This study examines the relationship between renewable energy use, industrialization, governance effectiveness, population growth, and technological innovation, and sovereign environmental, social, and governance (ESG) performance, used as a proxy for sustainable development, in China over the period 1996–2023. The analysis employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to capture both short-run dynamics and long-run relationships among the variables. The findings indicate that population growth is negatively associated with ESG performance, whereas governance quality, renewable energy use, industrialization, and technological innovation are positively associated with improvements in ESG outcomes. To ensure robustness, the long-run estimates are validated using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR), and a series of diagnostic tests confirms the model’s stability and reliability. Granger causality results suggest unidirectional predictive relationships from renewable energy, industrialization, and population growth to ESG, as well as bidirectional predictive linkages between technological innovation and ESG. Overall, the findings highlight the importance of institutional quality, technological progress, and the energy transition in shaping China’s sovereign ESG performance.
Mohammad Ridwan, Jeremy Ko, Afsana Akther et al.· Discover Sustainability· 0 citations
The Gulf Cooperation Council (GCC) economies, among the world’s largest per-capita carbon emitters, face a pressing policy dilemma of environmental sustainability. The conventional mean-based studies often mask heterogeneous effects across the emissions distribution and yield inconclusive results for resource-rich, energy-intensive settings such as the GCC. This gap limits the design of targeted decarbonization strategies aligned with national visions (e.g., Saudi Vision 2030 and UAE Net Zero 2050). Hence, this study revisits the Environmental Kuznets Curve (EKC) hypothesis for the six GCC countries over 2000–2024 using annual panel data. This study applies quantile regression to capture distribution-specific impacts of economic growth, trade openness, energy use, and urban population on carbon emissions. Results are validated through Dumitrescu-Hurlin causality tests and robustness checks. Findings consistently reject the EKC: economic growth exerts a monotonic positive effect on carbon emissions with no turning point. Energy efficiency and renewable adoption mitigate emissions, while trade openness and technological diffusion also exert reducing effects. In contrast, urbanization significantly amplifies emissions, highlighting demographic pressures. The results underscore that environmental improvements in the GCC require deliberate structural shifts in energy diversification, urban planning, and trade policies rather than growth alone. These context-specific insights advance the environmental economics literature and offer actionable guidance for sustainable development in resource-dependent economies.
Mohammad Ridwan, Zulfiquar Ali Antor, Afsana Akther et al.· Discover Environment· 0 citations