Dilshod Karimboev

This study examines the impact of renewable energy consumption, CO₂ emissions, and renewable electricity generation on the Sustainable Development Index in Uzbekistan over the period 1990–2023. Using an autoregressive distributed lag (ARDL) model, the study estimates the short- and long-run relationships between these variables. The Sustainable Development Index is constructed using indicators of primary school enrollment, life expectancy at birth, and female labor force participation using a min-max normalization method. The results indicate a long-run positive impact of renewable energy consumption (β = 0.0552, p < 0.05), underscoring its significant contribution to sustainable development. Conversely, renewable electricity generation has a significant negative impact in the long run (–0.0153, p < 0.01), which may be due to initial high transformation costs and short-term economic adjustments. CO₂ emissions did not have a statistically significant impact on the Sustainable Development Index. The model is robust, with no autocorrelation or heteroscedasticity issues, indicating reliable results. This study underscores the importance of strategic investments in renewable energy and offers valuable insights for policy development, thereby enhancing Uzbekistan’s sustainable development trajectory.

Type of the article: Research Article

Abstract
The study examines the nexus between environmental tax revenues, renewable energy adoption, transport research and development expenditure, and green growth across EU-27 countries from 2000 to 2024. The study addresses the critical gap in understanding how fiscal environmental instruments and technological innovation in transport sectors contribute to sustainable development outcomes. Using panel data analysis, the paper employs cross-sectionally augmented autoregressive distributed lag (CS-ARDL) and method of moments quantile regression (MMQR) models to analyze both short-run and long-run relationships while accounting for cross-sectional dependence and heterogeneity. Results reveal that environmental tax revenues positively influence green growth with a long-run elasticity of 0.358, indicating that a 1% increase in environmental taxes enhances adjusted net savings by 0.358%. Renewable energy adoption demonstrates a stronger positive effect with an elasticity of 0.531 in the long run, while transport R&D expenditure exhibits a coefficient of 0.289, suggesting significant contributions to sustainable outcomes. The MMQR analysis demonstrates heterogeneous effects across quantiles, with stronger impacts observed at higher green growth levels. Cross-sectional dependency tests confirm significant spatial spillover effects among EU member states. The findings provide empirical evidence supporting the effectiveness of coordinated environmental fiscal policies and targeted innovation investments in transport sectors.