[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v350y2023ics0306261923011443.html
   My bibliography  Save this article

Impact of internal migration on household energy poverty: Empirical evidence from rural China

Author

Listed:
  • Shi, Xinjie
  • Cui, Liu
  • Huang, Zuhui
  • Zeng, Pei
  • Qiu, Tongwei
  • Fu, Linlin
  • Jiang, Qiang
Abstract
Reducing energy poverty has been recognized as an effective way to eliminate overall poverty and achieve sustainable development for individuals, which are two major global challenges. This study investigated how migration affected household energy poverty in rural China. Drawing on data from the China Family Panel Studies, we adopted the instrumental variable method to examine the causal relationship between internal migration and energy poverty and probe its mechanisms. We found that internal migration significantly reduced the likelihood of family energy poverty. Specifically, the probability of energy poverty in a family with labor migration was 13.1% lower than in a family without labor migration, and the probability of energy poverty decreased by 6.4% when each additional laborer in the family migrated. Furthermore, a heterogeneity analysis revealed that labor migration had a particularly significant impact on families in central and western regions and villages near counties. Migration also plays amore important role for low-income households with less-educatedmale heads. The mechanism analysis revealed that labor migration could reduce the probability of family energy poverty by increasing family income, which outweighed the negative effects of the increased share of elderly and children left behind by migration. These findings offer important policy insights for countries undergoing development and transformation.

Suggested Citation

  • Shi, Xinjie & Cui, Liu & Huang, Zuhui & Zeng, Pei & Qiu, Tongwei & Fu, Linlin & Jiang, Qiang, 2023. "Impact of internal migration on household energy poverty: Empirical evidence from rural China," Applied Energy, Elsevier, vol. 350(C).
    • Handle: RePEc:eee:appene:v:350:y:2023:i:c:s0306261923011443
    DOI: 10.1016/j.apenergy.2023.121780
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923011443
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.121780?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. Cheng, Zhiming & Guo, Liwen & Smyth, Russell & Tani, Massimiliano, 2022. "Childhood adversity and energy poverty," Energy Economics, Elsevier, vol. 111(C).
    2. Yang, Lin & Xu, Mao & Fan, Jingli & Liang, Xi & Zhang, Xian & Lv, Haodong & Wang, Dong, 2021. "Financing coal-fired power plant to demonstrate CCS (carbon capture and storage) through an innovative policy incentive in China," Energy Policy, Elsevier, vol. 158(C).
    3. Nong Zhu & Xubei Luo, 2010. "The impact of migration on rural poverty and inequality: a case study in China," Agricultural Economics, International Association of Agricultural Economists, vol. 41(2), pages 191-204, March.
    4. Wei Jiang, 2017. "Have Instrumental Variables Brought Us Closer to the Truth," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 6(2), pages 127-140.
    5. Wang, Xiang & Shao, Shuai & Li, Ling, 2019. "Agricultural inputs, urbanization, and urban-rural income disparity: Evidence from China," China Economic Review, Elsevier, vol. 55(C), pages 67-84.
    6. Chang, Hongqin & Dong, Xiao-yuan & MacPhail, Fiona, 2011. "Labor Migration and Time Use Patterns of the Left-behind Children and Elderly in Rural China," World Development, Elsevier, vol. 39(12), pages 2199-2210.
    7. Hara, Keishiro & Uwasu, Michinori & Kishita, Yusuke & Takeda, Hiroyuki, 2015. "Determinant factors of residential consumption and perception of energy conservation: Time-series analysis by large-scale questionnaire in Suita, Japan," Energy Policy, Elsevier, vol. 87(C), pages 240-249.
    8. Wang, Yao & Lin, Boqiang, 2022. "Can energy poverty be alleviated by targeting the low income? Constructing a multidimensional energy poverty index in China," Applied Energy, Elsevier, vol. 321(C).
    9. Fu Wang & Hong Geng & Donglan Zha & Chaoqun Zhang, 2023. "Multidimensional Energy Poverty in China: Measurement and Spatio-Temporal Disparities Characteristics," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 45-78, August.
    10. Emily Oster, 2019. "Unobservable Selection and Coefficient Stability: Theory and Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 187-204, April.
    11. Rahut, Dil Bahadur & Behera, Bhagirath & Ali, Akhter, 2016. "Household energy choice and consumption intensity: Empirical evidence from Bhutan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 993-1009.
    12. Day, Rosie & Walker, Gordon & Simcock, Neil, 2016. "Conceptualising energy use and energy poverty using a capabilities framework," Energy Policy, Elsevier, vol. 93(C), pages 255-264.
    13. Che, Xiahui & Zhu, Bangzhu & Wang, Ping, 2021. "Assessing global energy poverty: An integrated approach," Energy Policy, Elsevier, vol. 149(C).
    14. Pan, Zehan & Xu, Wei & Wang, Guixin & Li, Sen & Yang, Chuankai, 2020. "Will remittances suppress or increase household income in the migrant-sending areas? Modeling the effects of remittances in rural China," China Economic Review, Elsevier, vol. 61(C).
    15. Xinjie Shi, 2022. "Moving out but not for the better: Health consequences of interprovincial rural‐urban migration in China," Health Economics, John Wiley & Sons, Ltd., vol. 31(4), pages 555-573, April.
    16. Stefan Bouzarovski & Sergio Tirado Herrero, 2017. "Geographies of injustice: the socio-spatial determinants of energy poverty in Poland, the Czech Republic and Hungary," Post-Communist Economies, Taylor & Francis Journals, vol. 29(1), pages 27-50, January.
    17. Nie, Peng & Li, Qiaoge & Sousa-Poza, Alfonso, 2021. "Energy poverty and subjective well-being in China: New evidence from the China Family Panel Studies," Energy Economics, Elsevier, vol. 103(C).
    18. Andadari, Roos Kities & Mulder, Peter & Rietveld, Piet, 2014. "Energy poverty reduction by fuel switching. Impact evaluation of the LPG conversion program in Indonesia," Energy Policy, Elsevier, vol. 66(C), pages 436-449.
    19. Wallis, Hannah & Nachreiner, Malte & Matthies, Ellen, 2016. "Adolescents and electricity consumption; Investigating sociodemographic, economic, and behavioural influences on electricity consumption in households," Energy Policy, Elsevier, vol. 94(C), pages 224-234.
    20. Papada, Lefkothea & Kaliampakos, Dimitris, 2018. "A Stochastic Model for energy poverty analysis," Energy Policy, Elsevier, vol. 116(C), pages 153-164.
    21. Adusah-Poku, Frank & Takeuchi, Kenji, 2019. "Energy poverty in Ghana: Any progress so far?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 853-864.
    22. Démurger, Sylvie & Wang, Xiaoqian, 2016. "Remittances and expenditure patterns of the left behinds in rural China," China Economic Review, Elsevier, vol. 37(C), pages 177-190.
    23. J. Edward Taylor & Scott Rozelle & Alan deBrauw, 1999. "Migration, Remittances, and Agricultural Productivity in China," American Economic Review, American Economic Association, vol. 89(2), pages 287-291, May.
    24. Yasmin, Nazia & Grundmann, Philipp, 2020. "Home-cooked energy transitions: Women empowerment and biogas-based cooking technology in Pakistan," Energy Policy, Elsevier, vol. 137(C).
    25. Fry, Jane M. & Farrell, Lisa & Temple, Jeromey B., 2022. "Energy poverty and retirement income sources in Australia," Energy Economics, Elsevier, vol. 106(C).
    26. 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).
    27. Healy, John D. & Clinch, J. Peter, 2004. "Quantifying the severity of fuel poverty, its relationship with poor housing and reasons for non-investment in energy-saving measures in Ireland," Energy Policy, Elsevier, vol. 32(2), pages 207-220, January.
    28. Mendoza, Celedonio B. & Cayonte, Dwane Darcy D. & Leabres, Michael S. & Manaligod, Lana Rose A., 2019. "Understanding multidimensional energy poverty in the Philippines," Energy Policy, Elsevier, vol. 133(C).
    29. Hong, Xudong & Wu, Shengnan & Zhang, Xueliang, 2022. "Clean energy powers energy poverty alleviation: Evidence from Chinese micro-survey data," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    30. Crentsil, Aba Obrumah & Asuman, Derek & Fenny, Ama Pokuaa, 2019. "Assessing the determinants and drivers of multidimensional energy poverty in Ghana," Energy Policy, Elsevier, vol. 133(C).
    31. Khanna, Rupali A. & Li, Yanfei & Mhaisalkar, Subodh & Kumar, Mahesh & Liang, Lim Jia, 2019. "Comprehensive energy poverty index: Measuring energy poverty and identifying micro-level solutions in South and Southeast Asia," Energy Policy, Elsevier, vol. 132(C), pages 379-391.
    32. Wang, Ke & Wang, Ya-Xuan & Li, Kang & Wei, Yi-Ming, 2015. "Energy poverty in China: An index based comprehensive evaluation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 308-323.
    33. Okushima, Shinichiro, 2016. "Measuring energy poverty in Japan, 2004–2013," Energy Policy, Elsevier, vol. 98(C), pages 557-564.
    34. Hailemariam, Abebe & Sakutukwa, Tutsirai & Yew, Siew Ling, 2021. "The impact of energy poverty on physical violence," Energy Economics, Elsevier, vol. 100(C).
    35. Wen, Hong-xing & Wang, Chan & Nie, Pu-yan, 2021. "Acceleration of rural households’ conversion to cleaner cooking fuels: The importance and mechanisms of peer effects," Energy Policy, Elsevier, vol. 154(C).
    36. Y. Zhu & Z. Wu & L. Peng & L. Sheng, 2014. "Where did all the remittances go? Understanding the impact of remittances on consumption patterns in rural China," Applied Economics, Taylor & Francis Journals, vol. 46(12), pages 1312-1322, April.
    37. Zhao, Jun & Jiang, Qingzhe & Dong, Xiucheng & Dong, Kangyin, 2021. "Assessing energy poverty and its effect on CO2 emissions: The case of China," Energy Economics, Elsevier, vol. 97(C).
    38. Zheng, Linyi, 2023. "Impact of off-farm employment on cooking fuel choices: Implications for rural-urban transformation in advancing sustainable energy transformation," Energy Economics, Elsevier, vol. 118(C).
    39. Oum, Sothea, 2019. "Energy poverty in the Lao PDR and its impacts on education and health," Energy Policy, Elsevier, vol. 132(C), pages 247-253.
    40. Abbas, Khizar & Xie, Xiaoqing & Xu, Deyi & Butt, Khalid Manzoor, 2021. "Assessing an empirical relationship between energy poverty and domestic health issues: A multidimensional approach," Energy, Elsevier, vol. 221(C).
    41. Timothy J. Bartik, 2006. "How Do the Effects of Local Growth on Employment Rates Vary With Initial Labor Market Conditions," Upjohn Working Papers 09-148, W.E. Upjohn Institute for Employment Research.
    42. Wenfeng Zhou & Chen Qing & Shili Guo & Jia He & Xin Deng & Jiahao Song & Dingde Xu, 2022. "Labor Off-Farm Employment and Farmers’ Cooking Clean Energy Use: Evidence from Rural China," Agriculture, MDPI, vol. 12(7), pages 1-14, July.
    43. Zhang, Quanda & Appau, Samuelson & Kodom, Peter Lord, 2021. "Energy poverty, children's wellbeing and the mediating role of academic performance: Evidence from China," Energy Economics, Elsevier, vol. 97(C).
    44. Lin, Boqiang & Wang, Yao, 2020. "Does energy poverty really exist in China? From the perspective of residential electricity consumption," Energy Policy, Elsevier, vol. 143(C).
    45. 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.
    46. Xu, Xiaojing & Chen, Chien-fei, 2019. "Energy efficiency and energy justice for U.S. low-income households: An analysis of multifaceted challenges and potential," Energy Policy, Elsevier, vol. 128(C), pages 763-774.
    47. Wu, Shu & Han, Hongyun, 2022. "Energy transition, intensity growth, and policy evolution: Evidence from rural China," Energy Economics, Elsevier, vol. 105(C).
    48. Nguyen, Trung Thanh & Nguyen, Thanh-Tung & Hoang, Viet-Ngu & Wilson, Clevo, 2019. "Energy transition, poverty and inequality: panel evidence from Vietnam," MPRA Paper 107182, University Library of Munich, Germany, revised 10 May 2019.
    49. Zou, Baoling & Luo, Biliang, 2019. "Rural household energy consumption characteristics and determinants in China," Energy, Elsevier, vol. 182(C), pages 814-823.
    50. Kaygusuz, K., 2011. "Energy services and energy poverty for sustainable rural development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 936-947, February.
    51. Pachauri, S. & Mueller, A. & Kemmler, A. & Spreng, D., 2004. "On Measuring Energy Poverty in Indian Households," World Development, Elsevier, vol. 32(12), pages 2083-2104, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Choumert-Nkolo, Johanna & le Roux, Leonard, 2024. "Leaving the hearth you know: Internal migration and energy poverty," World Development, Elsevier, vol. 180(C).
    2. Ye, Juntao & Cai, Liming & Shi, Xinjie & Cheng, Mingwang, 2024. "Pursuing a brighter future: Impact of the Hukou reform on human capital investment in migrant children in China," China Economic Review, Elsevier, vol. 85(C).

    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. Huang, Yatao & Jiao, Wenxian & Wang, Kang & Li, Erling & Yan, Yutong & Chen, Jingyang & Guo, Xuanxuan, 2022. "Examining the multidimensional energy poverty trap and its determinants: An empirical analysis at household and community levels in six provinces of China," Energy Policy, Elsevier, vol. 169(C).
    2. Fu Wang & Hong Geng & Donglan Zha & Chaoqun Zhang, 2023. "Multidimensional Energy Poverty in China: Measurement and Spatio-Temporal Disparities Characteristics," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 45-78, August.
    3. Awan, Ashar & Bilgili, Faik & Rahut, Dil Bahadur, 2022. "Energy poverty trends and determinants in Pakistan: Empirical evidence from eight waves of HIES 1998–2019," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. Li, Jinkai & Gao, Ming & Luo, Erga & Wang, Jingyi & Zhang, Xuebiao, 2023. "Does rural energy poverty alleviation really reduce agricultural carbon emissions? The case of China," Energy Economics, Elsevier, vol. 119(C).
    5. Liu, Zhong & Zhou, Zuanjiu & Liu, Chang, 2023. "Estimating the impact of rural centralized residence policy interventions on energy poverty in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    6. Omar, Md Abdullah & Hasanujzaman, Muhammad, 2021. "Multidimensional energy poverty in Bangladesh and its effect on health and education: A multilevel analysis based on household survey data," Energy Policy, Elsevier, vol. 158(C).
    7. Dong, Kangyin & Ren, Xiaohang & Zhao, Jun, 2021. "How does low-carbon energy transition alleviate energy poverty in China? A nonparametric panel causality analysis," Energy Economics, Elsevier, vol. 103(C).
    8. Recep Ulucak & Ramazan Sari & Seyfettin Erdogan & Rui Alexandre Castanho, 2021. "Bibliometric Literature Analysis of a Multi-Dimensional Sustainable Development Issue: Energy Poverty," Sustainability, MDPI, vol. 13(17), pages 1-21, August.
    9. Shahzad, Umer & Gupta, Mansi & Sharma, Gagan Deep & Rao, Amar & Chopra, Ritika, 2022. "Resolving energy poverty for social change: Research directions and agenda," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    10. Siksnelyte-Butkiene, Indre & Streimikiene, Dalia & Balezentis, Tomas, 2022. "Addressing sustainability issues in transition to carbon-neutral sustainable society with multi-criteria analysis," Energy, Elsevier, vol. 254(PA).
    11. Lin, Boqiang & Wang, Yao, 2020. "Does energy poverty really exist in China? From the perspective of residential electricity consumption," Energy Policy, Elsevier, vol. 143(C).
    12. Lan, Jing & Khan, Sufyan Ullah & Sadiq, Muhammad & Chien, Fengsheng & Baloch, Zulfiqar Ali, 2022. "Evaluating energy poverty and its effects using multi-dimensional based DEA-like mathematical composite indicator approach: Findings from Asia," Energy Policy, Elsevier, vol. 165(C).
    13. Ren, Yi-Shuai & Jiang, Yong & Narayan, Seema & Ma, Chao-Qun & Yang, Xiao-Guang, 2022. "Marketisation and rural energy poverty: Evidence from provincial panel data in China," Energy Economics, Elsevier, vol. 111(C).
    14. Yuxiang Xie & E. Xie, 2023. "Measuring and Analyzing the Welfare Effects of Energy Poverty in Rural China Based on a Multi-Dimensional Energy Poverty Index," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    15. Tiwari, Sunil & Si Mohammed, Kamel & Guesmi, Khaled, 2023. "A way forward to end energy poverty in China: Role of carbon-cutting targets and net-zero commitments," Energy Policy, Elsevier, vol. 180(C).
    16. Lozano, Lorafe & Taboada, Evelyn B., 2020. "Demystifying the authentic attributes of electricity-poor populations: The electrification landscape of rural off-grid island communities in the Philippines," Energy Policy, Elsevier, vol. 145(C).
    17. Richard S. J. Tol, 2023. "Navigating the energy trilemma during geopolitical and environmental crises," Papers 2301.07671, arXiv.org.
    18. Wang, Hanjie & Maruejols, Lucie & Yu, Xiaohua, 2021. "Predicting energy poverty with combinations of remote-sensing and socioeconomic survey data in India: Evidence from machine learning," Energy Economics, Elsevier, vol. 102(C).
    19. Junhong Qu & Xiaoli Hao, 2022. "Digital Economy, Financial Development, and Energy Poverty Based on Mediating Effects and a Spatial Autocorrelation Model," Sustainability, MDPI, vol. 14(15), pages 1-24, July.
    20. Qiu, Hua & Sha, Yezhou & Zhang, Yixing, 2024. "Energy affordability and subjective well-being in China: Causal inference, heterogeneity, and the mediating role of disaster risk," Energy Economics, Elsevier, vol. 129(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:appene:v:350:y:2023:i:c:s0306261923011443. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.