Assessing ESG and Profitability in S&P 500 Industrial Companies: A Panel Data Approach

Georgiana Danilov ()
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Georgiana Danilov: Bucharest University of Economic Studies

A chapter in Leading Change in Disruptive Times, 2026, pp 206-220 from Springer

Abstract: Abstract This study enhances the understanding of how environmental, social, and governance factors influence corporate performance, offering insights into governance dynamics and financial sustainability. This topic remains highly relevant in contemporary academic literature. Accordingly, this study analyzes the impact of environmental, social, and governance factors on industrial firms within the Standard & Poor’s 500 index, focusing on 76 companies over the period 2000 to 2024. The research employs fixed and random-effects linear and nonlinear effects regression models, incorporating interaction terms to evaluate the effects of the health crisis. The findings reveal that total water withdrawal, renewable energy produced, and women employees have a positive impact on firm performance, while women in managerial positions, the highest remuneration package, and ethnic minority board representation exert a negative influence. Additionally, turning points suggest that beyond a certain threshold, the negative impact of women managers and executive compensation turns positive. This indicates that, initially, these factors may hinder performance, but over time, they contribute to enhanced firm outcomes. Furthermore, the pandemic crisis intensified the negative effect of ethnic minorities on boards, suggesting that firms struggled to integrate diverse leadership structures during economic uncertainty. These results highlight the complex relationship between environmental, social, and governance factors, financial performance, and external disruptions. They offer valuable guidance for policymakers and corporate leaders on fostering inclusive governance and developing strategies to enhance corporate resilience in response to economic challenges.

Keywords: ESG Factors; Regression Models; Industrial Companies (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-032-19276-9_16

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DOI: 10.1007/978-3-032-19276-9_16

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