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To gain a deeper understanding of the intrinsic dynamic relationship between energy consumption and economic growth in China. This study employs panel cointegration and causality models, utilizing the SYS-GMM technique to assess the factors influencing economic growth in China's green finance sector from 2002 to 2022. The research explores the interactions among multiple variables related to the Chinese economic context, including economic growth, carbon dioxide emissions, total natural resource rents, energy consumption, and environmental impact. While considering key factors that may cause structural disturbances in the time series analysis. The findings indicate the existence of long-term cointegration relationships among these variables, with positive correlations between economic growth and total natural resource rents, energy consumption, energy quantity, and ecological footprint. Results also show a bidirectional causal relationship between carbon dioxide emissions and energy consumption and a unidirectional correlation between energy consumption and GDP growth. Additionally, energy intensity (EI) improvements supported by green finance are linked to a significant reduction in CO2 emissions, with a coefficient of -1.933 (p < 0.05), underscoring the role of technological innovation. Further evaluations suggest that investments in renewable energy can promote economic growth, create job opportunities, and reduce greenhouse gas emissions. Energy-saving measures and green finance-supported technological innovations play crucial roles in improving energy intensity and reducing CO2 emissions. The study also underscores the importance of economic diversification to reduce dependence on natural resources and enhance economic stability. Future research should further explore the economic feasibility and environmental benefits of emerging technologies such as Carbon Capture and Storage (CCS), providing deeper insights into sustainable energy practices. [ABSTRACT FROM AUTHOR]

Economic development and environmental sustainability have recently become global priorities. This study utilizes the nonlinear autoregressive distribution lag model (NARDL) to investigate the asymmetric effects of natural resource rents on economic growth and environmental quality in China and the United States from 1970 to 2020. The findings indicate that natural resource rents exert asymmetric effects on economic growth and environmental quality in both countries; however, the impact patterns differ between the two countries. In the short term, a decrease in natural resource rents significantly increases GDP per capita in the US, while an increase in natural resource rents has no effect. Moreover, natural resource rents do not influence the ecological footprint in the US. By contrast, China's GDP per capita remains unaffected by natural resource rents, while the ecological footprint is significantly influenced by both positive and negative changes in natural resource rents, exhibiting asymmetric impacts. In the long run, an increase in natural resource rents significantly impacts both GDP per capita and the ecological footprint in the US, while a decrease only impacts the ecological footprint. By contrast, both increases and decreases in natural resource rents impact per capita GDP and the ecological footprint in China. These findings highlight the importance of tailoring country‐specific policies to facilitate sustainable economic development and enhance environmental quality. [ABSTRACT FROM AUTHOR]

This paper examines the relationship among ecological footprint (EF), electricity consumption, and GDP in China using annual data ranging from 1960 to 2019. However, factors like trade openness, urbanization, and life expectancy might increase EF as ecological distortions are mainly human-induced. This study explores the effect of these variables on the environment, which is captured by EF. Quantile Regression estimates indicate that electricity consumption and real GDP increase environmental degradation, while trade and urbanization reduce EF, allowing for a higher environmental quality. On the other hand, the spectral Granger-causality tests reveal that only urbanization and life expectancy affect environmental degradation over the whole frequency domain. In the current geopolitical scenario, relevant policy implications may be derived. [ABSTRACT FROM AUTHOR]