فهرست نشریات علمی دسترسی آزاد ایران

This study introduces a novel methodological approach in environmental finance by developing a machine learning-enhanced green insurance indicator integrated within a System GMM framework. Leveraging data from 20 OECD countries during 2012–2022, we examine the drivers of green investment, focusing on economic capacity, financial innovation, and environmental pressures. The hybrid design combines XGBoost-based feature selection with dynamic panel econometrics, improving precision in measurement and causal inference. By constructing this new quantitative indicator, the study provides a more nuanced and accurate assessment of green insurance’s role across countries. Our findings reveal that GDP per capita is the strongest driver, green insurance contributes positively as a secondary factor, and CO₂ emissions negatively affect investment. The results highlight how financial innovation and environmental policy mechanisms interact with economic conditions to shape sustainable investment patterns. By employing this innovative hybrid modeling approach, the study offers both methodological advancement and practical insights for policymakers aiming to align economic growth with ecological sustainability. Overall, the integration of machine learning with advanced econometric techniques demonstrates strong potential for improving the understanding of complex, cross-country environmental investment dynamics.