IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v185y2024ics0301421523005414.html
   My bibliography  Save this article

Who is most affected by carbon tax? Evidence from Chinese residents in the context of aging

Author

Listed:
  • Yu, Yan-Yan
  • Liu, Li-Jing
  • Wang, He-Jing

Abstract

Previous research on the distributional effects of carbon tax has primarily focused on different income groups, with less examination of different age groups. Nevertheless, significant differences in the effect of carbon tax are expected for different age groups, particularly for the vulnerable elderly. Based on detailed data regarding the consumption patterns, this study first investigates direct and indirect emissions for different age groups of residents. And then we analyze the distributional effects of carbon tax on residents of different ages and income groups using an input–output price model. The results show that the indirect carbon payment burden rate on the elderly (i.e., the proportion of carbon tax expenditure in total expenditure) is 1.2 times that of the general population. The combined impact of income and age on comprehensive indirect carbon payment rates is estimated to be 1.4 times that of the general people, showing that the carbon tax exacerbates the energy poverty of low-income seniors to a greater extent. In addition, supportive measures can effectively reduce the carbon tax cost burden of the elderly and low-income residents. Even if the carbon tax is levied more vigorously, it can still enhance the ability of vulnerable groups to overcome negative energy shocks.

Suggested Citation

  • Yu, Yan-Yan & Liu, Li-Jing & Wang, He-Jing, 2024. "Who is most affected by carbon tax? Evidence from Chinese residents in the context of aging," Energy Policy, Elsevier, vol. 185(C).
    • Handle: RePEc:eee:enepol:v:185:y:2024:i:c:s0301421523005414
    DOI: 10.1016/j.enpol.2023.113956
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421523005414
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2023.113956?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. Arik Levinson, 2019. "Energy Efficiency Standards Are More Regressive Than Energy Taxes: Theory and Evidence," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 6(S1), pages 7-36.
    2. Jiang, Zhujun & Shao, Shuai, 2014. "Distributional effects of a carbon tax on Chinese households: A case of Shanghai," Energy Policy, Elsevier, vol. 73(C), pages 269-277.
    3. Zhao, Fang & Xu, Jiayi & Fang, Guanfu, 2022. "The heterogeneous effects of employment-based pension policies on employment: Evidence from urban China," Journal of Asian Economics, Elsevier, vol. 78(C).
    4. Berry, Audrey, 2019. "The distributional effects of a carbon tax and its impact on fuel poverty: A microsimulation study in the French context," Energy Policy, Elsevier, vol. 124(C), pages 81-94.
    5. Magnus Bergquist & Andreas Nilsson & Niklas Harring & Sverker C. Jagers, 2022. "Meta-analyses of fifteen determinants of public opinion about climate change taxes and laws," Nature Climate Change, Nature, vol. 12(3), pages 235-240, March.
    6. Menz, Tobias & Welsch, Heinz, 2012. "Population aging and carbon emissions in OECD countries: Accounting for life-cycle and cohort effects," Energy Economics, Elsevier, vol. 34(3), pages 842-849.
    7. Zhang, Mingming & Liu, Jinghui & Liu, Liyun & Zhou, Dequn, 2023. "Inequality in urban household energy consumption for 30 Chinese provinces," Energy Policy, Elsevier, vol. 172(C).
    8. Fan, Jianshuang & Zhou, Lin & Zhang, Yan & Shao, Shuai & Ma, Miao, 2021. "How does population aging affect household carbon emissions? Evidence from Chinese urban and rural areas," Energy Economics, Elsevier, vol. 100(C).
    9. Haiyan Ding & Hui He, 2018. "A Tale of Transition: An Empirical Analysis of Economic Inequality in Urban China, 1986-2009," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 29, pages 106-137, July.
    10. Andrea Baranzini & Jeroen C. J. M. van den Bergh & Stefano Carattini & Richard B. Howarth & Emilio Padilla & Jordi Roca, 2017. "Carbon pricing in climate policy: seven reasons, complementary instruments, and political economy considerations," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 8(4), July.
    11. Wang, Xue-Chao & Klemeš, Jiří Jaromír & Wang, Yutao & Dong, Xiaobin & Wei, Hejie & Xu, Zihan & Varbanov, Petar Sabev, 2020. "Water-Energy-Carbon Emissions nexus analysis of China: An environmental input-output model-based approach," Applied Energy, Elsevier, vol. 261(C).
    12. Callan, Tim & Lyons, Sean & Scott, Susan & Tol, Richard S.J. & Verde, Stefano, 2009. "The distributional implications of a carbon tax in Ireland," Energy Policy, Elsevier, vol. 37(2), pages 407-412, February.
    13. Hu, Wenhao & Ho, Mun S. & Cao, Jing, 2019. "Energy consumption of urban households in China," China Economic Review, Elsevier, vol. 58(C).
    14. Wen, Hong-xing & Chen, Zhe & Yang, Qian & Liu, Jin-yi & Nie, Pu-yan, 2022. "Driving forces and mitigating strategies of CO2 emissions in China: A decomposition analysis based on 38 industrial sub-sectors," Energy, Elsevier, vol. 245(C).
    15. Bardazzi, Rossella & Pazienza, Maria Grazia, 2017. "Switch off the light, please! Energy use, aging population and consumption habits," Energy Economics, Elsevier, vol. 65(C), pages 161-171.
    16. Brenner, Mark & Riddle, Matthew & Boyce, James K., 2007. "A Chinese sky trust?: Distributional impacts of carbon charges and revenue recycling in China," Energy Policy, Elsevier, vol. 35(3), pages 1771-1784, March.
    17. Kerkhof, Annemarie C. & Moll, Henri C. & Drissen, Eric & Wilting, Harry C., 2008. "Taxation of multiple greenhouse gases and the effects on income distribution: A case study of the Netherlands," Ecological Economics, Elsevier, vol. 67(2), pages 318-326, September.
    18. Zhao, Da & Wu, Tianhao & He, Qiwei, 2017. "Consumption inequality and its evolution in urban China," China Economic Review, Elsevier, vol. 46(C), pages 208-228.
    19. Xiaoyan Lei & John Strauss & Meng Tian & Yaohui Zhao, 2015. "Living arrangements of the elderly in China: evidence from the CHARLS national baseline," China Economic Journal, Taylor & Francis Journals, vol. 8(3), pages 191-214, September.
    20. Biying Yu & Yi-Ming Wei & Kei Gomi & Yuzuru Matsuoka, 2018. "Future scenarios for energy consumption and carbon emissions due to demographic transitions in Chinese households," Nature Energy, Nature, vol. 3(2), pages 109-118, February.
    21. Perobelli, Fernando Salgueiro & Faria, Weslem Rodrigues & Vale, Vinicius de Almeida, 2015. "The increase in Brazilian household income and its impact on CO2 emissions: Evidence for 2003 and 2009 from input–output tables," Energy Economics, Elsevier, vol. 52(PA), pages 228-239.
    22. Jiang, Lu & Yu, Lu & Xue, Bing & Chen, Xingpeng & Mi, Zhifu, 2020. "Who is energy poor? Evidence from the least developed regions in China," Energy Policy, Elsevier, vol. 137(C).
    23. Tiezzi, Silvia, 2005. "The welfare effects and the distributive impact of carbon taxation on Italian households," Energy Policy, Elsevier, vol. 33(12), pages 1597-1612, August.
    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. Wang, Qian & Hubacek, Klaus & Feng, Kuishuang & Wei, Yi-Ming & Liang, Qiao-Mei, 2016. "Distributional effects of carbon taxation," Applied Energy, Elsevier, vol. 184(C), pages 1123-1131.
    2. Moz-Christofoletti, Maria Alice & Pereda, Paula Carvalho, 2021. "Winners and losers: the distributional impacts of a carbon tax in Brazil," Ecological Economics, Elsevier, vol. 183(C).
    3. Wang, Qian & Hubacek, Klaus & Feng, Kuishuang & Guo, Lin & Zhang, Kun & Xue, Jinjun & Liang, Qiao-Mei, 2019. "Distributional impact of carbon pricing in Chinese provinces," Energy Economics, Elsevier, vol. 81(C), pages 327-340.
    4. You-Yi Guo & Jin-Xu Lin & Shih-Mo Lin, 2022. "The Distribution Effects of a Carbon Tax on Urban and Rural Households in China," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
    5. Tram T.H. Nguyen and Wonho Song, 2021. "Carbon Pricing and Income Inequality: An Empirical Investigation," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 46(2), pages 155-182, June.
    6. Zhu, Penghu & Lin, Boqiang, 2022. "Do the elderly consume more energy? Evidence from the retirement policy in urban China," Energy Policy, Elsevier, vol. 165(C).
    7. Heindl, Peter & Löschel, Andreas, 2015. "Social implications of green growth policies from the perspective of energy sector reform and its impact on households," ZEW Discussion Papers 15-012, ZEW - Leibniz Centre for European Economic Research.
    8. Qiao-Mei Liang & Qian Wang & Yi-Ming Wei, 2013. "Assessing the Distributional Impacts of Carbon Tax among Households across Different Income Groups: The Case of China," Energy & Environment, , vol. 24(7-8), pages 1323-1346, December.
    9. Jia, Zhijie & Lin, Boqiang & Liu, Xiying, 2023. "Rethinking the equity and efficiency of carbon tax: A novel perspective," Applied Energy, Elsevier, vol. 346(C).
    10. Lucia Rotaris & Alessandro Gardelli, 2018. "Carbon Tax acceptability: A comparative experimental analysis," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2018(1), pages 117-132.
    11. Qin, Ping. & Chen, Peilin. & Zhang, Xiao-Bing. & Xie, Lunyu., 2020. "Coal taxation reform in China and its distributional effects on residential consumers," Energy Policy, Elsevier, vol. 139(C).
    12. Corbett A. Grainger & Charles D. Kolstad, 2010. "Distribution and Climate Change Policies," Chapters, in: Emilio Cerdá Tena & Xavier Labandeira (ed.), Climate Change Policies, chapter 7, Edward Elgar Publishing.
    13. Labandeira, Xavier & Labeaga, José M. & Rodríguez, Miguel, 2009. "An integrated economic and distributional analysis of energy policies," Energy Policy, Elsevier, vol. 37(12), pages 5776-5786, December.
    14. Saelim, Supawan, 2019. "Carbon tax incidence on household consumption: Heterogeneity across socio-economic factors in Thailand," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 159-174.
    15. Kirchner, Mathias & Sommer, Mark & Kratena, Kurt & Kletzan-Slamanig, Daniela & Kettner-Marx, Claudia, 2019. "CO2 taxes, equity and the double dividend – Macroeconomic model simulations for Austria," Energy Policy, Elsevier, vol. 126(C), pages 295-314.
    16. Zhou, Yang & Wang, Heng & Qiu, Huanguang, 2023. "Population aging reduces carbon emissions: Evidence from China's latest three censuses," Applied Energy, Elsevier, vol. 351(C).
    17. Shuyu Li & Qiang Wang & Rongrong Li, 2024. "How aging impacts environmental sustainability—insights from the effects of social consumption and labor supply," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-16, December.
    18. Waldemar Marz, 2019. "Climate Policy and Inequality in Two-Dimensional Political Competition," ifo Working Paper Series 319, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    19. Jiang, Zhujun & Shao, Shuai, 2014. "Distributional effects of a carbon tax on Chinese households: A case of Shanghai," Energy Policy, Elsevier, vol. 73(C), pages 269-277.
    20. Fan, Jianshuang & Zhou, Lin & Zhang, Yan & Shao, Shuai & Ma, Miao, 2021. "How does population aging affect household carbon emissions? Evidence from Chinese urban and rural areas," Energy Economics, Elsevier, vol. 100(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:enepol:v:185:y:2024:i:c:s0301421523005414. 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/locate/enpol .

    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.