Does it pay to deliver superior ESG performance? Evidence from US S&P 500 companies

Abstract

Purpose The purpose of this paper is to investigate the relationship between a company’s environmental, social and governance (ESG) performance and its financial performance. This paper also investigates the relationship between ESG performance and a company’s market valuation. This paper provides convincing empirical evidence that delivering superior ESG performance pays off financially. Design/methodology/approach The financial data and ESG scores of 150 publicly traded companies listed in the Standard and Poor’s 500 index for 2017–2020, comprising 5,750 observations, were collected. STATA was used to run a fixed-effect regression and a weighted least squares model to analyze the panel data. Findings The results of the empirical analysis suggest that companies with superior ESG performance perform better financially and are valued higher in the market compared to their industry peers. The ESG rating score impacts both return-on-capital-employed as a proxy for financial performance and Tobin’s Q as a proxy for the market valuation of a company. Originality/value This study contributes to the existing research on ESG performance and financial performance relationship by providing empirical evidence to resolve confusion in the existing literature caused by contradictory evidence. Taking advantage of worldwide crisis caused by the COVID-19 pandemic, this study shows that a positive relationship between ESG performance and a company’s market valuation holds even during times of unexpected crises. Further, this study contributes to business practitioners’ knowledge by showing that ESG aspects constitute highly relevant non-financial information that impact the market’s perception of a company and that investing in sustainability positively impacts a company’s bottom line.

The Influence of Environmental, Social, and Governance (ESG) Practices on US Firms’ Performance: Evidence from the Coronavirus Crisis

“…In most cases, the results suggest that firms with higher environmental, social, and governance performance have better market value measures. These results are consistent with previous research showing that better total and individual ESG practices can improve FP (Ademi & Klungseth, 2022;Ahmad et al, 2021;Al Amosh et al, 2022;Alareeni & Hamdan, 2020;Carnini Pulino et al, 2022;Habib, 2022;Han et al, 2016;Hu et al, 2018;Kalia & Aggarwal, 2022;Nguyen et al, 2022;Nurim et al, 2022;Qiu et al, 2016). Accordingly, this is an opportunity for firm leaders to concentrate on adopting and enhancing ESG practices to improve FP and achieve continuous improvement.…”

“…These results support H1a. These results are consistent with the findings of the following previous studies (Ademi & Klungseth, 2022;Ahmad et al, 2021;Al Amosh et al, 2022;Alareeni & Hamdan, 2020;Carnini Pulino et al, 2022;Habib, 2022;Kalia & Aggarwal, 2022;Nguyen et al, 2022;Nurim et al, 2022). Accordingly, this is considered an opportunity for firm decision-makers to concentrate on adopting and enhancing ESG practices to improve FP.…”

“…In addition, Ademi and Klungseth (2022) investigate the linkage between ESG performance and FP using a sample of 150 US firms from 2017 to 2020. The results show a positive influence on FP.…”

The relationship between ESG and firm value. Case study of the automotive industry

“…Also, they found a positive relationship between companies' market capitalisation and the quality of their ESG reports, and that companies' market values are positively, but not strongly affected by the ESG-indexes. Ademi and Klungseth (2022) investigated the relation between ESG performances and financial performances for 150 Standard and Poor's listed companies for the 2017-2020 period. The authors found that companies with superior ESG performance perform better (both financially and in market values) compared to their industry peers.…”

Predicting of Credit Default by SVM and Decision Tree Model Based on Credit Card Data

“…The greatest margin hyperplane that resolves the planning concerns in the learning sample serves as its decision boundary. Support vector machines offer a more efficient and effective method of learning complex nonlinear equations when compared to logistic regression and neural networks [6][7]. It is crucial to find the ideal classification hyper-plane of the two categories of samples in the original space when they are linearly separable.…”