IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v242y2022ics0360544221031959.html
   My bibliography  Save this article

Policy implications of China's rural household coal governance from the perspective of the spillover effect

Author

Listed:
  • Han, Jiashi
  • Hou, Xiaochao
  • Zhang, Lei

Abstract

China's Rural Civilian Bulk Coal (RCBC) governance is proceeding in an orderly manner, but it is encountering some difficulties, such as the establishment of an energy guarantee mechanism, the selection of a promotion pilot, and economic cost control. This study uses the Multi-Model Comparison and Regression Optimisation of Spatio-Temporal Analysis (MMC&ROSTA) technology of RCBC consumption to analyse the provincial panel data, and it examines the time effect and spatial spillover effect on RCBC consumption to solve the governance problems. The results show that (1) RCBC has an “inverted U-shaped” income effect, and urbanisation and coal resource endowments have negative and positive effects on RCBC, respectively; (2) RCBC consumption has an inter-provincial demonstration effect, and the economic development linkage, population movement, and resource market competition will all bring about the spatial spillover of RCBC consumption; and (3) residents' energy use habits (REUH) will increase RCBC consumption and delay the change of RCBC consumption with increasing income. In summary, the governance of RCBC should adhere to the principles of inter-provincial coordination, use inner-provincial conditions as a basis to both determine governance guidelines and establish a subsidy mechanism and use resource competition to guide changes in REUH while coordinating with urbanisation.

Suggested Citation

  • Han, Jiashi & Hou, Xiaochao & Zhang, Lei, 2022. "Policy implications of China's rural household coal governance from the perspective of the spillover effect," Energy, Elsevier, vol. 242(C).
    • Handle: RePEc:eee:energy:v:242:y:2022:i:c:s0360544221031959
    DOI: 10.1016/j.energy.2021.122946
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221031959
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.122946?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zou, Baoling & Mishra, Ashok K., 2020. "Appliance usage and choice of energy-efficient appliances: Evidence from rural Chinese households," Energy Policy, Elsevier, vol. 146(C).
    2. Zeng, Yangmei & Zhang, Junbiao & He, Ke, 2019. "Effects of conformity tendencies on households’ willingness to adopt energy utilization of crop straw: Evidence from biogas in rural China," Renewable Energy, Elsevier, vol. 138(C), pages 573-584.
    3. Chen, Qiu & Yang, Haoran & Liu, Tianbiao & Zhang, Lin, 2016. "Household biomass energy choice and its policy implications on improving rural livelihoods in Sichuan, China," Energy Policy, Elsevier, vol. 93(C), pages 291-302.
    4. Li, Jianglong & Chen, Chang & Liu, Hongxun, 2019. "Transition from non-commercial to commercial energy in rural China: Insights from the accessibility and affordability," Energy Policy, Elsevier, vol. 127(C), pages 392-403.
    5. Niu, Shuwen & Li, Zhen & Qiu, Xin & Dai, Runqi & Wang, Xiang & Qiang, Wenli & Hong, Zhenguo, 2019. "Measurement of effective energy consumption in China's rural household sector and policy implication," Energy Policy, Elsevier, vol. 128(C), pages 553-564.
    6. Karasu, Seçkin & Altan, Aytaç & Bekiros, Stelios & Ahmad, Wasim, 2020. "A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series," Energy, Elsevier, vol. 212(C).
    7. Song, Conghe & Bilsborrow, Richard & Jagger, Pamela & Zhang, Qi & Chen, Xiaodong & Huang, Qingfeng, 2018. "Rural Household Energy Use and Its Determinants in China: How Important Are Influences of Payment for Ecosystem Services vs. Other Factors?," Ecological Economics, Elsevier, vol. 145(C), pages 148-159.
    8. Niu, Hewen & He, Yuanqing & Desideri, Umberto & Zhang, Peidong & Qin, Hongyi & Wang, Shijin, 2014. "Rural household energy consumption and its implications for eco-environments in NW China: A case study," Renewable Energy, Elsevier, vol. 65(C), pages 137-145.
    9. He, Guizhen & Bluemling, Bettina & Mol, Arthur P.J. & Zhang, Lei & Lu, Yonglong, 2013. "Comparing centralized and decentralized bio-energy systems in rural China," Energy Policy, Elsevier, vol. 63(C), pages 34-43.
    10. He, Ke & Zhang, Junbiao & Wang, Anbang & Chang, Huayi, 2020. "Rural households’ perceived value of energy utilization of crop residues: A case study from China," Renewable Energy, Elsevier, vol. 155(C), pages 286-295.
    11. Zhang, Shuangqi & Deng, Mengsi & Shan, Ming & Zhou, Chuang & Liu, Wei & Xu, Xiaoqiu & Yang, Xudong, 2019. "Energy and environmental impact assessment of straw return and substitution of straw briquettes for heating coal in rural China," Energy Policy, Elsevier, vol. 128(C), pages 654-664.
    12. Xin Tang & Hua Liao, 2014. "Energy poverty and solid fuels use in rural China: Analysis based on national population census," CEEP-BIT Working Papers 57, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    13. Liu, Zhong & Wang, Menghan & Xiong, Qinqin & Liu, Chang, 2020. "Does centralized residence promote the use of cleaner cooking fuels? Evidence from rural China," Energy Economics, Elsevier, vol. 91(C).
    14. Peng, Liqun & Zhang, Qiang & Yao, Zhiliang & Mauzerall, Denise L. & Kang, Sicong & Du, Zhenyu & Zheng, Yixuan & Xue, Tao & He, Kebin, 2019. "Underreported coal in statistics: A survey-based solid fuel consumption and emission inventory for the rural residential sector in China," Applied Energy, Elsevier, vol. 235(C), pages 1169-1182.
    15. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    16. Chen, Guangwu & Zhu, Yuhan & Wiedmann, Thomas & Yao, Lina & Xu, Lixiao & Wang, Yafei, 2019. "Urban-rural disparities of household energy requirements and influence factors in China: Classification tree models," Applied Energy, Elsevier, vol. 250(C), pages 1321-1335.
    17. Ma, Wanglin & Zhou, Xiaoshi & Renwick, Alan, 2019. "Impact of off-farm income on household energy expenditures in China: Implications for rural energy transition," Energy Policy, Elsevier, vol. 127(C), pages 248-258.
    18. Liang, Long & Wu, Wenliang & Lal, Rattan & Guo, Yanbin, 2013. "Structural change and carbon emission of rural household energy consumption in Huantai, northern China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 767-776.
    19. He, Ke & Zhang, Junbiao & Zeng, Yangmei, 2018. "Rural households' willingness to accept compensation for energy utilization of crop straw in China," Energy, Elsevier, vol. 165(PA), pages 562-571.
    20. Ma, Ben & Yu, Yihua & Urban, Frauke, 2018. "Green transition of energy systems in rural China: National survey evidence of households’ discrete choices on water heaters," Energy Policy, Elsevier, vol. 113(C), pages 559-570.
    21. Qiu, Huanguang & Yan, Jianbiao & Lei, Zhen & Sun, Dingqiang, 2018. "Rising wages and energy consumption transition in rural China," Energy Policy, Elsevier, vol. 119(C), pages 545-553.
    22. Zou, Baoling & Luo, Biliang, 2019. "Rural household energy consumption characteristics and determinants in China," Energy, Elsevier, vol. 182(C), pages 814-823.
    23. Han, Hongyun & Wu, Shu & Zhang, Zhijian, 2018. "Factors underlying rural household energy transition: A case study of China," Energy Policy, Elsevier, vol. 114(C), pages 234-244.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Han, Jiashi & Zhang, Lei & Li, Yang, 2022. "Spatiotemporal analysis of rural energy transition and upgrading in developing countries: The case of China," Applied Energy, Elsevier, vol. 307(C).
    2. Wang, Shubin & Sun, Shaolong & Zhao, Erlong & Wang, Shouyang, 2021. "Urban and rural differences with regional assessment of household energy consumption in China," Energy, Elsevier, vol. 232(C).
    3. Li, Meng & Jin, Tianyu & Liu, Shenglong & Zhou, Shaojie, 2021. "The cost of clean energy transition in rural China: Evidence based on marginal treatment effects," Energy Economics, Elsevier, vol. 97(C).
    4. Wang, Menghan & Liu, Zhong & Xu, Aiyan & Yang, Dan, 2022. "Fuel choice for rural Tibetan households: Impacts of access to credit," Energy Economics, Elsevier, vol. 115(C).
    5. Wang, Anbang & He, Ke & Zhang, Junbiao & Zeng, Yangmei, 2021. "Green Production Technologies and Technical Efficiency of Rice Farmers in China: A Case Study of Straw-Derived Biochar," 2021 Conference, August 17-31, 2021, Virtual 315026, International Association of Agricultural Economists.
    6. Ma, Wanglin & Zheng, Hongyun & Gong, Binlei, 2021. "Household Energy Choice for Cooking: Do Rural Income Growth and Ethnic Difference Play a Role?," 2021 Conference, August 17-31, 2021, Virtual 314990, International Association of Agricultural Economists.
    7. Qiang Wang & Thomas Dogot & Guosheng Wu & Xianlei Huang & Changbin Yin, 2019. "Residents’ Willingness for Centralized Biogas Production in Hebei and Shandong Provinces," Sustainability, MDPI, vol. 11(24), pages 1-16, December.
    8. Chen, Feifei & Qiu, Huanguang & Zhang, Jun, 2022. "Energy consumption and income of the poor in rural China: Inference for poverty measures," Energy Policy, Elsevier, vol. 163(C).
    9. Liu, Zhong & Wang, Menghan & Xiong, Qinqin & Liu, Chang, 2020. "Does centralized residence promote the use of cleaner cooking fuels? Evidence from rural China," Energy Economics, Elsevier, vol. 91(C).
    10. Sun, Mingxing & Xu, Xiangbo & Wang, Le & Li, Chang & Zhang, Linxiu, 2021. "Stable energy, energy inequality, and climate change vulnerability in Pan-Third Pole regions: Empirical analysis in cross-national rural areas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    11. Wu, Shu & Han, Hongyun, 2022. "Energy transition, intensity growth, and policy evolution: Evidence from rural China," Energy Economics, Elsevier, vol. 105(C).
    12. Yang, Aoxi & Wang, Yahui, 2023. "Transition of household cooking energy in China since the 1980s," Energy, Elsevier, vol. 270(C).
    13. Shuxin Mao & Sha Qiu & Tao Li & Mingfang Tang & Hongbing Deng & Hua Zheng, 2020. "Using Characteristic Energy to Study Rural Ethnic Minorities’ Household Energy Consumption and Its Impact Factors in Chongqing, China," Sustainability, MDPI, vol. 12(17), pages 1-14, August.
    14. Niu, Shuwen & Li, Zhen & Qiu, Xin & Dai, Runqi & Wang, Xiang & Qiang, Wenli & Hong, Zhenguo, 2019. "Measurement of effective energy consumption in China's rural household sector and policy implication," Energy Policy, Elsevier, vol. 128(C), pages 553-564.
    15. Huaquan Zhang & Yashuang Tang & Martinson Ankrah Twumasi & Abbas Ali Chandio & Lili Guo & Ruixin Wan & Shilei Pan & Yun Shen & Ghulam Raza Sargani, 2022. "The Effects of Ecological Public Welfare Jobs on the Usage of Clean Energy by Farmers: Evidence from Tibet Areas—China," Agriculture, MDPI, vol. 12(7), pages 1-16, June.
    16. Addai, Bismark & Tang, Wenjin & Twumasi, Martinson Ankrah & Asante, Dennis & Agyeman, Annette Serwaa, 2022. "Access to financial services and lighting energy consumption: Empirical evidence from rural Ghana," Energy, Elsevier, vol. 253(C).
    17. Ma, Wanglin & Zheng, Hongyun & Gong, Binlei, 2022. "Rural income growth, ethnic differences, and household cooking fuel choice: Evidence from China," Energy Economics, Elsevier, vol. 107(C).
    18. Wang, Yi-Jia & Wang, Qi & Wang, Naihui, 2023. "The role of rationality and altruism in rural households' acceptance of straw energy utilization: Evidence from Northeast China," Energy Policy, Elsevier, vol. 177(C).
    19. He, Jia & Qing, Chen & Guo, Shili & Zhou, Wenfeng & Deng, Xin & Xu, Dingde, 2022. "Promoting rural households' energy use for cooking: Using Internet," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    20. Ma, Shaoyue & Man, Hecheng & Li, Xiao & Xu, Xiangbo & Sun, Mingxing & Xie, Minghui & Zhang, Linxiu, 2023. "How nonfarm employment drives the households’ energy transition: Evidence from rural China," Energy, Elsevier, vol. 267(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:242:y:2022:i:c:s0360544221031959. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.