Spatiotemporal evolution and driving factors of green energy efficiency in Jiangsu Province: a sustainable development perspective DOI Creative Commons
Xin Zhang, Yan Wang, Songyu Jiang

et al.

Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 13

Published: March 7, 2025

With the ongoing global climate change and energy structure transformation, green efficiency has become one of key indicators for achieving sustainable development. This study uses panel data from 13 prefecture-level cities in Jiangsu Province, China, 2012 to 2022 explore spatiotemporal evolution driving factors efficiency. The employs super-efficiency Slack-Based Measure (SBM) method measure each region. It Gini coefficient kernel density estimation methods analyze characteristics Furthermore, based on a fixed effects model, delves into main influencing results show that Province is generally an upward trend. coefficients both southern northern regions have increased, but gap between two gradually widened. degree government intervention level industrialization are unfavorable growth In contrast, foreign investment levels, financial development, urbanization significant positive effects. Finally, empirical findings, targeted recommendations provided promote efficiency, offering important theoretical support evidence country’s strategic goals low-carbon

Language: Английский

Spatiotemporal evolution and driving factors of green energy efficiency in Jiangsu Province: a sustainable development perspective DOI Creative Commons
Xin Zhang, Yan Wang, Songyu Jiang

et al.

Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 13

Published: March 7, 2025

With the ongoing global climate change and energy structure transformation, green efficiency has become one of key indicators for achieving sustainable development. This study uses panel data from 13 prefecture-level cities in Jiangsu Province, China, 2012 to 2022 explore spatiotemporal evolution driving factors efficiency. The employs super-efficiency Slack-Based Measure (SBM) method measure each region. It Gini coefficient kernel density estimation methods analyze characteristics Furthermore, based on a fixed effects model, delves into main influencing results show that Province is generally an upward trend. coefficients both southern northern regions have increased, but gap between two gradually widened. degree government intervention level industrialization are unfavorable growth In contrast, foreign investment levels, financial development, urbanization significant positive effects. Finally, empirical findings, targeted recommendations provided promote efficiency, offering important theoretical support evidence country’s strategic goals low-carbon

Language: Английский

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