中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
How nonfarm employment drives the households' energy transition: Evidence from rural China

文献类型:期刊论文

作者Ma, Shaoyue1,4,5; Man, Hecheng2,5; Li, Xiao3; Xu, Xiangbo1,4; Sun, Mingxing1,4,6; Xie, Minghui4; Zhang, Linxiu1,4
刊名ENERGY
出版日期2023-03-15
卷号267页码:14
ISSN号0360-5442
关键词Energy consumption Nonfarm employment Impact mechanism Rural China
DOI10.1016/j.energy.2022.126486
通讯作者Sun, Mingxing(sunmx@igsnrr.ac.cn)
英文摘要Amid the rapid increase of energy consumption, the air pollution and related health problems caused by traditional energy consumption have become increasingly severe in rural areas, and it is now urgent to expand clean energy consumption and achieve energy upgrades. Nonfarm employment can significantly raise rural residents' incomes, which can then affect the available energy consumption choices. However, whether nonfarm employment can promote the transition of energy consumption and its potential influencing mechanisms must be further studied. Based on 2018 survey data on energy consumption in rural China, a cross-sectional regression method with instrumental variables is used to explore the effect of nonfarm employment on energy consumption. The results demonstrate that nonfarm employment has a significantly positive impact on energy efficiency and effective energy consumption per capita, but no significant impact is found on total energy consumption per capita. Specifically, nonfarm employment increases electricity, natural gas, and liquefied petroleum gas con-sumption, and reduces coal and biomass energy consumption. Nonfarm employment can affect household energy consumption in rural areas through income, demonstration, and labor effects. Income effect indicates that when nonfarm income increases by 1%, energy efficiency significantly increases by 0.108%, and effective energy consumption per capita significantly increases by 0.074%. Demonstration effect indicates that nonfarm employment outside the county significantly improves energy efficiency. Labor effect indicating that the threshold values of nonfarm employment time on energy efficiency and effective energy consumption are 10.278 standard working months and 11.367 standard working months. The research shows that nonfarm employment plays an important role in the clean and efficient transformation of energy in rural areas.
WOS关键词OFF-FARM EMPLOYMENT ; EMPIRICAL-EVIDENCE ; ECONOMIC-GROWTH ; CONSUMPTION ; COOKING ; CHOICE ; PANEL ; DETERMINANTS ; EMISSIONS ; PROVINCE
资助项目National Natural Science Foundation of China[52000170] ; National Natural Science Foundation of China[72061147003] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA20010303]
WOS研究方向Thermodynamics ; Energy & Fuels
语种英语
出版者PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号WOS:000921189300001
资助机构National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences
源URL[http://ir.igsnrr.ac.cn/handle/311030/189515]  
专题中国科学院地理科学与资源研究所
通讯作者Sun, Mingxing
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
2.Chinese Res Inst Environm Sci, Beijing 100012, Peoples R China
3.Xi An Jiao Tong Univ, Sch Publ Policy & Adm, 28 Xianning West Rd, Xian 710049, Shaanxi, Peoples R China
4.UN Environm Programme Int Ecosyst Management Partn, Beijing 100101, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714
Ma, Shaoyue,Man, Hecheng,Li, Xiao,et al. How nonfarm employment drives the households' energy transition: Evidence from rural China[J]. ENERGY,2023,267:14.
APA Ma, Shaoyue.,Man, Hecheng.,Li, Xiao.,Xu, Xiangbo.,Sun, Mingxing.,...&Zhang, Linxiu.(2023).How nonfarm employment drives the households' energy transition: Evidence from rural China.ENERGY,267,14.
MLA Ma, Shaoyue,et al."How nonfarm employment drives the households' energy transition: Evidence from rural China".ENERGY 267(2023):14.

入库方式: OAI收割

来源:地理科学与资源研究所

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