A Study of the Green Jobs Effect of Corporate ESG Performance: Evidence from China

Abstract

Achieving comprehensive green transformation and deep decarbonization of socio-economic systems constitutes a pivotal pathway toward high-quality development. Green employment, as the core link between ecological governance and economic growth, requires further exploration of its development mechanisms. Drawing upon Huazheng ESG rating data, this study employs a sample of Chinese A-share listed green enterprises spanning 2013–2023 to empirically scrutinize how corporate ESG performance shapes green employment scales and the intricate transmission channels involved. The findings indicate that corporate ESG performance significantly promotesgreen employment growth, a conclusion that remains valid after robustness and endogeneity tests, including replacing explanatory variables, adding control variables, lagging core explanatory variables, and using instrumental variable methods. Mechanism tests indicate that ESG performance primarily influences green employment through three pathways: production-scale expansion effects, increased R&D investment, and enhanced green innovation capabilities. Heterogeneity analysis shows that these promotional effects are more pronounced in state-owned enterprises, technology-intensive enterprises, and high-tech enterprises. This study specifically focuses on the green employment sector, delves into multiple mechanism pathways, and conducts heterogeneity analysis based on China’s institutional context—including property rights nature, factor intensity, and technological level—to provide a more detailed microlevel perspective andempirical support for understanding ESG’s employment effects and formulating targeted policies. The research conclusions offer theoretical and empirical support for enterprises to promote green employment and achieve synergies between economic and social sustainability through ESG practices.

Received: 9 March 2025 | Revised: 10 November 2025 | Accepted: 17 December 2025

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data available on request from the corresponding author upon reasonable request.

Author Contribution Statement

Chunyi Han: Formal analysis, Investigation, Data curation, Writing - original draft, Visualization, Investigation. Pengfei Zhou: Conceptualization, Methodology, Resources, Writing - review & editing, Supervision, Project administration, Funding acquisition. Yang Shen: Software, Validation.