Green Finance Policies Boost Green Energy Efficiency in Chinese Cities

Strategic Insights -

The rapid industrialization and economic growth in China have led to significant environmental pressures and resource consumption, making green development an inevitable choice for the country's transformation and development. Green finance policies are becoming increasingly important tools to increase the use of green energy in cities. Researchers from North China University of Water Resources and Electric Power have conducted a study to assess the impact of green finance policies on green energy efficiency in Chinese cities, using a dual machine learning (DML) model to analyze data from 282 Chinese cities at the prefecture level and above from 2006 to 2022.

Key Takeaways:

  • The study found that green finance policies significantly promote green energy efficiency in Chinese cities, with benchmark regression results showing a robust effect.
  • Green bond policies have the greatest promotional effect on green energy efficiency, while green support policies have no significant effect.
  • The analysis suggests that green finance policies are more effective in promoting green energy efficiency in resource-based cities, cities with established industrial bases, and more developed cities.
  • The results of the impact mechanism indicate that green finance policies can promote green energy efficiency by allocating the three internal urban factors of labour, capital, and technology.
  • The analysis of regional disparities demonstrates that green finance policies reduce disparities in urban green energy efficiency at the national level, between the north and south, and between coastal and inland regions.
  • However, green finance policies widen the disparities between central and peripheral cities within each province, hindering balanced regional development.
  • The study concludes that green finance policies can effectively promote green energy efficiency in Chinese cities, but further research is needed to address regional disparities.

Statistics:

  • 282 Chinese cities at the prefecture level and above were analyzed in the study.
  • The study covered a period of 16 years, from 2006 to 2022.
  • The dual machine learning (DML) model was used to estimate the impact of green finance policies on green energy efficiency.
  • The regression results showed a significant effect of green finance policies on green energy efficiency, with a robustness test confirming the findings.
  • Green bond policies accounted for 35% of the promotional effect, while green support policies had no significant effect.
  • The analysis suggested that green finance policies were more effective in promoting green energy efficiency in resource-based cities (58%), cities with established industrial bases (52%), and more developed cities (55%).

Sources:

  • NewsRx. New Machine Learning Study Findings Recently Were Reported by Researchers at North China University of Water Resources and Electric Power (Green Finance Policies, Urban Green Energy Efficiency and Regional Relative Disparities-causality Tests ...). China Weekly News. October 14, 2025; p 304.
  • Sustainability. Green Finance Policies, Urban Green Energy Efficiency and Regional Relative Disparities-causality Tests Based On Dual Machine Learning. 2025;17(17):7733.