SYSTEMATIC REVIEW article

Front. Sustain., 21 September 2022

Sec. Quantitative Sustainability Assessment

Volume 3 - 2022 | https://doi.org/10.3389/frsus.2022.920955

ESG metrics and social equity: Investigating commensurability

  • 1. Department of Civil Engineering, Kyushu University, Fukuoka, Japan

  • 2. Urban Institute, Kyushu University, Fukuoka, Japan

  • 3. International Institute for Carbon-Neutral Energy Research, Kyushu University, Fukuoka, Japan

Article metrics

View details

37

Citations

11,9k

Views

3,7k

Downloads

Abstract

During the past two decades, the world has seen exponential growth in the number of companies reporting environmental, social, and governance (ESG) data, and various ESG metrics have been proposed and are now in use. ESG metrics play a crucial role as an enabler of investment strategies that consider ESG factors, which are often referred to as “ESG investments”. The ESG metrics and investment market are evolving rapidly, as investors, corporations, and the public are giving more priority to the “S” in ESG, including social equity issues, such as diversity, income inequality, worker safety, systemic racism, and companies' broader role in society. In this critical, systematic review, utilizing in-depth assessments, we investigate and compare the approaches employed in major ESG metrics and studies, then, we shed light on the “S” aspect by reviewing existing approaches used to assess social equity to clarify commensurability with ESG. Through the systematic review, this paper confirms that ESG investments can be expected to provide stable and high returns especially over the long term. This paper also clarifies how elements considered in social equity studies are largely reflected in major ESG metrics.

Introduction

Environmental, social, and governance (ESG) investment has become an opportunity for businesses to tap into the growing social demand for lasting change and the emerging ESG market. According to a report by the Global Sustainable Investment Alliance (Global Sustainable Investment Alliance, 2021), total global ESG investments in 2020 reached $35.3 trillion, which is an increase of 15% from 2018 and 55% from 2016. The $35.3 trillion figure represents 35.9% of the $98.4 trillion in assets managed by all of the institutional investors surveyed1. A comprehensive literature review by Camilleri (2020) confirms that the providers of financial capital are increasingly allocating funds toward positive impact and sustainable investments. Because of the growth in environmental and ethical consciousness, both consumers and investors want companies to consider these values. And the growth in such demand increases the importance of developing sound ESG metrics to evaluate ESG activities. As shown by the recent adoption of a proposal for a Directive on corporate sustainability due diligence by the European Commission on February 23, 2022 that aims to foster not just environmentally but also socially responsible corporate behavior throughout global value chains, investors, corporations, and the public are giving more priority to the “S” in ESG, including social equity issues, such as diversity, income inequality, worker safety, systemic racism, and companies' broader role in society. Despite the growing importance of ESG metrics and social aspects of ESG, there is a lack of academic scholarship investigating the commensurability of these metrics, and especially how important social elements are reflected in these metrics.

In recent years, there has been a growing awareness of the problem of the disarray of standards for disclosing ESG information, which is important in assessing the ESG initiatives of companies. The main disclosure standards for ESG information vary, depending on the purpose of the disclosure, such as the areas to be disclosed, whether it is principle or detailed based, the assumed stakeholders, disclosure channels, principles to be followed, and disclosure items. There has been a move toward the unification of standards, including a joint statement by standard-setting bodies and a proposal by the International Financial Reporting Standards Foundation to set sustainability reporting standards. Many studies have critiqued the lack of common theorization and commensurability among the ESG metrics mainly used in the market (Chatterji et al., 2016). Some studies have pointed out that the divergence of ESG ratings is mostly due to the differences in the scope, measurement, and weights of the metrics (Berg et al., 2022), but a critical analysis of ESG metrics and studies that have employed the metrics is required to solve the lack of common theorization and commensurability. We conduct this critical analysis in this study through a systematic review and a detailed examination of ESG metrics, and we investigate and compare the assessment approaches employed in the major ESG metrics and studies. Through the systematic review, we also examine the impact of ESG performance on financial performance and how the results differ among studies using different ESG metrics for the analyses. Additionally, to further examine how the major ESG metrics incorporate important social elements, we shed light on the “S” aspect by reviewing existing approaches used to assess social equity and examine how the elements considered in existing approaches are reflected.

Through the systematic review, this paper confirms that ESG investments can be expected to provide stable and high returns especially over the long term. Regarding the commensurability of the metrics, based on accessible methodology descriptions for four leading ESG metrics widely used in academic research, and business, this paper finds that the elements assessed have a significant divergence across the metrics: only four elements are common among all four ESG metrics, with the ratios of exclusive elements being 37.3, 38.1, 4.4, and 7.1% for the four metrics. This paper also clarifies how the elements considered in the social equity studies are reflected in the major ESG metrics. Some of the common factors that we find in the studies that evaluated social equity quantitatively are the concept of employment, such as relations, unemployment ratios and age groups, as well as income and education, which are also important elements in ESG metrics (e.g., gender balance, salary, and training). This paper also clarifies that access is a factor that can be quantified and used frequently in social equity studies, including access to energy, transportation, and essential facilities, whereas quantifying access is hardly observed in the major ESG metrics. The results of this paper contribute to advancing the research community's and practitioners' knowledge by providing a detailed examination of commensurability of the major ESG metrics, and how the ESG metrics capture important social elements.

The remainder of this paper is structured as follows. Section Systematic review of the literature that has employed ESG metrics provides the results of the systematic review of the ESG and social equity literature. Section ESG metrics and social equity: A closer look at the methodology and elements assessed provides a closer look at the major ESG metrics and critical elements of social equity studies. The discussion and conclusions, which are based on the systematic review and a detailed examination of the elements assessed, are presented in Section Discussion and conclusion.

Systematic review of the literature that has employed ESG metrics

This section provides the result of the systematic review of the ESG and social equity literature to capture the trends in the literature, such as investigated issues, geographical region, industries, and research fields.

Data

The ESG articles reviewed in this study are collected from Scopus, Thomson Reuters' Web of Science, and the top-ranked journals in finance. Considering the fact that ESG studies have been increasingly undertaken in the past decades, we set the search period from January 1, 2000 to December 31, 2021. Following the keywords in previous systematic reviews, the keywords of the ESG topic include “CSR,” “corporate social responsibility,” “ESG,” and “environmental social* governance” (Kong et al., 2020; Widyawati, 2020), where the * stands for any other patterns of the word. The keywords of the ESG database include “MSCI,” “KLD,” “Kinder Lydenberg Domini,” “Refinitiv,” “Thomson Reuters Asset4,” “Bloomberg,” “FTSE Russell,” and “Arabesque S-Ray,” which are the major ESG data providers in the global market (Escrig-Olmedo et al., 2019). Keywords of financial performance that usually appear in the literature include “CFP,” “financial performance,” “stock return,” “ROA,” “ROE,” and “Tobin's Q.” We perform two search strategies in both Scopus and Web of Science2. Strategy 1 is keywords of ESG topic and financial performance, and Strategy 2 is keywords of ESG topic and ESG database. After filtering research articles in English and highly cited or hot papers on the Web of Science, Strategy 1 found 90 results, and Strategy 2 found 18 results. Moreover, after combining Strategies 1 and 2, 932 results were found on Scopus. We then searched for papers in the top-ranked journals in finance (Journal of Banking and Finance, Journal of Corporate Finance, Journal of Finance, Journal of Financial Economics, and Review of Financial Studies) to supplement the results from Scopus and Web of Science. This screening process was conducted by one author and verified by another author.

Figure 1 presents the screening procedure, starting from original articles in Scopus, Web of Science, and top-ranked journals in finance. After removing duplicated articles, we identified 1,293 articles. We manually checked all articles to filter out empirical studies that used the ESG database we are focusing on, and we had 239 articles. Figure 2 presents the number of publications in the selected empirical studies. Most of the studies that used ESG metrics were in the field of corporate finance, followed by specialized CSR journals. We then listed studies that discussed the impact of ESG activities on corporate financial performance. ESG activities are proxied by ESG scores or any specific ESG indicators in the ESG databases. Corporate financial performance is proxied by ROA, ROE, Tobin's Q, and other indicators of market return. After excluding studies that are not our focus, the final sample is 80 articles.

Figure 1

Figure 1

Screening procedure of ESG literature reviewed.

Figure 2

Figure 2

The number of publications among the selected empirical studies.

Regarding the social equity literature, following the review process for the ESG literature, the articles reviewed are from Scopus and Thomson Reuters' Web of Science, with the search period set from January 1, 2000 to December 31, 2021. As one of the main objectives of this study is to investigate how the elements considered in social equity evaluation studies are reflected in major ESG metrics, the keywords for this systematic review are “social equity,” “assessment/evaluation,” and “quantitative.” The screening procedure is presented in Figure 3. Initially, there were 29 papers from the Web of Science and 170 papers from Scopus. After dropping duplicates, we obtained 172 articles. To identify papers with high impact, we employed a selection strategy where the databases were grouped by publication year—Group 1 ends in 2015; Group 2 is from 2016 to 2020, and Group 3 is 2021. In Group 1, papers whose citation count is less than the 50% average level are excluded. In Group 2, papers whose citation count is less than the 25% level are excluded. Regarding papers in 2021, all articles reflected the time-function nature of citations. After filtering out using our citation count quota approach, 128 articles were left. Finally, after excluding studies that did not focus on social equity evaluation, we had 24 articles and 26 case studies for the review.

Figure 3

Figure 3

Screening procedure of social equity literature reviewed.

Analysis and discussion

Based on the final articles selected from 2014 to 2021, we review how the conclusions and implications change across different topics and databases. Figure 1 depicts how the frequency of using ESG metrics increased in the reviewed period. Three databases that are mostly used in the literature are MSCI, Bloomberg, and Refinitiv. The number of publications increased in 2014 after MSCI's ESG database became available and kept growing in subsequent years. Initially, MSCI's ESG database was the most used. However, the number of studies that use Refinitiv's ESG database surged in 2021, becoming comparable to that of MSCI's ESG database. The use of Bloomberg's ESG database had a steady growth in the past 5 years (Figure 4).

Figure 4

Figure 4

The frequency of using ESG metrics in reviewed papers. This figure shows the frequency of using ESG databases from 2014 to 2021. There are several studies using multiple databases.

Table 1 presents four panels that focus on different topics about the effect of ESG factors on corporate performance. In all panels, ESG factors (overall or each factor) are used as independent variables. Table 1A summarizes studies that used accounting measures, such as ROA, ROE, and EBITDA, as dependent variables; Table 1B summarizes studies that used market evaluation Tobin's Q, that is, firm value as dependent variables; Table 1C summarizes studies that used stock return as dependent variables; Table 1D summarizes studies that used the cost of capital and risk indicators as dependent variables.

Table 1

ReferencesDependent variableESG metricsIndependent variableConclusion
Overall, E, S, GVariable name(Positive; Negative; Mixed)
(A) Dependent variable:ROA, ROE, EBITDA
Duque-Grisales and Aguilera-Caracuel (2021)ROAThomson ReutersOverallESG score(Mostly) Negative
Asset4OverallESG score × slack(Mostly) Positive
Griffin et al. (2021)ROAThomson Reuters
Asset4
E, SE/S(Mostly) Positive
Bátae et al. (2021)ROARefinitivEEnv_RU (resource use efficiency)Not significant
EEnv_EM (emission and waste reductions)Positive
EEnv_IN (environmental innovation)Not significant
SSoc_WF (workforce)Not significant
SSoc_HRights (human rights)Not significant
SSoc_COM (community)Not significant
SSoc_PRD (product responsibility)Not significant
GGov_MN (management and oversight)Negative
GGov_SH (shareholder rights)Not significant
GGov_CSR (CSR strategy)Not significant
ROERefinitivEEnv_RUNot significant
EEnv_EMPositive
EEnv_INNot significant
SSoc_WFNot significant
SSoc_HRightsNot significant
SSoc_COMNot significant
SSoc_PRDNot significant
GGov_MNNot significant
GGov_SHNot significant
GGov_CSRNot significant
Kuzey et al. (2021)ROARefinitivOverallESGsNot significant
OverallΔESGsNot significant
OverallCSRcom (CSR committee)(Partially) Negative
OverallESGs × CSRcomNot significant
OverallΔESGs × CSRcomNot significant
ROERefinitivOverallESGsNot significant
OverallΔESGsNot significant
OverallCSRcomNot significant
OverallESGs × CSRcomNot significant
OverallΔESGs × CSRcomNot significant
Atif et al. (2021)ROABloombergGWOBP (% of women on the board)Positive
GWOBP × REN/TC (Total renewable energy consumption as a percentage of total energy use)Positive
ROEBloombergGWOBP × REN/TCPositive
Naseem et al. (2020)ROAThomson ReutersOverallCSRPositive
Asset4OverallPCSRhat (predicted value of CSR)Positive
ROEThomson ReutersOverallCSRPositive
Asset4OverallPCSRhat (predicted value of CSR)(Partially) Positive
Cai et al. (2020)ROA Low = 1, ROA High = 2 (multinomial probit regressions)MSCI, KLDOverallNet adjusted CSR scorePositive
Liu et al. (2020)ROAMSCI, KLDOverallCSRPositive
ROEMSCI, KLDOverallCSRNot significant
Nguyen et al. (2020)ln (1 + profitability)MSCI, KLDOverallCSR proxyPositive
OverallLong-term investor ownership × CSR proxyNot significant
Devie et al. (2020)CFP (corporate financial performance)Bloomberg, other reliable sourcesOverallCSR(Mostly) Positive
Alareeni and Hamdan (2020)ROABloombergOverallESG indexPositive
EEVN indexNegative
OverallCSR indexNegative
GCG indexPositive
ROEBloombergOverallESG indexPositive
EEVN indexNegative
OverallCSR indexNegative
GCG indexNegative
Hoang et al. (2020)ROABloombergEEDS (environmental disclosure score)(Mostly) Positive
EGHG (greenhouse gas emissions per unit of revenue)(Mostly) Positive
EWATER (total water uses per unit of revenue)Not significant
EWASTE (total waste per unit of revenue)Not significant
Saleem et al. (2021)ROABloombergGGDev-index-index (the governance deviance index)Negative
Albuquerque et al. (2019)Change in ROAMSCI, KLDOverallCSR1 variableNot significant
OverallCSR1 × GDP growthNegative
OverallCSR2 variableNot significant
OverallCSR2 × GDP growthNegative
Luffarelli et al. (2019)EBITDAMSCI, KLDOverallCSPNot significant
OverallCSP × PMP (product-market profile)Negative
Xie et al. (2019)ROABloombergEVerification typeNot significant
EGreen building policyPositive
ESustainable packagingPositive
EEnvironmental quality management policyNot significant
EEnvironmental supply chain managementNot significant
EClimate change policyNot significant
EClimate change opportunities discussedNot significant
ERisks of climate change discussedNot significant
EEmissions reduction initiativesNot significant
ENew products climate changeNot significant
EEnergy efficiency policyNot significant
SEqual opportunity policyNot significant
SHuman rights policyNot significant
STraining policyNot significant
SEmployee CSR trainingNegative
SHealth and safety policyNot significant
SFair remuneration policyNot significant
Fauver et al. (2018)ROAThomson Reuters
Asset4
SEF IndexPositive
Brogi and Lagasio (2019)ROAMSCI, KLDOverallESGSCORENot significant
EESCORENot significant
SSSCORENot significant
GGSCORE(Partially) Positive
Byun and Oh (2018)ΔROAMSCI, KLDSNet CSR coverage (positive CSR-related news articles minus negative CSR-related news articles. its articles covering topics in community, diversity, and employee relations)Positive
OverallKLD indexNot significant
Hoi et al. (2018)ROAMSCI, KLDOverallCSP(Partially) Positive
OverallCSP × high social capitalPositive
OverallPositive CSRPositive
OverallPositive CSR × high social capitalPositive
OverallNegative CSRNot significant
OverallNegative CSR × high social capitalNegative
Bhandari and Javakhadze (2017)ROAMSCI, KLDOverallKLDNegative
Wang and Sarkis (2017)ROABloombergGCSRGOVNot significant
ECSRENVNot significant
Cornett et al. (2016)ROAMSCI, KLDOverallESG indexPositive
OverallESG index × small(Partially) Positive
ROEMSCI, KLDOverallESG indexPositive
OverallESG index × small(Partially) Positive
Harrison and Berman (2016)ROAMSCI, KLDOverallCSP (total strengths)Negative
OverallCSP (total concerns)(Partially) Negative
Tebini et al. (2016)ROAMSCI, KLDEEnvtNot significant
EEnvt (-1)Positive
EEnvt (-2)Positive
EEnvt (-3)Positive
EEnvt × sizePositive
EEnvt × investNegative
EEnvt × beta (systematic risk)Negative
Lys et al. (2015)ΔROAThomson ReutersOverallCSRPositive
Asset4EENV_COMPNot significant
SSOC_COMPPositive
GCORPGOVNot significant
Nguyen and Nguyen (2015)ROAMSCI, KLDOverallAggregate strengthsPositive
OverallAggregate concernsPositive
Boesso et al. (2015)EBITDAMSCI, KLDSCommunity(Mostly) Positive
GGovernance(Mostly) Positive
SDiversity(Mostly) Positive
SEmployee(Mostly) Positive
EEnvironment(Mostly) Negative
SHuman rightsNegative
SProductNegative
Di Giuli and Kostovetsky (2014)ROA Δ next 3 yearsMSCI, KLDOverallKLD strengthsNegative
OverallKLD concernsNot significant
Kumar et al. (2016)EBITDAMSCI, KLDEEmployee weaknessNot significant
EEmployee strengthsPositive
SCostumer weaknessNot significant
SCostumer strengthsNot significant
SCommunity weaknessNot significant
SCommunity strengthsNot significant
GGovernance weaknessNot significant
GGovernance strengthsPositive
EEnvironment weaknessNot significant
EEnvironment strengthsNot significant
SDiversity weaknessNegative
SDiversity strengthsPositive
SHuman rights weaknessNegative
SHuman rights strengthsPositive
Moura-Leite et al. (2014)ROAMSCI, KLDE, SPrimary stakeholder managementPositive
(B) Dependent variable:Tobin's Q
Griffin et al. (2021)Tobin's QThomson Reuters
Asset4
E, SE/SPositive
Bátae et al. (2021)TQRefinitivEEnv_RU (resource use efficiency)Not significant
EEnv_EM (emission and waste reductions)Not significant
EEnv_IN (environmental innovation)Not significant
SSoc_WF (workforce)Not significant
SSoc_HRights (human rights)Not significant
SSoc_COM (community)Not significant
SSoc_PRD (product responsibility)Not significant
GGov_MN (management and oversight)Not significant
GGov_SH (shareholder rights)Not significant
GGov_CSR (CSR strategy)Not significant
Kuzey et al. (2021)Tobin's QRefinitivOverallESGsMixed
OverallΔESGsNot significant
OverallCSRcom (CSR committee)(Partially) Negative
OverallESGs × CSRcom(Partially) Positive
OverallΔESGs × CSRcomNot significant
Dai et al. (2021)Market-to-bookMSCI, KLD,OverallCSRc × CSRs _Supplier controlsPositive
Thomson ReutersOverallCSRs _Supplier controlsPositive
Asset4OverallCSRc _Supplier controlsNegative
OverallCSRc × CSRs _Customer controlsPositive
OverallCSRs _Customer controlsNegative
OverallCSRc _Customer controlsNot significant
Bu et al. (2021)Tobin's QMSCI, KLDOverallCSR_PRE (a variable denoting the optimal level of CSR activities)Positive
OverallTID (talented inside directors) × CSR_PREPositive
OverallCSR_RES (excessive level of CSR activities, calculated as CSR minus CSR_PRE)Negative
OverallTID × CSR_RES(Partially) Positive
OverallCSRPositive
OverallTID × CSRPositive
Ertugrul and Marciukaityte (2021)log (Tobin's q)MSCI, KLDOverallCSR net (CSR strengths – CSR concerns)(Partially) Positive
OverallUnionization × CSR netNegative
Lu et al. (2021)Tobin's QMSCI, KLDOverallCSRNot significant
OverallCSR × financial riskPositive
Overall, ECSR × environmental riskPositive
OverallCSR × earnings stabilityPositive
OverallCSR × sales growthNot significant
Hannah et al. (2021)Tobin's QKLD, MSCI,OverallCSRPositive
BloombergOverallCSR2Partially) Positive
OverallCSRPositive
OverallCSR2(Partially) Positive
OverallCSR × SalesGR(Partially) Positive
OverallCSR × AssetGR(Partially) Positive
Atif et al. (2021)Tobin's qBloombergGWOBP (% of women on the board) × REN/TC (Total renewable energy consumption as a percentage of total energy use)Positive
Jia and Li (2020)TobinsQThomson Reuters
Asset4
OverallCSPD (above the sample median of sustainability performance)Positive
OverallECC (exposure to climate change) × CSPDPositive
OverallCSPD(Partially) Positive
OverallEPU (economic policy uncertainty) × CSPDPositive
OverallCSPD(Partially) Positive
OverallPOLI (political instability) × CSPDPositive
Bardos et al. (2020)Tobin's QMSCI, KLDE, SCommunity/environmental CSR(Partially) Positive
Brower and Dacin (2020)Tobin's QMSCI, KLDOverallOverall CSR activities (lag)Positive
OverallPrimary CSR activities (lag) (primary CSP level is calculated as the sum of the firm's CSP strength scores for governance, employee relations, and product strengths for each firm-year observation in the data)Positive
OverallSecondary CSR activities (lag) (secondary CSP level is calculated as the sum of each firm's CSP strength scores for environmental impact, community involvement, and diversity strengths for each firm year observation in the data)Positive
Liu et al. (2020)Tobin's QMSCI, KLDOverallCSRPositive
Nguyen et al. (2020)ln (market-to-book)MSCI, KLDOverallCSR proxyPositive
OverallLong-term investor ownership × CSR proxyPositive
Alareeni and Hamdan (2020)Tobin's QBloombergOverallESG indexPositive
EEVN indexPositive
OverallCSR indexPositive
GCG indexPositive
Saleem et al. (2021)Tobin's-QBloombergGGdev-index-index (the governance deviance index)Positive
Boubakri et al. (2019)Tobin's QThomson ReutersOverallPCSR (predicted CSR intensity)(Mostly) Positive
Asset4OverallSTATE (percentage of shares held by a government) × PCSRPositive
Albuquerque et al. (2019)Tobin's QMSCI, KLDOveralllagged CSR1 variablePositive
Overalllagged CSR2 variablePositive
Luffarelli et al. (2019)Tobin's qMSCI, KLDOverallCSPNot significant
OverallCSP × PMP (product-market profile)Positive
Zolotoy et al. (2019)Tobin's QMSCI, KLDOverallCSR(Mostly) Positive
OverallCSR × religious adherence(Mostly) Negative
Xie et al. (2019)Market valueBloombergEVerification typePositive
(Tobin's Q)EGreen building policyNot significant
ESustainable packagingPositive
EEnvironmental quality management policyNegative
EEnvironmental supply chain managementNot significant
EClimate change policyNot significant
EClimate change opportunities discussedNot significant
ERisks of climate change discussedNot significant
EEmissions reduction initiativesNot significant
ENew products climate changeNot significant
EEnergy efficiency policyNot significant
SEqual opportunity policyPositive
SHuman rights policyPositive
STraining policyPositive
SEmployee CSR trainingNot significant
SHealth and safety policyNot significant
SFair remuneration policyNot significant
Fauver et al. (2018)Tobin's QThomson Reuters
Asset4
SEF (employee-friendliness) index(Mostly) Positive
Byun and Oh (2018)log (Tobin's q)MSCI, KLDSNet CSR coverage (positive CSR-related news articles minus negative CSR-related news articles. its articles covering topics in community, diversity, and employee relations)Positive
OverallKLD index(Partially) Positive
Buchanan et al. (2018)Tobin's QBloombergOverallCSRPositive
OverallCSR × crisis (2008Q3 - 2009Q1)Negative
Taylor et al. (2018)Tobin's QBloombergOverallESG, social, environmental, governance disclosure(Partially) Positive
OverallADSALE (advertising expenditures to sales) × ESG, social, environmental, governance(Partially) Positive
OverallCSR firmNegative
Yu et al. (2018)Industry-adjustedBloombergOverallESG disclosure (industry-adjusted)(Partially) Negative
Tobin's QOverall(ESG disclosure)2(Partially) Positive
Shahzad and Sharfman (2017)Tobin's qMSCI, KLDOverallCSPMixed
Wang and Sarkis (2017)Tobin's QBloombergGCSRGOVNot significant
ECSRENVNot significant
Hawn and Ioannou (2016)Log Tobin's qThomson ReutersOverallInternal (CSR) t − 1 /assetsNot significant
Asset4OverallExternal (CSR) t /assetsPositive
Cornett et al. (2016)Tobin's QMSCI, KLDOverallESG index(Partially) Positive
OverallESG index × small(Partially) Positive
Ferrell et al. (2016)Tobin's QMSCI, KLDOverallCSR(Partially) Positive
OverallCSR × entrenchment indexPositive
Cahan et al. (2015)Tobin's QMSCI, KLDOverallCSRNot significant
OverallCSR × mediaNot significant
OverallCSR × H-HPositive
OverallCSR × media × H-HPositive
Gao and Zhang (2015)Tobin's QMSCI, KLDOverallCSR scoreNot significant
OverallCSR × DAS (discretionary accrual smoothing)Positive
Jha and Cox (2015)Tobin's QMSCI, KLDOverallCSR_S (it is the sum of CSR_STRENGTHS and CSR_CONCERNS. the detailed descriptions of how CSR_STRENGTHS and CSR_CONCERNS are calculated are described later in this table. a higher number indicates greater social responsibility)Positive
OverallCSR_SPositive
OverallCSR_S × HIGH SOCIAL CAPITALNot significant
Nguyen and Nguyen (2015)Tobin's QMSCI, KLDOverallAggregate strengthsPositive
OverallAggregate concernsPositive
Vomberg et al. (2015)Tobin's QMSCI, KLDSHuman capitalNot significant
SBrand equity × human capitalPositive
SHuman capital × FMCG (fast moving consumer goods)Negative
SHuman capital × consumer durablesNegative
SHuman capital × retailNegative
Moura-Leite et al. (2014)Tobin's QMSCI, KLDE, SPrimary stakeholder managementPositive
(C) Dependent variable:Stock return, contains CAR, AR
Ding et al. (2021)Weekly stock returnThomson ReutersOverallCSR score × COVID19Positive
Abnormal returnAsset4OverallCSR score × COVID19Positive
Garel and Petit-Romec (2021)Stock returns (Feb. 20–Mar. 20)Thomson Reuters
Asset4
EEnvironmental score(Mostly) Positive
Bose et al. (2021)CARRefinitivOverallHIGH_CSR(Mostly) Positive
E, OverallLNEMISSION × HIGH_CSR(Mostly) Negative
Bolton and Kacperczyk (2021)Stock returns (RET)MSCI, KLD,ESCOPE 1(Partially) Positive
Thomson ReutersESCOPE 2(Partially) Positive
Asset4, BloombergESCOPE 3(Partially) Positive
Bae et al. (2021)Raw_firm-level stockMSCI, KLDOverallCSR_MSCINot significant
returnsRefinitiv, Thomson
Reuters Asset4
OverallCSR_REFINITIVNot significant
Mkt-adj_firm-levelMSCI, KLDOverallCSR_MSCINot significant
stock returnsRefinitiv, Thomson
Reuters Asset4
OverallCSR_REFINITIV(Partially) Positive
Avramov et al. (2021)Excess returnMSCI, KLD, MSCI IVA, Bloomberg, Asset4 (Refinitiv), Sustainalytics, and RobecoSAMOverallESGNot significant
OverallESG × low ESG uncertaintyNegative
OverallLow ESG uncertainty(Partially) Positive
CAPM-adjustedOverallESGNot significant
returnOverallESG × low ESG uncertaintyNegative
OverallLow ESG uncertainty(Partially) Positive
Doukas and Zhang (2021)CAR (-3, +3)MSCI, KLDOverallAdjusted CSR (compute the total strengths and total concerns for each category and then divide the scores for each category by the respective maximum numbers of strength and concern scores to obtain adjusted strength and concern scores for each dimension. Finally, take the net difference between the total adjusted strength and total adjusted concern scores)(Partially) Negative
OverallAdjusted CSR × MA (managerial ability) -ScorePositive
One-year BHAROverallAdjusted CSRNegative
OverallAdjusted CSR × MA-scorePositive
Liang et al. (2020)Acquirer CAR [−1, +1]Thomson Reuters
Asset4
SAcquirer employment quality (domestic)Positive
SAcquirer employment quality (cross-border)Negative
Boone and Uysal (2020)CAR (−5, +5)MSCI, KLDEDifferent reputation dummy (takes a value of one if an acquirer and its target do not fall into the same environmental grouping)Negative
EGreen firm dummyNot significant
ERatio of green firmsNot significant
EToxic firm dummyNegative
EGreen firm dummyNot significant
P.-A. Nguyen et al. (2020)Excess stock returnsMSCI, KLDOverallCSR proxyNot significant
OverallLong-term investor ownership × CSR proxy(Partially) Negative
Tong et al. (2020)Acquirer announcement returnMSCI, KLDOverallTarget CSR(Mostly) Positive
Zolotoy et al. (2019)Market modelMSCI, KLDOverallCSRPositive
AR_during 2008–2009OverallCSR × religious adherenceNegative
Fama–French–CarhartMSCI, KLDOverallCSRPositive
model AR_during 2008–2009OverallCSR × religious adherenceNegative
Dutordoir et al. (2018)CAR: SEOs (seasoned equity offerings) announcementsMSCI, KLDOverallAdjCSR (sum of yearly adjusted community activities, diversity, employee relations, environmental record, human rights, and product quality and safety scores from KLD)Positive
Feng et al. (2018)CAR_SEO (seasoned equity offerings)MSCI, KLDOverallCSRPositive
Choy et al. (2017)CARThomson Reuters
Asset4
OverallCorporate social responsibilityNot significant
Lins et al. (2017)Raw returnMSCI, KLDOverallCSR(Mostly) Positive
Abnormal returnOverallCSR(Partially) Positive
Shiu and Yang (2017)Abnormal returnsMSCI, KLDOverallShort-term CSR engagement(Partially) Positive
OverallLong-term CSR engagementPositive
Cumulative abnormalOverallShort-term CSR engagementNot significant
returnsOverallLong-term CSR engagementPositive
Gao and Zhang (2015)Rett (ex-dividend stock return during fiscal year t)MSCI, KLDOverallCSR × DASPositive
Borghesi et al. (2014)Annual stock returnMSCI, KLDOverallCSRNot significant
premiums (1992 to 2006)OverallIndustry adjusted CSRNot significant
Di Giuli and Kostovetsky (2014)Stock returnsMSCI, KLDOverallKLD strengths(Partially) Negative
(monthly)OverallKLD concernsNot significant
Stock returns (monthly) Fama-MacBethOverallKLD strengths(Partially) Negative
OverallKLD concernsNot significant
(D) Dependent variable:Cost of equity, Other Risks
Tsang et al. (2021)ROA_VolatilityThomson Reuters
Asset4
OverallCSRContracting (an indicator variable that equals 1 if senior executives' compensation is linked to CSR/H&S (Health and Safety)/sustainability targets (CSR contracting) in the year and 0 otherwise)Positive
S, ECSRPerf (the average of Social performance score and Environmental performance score)Negative
Stock_Return_VolatilityOverallCSRContractingPositive
S, ECSRPerfNegative
Chen et al. (2021)NSKEW (the negative skewness of firm-specific weekly returns over the fiscal year period)MSCI, KLDOverallCSRNot significant
DUVOL (the natural logarithm of the ratio of the standard deviation in the “down” weeks to the standard deviation in the “up” weeks)OverallCSRNot significant
Devie et al. (2020)RISKBloomberg, other reliable sourcesOverallCSRNegative
Boubakri et al. (2019)Cost of equity capitalThomson ReutersOverallPCSR (predicted CSR intensity)Not significant
Asset4OverallSTATE (percentage of shares held by a government) × PCSRNegative
Albuquerque et al. (2019)Firm BetaMSCI, KLDOveralllagged CSR1 variableNegative
Overalllagged CSR2 variableNegative
Chang et al. (2019)BETA (systematic risk)MSCI, KLDOverallSD_CSR (the standardized CSR score, which is equal to the sum of standardized CSR scores over six categories: environment, community, human rights, diversity, employee relations, and product)Negative
Albarrak et al. (2019)Cost of equityBloombergEENV_COMMITEE (environmental committee)(Partially) Negative
EENV_SCORENot significant
EiCarbon × ENV_SCORENot significant
Lueg et al. (2019)TRSK (Total Risk)BloombergOverallESGNot significant
BETA (Systematic Risk)OverallESGNegative
IDIO (Idiosyncratic Risk)OverallESGNot significant
Breuer et al. (2018)Implied cost of equityThomson ReutersOverallCSR(Partially) Negative
BETAAsset4OverallCSRNot significant
SIGMAOverallCSRNot significant
Bhandari and Javakhadze (2017)Alpha 3factorMSCI, KLDOverallKLDNegative
Alpha 4factorOverallKLDNegative
El Ghoul and Karoui (2017)AlphaMSCI, KLDOverallCSR (CSR score)Negative
OverallCSR (Strengths)Negative
OverallCSR (Concerns)Not significant
Oh et al. (2017)Idiosyncratic riskMSCI, KLDOverallADV (CSR)Not significant
OverallADV (CSR) × SIN stockPositive
OverallProbability of KLD reportNot significant
L. Cai et al. (2016)CAPM_BETAMSCI, KLDEENVNegative
FF_MKT_BETAEENVNegative
DEVRETEENVNegative
Cheung (2016)idio (idiosyncratic risk)MSCI, KLDOverallCSRNegative
beta (systematic risk)OverallCSRNegative
Becchetti et al. (2015)Idiosyncratic volatilityMSCI, KLDE, SStakeholder risk (stakeholder risk as the relative sum of weaknesses (concerns) in corporate responsibility in the domains of community, diversity, employee relations, environment, human rights, and product quality according to official ratings of a primary (KLD) CSR rating agency)Negative
Cahan et al. (2015)Cost of capitalMSCI, KLDOverallCSRNot significant
OverallCSR × mediaNot significant
OverallCSR × H-HNot significant
OverallCSR × media × H-HNegative
Ng and Rezaee (2015)Cost of equity_IndEPMSCI, KLDEENVNegative
SSOC(Partially) Negative
GGOVNegative
OverallKLDNegative
Cost of equity_GORDONEENVNegative
SSOC(Partially) Negative
GGOVNegative
OverallKLDNegative
Kim et al. (2014)NCSKEW (the negative conditional skewness of firm-specific weekly returns over the fiscal year)MSCI, KLDOverallCSR_SCORENegative
DUVOL (the natural logarithm of the ratio of the standard deviation in the “down” weeks to the standard deviation in the “up” weeks)OverallCSR_SCORENegative

List of studies using ESG metrics reviewed.

The frame means that the enclosed variables are estimated using the same formula.

We now discuss the systematic review results. Table 1 uses the notation “positive (negative),” “mostly positive (negative),” “partially positive (negative),” “mixed,” or “not significant” for the conclusion of each study. Most of the studies considered in this systematic review estimated the relationship between dependent and independent variables multiple times under various models, with minor changes, to test for robustness. In Table 2, positive (negative) means that a “positive (negative)” coefficient value is observed in all the estimation models in each of the papers. In addition, “mostly” indicates a case in which most of the estimation models are positive (negative), whereas “partially” indicates a case in which positive (negative) results are reported in a few of the estimation models. However, “mixed” refers to cases where the study had different trends (positive and negative) depending on the estimation model. The square frames in Table 2 mean that the enclosed variables are estimated using the same formulas, and the variables enclosed in this square frame contain interaction terms. In this study, to simplify the discussion, the results are considered “mixed” even when the variables in the framework lack consistent trends (positive and negative) due to the influence of specific elements. In addition, for independent variables, most of the studies employed variables in which the greater the value, the higher the degree of ESG management. In contrast, some studies used non-ESG management variables (e.g., CSR concern, negative CSR, toxic firm dummy, and SIN stock), where the greater the value, the lower the degree of ESG management. Finally, the following discussion captures the whole trend of individual papers. If the same study reports both positive and negative trends, we count it as mixed. For studies that report both positive (negative) and non-significant trends, we count them as positive (negative). However, studies that employ more than two ESG metrics are excluded from the count. We also present the results of the reviewed studies on selected dependent variables in the form of heatmaps in Figure 5 (ROA, ROE, and EBITDA), Figure 6 (Stock Return), and Figure 7 (Tobin's Q). To show the trend in more simple way, “mostly positive” and “partially positive” results are presented as positive in the heatmaps and “mostly negative” and “partially negative” are presented as negative, while in the case of “mixed”, one count is added to both positive and negative. The heatmaps presents the breakdown of the results by showing the count for ESG, E, S, G (and the combinations) as explanatory variables.

Table 2

RefinitivMSCIArabesque S-ray
EnvironmentalResource useNatural resourcesResource use
EmissionsClimate changeEmissions
InnovationEnvironmental opportunitiesEnvironmental solutions
Pollution and wasteWaste
Water
Environmental stewardship
Environmental management
SocialWorkforceHuman capitalEmployment quality
CommunitySocial opportunitiesCommunity relations
Product responsibilityProduct liabilityProduct quality and safety
Human rightsHuman rights
Stakeholder opposition
Diversity
Occupational health and safety
Training and development
Product access
Labor rights
Compensation
Corporate governanceManagementCorporate governanceCorporate governance
Shareholders
CSR strategy
Corporate behaviorBusiness ethics

Comparison of ESG score rating structure.

Here, the Bloomberg ESG database is omitted, since there are no ESG categorical topics.

Figure 5

Figure 5

Heatmap of the results of the studies with ROA, ROE, EBITDA as dependent variables.

Figure 6

Figure 6

Heatmap of the results of the studies with Tobin's Q as dependent variables.

Figure 7

Figure 7

Heatmap of the results of the studies with Stock Return as dependent variables.

Regarding the relationship between ESG and profitability (see Table 1A; Figure 5), the results are mixed. We find that seven studies used Bloomberg as ESG metrics, among which three studies reported a positive relationship; one study found a non-significant relationship; two studies reported a mixed relationship, and one study reported a negative relationship. Similarly, seven studies used Refinitiv or Asset4 as ESG metrics, among which four studies reported a positive and significant trend, two mixed, and one negative. However, 17 studies used MSCI or KLD as ESG metrics, among which four studies suggested a negative relationship; nine studies suggested a positive relationship, and the remaining four studies found a mixed relationship. From the heatmap, we can observe that for ROA, ROE, and EBITDA “Positive” ≥ “Nagative” holds in all of the cases except for EBITDA with overall ESG score as explanatory variable. However, there are still statistically non-significant results and negative results that cannot be neglected. Thus, in the short term, it is hard to prove the positive effects of ESG factors on profitability.

Regarding Tobin's Q (see Table 1B; Figure 6), the studies revealed that ESG factors have a positive effect on firm value. Among the 20 studies that used MSCI and KLD as ESG metrics, all reported positive trends, except for six studies that reported a mixed result. This trend is also similar for studies that used Bloomberg, Refinitiv, and Thomson Reuters' Asset4 as ESG metrics, which generally confirms a positive direction, except for two studies that did not find statistical significance and five studies that reported a mixed trend. Figure 6 shows that “Positive” > “Nagative” holds in all of the cases. Therefore, regardless of the type of ESG metrics for Tobin's Q, it is confirmed that the most recent studies report a positive direction. In summary, ESG factors are found to have robust and positive effects on corporate performance in the long term.

Table 1C summarizes the effect of ESG factors on stock return. Refinitiv's Thomson Reuters Asset4 was used in five studies, among which three reported a positive direction; one suggested a mixed trend, and one did not find any significant result. However, 12 studies used MSCI and KLD as ESG metrics, among which seven reported positive effects; two reported a negative result; two suggested a mixed trend, and the remaining one reported a non-significant relationship. Based on these results, studies that used Refinitiv's Thomson Reuters Asset4 tend to have positive results, whereas those that used MSCI and KLD found more complicated results. From the heatmap, as shown in Figure 7, “Positive” ≥ “Negative” holds in most of the cases. However, the impact of ESG factors on stock returns naturally depends on the research period, samples, and other environmental factors. In Table 1C, studies that used interaction models mostly had complicated results, indicating the external contingency of ESG factors. Some studies focused on the time trend of negative shocks to the stock prices of many firms, but it is not necessary to compare this in an analysis that focuses on normal stock returns. We recognize these limitations, but we do not generalize and make comparisons for discussion.

Regarding the cost of equity and other risks (see Table 1D), the studies revealed a negative trend, which means that ESG factors are effective in reducing financial risk and cost. In the 12 studies that used MSCI and KLD as ESG metrics, almost all of them reported negative trends, except one study that reported a positive trend and another study that did not find statistical significance. This trend is also similar in the case of studies that used Bloomberg, Refinitiv, and Thomson Reuters Asset4 as ESG metrics, which generally found a negative direction, except one study that reported a mixed trend. Therefore, regardless of the type of ESG metrics employed, most recent studies have reported a negative effect, implying that engaging in ESG activities leads to robust and favorable results. If other conditions, such as free cash flow, are constant, the lower the value of the cost of capital, the greater the firm's value. Therefore, the robust trends observed in Tables 1B,D can be interpreted as an improvement in the firm's value assessment as a result of risk reduction due to ESG management.

Regarding social equity studies, based on articles selected from 2013 to 2021, we review the investigated issues, critical factors, geographical regions, and research fields, as presented in Table 3. Compared with qualitative theoretical analysis, quantitative analysis of social equity is a relatively new research area. The reviewed articles mostly appeared in the last 5 years. Social equity issues have been discussed worldwide, and quantitative analysis has been applied to a number of case studies in both developed and developing countries and regions.

Table 3

RefinitivBloombergMSCIS-ray
Score range0–1000–1000–100–100
Grade rangeD- to A+ (12 grades)CCC to AAA (7 grades)
Other measuresControversiesControversiesGlobal compact score
Preferences filter
Data sourcesCompany disclosure
Media sources
Company disclosureCompany disclosure
Media sources
Specialized datasets (government databases, NGO, academic, etc.)
Company disclosure
Media sources
NGO
Coverage*Around 9,000 firmsAround 12,000 firmsAround 8,500 firmsAround 8,000 firms
Update frequencyMonthlyYearlyMonthlyDaily
Object of the EvaluationDisclosure and performanceDisclosurePerformance (management capability) given both risks and opportunitiesPerformance given long and short-term risks and opportunities
Rating methodFull data-driven evaluationDisclosure-based evaluationAnalysts' reviewSemi data-driven evaluation and human oversight
Weight calculationData-based inner- and inter- industry adjustmentIndustry adjustmentIndustry adjustment
Risk and opportunity exposure adjustment
Static review and data-based adjustment (sector- and industry-level, equal- and market cap-weighted monthly index returns)
Industry classificationTRBCGICSGICSFactSet definition

Summary of methodology across ESG metrics.

*

The number of firms assessed was counted in 2019.

In terms of the research field, social equity issues in transportation are the most studied topics. Accessibility of horizontal and vertical equity was used as an indicator to assess the extent to which residents can access the job market (El-Geneidy et al., 2016) and facilities (Yuan et al., 2017; Chen et al., 2018; Guo et al., 2020), as well as to discuss transportation design problems (Caggiani et al., 2017; Ruiz et al., 2017; Camporeale et al., 2019; Henke et al., 2020). Regarding transdisciplinary fields, social equity estimation is an essential part of the social sustainability index (Shaker and Sirodoev, 2016; Silva et al., 2018; Larimian and Sadeghi, 2021). Income gap has also been used as an indicator of social equity (Kangmennaang et al., 2017; Su et al., 2017). Regarding environmental issues, some studies have investigated the dissimilarity in costs or benefits and natural resources among different entities or protected areas (Halpern et al., 2013; Gurney et al., 2015) and constructed a social equity score that integrates energy issues (Chapman et al., 2021). Section Social equity will discuss the critical factors used in social equity evaluation in detail.

ESG metrics and social equity: A closer look at the methodology and elements assessed

This section first provides the details of the ESG metrics, with a brief background, methodology, and composition of the elements assessed. Then, the details of social equity evaluation studies are presented using the same procedure.

ESG metrics

Corporate sustainability reporting and rating, which are expected to impact individual corporations' behavior, surged in the last two decades (Scalet and Kelly, 2010). However, compared with financial reporting, which has a long history of evolution, it is still in its infancy (Tschopp and Huefner, 2015). Marlin and Marlin (2003) noted that the first phase of the corporate sustainability report in the 1970s and 1980s only focused on environmental management. Since then, CSR reporting has developed to involve multiple stakeholders and provide verifiable materials from the social auditor (the second phase is the 1990s) and has met third-party global reporting standards (the third phase is the 2000s) (Marlin and Marlin, 2003). Since then, various corporate sustainability reporting tools, such as frameworks (principles, initiatives, or guidelines) and standards, have been widely applied to evaluate corporations' efforts to achieve sustainability (Siew, 2015). Many ESG rating agencies assess corporate sustainability based on the disclosed CSR reports and provide rating reports for multiple stakeholders. In the last 10 years, new criteria have been added to the assessment models, remarkably enhancing the accuracy and robustness of ESG ratings (Escrig-Olmedo et al., 2019).

Many studies have critiqued the low convergence of ESG ratings and called for being cautious about drawing conclusions based on these ratings (Siew, 2015; Chatterji et al., 2016; Berg et al., 2022). The main problems are the lack of common theorization (different definitions of good CSR) and commensurability (different measurements) (Chatterji et al., 2016). The scope, measurement, and weights contribute to the divergence of ESG ratings (Berg et al., 2022). Moreover, only a few ESG rating agencies disclose the details of their evaluating criteria and methods, leaving a black box in the ratings. Therefore, a universal ESG accounting standard with “dynamic materiality” is needed (Eccles and Mirchandani, 2022). Based on the accessible information about the rating methods and the elements assessed, we investigate four leading ESG databases widely used in academic research, investment, and business—Thomson Reuters' Refinitiv, MSCI, Bloomberg, and Arabesque S-Ray.

We first looked at how the ESG rating results correlate across the four databases and discuss the similarities and differences in the methodology and elements assessed in detail. Figure 8 depicts the distribution of ESG scores in each database and the correlation of scores based on the dataset in 2019. The ESG scores and the scores of the components (E, S, and G) in the MSCI database have similar distributions, which are close to a normal distribution. However, the distribution in Bloomberg's ESG database varies, with a higher average G score and a lower average E score. As for Refinitiv's ESG ratings, the G score has a right-skewed distribution, whereas the others skew to the left to different extents. The scores of ESG components in S-Ray have right-skewed distributions. As noted in previous studies, the four investigated databases have low correlations. Most of the correlation coefficients are <0.5, ranging from −0.012 to 0.670. The correlations of integrated ESG scores range from 0.318 (MSCI and Bloomberg) to 0.549 (Refinitiv and Bloomberg). Regarding the ratings of ESG components, it is hard to find strong correlations between these databases. Regarding the E and S scores, MSCI ratings have the lowest correlation with the other three databases. Compared with those of E and S scores, the correlations of G scores are weaker and even insignificant between MSCI and Bloomberg, S-Ray and Reginitiv, as well as S-Ray and Bloomberg. We assume that the inconsistency between these ratings is due to the different methodologies and elements assessed, which will be discussed in the following parts.

Figure 8

Figure 8

Correlation between ESG scores across different databases. This figure is based on the four databases in 2019.

In Table 2, we summarize the methodology of the four ESG databases. The final ESG ratings range from 0 to 100 points, except for MSCI, which uses 10 points as the maximum. In addition to ESG scores, Refinitiv and MSCI also provide concise and explicit ESG grade evaluations. The assessments are usually based on information individual firms disclose. Except Bloomberg, the other raters utilize media sources to construct controversies to adjust the final ESG ratings. All the four databases have a global coverage of at least 8,000 firms. Bloomberg's ESG scores are updated annually. Refinitiv and MSCI's ESG scores are updated monthly, and S-Ray's ESG score is updated daily.

Here, we follow the framework in previous studies to discuss the purpose of the evaluation (the scopes) and the rating procedure (the measures), including the method and weight (Chatterji et al., 2016; Berg et al., 2022). The purpose of the evaluation reflects how the rater defines good CSR, i.e., the theorization or scope of the assessment. In the four databases, there are mainly two directions in determining what is good CSR—information transparency and CSR performance. Bloomberg's disclosure score treats the transparency of ESG information as the most vital factor of CSR. Thus, for Bloomberg's ESG scores, higher information disclosure leads to higher rating results, without accounting for performance. Both MSCI and S-Ray's ESG ratings aim to assess performance in terms of ESG issues but from different perspectives. MSCI's ESG scores tend to evaluate the management's capability in handling both risks and opportunities. S-Ray's ESG scores account for performance, considering both long-term and short-term risks and opportunities, and the evaluation is conducted daily. Refinitiv's ESG scores evaluate both disclosure rate and relative performance among peers.

Regarding the rating process, there is no fully disclosed methodology information in these databases. Based on the accessible materials on methodology, we summarize some of the features as follows. Refinitiv has the advantage of a clear and verifiable method, as the assessment is entirely data-driven without any human intervention. Bloomberg's ESG scores only consider the degree of information disclosure, which makes the rating easy to understand and straightforward. However, MSCI's ESG scores reflect a more subjective assessment by specialists and analysts, which involves highly professional views, but the assessment is not easily understandable by users. S-Ray's ratings aim to seek a balance by combining a semi data-driven evaluation and human intervention. Regarding the weights, Refinitiv's ratings conduct inter- and intra-industry adjustment, which is a fully data-driven process that takes time. The industry classification is based on The Refinitiv Business Classifications. MSCI and Bloomberg's ratings are adjusted based on the Global Industry Classification Standard. Notably, MSCI's ratings are adjusted for risk or opportunities in each element assessed. Thus, the ratings in MSCI are not only a relative peer comparison but also an evaluation of firms' management capability in handling potential risks and opportunities.

Before comparing the detailed elements assessed, it is essential to note that the structures of ESG scores also vary across each database, as presented in Table 4. The main difference is categorizing the elements under the E, S, and G pillars. In the E pillar, the common categories are resource, emission, and innovation. Although it is given different names, all the three databases have these categories. In addition, pollution and waste are also evaluated in MSCI and S-Ray's ESG database. S-Ray also provides “environmental stewardship” and “environmental management” scores. In the S pillar, categories of human resource, community, and product responsibility are common among the three databases. Refinitiv and S-Ray have a category of “human rights,” whereas MSCI provides another category of “stakeholder opposition.” S-Ray's ESG scores provide detailed topics in the S pillar, including diversity, occupational health and safety, training and development, product access, labor rights, and compensation. In terms of the G pillar, a similar category among the three databases is corporate governance or management. Moreover, categories of shareholders, CSR strategy, corporate behavior, and business ethics are provided across the databases.

Table 4

ReferencesIndicators out of socioeconomic factorsSocial (vulnerability) indicatorSector or research fieldTarget areaCountry or regions
Valizadeh and Hayati (2021)Education
Economic factors
Right to quality of life
Capacity development
Fair pricing and TRN contracts
Employment relations
Child labor
Non-discrimination and sup. Vuln. People
Health cover, access, medic care
Agricultural and biological sciences (miscellaneous)Fars provinceIran
Larimian and Sadeghi (2021)Access to essential facilities
Access to recreational facilities
Access to educational facilities
Access to transportation facilities
Urban studiesDunedin cityNew Zealand
A. Chapman et al. (2021)Ratio of renewable energy to the total electricity
Electricity access
PM 2.5 explosure
Environmental improvement indicator
Energy poverty indicator
Income distribution
GDP per capita
Unemployment ratio
Renewable energy, sustainability and the environment99 countries
Emrich et al. (2020)Housing tenure
Fianncial capital
Race
Language proficiency
Housing quality
Age
Employment
Management, monitoring, policy and lawSouth Carolina floods 2015United States
Henke et al. (2020)Travel timeTotal number of employees in traffic zoneTransportationPugliaItaly
Karakoc et al. (2020)Population over the age of 65
Population under the age of 5
Population that is Hispanic
Single-female based households
Households that are in poverty
Urban studiesShelby CountyUnited States
Bennett et al. (2020)Recognitional equity (4 items as below) (Rights LivelihoodsNature and landscape conservation6 countries on the Mediterranean Sea6 countries on the Mediterranean Sea
Traditional Knowledge Culture)
Procidural equity (8 items)
Distributional equity (8 items)
Shigetomi et al. (2020)GHG emissions
Primary PM 2.5
Blue and green water
mining risk for neodymium
Industrial waste
Household bracket based on cumulative share of consumptionRenewable energy, sustainability and the environmentJapan
Guo et al. (2020)Park accessibilityElderly populationTransportationHarbin cityChina
Camporeale et al. (2019)Number of bus tripsUnemployed population
Young (<19 years old)
Old (more than 65 years old)
TransportationMolfettaItaly
Chen et al. (2018)Service area ratio
Service density
Service frequency
Route diversity
Accessibility within a statistical area
Accessibility across statistical area
Percentage of senior populationTransportationEdmontonCanada
Silva et al. (2018)Poverty
Households with income below poverty line (%)
Population living in extreme poverty (%)
Average monthly income (ln)
Gender Equality
Ratio between average wages for women and men
Social sciences (miscellaneous)State of CearaBrazil
Su et al. (2017)Urban-rural income gapUrban studiesMegaregion around Hangzhou BayChina
Ruiz et al. (2017)Bus Service Level by districtsPopulation by districts
Dependent population rate
Immigrant population rate
Female population rate
Level of economic activity
TransportationPalmaSpain
Kangmennaang et al. (2017)Firm pay gapAgricultural and biological sciences (miscellaneous)China
Yuan et al. (2017)Public parks accessibilityTotal population
Rate of the Female population
Rate of the population aged 0–19
Rate of the population aged 60 and over
Rate of ethnic minority population
Rate of the illiterate population
Rate of the laid-off population
Rate of the unemployed population
TransportationChangtingChina
Caggiani et al. (2017)Residing population
Workers
Number of employees
Residing disadvantaged population
Young
Unemployed population
Low-income population
TransportationMolfettaItaly
El-Geneidy et al. (2016)Travel time
Transit fares
Household income
Percentage of recent immigrants (since 2006)
Percentage of workforce that is unemployed
Percentage of residents with education at the level of only a high school diploma (25–64 years old)
TransportationMontrealCanada
Shaker and Sirodoev (2016)Type of cooking fuel
Computers, mobile phone, microwave, and DVD/VCR
Access to improved water source
Access and type of sanitation facility
Number of household members outside the country
Head of household education level
Social sciences (miscellaneous)Moldova
Oswald Beiler and Mohammed (2016)Public transit
Access
School proximity
Network connectivity
Mixed land uses
Flood hazard
Crash rates
Truck volume
Intermodal facilities
Race
Limited English proficiency
Age
Disability
Economic development
Vehicles per household
Household income
Single parent household
Cost of living
Travel time
TransportationSullivan CountyUnited States
Gurney et al. (2015)Inverse of the Gini coefficient in terms of the percentage of retained catch per unit effort (CPUE)Nature and landscape conservationKubulauFiji
Farber et al. (2014)Ridership percentage
Trip generations
Distance traveled (miles)
Household income
Hispanic
Race
Age
Employment
Education
Licensed
Limited mobility
Home ownership
Years of residence
Place type
Residence type
TransportationWasatch Front, UtahUnited States
Di Ciommo and Lucas (2014)Travel times
Transport costs
IncomeTransportationMadridSpain
Halpern et al. (2013)Fraction of fishing value lost inside marine reservesNature and landscape conservationCaliforniaUnited States
Fraction of community fishing grounds lost inside marine reservesNature and landscape conservationMisool, Raja AmpatIndonesia
Fraction of money spent; fraction of area placed into marine reservesNature and landscape conservationCoral TriangleSoutheast Asia

List of quantitative studies of social equity.

Based on accessible methodology materials of the four ESG ratings, we collect the elements assessed in each ESG database. The total number of elements assessed in all the four databases is 842. The elements assessed have a significant divergence across the four databases. The Venn diagram of Figure 9 compares all the elements assessed, in which only four elements are common among all the four ESG ratings. The ratios of exclusive elements are 37.3% in Refinitiv's ESG scores, 38.1% in MSCI's ESG scores, 4.4% in S-Ray's ESG scores, and 7.1% in Bloomberg's ESG scores. Regarding the social aspect, there are 281 total elements across the four databases, which is 33.4% of all the ESG elements. Surprisingly, there are no common items in all the databases. The number of social elements in Bloomberg and S-Ray is much less than that in Refinitiv and MSCI. The observed significant divergence in the assessed elements across the four databases emphasizes the importance of developing a universal ESG accounting standard with “dynamic materiality”, elaborated by Eccles and Mirchandani (2022).

Figure 9

Figure 9

Comparison of evaluated factors across ESG database.

Social equity

Here, when we refer to social equity, we are referring to a metric used to evaluate the equitability of various energy and environment issues, as well as the social aspects of sustainability. Energy-related social equity has its roots in the energy justice movement, which is based on environmental justice (Pettit, 2004) and climate justice (Bulkeley et al., 2013), focusing on energy issues and environmental benefits (Jenkins, 2018). Energy justice focuses on three key tenets—distributional justice (the distribution of costs and benefits), recognition justice (identifying who benefits or is burdened), and procedural justice [open access and engagement in policy decision-making processes (Jenkins et al., 2016)]. Social equity evaluations have been used for energy policy, energy emissions, energy law, energy finance, climate policy, and, most recently, energy transitions (McCauley and Heffron, 2018; Chapman et al., 2019).

Regarding energy-related sustainability evaluations, most of the studies focused on the more easily quantified environmental and economic aspects, or when considering social equity, they place more emphasis on qualitative rather than quantitative factors (Evans et al., 2009; Chapman et al., 2016).

In studies that evaluate sustainability and social equity quantitatively, a number of common factors come to the fore. Among them is the concept of employment, including relations (Valizadeh and Hayati, 2021), unemployment ratios and age groups (Farber et al., 2014; El-Geneidy et al., 2016; Caggiani et al., 2017; Yuan et al., 2017; Camporeale et al., 2019; Emrich et al., 2020; Chapman et al., 2021), and how different policies and technological shift affect employment outcomes. Moreover, income and education, which are often closely correlated, are also considered important in the literature (Farber et al., 2014; Oswald Beiler and Mohammed, 2016; Silva et al., 2018; Shigetomi et al., 2020; Chapman et al., 2021). Access is another factor of social equity that can be quantified, including access to energy, transportation, and essential facilities (Farber et al., 2014; Shigetomi et al., 2020; Chapman et al., 2021; Larimian and Sadeghi, 2021). Furthermore, recognizing that there is often a gap not only between nations but also within nations, some studies also investigate the urban–rural divide and the gaps between genders and different age groups (Farber et al., 2014; Oswald Beiler and Mohammed, 2016; Ruiz et al., 2017; Su et al., 2017; Yuan et al., 2017; Chen et al., 2018; Silva et al., 2018; Guo et al., 2020; Karakoc et al., 2020). Generally, the literature includes distributive, recognition, and procedural aspects of social equity evaluations, with some focusing on this aspect quantitatively (Bennett et al., 2020). As the concept of social equity is still in its nascent phase, the overlap of concepts is not consistent, and to enable quantitative evaluations of social aspects, economic and environmental factors are co-opted when considered socially important.

From a regional perspective, Europe is strongly represented in the literature along with the United States and with some case studies on Southeast Asia. Global studies are only beginning to emerge in the most recent literature, which is largely due to the relatively recent emergence of concepts and data limitations.

Discussion and conclusion

As the ESG market is expanding rapidly, with total global ESG investments of $35.3 trillion in 2020, ESG rating providers play an increasingly important role in the investment process through their assessments of companies across various ESG metrics. However, the lack of common theorization (different definitions of good CSR) and commensurability (different measurements), which has been pointed out in various studies (Chatterji et al., 2016) and examined in detail in this paper, highlights the improvements required in the field of ESG assessment to provide clear and transparent information to investors and to reduce confusion among companies that are trying to enhance their ESG performance.

Considering the effect of ESG factors on corporate performance, in summary, we find that the overall trend of the short-term effect on profitability is unclear. The effect on ROA or ROE is still far from conclusive. In terms of stock return, the results vary, as they utilize different ESG metrics. Multiple factors, such as samples from different markets and periods, could also be a reason for the inconsistent results. However, most of the current ESG evaluations do not reflect the financial impact, accounting measures, and short-term market returns sufficiently. The trend is robust and favorable when testing the effect on Tobin's Q, cost of equity, or other risks, which indicate the nature of ESG activities, thereby enhancing corporate sustainability in the long term. Although it is out of scope of this paper, future research could focus on the difference between ESG metrics and conduct an in-depth analysis of the metrics that impact upon financial outcomes.

To have a closer look at the ESG metrics, we first investigate how the results of the ESG ratings correlate across the four widely used databases (Thomson Reuters' Refinitiv, MSCI, Bloomberg, and Arabesque S-Ray). The results reveal that the four investigated databases have low correlations, with the correlations of integrated ESG scores ranging from 0.318 (MSCI and Bloomberg) to 0.549 (Refinitiv and Bloomberg). Moreover, regarding the ratings of the ESG components, it is also difficult to find strong correlations between these databases. Based on the accessible methodology materials of the four ESG ratings, we also collect the elements assessed in each ESG database and present the significant divergence of the elements assessed across the four databases. The ratios of exclusive elements are 37.3% in Refinitiv's ESG scores, 38.1% in MSCI's ESG scores, 4.4% in S-Ray's ESG scores, and 7.1% in Bloomberg's ESG scores. Regarding the social aspect, there are 281 elements in all the four databases, which is 33.4% of all the ESG elements. There are no common items in all the databases. The number of social elements in Bloomberg and S-Ray is much lower than that of Refinitiv and MSCI. Although the ESG metrics and the investment market are evolving rapidly, with investors, corporations, and the public giving more priority to the “S” in ESG, which includes social equity issues, such as diversity, income inequality, workers' safety, systemic racism, and companies' broader role in society. There is significant divergence among the different ESG databases in the elements assessed under the social category.

To provide a suitable yardstick for the assessment of social aspects, we investigated existing approaches used for social equity evaluations through a systematic review and closely examined the key elements assessed in these studies. Some of the common factors that we find in the studies that evaluated sustainability and social equity quantitatively are the concept of employment, such as relations, unemployment ratios and age groups, as well as income and education, which were also found to be important elements in ESG metrics (e.g., gender balance, salary, and training). In social equity studies, access is a factor which is considered important and which can be quantified, including access to energy, transportation, and essential facilities, whereas quantifying access is rarely observed in the major ESG metrics. Due to the influence of ESG metrics, the differences in the rating methodologies and the level of transparency in the rating decisions, which also incorporate qualitative judgments, are critical to understanding the resilience of the ESG financial intermediation chain. The results of this paper contribute to advancing the research community's and practitioners' knowledge by providing a detailed examination of commensurability of major ESG metrics, and whether these ESG metrics capture critical social elements. Furthermore, the results of this paper reveals the importance of promoting the transparency and comparability of scoring methodologies of established ESG rating providers and indices, as well as highlighting the importance of investigating studies and practices that quantitatively assess sustainability and social equity issues to ensure the overall veracity and quality of ESG metrics, as well as providing some evidence for their future expansion and improvement.

Funding

This research is supported by JSPS KAKENHI Grant Number JP20H00648 and the Environment Research and Technology Development Fund (JPMEERF20201001) of the Environmental Restoration and Conservation Agency of Japan.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Author disclaimer

Any opinions, findings, and conclusions expressed in this paper are those of the authors and do not necessarily reflect the views of the funding agencies.

Statements

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

AK, AC, KY, JX, JI, and ST carried out the analyses and wrote the manuscript with support from SM. AK and SM supervised the project. All authors contributed to the article and approved the submitted version.

Acknowledgments

We would like to thank Mr. Okita and Mr. Ike from Vector Group for providing their insights and expertise on ESG investment market during number of discussions.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

1.^GSIA has surveyed institutional investors in the five regions: Europe; the US; Canada; Australia; NZ; and Japan.

2.^The search date is January 6 2022.

References

  • 1

    AlareeniB. A.HamdanA. (2020). ESG impact on performance of US S&P 500-listed firms. Corp. Governance Int. J. Bus. Soc.20, 14091428. 10.1108/CG-06-2020-0258

  • 2

    AlbarrakM. S.ElnahassM.SalamaA. (2019). The effect of carbon dissemination on cost of equity. Bus. Strategy Environ.28, 11791198. 10.1002/bse.2310

  • 3

    AlbuquerqueR.KoskinenY.ZhangC. (2019). Corporate social responsibility and firm risk: theory and empirical evidence. Manage. Sci.65, 44514469. 10.1287/mnsc.2018.3043

  • 4

    AtifM.HossainM.AlamM. S.GoergenM. (2021). Does board gender diversity affect renewable energy consumption?J. Corp. Financ.66, 101665. 10.1016/j.jcorpfin.2020.101665

  • 5

    AvramovD.ChengS.LiouiA.TarelliA. (2021). Sustainable investing with ESG rating uncertainty. J. Financ. Econ. 145, 64266410.1016/j.jfineco.2021.09.009

  • 6

    BaeK.-H.El GhoulS.GongZ.GuedhamiO. (2021). Does CSR matter in times of crisis? Evidence from the COVID-19 pandemic. J. Corp. Financ.67, 101876. 10.1016/j.jcorpfin.2020.101876

  • 7

    BardosK. S.ErtugrulM.GaoL. S. (2020). Corporate social responsibility, product market perception, and firm value. J. Corp. Financ.62, 101588. 10.1016/j.jcorpfin.2020.101588

  • 8

    BátaeO. M.DragomirV. D.FeleagáL. (2021). The relationship between environmental, social, and financial performance in the banking sector: a European study. J. Clean. Prod.290, 125791. 10.1016/j.jclepro.2021.125791

  • 9

    BecchettiL.CicirettiR.HasanI. (2015). Corporate social responsibility, stakeholder risk, and idiosyncratic volatility. J. Corp. Financ.35, 297309. 10.1016/j.jcorpfin.2015.09.007

  • 10

    BennettN. J.CalòA.Di FrancoA.NiccoliniF.MarzoD.DominaI.et al. (2020). Social equity and marine protected areas: perceptions of small-scale fishermen in the Mediterranean Sea. Biol. Conserv.244, 108531. 10.1016/j.biocon.2020.108531

  • 11

    BergF.KoelbelJ.RigobonR. (2022). Aggregate confusion: The divergence of ESG ratings. Review of Finance. 2022:rfac033. 10.1093/rof/rfac033

  • 12

    BhandariA.JavakhadzeD. (2017). Corporate social responsibility and capital allocation efficiency. J. Corp. Financ.43, 354377. 10.1016/j.jcorpfin.2017.01.012

  • 13

    BoessoG.FavottoF.MichelonG. (2015). Stakeholder prioritization, strategic corporate social responsibility and company performance: further evidence. Corp. Soc. Respons. Environ. Manage.22, 424440. 10.1002/csr.1356

  • 14

    BoltonP.KacperczykM. (2021). Do investors care about carbon risk?J. Financ. Econ.142, 517549. 10.1016/j.jfineco.2021.05.008

  • 15

    BooneA.UysalV. B. (2020). Reputational concerns in the market for corporate control. J. Corp. Financ.61, 101399. 10.1016/j.jcorpfin.2018.08.010

  • 16

    BorghesiR.HoustonJ. F.NaranjoA. (2014). Corporate socially responsible investments: CEO altruism, reputation, and shareholder interests. J. Corp. Financ.26, 164181. 10.1016/j.jcorpfin.2014.03.008

  • 17

    BoseS.MinnickK.ShamsS. (2021). Does carbon risk matter for corporate acquisition decisions?J. Corp. Financ.70, 102058. 10.1016/j.jcorpfin.2021.102058

  • 18

    BoubakriN.GuedhamiO.KwokC. C. Y.WangH. (2019). Is privatization a socially responsible reform?J. Corp. Financ.56, 129151. 10.1016/j.jcorpfin.2018.12.005

  • 19

    BreuerW.MüllerT.RosenbachD.SalzmannA. (2018). Corporate social responsibility, investor protection, and cost of equity: a cross-country comparison. J. Bank. Financ.96, 3455. 10.1016/j.jbankfin.2018.07.018

  • 20

    BrogiM.LagasioV. (2019). Environmental, social, and governance and company profitability: Are financial intermediaries different?Corp. Soc. Respons. Environ. Manage.26, 576587. 10.1002/csr.1704

  • 21

    BrowerJ.DacinP. A. (2020). An institutional theory approach to the evolution of the corporate social performance – corporate financial performance relationship. J. Manage. Stud.57, 805836. 10.1111/joms.12550

  • 22

    BuL.ChanK. C.ChoiA.ZhouG. (2021). Talented inside directors and corporate social responsibility: a tale of two roles. J. Corp. Financ.70, 102044. 10.1016/j.jcorpfin.2021.102044

  • 23

    BuchananB.CaoC. X.ChenC. (2018). Corporate social responsibility, firm value, and influential institutional ownership. J. Corp. Financ.52, 7395. 10.1016/j.jcorpfin.2018.07.004

  • 24

    BulkeleyH.CarminJ. A.Castán BrotoV.EdwardsG. A. S.FullerS. (2013). Climate justice and global cities: mapping the emerging discourses. Global Environ. Change23, 914925. 10.1016/j.gloenvcha.2013.05.010

  • 25

    ByunS. K.OhJ.-M. (2018). Local corporate social responsibility, media coverage, and shareholder value. J. Bank. Financ.87, 6886. 10.1016/j.jbankfin.2017.09.010

  • 26

    CaggianiL.CamporealeR.OttomanelliM. (2017). Planning and design of equitable free-floating bike-sharing systems implementing a road pricing strategy. J. Adv. Transport.2017, 118. 10.1155/2017/3182387

  • 27

    CahanS. F.ChenC.ChenL.NguyenN. H. (2015). Corporate social responsibility and media coverage. J. Bank. Financ.59, 409422. 10.1016/j.jbankfin.2015.07.004

  • 28

    CaiL.CuiJ.JoH. (2016). Corporate environmental responsibility and firm risk. J. Bus. Ethics139, 563594. 10.1007/s10551-015-2630-4

  • 29

    CaiX.GaoN.GarrettI.XuY. (2020). Are CEOs judged on their companies' social reputation?J. Corp. Financ.64, 101621. 10.1016/j.jcorpfin.2020.101621

  • 30

    CamilleriM. A. (2020). The market for socially responsible investing: a review of the developments. Soc. Respons. J.17, 412428. 10.1108/SRJ-06-2019-0194

  • 31

    CamporealeR.CaggianiL.OttomanelliM. (2019). Modeling horizontal and vertical equity in the public transport design problem: a case study. Transport. Res. Part A Policy Pract.125, 184206. 10.1016/j.tra.2018.04.006

  • 32

    ChangC.-H.ChenS.-S.ChenY.-S.PengS.-C. (2019). Commitment to build trust by socially responsible firms: evidence from cash holdings. J. Corp. Financ.56, 364387. 10.1016/j.jcorpfin.2019.03.004

  • 33

    ChapmanA.FraserT.DennisM. (2019). Investigating ties between energy policy and social equity research: a citation network analysis. Soc. Sci.8, 135. 10.3390/socsci8050135

  • 34

    ChapmanA.ShigetomiY.OhnoH.McLellanB.ShinozakiA. (2021). Evaluating the global impact of low-carbon energy transitions on social equity. Environ. Innovat. Societal Trans.40, 332347. 10.1016/j.eist.2021.09.002

  • 35

    ChapmanA. J.McLellanB.TezukaT. (2016). Proposing an evaluation framework for energy policy making incorporating equity: applications in Australia. Energy Res. Soc. Sci.21, 5469. 10.1016/j.erss.2016.06.021

  • 36

    ChatterjiA. K.DurandR.LevineD. I.TouboulS. (2016). Do ratings of firms converge? Implications for managers, investors and strategy researchers. Strategic Manage. J.37, 15971614. 10.1002/smj.2407

  • 37

    ChenYBoufergueneA.LiH. X.LiuH.ShenY.Al-HusseinM. (2018). Spatial gaps in urban public transport supply and demand from the perspective of sustainability. J. Clean. Prod.195, 12371248. 10.1016/j.jclepro.2018.06.021

  • 38

    ChenY.FanQ.YangX.ZolotoyL. (2021). CEO early-life disaster experience and stock price crash risk. J. Corp. Financ.68, 101928. 10.1016/j.jcorpfin.2021.101928

  • 39

    CheungA. (2016). Corporate social responsibility and corporate cash holdings. J. Corp. Financ.37, 412430. 10.1016/j.jcorpfin.2016.01.008

  • 40

    ChoyS. K.LaiT.-K.NgT. (2017). Do tax havens create firm value?J. Corp. Financ.42, 198220. 10.1016/j.jcorpfin.2016.10.016

  • 41

    CornettM. M.ErhemjamtsO.TehranianH. (2016). Greed or good deeds: An examination of the relation between corporate social responsibility and the financial performance of U.S. commercial banks around the financial crisis. J. Bank. Financ.70, 137159. 10.1016/j.jbankfin.2016.04.024

  • 42

    DaiR.LiangH.NgL. (2021). Socially responsible corporate customers. J. Financ. Econ.142, 598626. 10.1016/j.jfineco.2020.01.003

  • 43

    DevieD.LimanL. P.TariganJ.JieF. (2020). Corporate social responsibility, financial performance and risk in Indonesian natural resources industry. Soc. Respons. J.16, 7390. 10.1108/SRJ-06-2018-0155

  • 44

    Di CiommoF.LucasK. (2014). Evaluating the equity effects of road-pricing in the European urban context – The Madrid Metropolitan Area. Appl. Geograp.54, 7482. 10.1016/j.apgeog.2014.07.015

  • 45

    Di GiuliA.KostovetskyL. (2014). Are red or blue companies more likely to go green? Politics and corporate social responsibility. J. Financ. Econ.111, 158180. 10.1016/j.jfineco.2013.10.002

  • 46

    DingW.LevineR.LinC.XieW. (2021). Corporate immunity to the COVID-19 pandemic. J. Financ. Econ.141, 802830. 10.1016/j.jfineco.2021.03.005

  • 47

    DoukasJ. A.ZhangR. (2021). Managerial ability, corporate social culture, and M&amp;As. J. Corp. Financ.68, 101942. 10.1016/j.jcorpfin.2021.101942

  • 48

    Duque-GrisalesE.Aguilera-CaracuelJ. (2021). Environmental, social and governance (ESG) scores and financial performance of multilatinas: moderating effects of geographic international diversification and financial slack. J. Bus. Ethics168, 315334. 10.1007/s10551-019-04177-w

  • 49

    DutordoirM.StrongN. C.SunP. (2018). Corporate social responsibility and seasoned equity offerings. J. Corp. Financ.50, 158179. 10.1016/j.jcorpfin.2018.03.005

  • 50

    EcclesR. G.MirchandaniB. (2022). We Need Universal ESG Accounting Standards. Harvard Business Review. Available online at: https://hbr.org/2022/02/we-need-universal-esg-accounting-standards (accessed March 15, 2022).

  • 51

    El GhoulS.KarouiA. (2017). Does corporate social responsibility affect mutual fund performance and flows?J. Bank. Financ.77, 5363. 10.1016/j.jbankfin.2016.10.009

  • 52

    El-GeneidyA.LevinsonD.DiabE.BoisjolyG.VerbichD.LoongC. (2016). The cost of equity: Assessing transit accessibility and social disparity using total travel cost. Transport. Res. Part A Policy Pract.91, 302316. 10.1016/j.tra.2016.07.003

  • 53

    EmrichC. T.TateE.LarsonS. E.ZhouY. (2020). Measuring social equity in flood recovery funding. Environ. Hazards19, 228250. 10.1080/17477891.2019.1675578

  • 54

    ErtugrulM.MarciukaityteD. (2021). Labor unions and corporate social responsibility. J. Bank. Financ.125, 106061. 10.1016/j.jbankfin.2021.106061

  • 55

    Escrig-OlmedoE.Fernández-IzquierdoM.Ferrero-FerreroI.Rivera-LirioJ.Muñoz-TorresM. (2019). Rating the raters: evaluating how ESG rating agencies integrate sustainability principles. Sustainability11, 915. 10.3390/su11030915

  • 56

    EvansA.StrezovV.EvansT. J. (2009). Assessment of sustainability indicators for renewable energy technologies. Renewable Sustain. Energy Rev.13, 10821088. 10.1016/j.rser.2008.03.008

  • 57

    FarberS.BartholomewK.LiX.PáezA.Nurul HabibK. M. (2014). Assessing social equity in distance based transit fares using a model of travel behavior. Transport. Res. Part A Policy Pract.67, 291303. 10.1016/j.tra.2014.07.013

  • 58

    FauverL.McDonaldM. B.TaboadaA. G. (2018). Does it pay to treat employees well? International evidence on the value of employee-friendly culture. J. Corp. Financ.50, 84108. 10.1016/j.jcorpfin.2018.02.003

  • 59

    FengZ.-Y.ChenC. R.TsengY.-J. (2018). Do capital markets value corporate social responsibility? Evidence from seasoned equity offerings. J. Bank. Financ.94, 5474. 10.1016/j.jbankfin.2018.06.015

  • 60

    FerrellA.LiangH.RenneboogL. (2016). Socially responsible firms. J. Financ. Econ.122, 585606. 10.1016/j.jfineco.2015.12.003

  • 61

    GaoL.ZhangJ. H. (2015). Firms' earnings smoothing, corporate social responsibility, and valuation. J. Corp. Financ.32, 108127. 10.1016/j.jcorpfin.2015.03.004

  • 62

    GarelA.Petit-RomecA. (2021). Investor rewards to environmental responsibility: evidence from the COVID-19 crisis. J. Corp. Financ.68, 101948. 10.1016/j.jcorpfin.2021.101948

  • 63

    Global Sustainable Investment Alliance. (2021). Global Sustainable Investment Review 2020. Available online at: http://www.gsi-alliance.org/wp-content/uploads/2021/08/GSIR-20201.pdf

  • 64

    GriffinD.GuedhamiO.LiK.LuG. (2021). National culture and the value implications of corporate environmental and social performance. J. Corp. Financ.71, 102123. 10.1016/j.jcorpfin.2021.102123

  • 65

    GuoM.LiuB.TianY.XuD. (2020). Equity to urban parks for elderly residents: perspectives of balance between supply and demand. Int. J. Environ. Res. Public Health17, 8506. 10.3390/ijerph17228506

  • 66

    GurneyG. G.PresseyR. L.BanN. C.Álvarez-RomeroJ. G.JupiterS.AdamsV. M. (2015). Efficient and equitable design of marine protected areas in Fiji through inclusion of stakeholder-specific objectives in conservation planning. Conserv. Biol.29, 13781389. 10.1111/cobi.12514

  • 67

    HalpernB. S.KleinC. J.BrownC. J.BegerM.GranthamH. S.MangubhaiS.et al. (2013). Achieving the triple bottom line in the face of inherent trade-offs among social equity, economic return, and conservation. Proc. Nat. Acad. Sci.110, 62296234. 10.1073/pnas.1217689110

  • 68

    HannahS. T.SayariN.HarrisF. H.deB.CainC. L. (2021). The direct and moderating effects of endogenous corporate social responsibility on firm valuation: theoretical and empirical evidence from the global financial crisis. J. Manage. Stud.58, 421456. 10.1111/joms.12586

  • 69

    HarrisonJ. S.BermanS. L. (2016). Corporate social performance and economic cycles. J. Bus. Ethics138, 279294. 10.1007/s10551-015-2646-9

  • 70

    HawnO.IoannouI. (2016). Mind the gap: the interplay between external and internal actions in the case of corporate social responsibility. Strategic Manage. J.37, 25692588. 10.1002/smj.2464

  • 71

    HenkeI.Carten,ìA.MolitiernoC.ErricoA. (2020). Decision-making in the transport sector: a sustainable evaluation method for road infrastructure. Sustainability12, 764. 10.3390/su12030764

  • 72

    HoangT.PrzychodzenW.PrzychodzenJ.SegbotangniE. A. (2020). Does it pay to be green? A disaggregated analysis of U.S. firms with green patents. Bus. Strategy Environ.29, 13311361. 10.1002/bse.2437

  • 73

    HoiC. K.WuQ.ZhangH. (2018). Community social capital and corporate social responsibility. J. Bus. Ethics152, 647665. 10.1007/s10551-016-3335-z

  • 74

    JenkinsK. (2018). Setting energy justice apart from the crowd: lessons from environmental and climate justice. Energy Res. Soc. Sci.39, 117121. 10.1016/j.erss.2017.11.015

  • 75

    JenkinsK.McCauleyD.HeffronR.StephanH.RehnerR. (2016). Energy justice: a conceptual review. Energy Res. Soc. Sci.11, 174182. 10.1016/j.erss.2015.10.004

  • 76

    JhaA.CoxJ. (2015). Corporate social responsibility and social capital. J. Bank. Financ.60, 252270. 10.1016/j.jbankfin.2015.08.003

  • 77

    JiaJ.LiZ. (2020). Does external uncertainty matter in corporate sustainability performance?J. Corp. Financ.65, 101743. 10.1016/j.jcorpfin.2020.101743

  • 78

    KangmennaangJ.KerrR. B.LupafyaE.DakishoniL.KatunduM.LuginaahI. (2017). Impact of a participatory agroecological development project on household wealth and food security in Malawi. Food Secur.9, 561576. 10.1007/s12571-017-0669-z

  • 79

    KarakocD. B.BarkerK.ZobelC. W.AlmoghathawiY. (2020). Social vulnerability and equity perspectives on interdependent infrastructure network component importance. Sustain. Cities Soc.57, 102072. 10.1016/j.scs.2020.102072

  • 80

    KimY.LiH.LiS. (2014). Corporate social responsibility and stock price crash risk. J. Bank. Financ.43, 113. 10.1016/j.jbankfin.2014.02.013

  • 81

    KongY.Antwi-AdjeiA.BawuahJ. (2020). A systematic review of the business case for corporate social responsibility and firm performance. Corp. Soc. Respon. Environ. Manage.27, 444454. 10.1002/csr.1838

  • 82

    KumarK.BoessoG.MichelonG. (2016). How do strengths and weaknesses in corporate social performance across different stakeholder domains affect company performance?Bus. Strategy Environ.25, 277292. 10.1002/bse.1874

  • 83

    KuzeyC.UyarA.NizaevaM.KaramanA. S. (2021). CSR performance and firm performance in the tourism, healthcare, and financial sectors: do metrics and CSR committees matter?J. Clean. Prod.319, 128802. 10.1016/j.jclepro.2021.128802

  • 84

    LarimianT.SadeghiA. (2021). Measuring urban social sustainability: scale development and validation. Environ. Plan. B Urban Anal. City Sci.48, 621637. 10.1177/2399808319882950

  • 85

    LiangH.RenneboogL.VansteenkisteC. (2020). Cross-border acquisitions and employment policies. J. Corp. Financ.62, 101575. 10.1016/j.jcorpfin.2020.101575

  • 86

    LinsK. V.ServaesH.TamayoA.BegleyT.ClubbC.CoccoJ.CooperM.et al. (2017). Social capital, trust, and firm performance: the value of corporate social responsibility during the financial crisis. J. Financ.72, 17851824. 10.1111/jofi.12505

  • 87

    LiuY.LeiL.ButtnerE. H. (2020). Establishing the boundary conditions for female board directors' influence on firm performance through CSR. J. Bus. Res.121, 112120. 10.1016/j.jbusres.2020.08.026

  • 88

    LuH.OhW.-Y.KleffnerA.ChangY. K. (2021). How do investors value corporate social responsibility? Market valuation and the firm specific contexts. J. Bus. Res.125, 1425. 10.1016/j.jbusres.2020.11.063

  • 89

    LuegK.KrastevB.LuegR. (2019). Bidirectional effects between organizational sustainability disclosure and risk. J. Clean. Prod.229, 268277. 10.1016/j.jclepro.2019.04.379

  • 90

    LuffarelliJ.MarkouP.StamatogiannakisA.GonçalvesD. (2019). The effect of corporate social performance on the financial performance of business-to-business and business-to-consumer firms. Corp. Soc. Respons. Environ. Manage. 26, 13331350. 10.1002/csr.1750

  • 91

    LysT.NaughtonJ. P.WangC. (2015). Signaling through corporate accountability reporting. J. Account. Econ.60, 5672. 10.1016/j.jacceco.2015.03.001

  • 92

    MarlinA.MarlinJ. T. (2003). A brief history of social reporting. Business Respect. Available online at: http://www.cityeconomist.com/images/A_brief_history_of_social_reporting-2003.doc

  • 93

    McCauleyD.HeffronR. (2018). Just transition: Integrating climate, energy and environmental justice. Energy Policy119, 17. 10.1016/j.enpol.2018.04.014

  • 94

    Moura-LeiteR. C.PadgettR. C.GalánJ. I. (2014). Stakeholder management and nonparticipation in controversial business. Bus. Soc.53, 4570. 10.1177/0007650310395547

  • 95

    NaseemT.ShahzadF.AsimG. A.RehmanI. U.NawazF. (2020). Corporate social responsibility engagement and firm performance in Asia Pacific: the role of enterprise risk management. Corp. Soc. Respons. Environ. Manage.27, 501513. 10.1002/csr.1815

  • 96

    NgA. C.RezaeeZ. (2015). Business sustainability performance and cost of equity capital. J. Corp. Financ.34, 128149. 10.1016/j.jcorpfin.2015.08.003

  • 97

    NguyenP.NguyenA. (2015). The effect of corporate social responsibility on firm risk. Soc. Respons. J.11, 324339. 10.1108/SRJ-08-2013-0093

  • 98

    NguyenP.-A.KecskésA.MansiS. (2020). Does corporate social responsibility create shareholder value? The importance of long-term investors. J. Bank. Financ.112, 105217. 10.1016/j.jbankfin.2017.09.013

  • 99

    OhH.BaeJ.KimS.-J. (2017). Can sinful firms benefit from advertising their CSR efforts? Adverse effect of advertising sinful firms' CSR engagements on firm performance. J. Bus. Ethics143, 643663. 10.1007/s10551-016-3072-3

  • 100

    Oswald BeilerM.MohammedM. (2016). Exploring transportation equity: development and application of a transportation justice framework. Transport. Res. Part D Transport Environ.47, 285298. 10.1016/j.trd.2016.06.007

  • 101

    PettitJ. (2004). Climate justice: a new social movement for atmospheric rights. IDS Bull.35, 102106. 10.1111/j.1759-5436.2004.tb00142.x

  • 102

    RuizM.Segui-PonsJ. M.Mateu-LLad,óJ. (2017). Improving bus service levels and social equity through bus frequency modelling. J. Transport Geogr.58, 220233. 10.1016/j.jtrangeo.2016.12.005

  • 103

    SaleemI.KhanM. N. A.HasanR.AshfaqM. (2021). Corporate board for innovative managerial control: implications of corporate governance deviance perspective. Corp. Governance Int. J. Bus. Soc.21, 450462. 10.1108/CG-04-2020-0151

  • 104

    ScaletS.KellyT. F. (2010). CSR rating agencies: what is their global impact?J. Bus. Ethics94, 6988. 10.1007/s10551-009-0250-6

  • 105

    ShahzadA. M.SharfmanM. P. (2017). Corporate social performance and financial performance: sample-selection issues. Bus. Soc.56, 889918. 10.1177/0007650315590399

  • 106

    ShakerR. R.SirodoevI. G. (2016). Assessing sustainable development across Moldova using household and property composition indicators. Habitat Int.55, 192204. 10.1016/j.habitatint.2016.03.005

  • 107

    ShigetomiY.ChapmanA.NansaiK.MatsumotoK.TohnoS. (2020). Quantifying lifestyle based social equity implications for national sustainable development policy. Environ. Res. Lett.15, 084044. 10.1088/1748-9326/ab9142

  • 108

    ShiuY. M.YangS. L. (2017). Does engagement in corporate social responsibility provide strategic insurance-like effects?Strategic Manage. J.38, 455470. 10.1002/smj.2494

  • 109

    SiewR. Y. J. (2015). A review of corporate sustainability reporting tools (SRTs). J. Environ. Manage.164, 180195. 10.1016/j.jenvman.2015.09.010

  • 110

    SilvaJ. F. B. A.RebouçasS. M. D. P.AbreuM. C. S.de RibeiroM.daC. R. (2018). Construção de um índice de desenvolvimento sustentável e análise espacial das desigualdades nos municípios cearenses. Revista de Administração Pública52, 149168. 10.1590/0034-7612163114

  • 111

    SuS.LiuZ.XuY.LiJ.PiJ.WengM. (2017). China's megaregion policy: performance evaluation framework, empirical findings and implications for spatial polycentric governance. Land Use Policy63, 119. 10.1016/j.landusepol.2017.01.014

  • 112

    TaylorJ.VithayathilJ.YimD. (2018). Are corporate social responsibility (CSR) initiatives such as sustainable development and environmental policies value enhancing or window dressing?Corp. Soc. Respons. Environ. Manage.25, 971980. 10.1002/csr.1513

  • 113

    TebiniH.M'ZaliB.LangP.Perez-GladishB. (2016). The economic impact of environmentally responsible practices. Corp. Soc. Respons. Environ. Manage.23, 333344. 10.1002/csr.1383

  • 114

    TongL.WangH.XiaJ. (2020). Stakeholder preservation or appropriation? The influence of target CSR on market reactions to acquisition announcements. Acad. Manage. J.63, 15351560. 10.5465/amj.2018.0229

  • 115

    TsangA.WangK. T.LiuS.YuL. (2021). Integrating corporate social responsibility criteria into executive compensation and firm innovation: international evidence. J. Corp. Financ.70, 102070. 10.1016/j.jcorpfin.2021.102070

  • 116

    TschoppD.HuefnerR. J. (2015). Comparing the evolution of CSR reporting to that of financial reporting. J. Bus. Ethics127, 565577. 10.1007/s10551-014-2054-6

  • 117

    ValizadehN.HayatiD. (2021). Development and validation of an index to measure agricultural sustainability. J. Clean. Prod.280, 123797. 10.1016/j.jclepro.2020.123797

  • 118

    VombergA.HomburgC.BornemannT. (2015). Talented people and strong brands: the contribution of human capital and brand equity to firm value. Strategic Manage. J.36, 21222131. 10.1002/smj.2328

  • 119

    WangZ.SarkisJ. (2017). Corporate social responsibility governance, outcomes, and financial performance. J. Clean. Prod.162, 16071616. 10.1016/j.jclepro.2017.06.142

  • 120

    WidyawatiL. (2020). A systematic literature review of socially responsible investment and environmental social governance metrics. Bus. Strategy Environ.29, 619637. 10.1002/bse.2393

  • 121

    XieJ.NozawaW.YagiM.FujiiH.ManagiS. (2019). Do environmental, social, and governance activities improve corporate financial performance?Bus. Strategy Environ.28, 286300. 10.1002/bse.2224

  • 122

    YuE. P.GuoC. Q.LuuB.Van. (2018). Environmental, social and governance transparency and firm value. Bus. Strategy Environ.27, 9871004. 10.1002/bse.2047

  • 123

    YuanY.XuJ.WangZ. (2017). Spatial equity measure on urban ecological space layout based on accessibility of socially vulnerable groups—A case study of changting, China. Sustainability9, 1552. 10.3390/su9091552

  • 124

    ZolotoyL.O'SullivanD.ChenY. (2019). Local religious norms, corporate social responsibility, and firm value. J. Bank. Financ.100, 218233. 10.1016/j.jbankfin.2019.01.015

Summary

Keywords

ESG metrics, social equity, systematic review, sustainability index, sustainable investment

Citation

Keeley AR, Chapman AJ, Yoshida K, Xie J, Imbulana J, Takeda S and Managi S (2022) ESG metrics and social equity: Investigating commensurability. Front. Sustain. 3:920955. doi: 10.3389/frsus.2022.920955

Received

15 April 2022

Accepted

30 August 2022

Published

21 September 2022

Volume

3 - 2022

Edited by

Dingsheng Li, University of Nevada, Reno, United States

Reviewed by

Elena Escrig Olmedo, University of Jaume I, Spain; Mark Anthony Camilleri, University of Malta, Malta

Updates

Copyright

*Correspondence: Alexander R. Keeley

This article was submitted to Quantitative Sustainability Assessment, a section of the journal Frontiers in Sustainability

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Outline

Figures

Cite article

Copy to clipboard


Export citation file


Share article

Article metrics