A Study on the Statistical Measurement and Determinants of China’s Energy Transition from a Justice Perspective

Currently, research on measuring energy transition fairness at the provincial level is still insufficient. Therefore, in this paper, based on the dual carbon goals, we used panel data from 31 Chinese provinces from 2010 to 2023 to build a comprehensive evaluation system that combines transition outcomes with energy fairness. We applied the entropy method, DEA model, and TOPSIS model to calculate the energy transition fairness level of each province, and then used a two-way fixed effects panel model to identify the driving mechanisms. The results show that the national level of energy transition fairness has steadily improved, but there are significant regional differences: first, the western region has the best overall transition foundation, while the eastern region leads in transition efficiency; second, economic development has a stage-specific negative impact on transition fairness, while per capita fiscal capacity is a crucial positive driving factor; third, the impact of various factors differs across regions. Based on the findings of this study, it’s recommended to adopt targeted policies, such as region-specific support, optimizing green financial investments, and setting up a dynamic provincial monitoring system, so that energy use can be both efficient and fair during the transition.

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Publication Details

Journal
Ecological Economics and Management
Published
2026-06-26
DOI
https://doi.org/10.53941/eem.2026.100009
Primary Topic
Energy, Environment, Economic Growth
Type
article
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A Study on the Statistical Measurement and Determinants of China’s Energy Transition from a Justice Perspective

Shuyu Xue
Ecological Economics and Management
Energy, Environment, Economic Growth
article

A Study on the Statistical Measurement and Determinants of China’s Energy Transition from a Justice Perspective

Shuyu Xue
article en

Abstract

Currently, research on measuring energy transition fairness at the provincial level is still insufficient. Therefore, in this paper, based on the dual carbon goals, we used panel data from 31 Chinese provinces from 2010 to 2023 to build a comprehensive evaluation system that combines transition outcomes with energy fairness. We applied the entropy method, DEA model, and TOPSIS model to calculate the energy transition fairness level of each province, and then used a two-way fixed effects panel model to identify the driving mechanisms. The results show that the national level of energy transition fairness has steadily improved, but there are significant regional differences: first, the western region has the best overall transition foundation, while the eastern region leads in transition efficiency; second, economic development has a stage-specific negative impact on transition fairness, while per capita fiscal capacity is a crucial positive driving factor; third, the impact of various factors differs across regions. Based on the findings of this study, it’s recommended to adopt targeted policies, such as region-specific support, optimizing green financial investments, and setting up a dynamic provincial monitoring system, so that energy use can be both efficient and fair during the transition.

Ecological Economics and ManagementVol. 2(2)
Affordable and clean energy
Openalex Percentile: Top 3%
Energy, Environment, Economic Growth
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