Abstract
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.