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The Impact of New Energy Demonstration Cities in China on Inclusive Green Growth: Evidence from Causal Inference Based on Double Machine Learning

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  • Yafei He

    (School of Public Administration, Guilin University of Technology, 319 Yanshan Street, Yanshan District, Guilin 541006, China)

  • Bixuan Sun

    (School of Public Administration, Guilin University of Technology, 319 Yanshan Street, Yanshan District, Guilin 541006, China)

  • Shan Huang

    (School of Public Administration, Guilin University of Technology, 319 Yanshan Street, Yanshan District, Guilin 541006, China)

Abstract

The construction of New Energy Demonstration Cities (NEDC) represents a crucial policy initiative in advancing China’s energy transition and serves as an institutional innovation to promote inclusive green growth (IGG) at the urban level. Based on panel data for 278 prefecture-level cities in China from 2011 to 2021, this study employs a double machine learning model to identify the causal impact of the NEDC on IGG and to further explore the underlying mechanisms. The empirical results show that the policy significantly enhances IGG overall. However, the positive effects are mainly observed in non-resource-based and non-old industrial cities, while the impacts in resource-based and old industrial cities are statistically insignificant. This finding indicates that structural constraints such as the resource curse and Dutch disease remain evident in these regions. Mechanism analysis reveals that the NEDC promotes IGG primarily through technological innovation and employment creation, forming a chained mediating pathway of ‘NEDC → technological innovation → employment creation → IGG.’ This study enriches the literature on the economic effects of energy reform pilot policies and provides empirical evidence and policy insights for achieving IGG goals in both China and other countries.

Suggested Citation

  • Yafei He & Bixuan Sun & Shan Huang, 2025. "The Impact of New Energy Demonstration Cities in China on Inclusive Green Growth: Evidence from Causal Inference Based on Double Machine Learning," Sustainability, MDPI, vol. 17(24), pages 1-21, December.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:24:p:11155-:d:1816665
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