The Impact of ESG Factors on the Propensity for Dividends for European Firms: A Machine Learning Approach
Contributions to Finance and Accounting, Springer Nature, ss.101-117, 2025
- Yayın Türü: Kitapta Bölüm / Araştırma Kitabı
- Basım Tarihi: 2025
- Doi Numarası: 10.1007/978-3-031-83266-6_7
- Yayınevi: Springer Nature
- Sayfa Sayıları: ss.101-117
- Anahtar Kelimeler: Dividend policy, ESG factors, Feature selection, Machine learning, Regularization
- Anadolu Üniversitesi Adresli: Evet
Özet
This study examines the influence of Environmental, Social, and Governance (ESG) factors on the propensity of European firms to pay dividends, using a machine learning approach for classification. Employing data from 1886 publicly traded firms in 2023, the analysis identifies the most influential ESG sub-dimensions and assesses their role in predicting dividend payouts. The findings highlight that environmental factors, particularly emissions, resource use, and innovation, have the strongest positive impact. Gradient boosting proved to be the most effective model, balancing predictive accuracy and interpretability. Using SHAP values, the study identifies key ESG sub-dimensions and their contributions to dividend payout predictions. This research advances the understanding of ESG factors’ role in dividend policy by focusing on sub-dimensions and integrating machine learning for enhanced predictive and explanatory insights.