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<p>Addressing regional inequalities in rural energy poverty (REP) and guaranteeing equitable access to the benefits of clean energy are critical for realizing the Sustainable Development Goals. However, previous research has predominantly neglected the regional variations and uneven distribution of REP. This research fills this gap by utilizing a provincial-level dataset and applying the Dagum Gini coefficient, kernel density estimation, and spatial β-convergence techniques to examine regional disparities, dynamic evolution, and spatial convergence trends of REP in China. The results reveal a declining trend in REP nationally and regionally throughout the study period. However, notable regional disparities persist, with intra-regional differences in REP gradually widening, and inter-regional imbalance remaining the primary contributor to REP variations in China, accounting for 45.87% of the overall variance. Kernel density analysis highlights pronounced REP imbalances in Northeast China, though no evidence of polarization is observed across regions. A conditional β spatial convergence trend is observed, indicating a catch-up effect between regions characterized by low and high levels of REP. This study enriches the spatial economic framework for understanding energy poverty and offers theoretical and policy insights to promote regional energy equity and sustainable development in rural areas.</p>

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Regional disparities and spatial convergence in energy poverty: evidence from China’s rural areas

  • 期刊论文

  • 发表日期：

    2025年7月8日

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  • Fu Wang,
  • Donglan Zha,
  • Hong Geng,
  • Chaoqun Zhang

摘要

Addressing regional inequalities in rural energy poverty (REP) and guaranteeing equitable access to the benefits of clean energy are critical for realizing the Sustainable Development Goals. However, previous research has predominantly neglected the regional variations and uneven distribution of REP. This research fills this gap by utilizing a provincial-level dataset and applying the Dagum Gini coefficient, kernel density estimation, and spatial β-convergence techniques to examine regional disparities, dynamic evolution, and spatial convergence trends of REP in China. The results reveal a declining trend in REP nationally and regionally throughout the study period. However, notable regional disparities persist, with intra-regional differences in REP gradually widening, and inter-regional imbalance remaining the primary contributor to REP variations in China, accounting for 45.87% of the overall variance. Kernel density analysis highlights pronounced REP imbalances in Northeast China, though no evidence of polarization is observed across regions. A conditional β spatial convergence trend is observed, indicating a catch-up effect between regions characterized by low and high levels of REP. This study enriches the spatial economic framework for understanding energy poverty and offers theoretical and policy insights to promote regional energy equity and sustainable development in rural areas.