Asymmetric effects of renewable energy and artificial intelligence on green growth: evidence from G20 countries
This study investigates the impact of renewable energy (RE) and artificial intelligence (AI) on green growth in 18 G20 countries from 2000 to 2023, employing Cross-Sectional Pooled Mean Group ARDL (CS-PMG-ARDL) and Nonlinear ARDL (CS-PMG-NARDL) models to capture symmetric and asymmetric dynamics. The bounds test confirms cointegration (F = 28.27, p < 0.001), and the error correction term indicates stable long-run adjustment (ECT = −0.145, p < 0.001 in ARDL; ECT = −0.115, p = 0.024 in NARDL). Results reveal that renewable energy exerts a positive and significant long-run effect on green growth (0.101, p < 0.001), with asymmetric responses confirmed by Wald tests (short-run χ² = 4.102, p = 0.043; long-run χ² = 5.42, p = 0.020): positive RE shocks yield stronger benefits (0.012, p = 0.011) than the adverse effects of negative shocks, which are statistically weaker in the short run ( − 0.020, p = 0.111) and significant but smaller in the long run ( − 0.012, p = 0.015). AI shows a significant short-run impact (0.018, p < 0.001) but becomes insignificant in the long run (0.001, p = 0.806), suggesting its effects are conditional on institutional and technological contexts. Critically, GMM estimations highlight significant synergistic interaction effects: the RE×AI term is positive (0.007, p = 0.004), indicating that AI amplifies the marginal contribution of renewable energy to green growth, while the RE×CO 2 interaction is negative ( − 0.041, p < 0.001), underscoring that high emissions undermine renewable energy benefits. The models exhibit strong explanatory power (adjusted R² = 0.909 for ARDL; 0.999 for NARDL) and pass all diagnostic tests for instrument validity and absence of second-order autocorrelation. The study provides tailored policy recommendations for G20 nations, emphasizing integrated strategies that combine green AI applications, renewable energy expansion, and institutional reforms to foster resilient, low-carbon economic growth.
Authors
- Sourour Guidara
- Maha Bouattour
- Kamel Helali (ORCID: https://orcid.org/0000-0003-2855-4518)
- Olfa ZARRAD
Institutions
- University of Sfax (TN)
- Imam Mohammad ibn Saud Islamic University (SA)
Publication Details
- Journal
- Humanities and Social Sciences Communications
- Published
- 2026-07-10
- DOI
- https://doi.org/10.1057/s41599-026-08130-x
- Primary Topic
- Energy, Environment, Economic Growth
- Type
- article
- Field-Weighted Citation Impact
- 0.00