Nuriddin Shanyazov

Type of the article: Research Article

Abstract
Mitigating the effects of climate change has emerged as a crucial global need, with carbon dioxide emissions serving as the principal driver of greenhouse gas accumulation. This paper analyzes the factors influencing CO₂ emissions in G20 countries from 2000 to 2021, emphasizing the effects of renewable energy consumption, trade openness, economic growth, and energy intensity. The study utilizes advanced dynamic panel econometric techniques, namely, the Augmented Mean Group (AMG) Estimator and the Common Correlated Effects Mean Group (CCEMG) Estimator, which address cross-sectional dependence and parameter heterogeneity among nations. The analysis indicates that the use of renewable energy noticeably decreases CO₂ emissions, with elasticity values between –0.15 and –0.16. The effect is especially significant in lower-income G20 countries and during the post-2005 era. Economic growth indicates a strong positive correlation with CO₂ emissions, characterized by elasticity values ranging from 0.83 to 0.89, whereas energy intensity also displays positive effects with coefficients between 0.69 and 0.82. Trade openness exhibits insignificant statistical effects in both models. The heterogeneity study reveals that the emission-reduction potential of renewable energy is significantly greater in emerging nations than in advanced economies, with coefficients of –0.25 and –0.08, respectively. The results highlight the essential role of renewable energy transitions and enhancements in energy efficiency for meeting climate goals, especially when aligned with specific policies for various income levels and timeframes within the G20 context.

Type of the article: Research Article

Abstract
This study aims to empirically examine the dynamic effects of geopolitical risk, economic policy uncertainty, and climate policy uncertainty on CO₂ emissions in G7 economies, utilizing annual data from 1990 to 2022. To account for cross-sectional dependence and parameter heterogeneity, the analysis employs a cross-sectional autoregressive distributed lag (CS-ARDL) model. Diagnostic tests confirm significant cross-sectional dependence and slope heterogeneity among the variables. All variables are integrated of order one, I (1), confirmed by unit root tests. In contrast, the cointegration test provides a strong indication of a stable long-run relationship among geopolitical risk, policy uncertainty measures, and CO₂ emissions. The outcomes show that a 1% rise in the geopolitical risk index leads to a statistically significant long-run rise of 0.042% in per capita CO₂ emissions. In addition, a 1% increase in economic policy uncertainty and climate policy uncertainty is associated with long-run increases of 0.028% and 0.015%, respectively. These results remain robust across alternative estimators. Overall, the evidence suggests that heightened geopolitical risk and policy-related uncertainties significantly exacerbate environmental degradation in G7 economies, highlighting the necessity for strategies that improve stability, reduce uncertainty, and encourage renewable energy adoption as part of a long-term environmental strategy.