IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i8p6812-d1126413.html
   My bibliography  Save this article

Effects of Rural Population Aging on Agricultural Carbon Emissions in China

Author

Listed:
  • Yongqiang Zhang

    (College of Economics & Management, Northeast Agricultural University, Harbin 150030, China)

  • Quanyao Dong

    (College of Economics & Management, Northeast Agricultural University, Harbin 150030, China)

  • Guifang Ma

    (College of Economics & Management, Northeast Agricultural University, Harbin 150030, China)

Abstract

The “double carbon” goal (China aims to achieve carbon peak by 2030 and carbon neutrality by 2060) puts forward new requirements for the low-carbon development of agriculture. However, with the increasing aging of the rural population and the gradual aging of the agricultural labor force, determining the best means of achieving the target of reducing agricultural carbon emissions is particularly urgent. Based on the IPAT identity relationship (method of decomposing environmental impact (I) into socio-economic variables: population (P), affluence (A), and technology (T)), aging of the rural population, rural residents’ income, and agricultural technology innovation were selected as threshold variables. Using provincial panel data from 2003 to 2020 in China, this study empirically analyzed the impact of rural population aging on agricultural carbon emissions through a threshold–STIRPAT expansion model. The results showed that agricultural carbon emissions showed an inverted U-shaped growth trend from 2003 to 2020 and reached a peak in 2016. Baseline regression found that rural population aging has a significant emission reduction effect on agricultural carbon emissions. In addition, rural residents’ income and agricultural technology innovation have significant positive and negative impacts on agricultural carbon emissions, respectively. Using the three environmental factors as threshold variables, it was found that there is a significant threshold effect. The emission reduction effect of rural population aging weakens with the deepening of the aging degree but is enhanced with the improvement of rural residents’ income and agricultural technology innovation. In view of these findings, policy suggestions are put forward for agricultural low-carbon development that alleviates the effects of rural population aging, increases rural residents’ income, and strengthens agricultural technological innovation.

Suggested Citation

  • Yongqiang Zhang & Quanyao Dong & Guifang Ma, 2023. "Effects of Rural Population Aging on Agricultural Carbon Emissions in China," Sustainability, MDPI, vol. 15(8), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6812-:d:1126413
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/8/6812/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/8/6812/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. He, Ke & Zhang, Junbiao & Zeng, Yangmei, 2020. "Households’ willingness to pay for energy utilization of crop straw in rural China：Based on an improved UTAUT model," Energy Policy, Elsevier, vol. 140(C).
    2. Yue-Jun Zhang & Zhao Liu & Huan Zhang & Tai-De Tan, 2014. "The impact of economic growth, industrial structure and urbanization on carbon emission intensity in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(2), pages 579-595, September.
    3. Heran Zheng & Yin Long & Richard Wood & Daniel Moran & Zengkai Zhang & Jing Meng & Kuishuang Feng & Edgar Hertwich & Dabo Guan, 2022. "Ageing society in developed countries challenges carbon mitigation," Nature Climate Change, Nature, vol. 12(3), pages 241-248, March.
    4. Chulin Pan & Huayi Wang & Hongpeng Guo & Hong Pan, 2021. "How Do the Population Structure Changes of China Affect Carbon Emissions? An Empirical Study Based on Ridge Regression Analysis," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    5. Balezentis, Tomas, 2020. "Shrinking ageing population and other drivers of energy consumption and CO2 emission in the residential sector: A case from Eastern Europe," Energy Policy, Elsevier, vol. 140(C).
    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. Le Jing & Bin Zhou & Zhenliang Liao, 2024. "Decoupling Analysis of Economic Growth and Carbon Emissions in Xinjiang Based on Tapio and Logarithmic Mean Divisia Index Models," Sustainability, MDPI, vol. 16(18), pages 1-17, September.
    2. 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.

    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. Fenghua Wen & Zhanlin Sun & Yu Luo, 2023. "Population Structure and Local Carbon Emission Reduction: Evidence from Guangdong, China," Sustainability, MDPI, vol. 15(5), pages 1-27, February.
    2. Wang, Qiang & Zhang, Chen & Li, Rongrong, 2022. "Towards carbon neutrality by improving carbon efficiency - A system-GMM dynamic panel analysis for 131 countries’ carbon efficiency," Energy, Elsevier, vol. 258(C).
    3. Chen, Zeyu & Tang, Yuhong & Shen, Hebin & Liu, Jiali & Hu, Zheng, 2024. "Threshold effects of Government digital development and land resource disparity on Urban carbon efficiency in China," Resources Policy, Elsevier, vol. 94(C).
    4. Huang, Haiping & Huang, Baolian & Sun, Aijun, 2023. "How do mineral resources influence eco-sustainability in China? Dynamic role of renewable energy and green finance," Resources Policy, Elsevier, vol. 85(PA).
    5. Yuru Guan & Jin Yan & Yuli Shan & Yannan Zhou & Ye Hang & Ruoqi Li & Yu Liu & Binyuan Liu & Qingyun Nie & Benedikt Bruckner & Kuishuang Feng & Klaus Hubacek, 2023. "Burden of the global energy price crisis on households," Nature Energy, Nature, vol. 8(3), pages 304-316, March.
    6. Su Yang & Jie Shen & Hongyang Li & Beibei Zhang & Jinchao Ma & Baoquan Cheng, 2023. "Unraveling the U-Shaped Linkage: Population Aging and Carbon Efficiency in the Construction Industry," Sustainability, MDPI, vol. 15(17), pages 1-15, September.
    7. Huang, Liqiao & Yoshida, Yoshikuni & Li, Yuan & Cheng, Nan & Xue, Jinjun & Long, Yin, 2024. "Sustainable lifestyle: Quantification and determining factors analysis of household carbon footprints in Japan," Energy Policy, Elsevier, vol. 186(C).
    8. Jiansheng You & Guohan Ding & Liyuan Zhang, 2022. "Heterogeneous Dynamic Correlation Research among Industrial Structure Distortion, Two-Way FDI and Carbon Emission Intensity in China," Sustainability, MDPI, vol. 14(15), pages 1-23, July.
    9. Zhang, Pingdan & Yuan, Haoming & Bai, Fuli & Tian, Xin & Shi, Feng, 2018. "How do carbon dioxide emissions respond to industrial structural transitions? Empirical results from the northeastern provinces of China," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 145-154.
    10. Abudureheman, Maliyamu & Jiang, Qingzhe & Dong, Xiucheng & Dong, Cong, 2022. "Spatial effects of dynamic comprehensive energy efficiency on CO2 reduction in China," Energy Policy, Elsevier, vol. 166(C).
    11. Feng Dong & Yuling Pan, 2020. "Evolution of Renewable Energy in BRI Countries: A Combined Econometric and Decomposition Approach," IJERPH, MDPI, vol. 17(22), pages 1-18, November.
    12. Zhang, Yue-Jun & Wang, Ao-Dong & Da, Ya-Bin, 2014. "Regional allocation of carbon emission quotas in China: Evidence from the Shapley value method," Energy Policy, Elsevier, vol. 74(C), pages 454-464.
    13. Minxing Jiang & Bangzhu Zhu & Julien Chevallier & Rui Xie, 2018. "Allocating provincial CO2 quotas for the Chinese national carbon program," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(3), pages 457-479, July.
    14. Janusz Myszczyszyn & Błażej Suproń, 2022. "Relationship among Economic Growth, Energy Consumption, CO 2 Emission, and Urbanization: An Econometric Perspective Analysis," Energies, MDPI, vol. 15(24), pages 1-18, December.
    15. Dong Jichang & He Jing & Li Xiuting & Mou Xindi & Dong Zhi, 2020. "The Effect of Industrial Structure Change on Carbon Dioxide Emissions: A Cross-Country Panel Analysis," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 1-16, February.
    16. Eryu Zhang & Xiaoyu He & Peng Xiao, 2022. "Does Smart City Construction Decrease Urban Carbon Emission Intensity? Evidence from a Difference-in-Difference Estimation in China," Sustainability, MDPI, vol. 14(23), pages 1-16, December.
    17. Lena Kilian & Anne Owen & Andy Newing & Diana Ivanova, 2022. "Exploring Transport Consumption-Based Emissions: Spatial Patterns, Social Factors, Well-Being, and Policy Implications," Sustainability, MDPI, vol. 14(19), pages 1-26, September.
    18. Jing Song & Mengyuan Li & Shaosong Wang & Tao Ye, 2022. "To What Extent Does Environmental Regulation Influence Emission Reduction? Evidence from Local and Neighboring Locations in China," Sustainability, MDPI, vol. 14(15), pages 1-9, August.
    19. Feng, Zhiying & Tang, Wenhu & Niu, Zhewen & Wu, Qinghua, 2018. "Bi-level allocation of carbon emission permits based on clustering analysis and weighted voting: A case study in China," Applied Energy, Elsevier, vol. 228(C), pages 1122-1135.
    20. Muhammad Imran Qureshi & Usama Awan & Zeeshan Arshad & Amran Md. Rasli & Khalid Zaman & Faisal Khan, 2016. "Dynamic linkages among energy consumption, air pollution, greenhouse gas emissions and agricultural production in Pakistan: sustainable agriculture key to policy success," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 367-381, October.

    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:gam:jsusta:v:15:y:2023:i:8:p:6812-:d:1126413. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.