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This study investigates the long-run impact of digital transformation and fintech innovation on environmental sustainability across OECD countries from 1999 to 2024. Drawing on a novel empirical framework that integrates panel fully modified ordinary least squares, the system-generalized method of moments, and machine learning estimators, the analysis captures both linear and nonlinear dynamics while addressing heterogeneity, endogeneity, and structural complexity. Environmental sustainability is measured by per capita CO2 emissions, while digital transformation and fintech innovation are proxied by secure internet servers and G06Q patent applications, respectively. The findings reveal that both digital infrastructure maturity and fintech-driven innovation significantly reduce carbon emissions, suggesting that technologically advanced digital ecosystems serve as effective instruments for climate mitigation. Robustness checks via the system-generalized method of moments confirm the stability of these relationships, while machine learning models—Random Forest and XGBoost—highlight digital variables as top predictors of emissions reduction. The convergence of results across estimation methods underscores the reliability of the digital–environmental nexus. Policy implications emphasize the need to embed sustainability metrics into digital strategies, promote green fintech regulation, and prepare labor markets for Industry 4.0 transitions. These findings position digital and fintech innovation not merely as enablers of economic growth, but as structural levers for achieving environmentally sustainable development in high-income economies.
Teng et al. (Thu,) studied this question.