Spatiotemporal Interaction and Socioeconomic Determinants of Rural Energy Poverty in China

Siyou Xia, Yu Yang (), Xiaoying Qian and Xin Xu
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Siyou Xia: Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Yu Yang: Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xiaoying Qian: Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xin Xu: Population Research Institute, Nanjing University of Posts and Telecommunications, Nanjing 210042, China

IJERPH, 2022, vol. 19, issue 17, 1-15

Abstract: This study investigated the energy poverty spatiotemporal interaction characteristics and socioeconomic determinants in rural China from 2000 to 2015 using exploratory time–space data analysis and a geographical detector model. We obtained the following results. (1) The overall trend of energy poverty in China’s rural areas was “rising first and then declining”, and the evolution trend of energy poverty in the three regions formed a “central–west–east” stepwise decreasing pattern. (2) There was a dynamic local spatial dependence and unstable spatial evolution process, and the spatial agglomeration of rural energy poverty in China had a relatively higher path dependence and locked spatial characteristics. (3) The provinces with negative connections were mainly concentrated in the central and western regions. Anhui and Henan, Inner Mongolia and Jilin, Jilin and Heilongjiang, Hebei and Shanxi, and Liaoning and Jilin constituted a strong synergistic growth period. (4) From a long-term perspective, the disposable income of rural residents had the greatest determinant power on rural energy poverty, followed by per capita GDP, rural labor education level, regulatory agencies, and energy investment. In addition, our findings showed that the selected driving factors all had enhanced effects on rural energy poverty in China through interaction effects.

Keywords: rural energy poverty; spatiotemporal interaction; socioeconomic determinants; collaborative poverty reduction; China (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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