advance both our theoretical and empirical understanding of how sustainable practices influence financial performance within the Brazilian context. Using quantitative methods with Refinitiv data and scores from 2018 to 2022, panel regression analysis, and quantile regression, with fixed effects, this study revealed significant connections between high ESG scores and lower cost of capital, in addition to better operating performance. When the scores were evaluated separately, only the impact of environmental performance was statistically significant in the cost of capital. The environmental, social, and governance scores were statistically significant and positive for operational performance.

1. Introduction

Interest in environmental, social, and corporate governance (ESG) practices has notably expanded, driven by the global awareness and recognition that sustainability can be a competitive and risky differentiator for companies and investors [1,2]. Recent reports by Bloomberg [3] and Bank of America [4] anticipate that a substantial amount of assets will be progressively invested from an ESG perspective over the next decade, reflecting a trend in the global investment landscape. In line with this, the use of ESG scores, which seek to align the practices of a company to a reference group, provides relevant information about the company’s performance in relation to its other stakeholders, going beyond the consideration of the objectives of its investors [5]. Consequently, the number of investors who use these instruments to guide their choices in M&A [6], stock portfolio construction [7], and credit risk is growing [8,9].
The research conducted by Gunnar Friede, Timo Busch, and Alexander Bassen [10] showed a positive correlation between ESG performance and return on assets (ROA). This association is reinforced by the findings of Mozaffar Khan, George Serafeim, and Aaron Yoon [11], who identified a positive correlation between corporate sustainability and financial performance, including ROA. In addition, Amel-Zadeh and George Serafeim [12] expanded the analysis of this correlation to different contexts, concluding that a better ESG performance is linked to a more robust financial performance. Subsequent studies, such as those conducted by Serafeim et al. [13], Whelan et al. [14], and Grewal et al. [15], strengthened the understanding of the impact of ESG practices on the financial, operational, and reputational performance of companies.
In Brazil, the integration of ESG practices is being increasingly valued by investors and companies, reflecting a significant change in the perception of sustainable performance and its impact on the value and cost of capital of organizations. On the academic side, for example, Miralles-Quirós et al. [16] showed that social responsibility practices were essential for increasing the value of companies listed on stock exchanges between 2010 and 2015, while Balassiano, Ikeda, and Jucá [17] explored how adopting such practices can reduce the cost of capital, highlighting the negative relationship between environmental practices and the cost of debt. These studies show that although the evolution of ESG practices is a competitive advantage, the Brazilian market is still in the maturing process regarding the financial benefits of sustainability, suggesting that investment opportunities value the energy transition and sustainable economic development of the country.
This study is justified by the need to understand the practical and operational implications that ESG practices have on the cost of capital and operating performance of publicly traded Brazilian companies at a time when the integration of sustainable criteria is increasingly important and valued by investors and regulators. This study is particularly relevant for Brazil for several reasons. First, the country’s vast natural resources and biodiversity make sustainability a crucial topic for Brazilian companies, offering them a unique opportunity to lead in this area. Second, there has been a significant increase in investor interest in ESG practices in Brazil, as evidenced by the growth in sustainable bond issuance and investment in companies adopting sustainable practices. Third, Brazil is undergoing regulatory transitions, with the implementation of policies that encourage sustainable practices and transparency in ESG reporting, such as the resolutions by the Central Bank of Brazil [18,19] and those from the European Union. Lastly, companies that adopt ESG practices can gain a competitive edge in the global market by attracting more investments and reducing capital costs due to a perceived lower risk [20], a clear advantage for those willing to embrace sustainability.
This study’s relevance is amplified with the use of a comprehensive and updated sample of companies listed on the stock exchange covering a significant period of economic and regulatory transition, which ran from 2018 to 2022. This research enriches the understanding on how ESG criteria influence resource allocation, offering insights for strategic decisions related to sustainability and social responsibility. Moreover, our methodology goes beyond average treatment effects, showing the distributional effects of ESG using quantile regressions and controlling for fixed effects in our estimation methods. Finally, it is particularly pertinent for investors and shareholders focused on ESG.
This study is organized into five sections. In addition to Section 1, which is of an introductory nature, Section 2 presents the relevant literature on the subject, discussing ESG practices and their relationship with capital structure and operating performance. Section 3 describes the methodology and the construction of regression models using panel data and quantile regression. Section 4 presents the results and discusses their theoretical and practical implications. Finally, Section 5 and Section 6 conclude the study and present suggestions for future research.

2. Literature Review

2.1. ESG Practices

ESG practices allow companies to broaden the topics they analyze to mitigate risks and capture opportunities. These practices consider how external factors, for example, the use of energy or other resources, impact the company under the single materiality approach. The dual materiality approach, in turn, also considers how the company affects the environment and people. In other words, it can generate positive effects on the social and environmental spheres and produce financial results. Thus, ESG practices are not dissociated from profit, because performance in the social and environmental spheres is incorporated into investor analyses, serving as a tool to validate social and environmental actions [21].
ESG practices are composed of three dimensions. Dimension E (environmental) requires companies to adhere to waste management criteria and policies against deforestation, as well as to use renewable energy sources and take a position on climate change issues, among others [2]. Dimension S (social) considers issues such as access to education, health care, financial inclusion, or essential services [22]. For investors, it is especially necessary to determine how the company is responsible for the well-being of its employees and how it incorporates diversity and inclusion considerations [2]. Dimension G (governance) is the most consolidated among the three ESG dimensions. It focuses on how the company is managed, the transparency of decision-making processes, corporate responsibility, and accountability. The company must clarify how executive management and the board of directors respond to the interests of shareholders and other stakeholders—communities, employees, customers, and suppliers [23].
From the investor’s point of view, organizations that disclose information beyond traditional financial reports, incorporating data on ESG practices, have become more attractive [24]. Investors want to know about the environmental protection, social responsibility, and corporate governance actions of companies. Thus, disclosing ESG reports has become a requirement for companies that care about their reputation [25]. Although the ESG agenda has shown its positive side in relation to sustainable development, it remains to be seen whether the application of these principles and practices can reward investors. As a result, concern is latent about the performance of ESG assets [26].
According to studies by Talan and Sharma [27], the integration of ESG factors is the most sustainable investment strategy used in the United States, Oceania, and Asia. A study by Alsayegh et al. [28] showed that ESG practices disclosed by companies in Asia strengthened corporate sustainability performance. The authors of [28] explained that providing quality ESG information increases the trust between agents and, consequently, the company’s performance, as also identified by the studies by Benkraiem et al. [29] and Piechocka-Kalunna et al. [25], which indicated that the correct disclosure of ESG practices can generate positive returns for an organization, as it implies the possibility of raising capital at a lower cost, inducing a better financial result. Figure 1 shows the exact connections between ESG performance and operational performance.
When analyzing the costs associated with ESG practices, considering different perspectives is essential. Flammer [30] highlighted that the initial costs of adopting and implementing ESG practices can be significant. These include investments in environmental technologies, corporate social responsibility programs, and robust governance structures. However, the costs can be offset by long-term financial and reputational benefits. Companies that adopt ESG practices may have access to less expensive capital, attract qualified talent, and achieve greater customer loyalty [20,30,31,32]. The investors’ increased focus has driven the growth of sustainable finance and the development of innovative financial instruments, such as ESG bonds and social impact bonds [33,34].
The literature still lacks a cause-and-effect analysis that uses econometric methods to eliminate the effects of unobservable variables that are important in the relationship between ESG performance and capital efficiency. Moskovic et al. [35] applied data envelopment analysis to construct an efficiency frontier and assess whether more efficient firms have better ESG scores. They argue that there is a gap in the study of causes and effects between efficiency and ESG outcomes. Although the authors sought to address this point, the field still lacks econometric methods that directly assess the causal impact of ESG (scores) on capital efficiency, measured by the firm’s cost of capital. This study precisely aimed to explore this gap. In the next subsection, we present the literature on capital structure and cost of capital and then elaborate the theoretical framework for this study.

2.2. Evolution of ESG Practices in Brazil

In recent decades, Latin America, and Brazil in particular, has witnessed a growing awareness and commitment to issues related to ESG practices, as highlighted by Calderan et al. [36] and De Mariz [37]. This increase is driven by stricter environmental legislation, as reported by Sion et al. [38] and Redondo Alamillos and De Mariz [39], and by the recognition by investors and managers that the adoption of ESG practices is in line with business ethics and offers competitive advantages, enhancing the reputation and financial performance of companies. This view is supported by studies by Martínez-Ferrero and García-Sánchez [40] and Schleich [41], which suggest a positive correlation between robust ESG practices and improved financial results. In addition, the market relevance of companies that adopt ESG practices was also highlighted, as such practices can attract greater investments and, consequently, increase the market capitalization of these companies [17].
Pinheiro et al. (2024) [42] analyzed the performance of ESG and traditional indices in Brazil and international markets, finding no significant difference in performance. However, the performance of the ESG index in Brazil was positively influenced by company size, leverage, and the basic materials industry. Similarly, de Melo Neto and Fontgalland (2023) [43] confirmed the long-term gains of ESG indices in Brazil, China, India, and South Africa, noting that ESG companies exhibited lower volatility risk. Moskovics (2023) [35] further examined the relationship between market structure, ESG performance, and corporate efficiency in Brazilian publicly traded companies, finding that firms with better environmental performance are more efficient and that market structure measures have varying impacts on ESG indices. Collectively, these studies indicate that while there may be no significant performance difference between traditional and ESG indices, factors such as company size, leverage, industry type, and environmental performance play crucial roles in enhancing corporate efficiency and stability in ESG investments. The sustainable financing market in Brazil, especially for sustainable bonds, has grown significantly. In 2021, sustainable bond issuance in Brazil represented 14% of total bond issuance, standing out in Latin America and reflecting a global increase in the adoption of sustainable investment practices. In Brazil, sustainability-linked bonds (SLBs) stood out, accounting for 64% of the total issuance of sustainable bonds in 2021. They offer unique advantages, as they do not require a predefined use of resources, allowing for a wider range of company beneficiaries and encouraging the integration of ESG commitments into the companies’ operations.
Thus, the implementation of ESG practices has been gaining relevance in the Brazilian business agenda, influencing various economic and operational aspects of companies. For example, ESG practices contribute to reducing the cost of capital by mitigating risks associated with environmental, social, and governance factors. Studies indicate that companies with high ESG performance are perceived as having lower risk by investors and rating agencies, resulting in lower funding costs [16,17]. The growing preference of investors for portfolios that demonstrate social responsibility and sustainability, thus aligning with the demands for a greener and socially responsible economy, explains this phenomenon.
In addition to the cost of capital, corporate efficiency is significantly impacted by the adoption of ESG practices. Companies that implement sustainable strategies often experience resource optimization, waste reduction, and supply chain improvement. These operational improvements can lower costs and improve financial performance [16,17]. The integration of ESG practices into business operations is therefore not only an ethical strategy but also an economically advantageous one. An analysis of the impacts of ESG practices on Brazilian companies showed a positive transformation in the country’s business landscape, with direct implications for sustainable development and global competitiveness. Continuing this trajectory is essential to align Brazilian companies with the best global practices and strengthen their position in international markets [37].
To standardize and disclose ESG practices is a substantial challenge, and overcoming this challenge is vital to consolidating the sustainable finance market. The literature suggests that the lack of uniformity in ESG scores and in the quality of second-party opinions (SPOs) may lead to significant discrepancies and potential risks of greenwashing [44]. Implementing stricter and clearer standards could therefore improve the transparency and reliability of ESG assessments, providing greater security to investors and strengthening market integrity [45].
In addition, regulatory and government initiatives play a crucial role in promoting sustainable financial practices. In the Brazilian context, the Central Bank of Brazil and the National Monetary Council have adopted several resolutions to incorporate socioenvironmental considerations into financial practices, such as Resolutions 4327 and 4661, which establish guidelines for the socioenvironmental responsibility policy of financial institutions [18,19]. These regulatory measures not only drive the integration of ESG criteria into financial analyses but also encourage companies to commit to adopting sustainable practices.
Finally, the Brazilian ESG market stands out for its innovative potential and expansion capacity, especially in view of its predominantly renewable energy matrix and significant social challenges, such as racial inclusion and diversity. The expansion in the issuance of securities, which include social key performance indicators (KPIs), responds to these challenges, reflecting a growing trend toward addressing social and environmental issues in an integrated manner [46]. Thus, Brazil has emerged as a fertile scenario for innovations in sustainable finance, with the possibility of becoming a center of excellence and innovation in this field [37].

2.3. ESG Performance, Cost of Capital, and Operating Performance

The Modigliani–Miller theorem externalizes the discussion about the capital structure of companies by analyzing the relationship between debt and equity in 1958. Transactions with various financing providers shape this structure. In ideal capital markets, according to Modigliani and Miller [47], the costs of the different forms of financing do not vary, and choosing between them has no advantage. Several authors have contributed to the development of theories on the cost of capital [48,49,50,51]. Measuring the cost of capital involves a comprehensive evaluation of the components of its structure, which include the cost of debt, the cost of shareholder funds, and the cost of hybrid financial instruments.
The cost of debt is generally calculated based on current market interest rates and the company’s credit risk. In turn, asset pricing models, such as the CAPM model by Sharpe [52], determine the cost of resources. The cost of capital is also an important metric for evaluating value creation. A company is considered a value generator when its return on capital exceeds the weighted average cost of capital (WACC). Moreover, investors and analysts use this measure to compare the performance of different companies and sectors and evaluate the efficiency of financial management [53]. El Ghoul et al. [51] examined the effect of ESG performance on the cost of equity in a large sample of US companies. Using various approaches to estimate the ex-ante cost of capital of companies, they found that those with better ESG ratings exhibited a lower cost of equity. Their findings suggest that investment in improving employee relations, environmental policies, and product strategies substantially contributes to reducing the cost of capital in the companies sampled.
To analyze the role of the ESG score in the cost of capital and in the financial performance of companies, La Rosa and Bernini [54] examined the effect of ESG practices on the cost of equity of companies listed in the European Union. The results showed that companies with better ESG performance had lower equity costs. Furthermore, the study revealed that securities regulation plays a moderating role in this relationship, strengthening the positive effects of ESG practices on the cost of capital. Martínez-Ferrero and García-Sánchez [40] explored the relationship between the guarantee of sustainability and the cost of capital, investigating whether the guarantee affects the credibility of corporate social responsibility (CSR) information. The study analyzed European companies and found that ensuring sustainability positively affects the credibility of CSR information. This suggests that guarantees can improve investor confidence in the ESG practices reported by companies, thus influencing the cost of capital.
Ramirez et al. [55] explored the relationship between the cost of capital and ESG scores in Latin American countries. Their results indicated that companies with better ESG scores experienced a reduction in the cost of capital compared to companies with worse ESG scores. Recent research suggests that ESG disclosures can impact a company’s cost of capital. Studies such as those by Houqe et al. [31] and Yu et al. [32] showed that ESG disclosures can reduce the cost of capital by increasing transparency and reducing information asymmetry. Financial institutions in 15 European countries, as highlighted by Eliwa et al. (2021) [20], positively reward companies that present strong ESG performance, resulting in lower debt costs. This suggests that the market values ESG performance, benefiting socially responsible companies. Lodh [56] addressed this same relationship, which is quite influential in the market. This evidence supports the hypothesis that the adoption of ESG practices can have positive impacts on the cost of capital of public companies.
Badreldin and Nietert [57] addressed the cost of capital for ESG and non-ESG stocks by comparing approaches based on panel regression. The study investigated whether the integration of ESG criteria into the cost of capital analysis can provide additional insights. The results suggest that approaches based on theories such as the capital asset pricing model (CAPM) and arbitrage pricing theory (APT) may be more appropriate for evaluating the cost of capital of ESG shares. These approaches may consider the specific characteristics of ESG companies, such as risks and opportunities related to environmental, social, and governance practices. Based on these results, the study presents the following first hypothesis:
H1. 
ESG scores are negatively associated with the cost of capital.
Regarding operational performance, Wagner and Schaltegger [58] found that companies with environmental policies tend to have a more intense positive relationship with respect to ROA than do those without such policies. Studies conducted by Murray et al. [59] reinforce this association, as they also identified a positive relationship between environmental performance and return on assets (ROA). A study by Nguyen et al. [60] also revealed a positive relationship between ESG performance and ROA in US companies. Aydogmuş et al. [61] analyzed 1720 publicly traded companies worldwide and found that the overall combined ESG score was positively and significantly associated with the company’s value. Individual social and governance scores had a positive and significant relationship; however, the environmental score did not have a significant relationship with the company’s value.
A study by Buallay [62] revealed a positive relationship between ESG performance and performance in the European banking sector. On the other hand, some studies contradict the argument that ESG practices positively contribute to the financial and operational performance of companies. A study by Zahid et al. [63] with 620 companies headquartered in Western Europe, including in Austria, Belgium, France, Germany, Luxembourg, Monaco, the Netherlands, and Switzerland, showed that ESG performance had a significantly negative effect on the financial performance of companies, as measured by ROA, supporting the trade-off hypothesis that investing in ESG activities increases the cost of doing business. Similarly, Orellano and Quiota [64] did not find a clear relationship between investment in socioenvironmental performance variables, such as external social investment and environmentally responsible actions, and the impact on measures of financial and operational performance, especially in the short term. Similarly, Correa-García and Vásquez-Arango [65] reported a negative relationship between environmental practices and the operating performance of Latin American companies, including those in Brazil, Chile, Colombia, and Mexico. This mix of evidence suggests heterogeneous effects of ESG performance, and the extent and direction of these impacts depend on the context. In turn, Fernandes and Linhares [66] evaluated the financial performance of ESG investments in emerging and developed countries. The results indicated that investments in ESG companies have better long-term financial performance than other investments, both for emerging and developed countries, except for the United States.
However, the risk-adjusted values of return were statistically significant only for emerging countries and Canada. Few studies have examined the relationship between ESG performance and financial performance in Brazil. Moche et al. [67] found a positive relationship between financial performance and ESG performance in companies listed on Ibovespa (the main performance indicator on the Brazilian Stock Exchange). Carvalhal and Nakahodo [68] found evidence that Brazilian companies with good ESG practices had significantly greater returns during the COVID-19 pandemic. They found that superior performance is broadly associated with ESG performance but not with governance.
Therefore, the literature lacks consensus, as some studies showed a positive relationship between ESG performance and operating performance [61,62] and others found a negative relationship on the matter [63,64,65]. Given this lack of clarity, additional research must be conducted to better understand the relationship between environmental ESG practices and companies’ operational performance. Therefore, this study presents the following second hypothesis:
H2. 
ESG scores are positively associated with ROA.
These two hypotheses provide a basis for investigating the role of ESG scores in the cost of capital and operating performance of public companies. Through empirical analyses and econometric methods, we sought to contribute to the understanding of the underlying mechanisms and provide relevant insights for managers, investors, and regulators interested in the role of ESG scores regarding the operating performance and cost of capital of publicly traded companies.
Thus, this article contributes to the literature by showing evidence that higher ESG scores are associated with higher corporate financial performance and with lower capital costs. As a contribution to the study of this issue in Brazil, the results enhance the understanding of how ESG factors influence resource allocation decisions within publicly traded companies. Additionally, from a practical perspective, the research can assist strategic decisions related to sustainability and social responsibility. Therefore, it is especially relevant for investors and shareholders interested in investment opportunities aligned with their ESG objectives. However, a limitation of this study is that the results are based only on Brazilian publicly traded companies. In the reviewed literature, we identified several gaps. Firstly, the studies were limited to observing the average treatment effect, whereas the effect of ESG scores on operational performance and the cost of capital can be heterogeneous, varying across the distribution of the dependent variable. Additionally, few studies evaluated the scores for the E, S, and G dimensions separately, analyzing their simultaneous impact on operational performance and the cost of capital. As presented, most studies focused on financial return measures. We contribute with data-driven evidence to fill this gap by shedding light not only on the average effects but also on the distributional (quantile) impacts of each ESG dimension.

3. Methodology

When analyzing the role of ESG scores in the operating performance and cost of capital of publicly traded Brazilian companies, this study adopted a quantitative and descriptive approach to test two research hypotheses grounded in the presented theoretical framework. The research questions were (1) How do ESG scores influence the cost of capital of publicly traded Brazilian companies? and (2) How do ESG scores affect the operational performance of these companies? The Refinitiv database was used to compile the study sample, covering 287 national publicly traded companies. From this initial collection, only companies that had an ESG score, cost of capital data, and operating performance in the time range from January 2018 to December 2022 were delimited, with data collected on a quarterly basis. The study also excluded financial sector companies and insurance companies due to the nature of their accounting operations, transactions with third parties, and the fact that they operate under a different set of regulations and business structures compared to nonfinancial companies, which may affect the comparability of the data. Given these criteria, the final sample consisted of 99 companies. Due to the particularities of these sectors, a specific analysis for companies in this grouping was more appropriate.
Regarding the data collection procedures, this study used dependent, independent, and control variables. The dependent variables were the cost of capital and ROA. The independent variables were the total ESG scores and ESG scores separately (environmental, social, and governance). The Refinitiv platform calculates the ESG score, which is composed of three main categories: environmental, social, and governance categories [69]. The control variables were revenue, size, ROE, liquidity, tangibility, leverage, and Tobin’s Q, as shown in Table 1.
Two models were derived from this. Empirical evidence on how ESG practices negatively affect the cost of capital of organizations supported the first model [70,71,72]:
Cost of Capital it = α0+ α1ESGit + α2Control variablesit + εit
where the cost of capital represents the cost of capital of Company i at time t. ESG and ESG scores of Company i at time t and the other variables represent the vector with the control variables (size, tangibility, liquidity, leverage, and Tobin’s Q).
The second model was supported by empirical demonstrations on how ESG scores positively affect the operational performance of organizations [14,15,73,74]:
ROA it = α0 + α1ESGit + α2Control variablesit + εit
The model follows the quantile regression presented by Machado and Silva [75] and incorporates individual fixed effects into a quantile regression model, Equation (3):
QY(τ│X) = αi(τ) + Xit′β + Xit′γFu − 1(τ)QY (τ│X) = αi (τ) + Xit′β + Xit′γFu − 1(τ)
where Q is the quantile of the conditional distribution of Y (conditional on X); α represents the fixed effect (shifted by quantile). Fu − 1 represents the quantile τ of the error term distribution. The model is known as the location-scale model.
Table 1. Main Variables.
Table 1. Main Variables.
DEPENDENT VARIABLES
Variable NumberNameFormulaDescriptionReferences
1Cost of CapitalWACC = Ke [a] * %Equity + Kd [b] * %Divida * (1 − IR)The cost of capital is the rate of return a company requires to finance its investments, representing the weighted average cost of equity and debt.Grewal et al., 2021, [15]; El Ghoul et al. [51]; La Rosa e Bemini, [54]; Ramirez et al. [55]
2ROAROE = Net Income/Total AssetsReturn on total assets.Nguyen et al. [60]; Aydoğmuş et al. [61]
INDEPENDENT VARIABLES
3ESG_ScoreThe scores range from 1 to 100ESG score—related to the score obtained by the company—converted into a number.Refinitiv ESG Scores
4E_ScoreThe scores range from 1 to 100Environmental score—related to the score obtained by the company—converted into a number.Refinitiv ESG Scores
5S_ScoreThe scores range from 1 to 100Social Grade—related to the score obtained by the company—converted into a number.Refinitiv ESG Scores
6G_ScoreThe scores range from 1 to 100Governance Score—related to the score obtained by the company—converted into a number.Refinitiv ESG Scores
CONTROL VARIABLES
7SizeSIZE = ln(Total Assets)The total assets represent the logarithm of the asset size.[73]
8LiquidityLIQUIDITY = Cash and Cash Equivalents/Total AssetsLiquidity of the company’s investment decisions—which represents total assets.[76]
9TangibilityTANGIBILITY = Property, plant, and equipment/Total AssetsTangibility demonstrates the percentage of fixed assets over total assets.Wong et al. [76]; [77]
10LeverageLEVERAGE = Total short- and long-term debt/Total AssetsLeverage is using third-party capital to finance part of a company’s investments, increasing the potential return for shareholders and financial riskEliwa et al. [20]; Wong et al. [76]; [78]
11Tobin’s QTobin’s Q = (MarketCap + Total short- and long-term debt)/Total AssetsTobin’s Q is an indicator that relates a company’s market value to its assets’ replacement value. It assesses whether the investments made are profitable or more advantageous to sell the assets and reinvest the capital in another opportunity.
This table presents the main variables used in the study, categorized as dependent, independent, and control variables. For each variable, the table provides the number, name, formula, description, and corresponding reference. The table details the structure of the analyzed variables, including the cost of capital and return on assets (ROA) as dependent variables, ESG scores and their components (environmental, social, and governance) as independent variables, and size, liquidity, tangibility, leverage, and Tobin’s Q as control variables. Source: Prepared by the authors.
Hence, all the equations were also estimated using individual and time fixed effects at company level for all time-invariant characteristics, e.g., sector. This is important since our sample belongs to the pandemic period, which affected firms in different sectors differently.
Table 1 shows all the variables used in the model and their academic references. Before starting the data analysis techniques, Cronbach’s alpha test was performed, resulting in an index of 0.7985. Cronbach’s alpha was used to validate the database, the sample, and the variables. Moreover, the database was treated for the presence of outliers so that all variables from 1% to 99% were Winsorized. The data analysis was performed using descriptive statistics, correlations, and regression with panel data. Descriptive statistics were used to identify central values and dispersions of the study variables. The correlation analysis aimed to verify the existence of a possible high correlation between the dependent and explanatory variables of the regression models and the use of panel data, as well as a possible high multicollinearity between their explanatory variables [79].
The regression model with panel data analyzes the same group of individuals over time [79,80,81,82]. This type of model is particularly useful in controlling unobserved heterogeneity, both between individuals and over time, allowing researchers to distinguish between temporal variations (within individuals) and variations between individuals.

4. Results

The sample included the data from publicly traded Brazilian companies from January 2018 to December 2022. Financial information and ESG score data were collected from the Refinitiv database. Table 1 shows the definitions of the dependent, independent, and control variables. Descriptive statistics, correlation analysis, and a panel regression model were used to analyze the constructs. These variables consider measures of accounting profitability (ROA, liquidity) as well as measures of growth (Tobin’s Q, size).
Regarding the dependent variables, the average cost of capital for the companies in the sample was 0.0969 with a standard deviation of 0.0493. For ROA, the mean was 0.0476 and the standard deviation was 0.0310. These results suggest that companies with better ESG scores tended to have a lower cost of capital, possibly due to a reduced perception of risk by investors. Additionally, the positive ROA indicates that sustainable practices may be associated with better operational efficiency. Among the independent variables, which include the ESG, ESG-E, S-SG, and SG-G scores, the mean ESG score was 50.7760, with a high standard deviation of 20.9015. The average ESG-E, S-SG, and G-SG scores were 47.7818, 52.4243, and 51.1969, respectively. The standard deviations were 26.2243 for ESG-E, 23.0598 for S-SG, and 22.9749 for G-SG. Table 2 shows the mean and standard deviation values of the set of variables.
There was a weak positive correlation between the cost of capital and the ESG score (0.0661) and ESG-E (0.0764). For ROA, there was a weak negative correlation between ESG performance (−0.1473), ESG performance (−0.1534), S-SG performance (−0.1294), and G-SG performance (−0.0965).
In the analysis by sector, when dealing with the cost of capital, it was more evident that higher capital costs mean lower scores on the ESG pillars; as for the “Interactive Media and Services” sector, which presented an average of 27.52% in the company’s cost of capital versus ROA (1.186%), E (0), S (11.10), G (46.07), and ESG (25.74). Thus, we corroborated Hypothesis 1, since we showed a negative association between the cost of capital and the ESG score. On the other hand, considering that a lower cost of capital is associated with a better score in sustainable practices, we can use the example of the “paper products” sector, which presented an average of 3.97% in the company’s cost of capital, compared to an ROA of 3.57%, S of 65.29, S of 85.39, F of 70.92, and ESG of 72.75. In contrast, when evaluating the ROA, we found that, on average, the “Medication Retail” sector presented 12.85% versus a 5.20% cost of capital, 56.68 E, 50.36 S, 58.70 G, and 54.30 ESG scores. Finally, the “Interactive Media and Services” sector presented the lowest ROA and the highest cost of capital (Table 3).
To empirically answer the research models, two equations were estimated. The first model estimates the cost of capital as a function of ESG practices and control variables. The second model estimates the performance of companies using ROA as a function of ESG practices and control variables. This study performed the Hausman test to assess the existence of unobservable fixed factors that affected the outcome variables and may be correlated with the explanatory variables, as shown in Table 4.
The Hausman test indicated the presence of unobservable time-invariant effects that may bias the regression coefficient estimator. Thus, the main finding of Equation (1)—model (1)—was that companies that obtained a statistically significant ESG score suffered a negative influence in the cost of capital. In other words, companies in the sample with better ESG scores had a lower cost of capital, while those with a lower ESG score had a higher cost of capital.
In addition, the control variables asset size, liquidity, tangibility, and Tobin’s Q showed a statistically significant and negative relationship with the cost of capital. Table 4 presents the results of the third model. The performance in terms of ROA was found to be a function of the ESG score, asset size, liquidity, leverage, tangibility, and Tobin’s Q. Following the same method as the previous model, the Hausman test indicated that the fixed effect should also be followed. The estimated model presented more variables with different levels of statistical significance. This showed that the ESG score was statistically significant and had a positive relationship with ROA, supporting Hypothesis 2. On the other hand, the control variables tangibility and Tobin’s Q showed a statistically significant and positive relationship with ROA and a negative and significant relationship with the dependent variable related to operating performance.
The quantile regression method was used to evaluate the heterogeneity of the results. Thus, this method aims to explain the quantile distribution of the resulting variables through changes in the explanatory variables. Figure 2 and Figure 3 show the relationship between the ESG score and the cost of capital and operating performance, respectively, for each quantile. That is, the graphs show, for each quantile, the marginal effect of the score on the quantile q_Y (τ) of the Y distribution.
The results indicate that the ESG score had a greater impact on companies with lower capital costs, i.e., the results were heterogeneous. Moreover, the results of the quantile regression were not statistically significant at the 5% level. The estimates were significant at the 10% level for the impact of the ESG score on operational performance between the 39% and 74% quantiles, with an increasing estimated value for the impact, indicating a greater impact for companies with greater operational performance. The estimate was based on the work of Machado and Silva [75], allowing for the analysis of individual fixed effects in quantile regression when estimating quantiles by means of moments.
Thus, Table 5 presents the descriptive statistics separating the companies into quartiles of the Y distribution. The first column contains the number of observations in each quartile. The value variation in the mean in relation to the variable cost of capital, which, in the second column, is increasing in the quartile, had a 0.05 average for the cost of capital in the first quartile against a 0.17 average in the fourth quartile.
In the case of ROA, the first quartile presented an average of 0.02, compared with 0.09 in the last quartile, i.e., the average ROA for companies in the top 25% was 4.5 times greater than the average ROA for companies in the bottom 25%. Table 5 also shows the standard deviation of each variable Y within each quartile and the lowest and highest values found in each quartile of the Y distribution.

5. Discussion

This study tested the following the hypotheses: H1—Are ESG scores negatively associated with the cost of capital? and H2—Are ESG scores positively associated with ROA? The hypotheses were tested in the sample using the regression method with panel data. The research hypotheses were supported considering the standard 5% significance level in the tests.
The guiding question for this study was “How do ESG scores affect the operating performance and cost of capital of publicly traded Brazilian companies?” Based on the cost of capital theory and the ESG practices approach, the study tested hypotheses to analyze the role of ESG scores in the cost of capital of publicly traded Brazilian companies from a sample of 99 companies. The data were collected from publicly traded Brazilian companies with ESG scores for the period of 2018–2022 based on quarterly data from the Refinitiv database. The testing of Hypothesis 1 corroborated the results of the studies by La Rosa and Bernini [54] in Europe, Ramirez et al. [55] in Latin America, and Yilmaz et al. [83] in the energy sector, showing that companies with better ESG performance tend to have a lower cost of capital. These findings support the hypothesis that the adoption of ESG practices can increase companies’ capital costs.
Therefore, the results align with those of Ramirez et al. [55], who explored the relationship between the cost of capital and ESG performance in Latin American countries. This study’s results indicated that companies with better ESG scores, such as Brazilian companies, experienced a reduction in the cost of capital compared to companies with worse ESG scores. In this sense, the results showed that the cost of capital was negatively influenced by companies with low ESG performance, indicating that better ESG performance is associated with a lower cost of capital. These results corroborate the findings of Houqe et al. [31], Eliwa et al. [20], and Yu et al. [32], who found that companies with higher ESG scores experienced a reduction in the cost of capital compared to those with lower ESG scores. Furthermore, the models showed that other variables, such as profitability, liquidity, asset size, and company value, influence the cost of capital.
Hypothesis 2 test showed a positive relationship between ESG score, revenue, and company value. However, it showed a negative relationship between ESG-E, ESG-S, and ESG-G scores, asset size, liquidity, and leverage. This study identified a congruence with the studies by Ramić [84]. However, this finding is not in line with those of Orellano and Quiota [64], and Correa-García and Vásquez-Arango [65], who observed a negative relationship between environmental practices and the operating performance of Latin American companies, including those in Brazil, Chile, Colombia, and Mexico. Thus, as mentioned by Aydogmus et al. [61] and Nguyen et al. [60], the literature is characterized by diverse conclusions, representing a lack of consensus regarding the direction of the relationship between ESG performance and operational performance. Some previous studies, such as those by Orellano and Quiota [64], Correa-García and Vásquez-Arango [65], and Zahid et al. [63], reported a negative relationship between ESG practices and companies’ operating performance.
Thus, the results indicated a statistically significant positive relationship between ESG practices, and the operating performance of the companies was investigated [60,61]. The results indicated that ESG practices are negatively associated the cost of capital and positively associated the operational performance of the analyzed companies. This finding is significant as it contradicts some recent studies in the literature, such as those by Orellano and Quiota (2011) [64] and Correa-García and Vásquez-Arango (2020) [65], which reported a negative association between ESG practices and operational performance. This discrepancy may be explained by contextual and methodological differences, suggesting that the impact of ESG may vary depending on the sector and the period analyzed [63,64,65]. Thus, this study provides empirical support for the positive relationship between ESG performance and the operating performance of companies, contributing to studies that aim to understand the relationship between operating performance, cost of capital, and ESG score [53,55,64,65,83,84].
In addition, the results in this study also support collaboration in practice with companies that intend to adopt ESG practices, helping investors who want to invest in ESG companies, which are relevant factors related to ESG, the cost of capital, and operational performance that were identified. These results have important implications for managers, investors, and regulators interested in adopting sustainable practices. The promotion of ESG practices could generate social and environmental benefits and result in operational and financial advantages, such as a reduced cost of capital and increased company performance, generating greater investor confidence and positive externalities for society. In contrast to ESG-S and ESG-G, this study indicates a significant association between ESG-E and company results.
Given that environmental concerns of the company’s operation are historically older than social and governance concerns, this heterogeneity of results may be caused by a more well-established measurement. Financial markets can more easily use these environmental factors because of their familiarity with them. We investigated the ESG-E components to understand the main “E” factors that drive these results. The debate about the quality of ESG metrics is important when considering their use in hypothesis testing. The consistency and reliability of ESG classifications can vary substantially between different platforms, as highlighted by Serafeim et al. [13]. In addition to these concerns, S&P recently shifted from quantitative ESG ratings to qualitative assessments. These differences in ESG measurement methodologies could impact the results of the hypothesis tests, raising questions about the correlation between ESG scores and financial measures of company performance.

6. Conclusions

This study investigated the effects of ESG practices on the performance and cost of capital of publicly traded Brazilian companies. We analyzed data from 99 publicly traded Brazilian companies from 2018 to 2022. The results indicated that ESG practices are negatively associated with the cost of capital and positively associated with the operating performance of the companies analyzed. In addition, they revealed that organizations with better ESG scores tended to have lower capital costs, indicating that the adoption of sustainable practices can generate financial benefits. There was a positive and statistically significant relationship between the ESG score and the cost of capital and company performance. When scores were evaluated separately, only environmental performance was significantly related to the cost of capital. The environmental, social, and governance scores were statistically significant for operating performance.
This article contributes to the literature by showing evidence that higher ESG scores are associated with higher corporate financial performance and with lower capital costs. As a contribution to the study of this issue in Brazil, the results enhance the understanding of how ESG factors influence resource allocation decisions within publicly traded companies. Additionally, from a practical perspective, the research can assist strategic decisions related to sustainability and social responsibility. Therefore, it is especially relevant for investors and shareholders interested in investment opportunities aligned with their ESG objectives. However, a limitation of this study is that the results are based only on Brazilian publicly traded companies. In addition, data on changes in regulatory policies and investor preferences can be included in the analysis, exploring quasi-experiment settings. Furthermore, it may be relevant to consider more specific measures of operating performance, such as return on equity (ROE), net margin, or operating cash flow, to assess the effects of ESG practices on different aspects of financial performance. Notably, our analysis focused on specific measures of ESG scores. Thus, a valuable extension of this research would involve testing the consistency of our findings using a variety of other ESG metrics. Another important limitation of the study is that our sample of ESG scores was collected almost entirely during the period of the pandemic. Since ESG scores are recent, new studies may address this point in the future with more data.

Author Contributions

Conceptualization, E.A.G.P., F.A.C. and F.d.M.; Methodology, J.R.F.S.; Software, F.A.C.; Validation, J.R.F.S. and F.d.M.; Formal analysis, J.R.F.S. and F.d.M.; Investigation, E.A.G.P. and F.A.C.; Data curation, F.A.C.; Writing—original draft, E.A.G.P. and F.A.C.; Writing—review & editing, J.R.F.S. and F.d.M. All authors have read and agreed to the published version of the manuscript.

Funding

A grant from CAPES, Brazil, partially supported this research.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Interconnections between ESG performance and the ability to track and disclose material metrics. Source: Prepared by the authors.
Figure 1. Interconnections between ESG performance and the ability to track and disclose material metrics. Source: Prepared by the authors.
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Figure 2. Impact of the ESG score on the cost of capital quantile 95% confidence interval.
Figure 2. Impact of the ESG score on the cost of capital quantile 95% confidence interval.
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Figure 3. Impact of the ESG score on the operational performance quantile 95% confidence interval.
Figure 3. Impact of the ESG score on the operational performance quantile 95% confidence interval.
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Table 2. Descriptive Statistics of the variables.
Table 2. Descriptive Statistics of the variables.
VariablesMeanStandard DeviationMinimumMaximum
Cost of Capital0.09690.04930.02560.2544
ROA0.04760.03100.00110.1527
ESG_score50.776020.901527.31189.7314
E_score47.781826.2243091.2216
S_score52.424323.059814.94394.9899
G_score51.196922.97493.4490.8625
Asset Size23.70951.270220.959727.5706
Liquidity0.07530.066800.3046
Tangibility0.24530.19110.00040.7120
Leverage0.38470.22630.00841.3144
Tobin’s Q1.25900.99190.21886.4907
Observations1397
Sectors55
Companies99
Source: Prepared by the authors.
Table 3. Pearson’s correlation.
Table 3. Pearson’s correlation.
VariablesCost of CapitalROAESG_scoreE_scoreS_scoreG_score
Cost of Capital1.0000
ROA−0.11341.0000
ESG_score0.0661−0.14731.0000
E_score0.0764−0.15340.86861.0000
S_score−0.0012−0.12940.92380.75851.0000
G_score0.0629−0.09650.76420.46650.57811.0000
Source: Prepared by the authors.
Table 4. Regression with Panel Data.
Table 4. Regression with Panel Data.
VariablesCost of CapitalReturn on Assets (ROA)
Fixed EffectFixed Effect
Models (1)(2)(3)(4)
_cons0.2081 ***0.1976 ***0.0995 ***0.1053 ***
(0.0220)(0.0222)(0.0171)(0.0171)
ESG_score−0.0001 ** 0.0001 ***
(0.0000) (0.0000)
E_score −0.0001 *** 0.0002 ***
(0.0000) (0.0000)
S_score 0.0000 −0.0002 ***
(0.0000) (0.0000)
G_score 0.0000 0.0001 ***
(0.0000) (0.0000)
Asset Size−0.0035 ***−0.0031 ***−0.0030 ***−0.0032 ***
(0.0009)(0.0009)(0.0007)(0.0007)
Liquidity−0.0524 ***−0.0544 ***−0.00340.0036
(0.0151)(0.0150)(0.0115)(0.0113)
Tangibility−0.0253 ***−0.0253 ***0.0204 ***0.0195 ***
(0.0056)(0.0056)(0.0045)(0.0045)
Leverage −0.0209 ***−0.0200 ***
(0.0034)(0.0034)
Tobin’s Q−0.0079 ***−0.0079 ***0.0119 ***0.0122 ***
(0.0010)(0.0010)(0.0007)(0.0007)
R210.77%11.29%17.32%21.57%
Observations1397139713971397
This table presents the data results in panels with fixed effect estimation. The estimated variables’ coefficients are the values ahead of the corresponding variable. In the data presented, (i) the numbers in parenthesis are the standard errors, and (ii) the asterisks show a significance of 1% [***], 5% [**]. Source: Prepared by the authors.
Table 5. Distribuition of Outcome Variables by Quartile.
Table 5. Distribuition of Outcome Variables by Quartile.
Y = Cost of Capital
No.MeanStandard DeviationMinimumMaximum
Quartile 13500.050.010.030.06
Quartile 23490.070.010.060.09
Quartile 33490.100.010.090.13
Quartile 43490.170.030.130.25
Y = ROA
No.MeanStandard DeviationMinimumMaximum
Quartile 13500.020.010.000.03
Quartile 23490.030.000.030.04
Quartile 33490.050.010.040.06
Quartile 43490.090.020.060.15
Source: Prepared by the authors.
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Possebon, E.A.G.; Cippiciani, F.A.; Savoia, J.R.F.; de Mariz, F. ESG Scores and Performance in Brazilian Public Companies. Sustainability 2024, 16, 5650. https://doi.org/10.3390/su16135650

AMA Style

Possebon EAG, Cippiciani FA, Savoia JRF, de Mariz F. ESG Scores and Performance in Brazilian Public Companies. Sustainability. 2024; 16(13):5650. https://doi.org/10.3390/su16135650

Chicago/Turabian Style

Possebon, Edna Aparecida Greggio, Felippe Aparecido Cippiciani, José Roberto Ferreira Savoia, and Frédéric de Mariz. 2024. "ESG Scores and Performance in Brazilian Public Companies" Sustainability 16, no. 13: 5650. https://doi.org/10.3390/su16135650

APA Style

Possebon, E. A. G., Cippiciani, F. A., Savoia, J. R. F., & de Mariz, F. (2024). ESG Scores and Performance in Brazilian Public Companies. Sustainability, 16(13), 5650. https://doi.org/10.3390/su16135650

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