35%是董事会性别多样性改善碳排放的最优比例
Board gender diversity and emissions performance: Insights from panel regressions, machine learning, and explainable AI
- 用面板回归与可解释AI发现性别多样性和碳排放呈非线性关系
- 性别比例达35%时碳排放表现最佳，22%为有效门槛
- 对政策制定者和企业治理有实证参考价值
在欧盟推行董事会性别配额的背景下，本文研究2016至2022年间欧洲企业董事会性别多样性（BGD）与碳排放表现（EP）的关系。通过面板回归、机器学习与可解释AI分析，发现二者呈非线性关系：当性别比例达到约35%时，碳排放表现最佳；低于22%则无明显改善。进一步分析显示，环境创新虽有助于减排，但并非性别多样性提升推动减排的中介路径。同时，环境、社会与治理（ESG）争议不影响该关系，表明其源于实质性治理机制而非象征性行为。研究结果对学术界、企业及监管机构具有重要启示。
原文摘要 · Abstract (English)
With European Union initiatives mandating gender quotas on corporate boards, a key question arises: Is greater board gender diversity (BGD) associated with better emissions performance (EP)? To answer this question, we examine the influence of BGD on EP across a sample of European firms from 2016 to 2022. Using panel regressions, advanced machine learning algorithms, and explainable AI, we reveal a non-linear relationship. Specifically, EP improves with BGD up to an optimal level of approximately 35 %, beyond which further increases in BGD yield no additional improvement in EP. A minimum BGD threshold of 22 % is necessary for meaningful improvements in EP. To assess the legitimacy of EP outcomes, this study examines whether ESG controversies weaken the BGD-EP relationship. The results show no significant effect, suggesting that BGD's impact is driven by governance mechanisms rather than symbolic actions. Additionally, path analysis indicates that while environmental innovation contributes to EP, it is not the mediating channel through which BGD promotes EP. The results have implications for academics, businesses, and regulators.
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