A Study of the Green Jobs Effect of Corporate ESG Performance: Evidence from China
企業のESGパフォーマンスがグリーンジョブに与える影響に関する研究：中国からの証拠 (AI 翻訳)
Chunyi Han, Pengfei Zhou, Yangdong Shen
🤖 gxceed AI 要約
日本語
本論文は、中国A株上場企業のESGパフォーマンスとグリーン雇用の関係を実証分析。2013〜2023年のデータを用い、ESG評価が高い企業ほどグリーン雇用を促進することを発見。そのメカニズムとして、生産規模拡大、研究開発投資増加、グリーンイノベーション能力向上の3経路を特定。国有企業や技術集約型企業で効果が顕著。
English
This study empirically examines how corporate ESG performance affects green employment using a sample of Chinese A-share listed green enterprises from 2013 to 2023. Results show that better ESG performance significantly increases green jobs, primarily through production scale expansion, higher R&D investment, and enhanced green innovation. The effect is stronger in state-owned, technology-intensive, and high-tech firms.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
中国のデータではあるが、ESGが雇用創出に与える影響を示す点で日本の企業や政策担当者にも示唆的。日本でもESGと人的資本の関連が注目されており、本研究成果は比較材料として有用。ただし、中国特有の制度要因（国有企業など）に留意が必要。
In the global GX context
This paper provides rare empirical evidence linking ESG performance to green job creation, filling a gap in the global literature. While focused on China, its findings on mechanisms (scale, R&D, innovation) are broadly relevant for researchers and policymakers interested in the labor market implications of ESG. The heterogeneity analysis by ownership and technology type offers insights for comparative studies.
👥 読者別の含意
🔬研究者:ESGと労働経済の交差領域の研究者に、中国の大規模サンプルを用いた実証結果を提供。
🏢実務担当者:ESG活動が雇用拡大につながることを示し、社内でのESG投資の正当化に活用できる。
🏛政策担当者:グリーン雇用政策の設計において、ESG評価の活用可能性を示唆するエビデンス。
📄 Abstract（原文）
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.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.47852/bonviewglce62025631first seen 2026-05-05 21:50:15
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