ARTIFICIAL INTELLIGENCE, CLIMATE RISK, GREEN INNOVATION, AND SUSTAINABLE DEVELOPMENT: THE INTERACTIVE EFFECTS OF INSTITUTIONAL QUALITY AND GENDER DIGITAL INCLUSION IN DEVELOPING ECONOMIES A PANEL DATA ANALYSIS

Abstract

This study investigates the interactive effects of Artificial Intelligence (AI), climate risk, green innovation, institutional quality, and gender digital inclusion on sustainable development in developing economies. As countries accelerate digital transformation while confronting climate challenges, understanding how AI-driven technological progress interacts with governance quality and gender-inclusive digital access has become increasingly important. Using an unbalanced panel dataset covering 45 developing economies from 2005 to 2024, the study employs advanced panel econometric techniques including Cross-sectional Dependence (CD) tests, CIPS unit root tests, Panel ARDL, Cross-Sectionally Augmented ARDL (CS-ARDL), Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), Augmented Mean Group (AMG), Common Correlated Effects Mean Group (CCEMG), Dynamic System GMM, Method of Moments Quantile Regression (MMQR), and Panel Quantile ARDL. The findings are expected to demonstrate that AI, green innovation, and institutional quality significantly improve sustainable development, while climate risk impedes environmental and economic performance. Furthermore, institutional quality and gender digital inclusion are hypothesized to moderate the effects of AI and green innovation, enhancing resilience and accelerating green economic transformation. The study contributes to the emerging literature on digital sustainability by integrating technological innovation, institutional governance, climate resilience, and gender-inclusive digitalization within a unified empirical framework.