IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i17p10573-d896804.html
   My bibliography  Save this article

Demographic Transition in Natural Watersheds: Evidence from Population Aging in the Yellow River Basin Based on Various Types of Migration

Author

Listed:
  • Zhibao Wang

    (College of Geography and Environment, Shandong Normal University, Jinan 250358, China)

  • Guangzhi Qi

    (College of Geography and Environment, Shandong Normal University, Jinan 250358, China)

Abstract

Environmental phenomena in natural watersheds have attracted much attention, while where demographic transition, especially population aging, have not. Therefore, we try to analyze regional evolution of population aging in the Yellow River Basin from the perspective of population migration during 1990–2020, in order to explain the laws and mechanism of demographic transition in natural watersheds. Population aging in the Yellow River Basin began in its downstream cities in 1990 and spread to its middle and upper reaches, showing positive spatial correlation. Aging population in the Yellow River Basin forms obvious geographic agglomeration, namely a nonstandard inverted M-shaped agglomeration pattern. During 2000–2020, regional evolution of population aging in the Yellow River Basin is affected by various types of population migration, whose extent varies greatly, especially for the scale of an aging population. Among them, the scale of an aging population in a slow and deep emigration area ( SDE ) and a slow and shallow emigration area ( SSE ) is significantly affected by migration speed ( Ms ), which is positive. However, the migration rate ( Mr ) has a negative impact on population aging in a slow and deep emigration area ( SDE ), slow and deep immigration area ( SDI ), slow and shallow emigration ( SSE ) and slow and shallow immigration area ( SSI ), whose degree of influence slightly differs. Only the power function graph of aging population ( AP ) in a slow and shallow immigration area ( SSI ) about migration speed ( Ms ) is convex, and that in other types about migration rate ( Mr ) or migration speed ( Ms ) is monotonically decreasing, while the inclination degree of whose graphs varies greatly.

Suggested Citation

  • Zhibao Wang & Guangzhi Qi, 2022. "Demographic Transition in Natural Watersheds: Evidence from Population Aging in the Yellow River Basin Based on Various Types of Migration," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10573-:d:896804
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/17/10573/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/17/10573/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Klaus Prettner, 2013. "Population aging and endogenous economic growth," Journal of Population Economics, Springer;European Society for Population Economics, vol. 26(2), pages 811-834, April.
    2. Michał Bernard Pietrzak & Justyna Wilk, 2014. "An Analysis of the Population Aging Phenomena in Poland from a Spatial Perspective," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(1), pages 153-170, January.
    3. David E. Bloom & Roddy McKinnon, 2010. "Social security and the challenge of demographic change," International Social Security Review, John Wiley & Sons, vol. 63(3‐4), pages 3-21, July.
    4. Yu, Ning & Shi, Qinghua & Jin, Hongtao, 2010. "Permanent land-use rights and endowment insurance: Chinese evidence of the substitution effect," China Economic Review, Elsevier, vol. 21(2), pages 272-281, June.
    5. Choi, Ki-Hong & Shin, Sungwhee, 2015. "Population aging, economic growth, and the social transmission of human capital: An analysis with an overlapping generations model," Economic Modelling, Elsevier, vol. 50(C), pages 138-147.
    6. Justyna Wilk & Michal Bernard Pietrzak, 2014. "The Analysis of Population Aging Phenomena in Poland in Spatial Perspective," Working Papers 5/2014, Institute of Economic Research, revised May 2014.
    7. Xin Xu & Yuan Zhao & Xinlin Zhang & Siyou Xia, 2018. "Identifying the Impacts of Social, Economic, and Environmental Factors on Population Aging in the Yangtze River Delta Using the Geographical Detector Technique," Sustainability, MDPI, vol. 10(5), pages 1-15, May.
    8. David E. Bloom & Roddy McKinnon, 2010. "Introduction: Social security and the challenge of demographic change," PGDA Working Papers 6110, Program on the Global Demography of Aging.
    9. Luping Shi & Zhongyao Cai & Xuhui Ding & Rong Di & Qianqian Xiao, 2020. "What Factors Affect the Level of Green Urbanization in the Yellow River Basin in the Context of New-Type Urbanization?," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    10. Luis Rosero‐Bixby, 2011. "Generational Transfers and Population Aging in Latin America," Population and Development Review, The Population Council, Inc., vol. 37(Supplemen), pages 143-157, January.
    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. Lanza Queiroz, Bernardo & Lobo Alves Ferreira, Matheus, 2021. "The evolution of labor force participation and the expected length of retirement in Brazil," The Journal of the Economics of Ageing, Elsevier, vol. 18(C).
    2. Yingzhu Yang & Rong Zheng & Lexiang Zhao, 2021. "Population Aging, Health Investment and Economic Growth: Based on a Cross-Country Panel Data Analysis," IJERPH, MDPI, vol. 18(4), pages 1-16, February.
    3. Wenqiang Qian & Xiangyu Cheng & Guoying Lu & Lijun Zhu & Fei Li, 2019. "Fiscal Decentralization, Local Competitions and Sustainability of Medical Insurance Funds: Evidence from China," Sustainability, MDPI, vol. 11(8), pages 1-21, April.
    4. Hande Barlin & Murat A. Mercan, 2020. "Occupation, Working Hours and Arthritis: Evidence from a Nationally Representative Sample of Older Age Adults," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 10(2), pages 1-8.
    5. Marga Peeters & Loek Groot, 2012. "A Global View On Demographic Pressure And Labour Market Participation," Journal of Global Economy, Research Centre for Social Sciences,Mumbai, India, vol. 8(2), pages 165-194, June.
    6. Queiroz, Bernardo L. & Souza, Laeticia R., 2017. "Retirement incentives and couple’s retirement decisions in Brazil," The Journal of the Economics of Ageing, Elsevier, vol. 9(C), pages 1-13.
    7. Neves, Pedro Cunha & Afonso, Óscar & Sequeira, Tiago Neves, 2018. "Population growth and the wage skill premium," Economic Modelling, Elsevier, vol. 68(C), pages 435-449.
    8. Queiroz, Bernardo L & Ferreira, Matheus L.A., 2018. "The Evolution of the Elderly Labor Force Participation and Retirement in Brazil," OSF Preprints db54h, Center for Open Science.
    9. Zhengyun Jiang & Yun Feng & Jinping Song & Chengzhen Song & Xiaodi Zhao & Chi Zhang, 2023. "Study on the Spatial–Temporal Pattern Evolution and Carbon Emission Reduction Effect of Industry–City Integration in the Yellow River Basin," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
    10. Elena Popkova & Svetlana Meshkova & Evgeniya Karpunina & Elena Karpushko & Marina Karpushko, 2016. "Developing Countries as New Growth Poles of Post-Crisis Global Economy," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 10(2), June.
    11. Sheng Liu & Ming Bai & Min Yao & Ke Huang, 2021. "Identifying the natural and anthropogenic factors influencing the spatial disparity of population hollowing in traditional villages within a prefecture-level city," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-21, April.
    12. Laurent Brembilla, 2016. "Endogenous lifetime and economic growth: the roleof the tax rate," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 4(2), pages 247-263, October.
    13. Kui Liu & Jian Wang & Xiang Kang & Jingming Liu & Zheyi Xia & Kai Du & Xuexin Zhu, 2022. "Spatio-Temporal Analysis of Population-Land-Economic Urbanization and Its Impact on Urban Carbon Emissions in Shandong Province, China," Land, MDPI, vol. 11(2), pages 1-20, February.
    14. Bloom, David E. & Canning, David & Kotschy, Rainer & Prettner, Klaus & Schünemann, Johannes, 2024. "Health and economic growth: Reconciling the micro and macro evidence," World Development, Elsevier, vol. 178(C).
    15. Mónica L. Azevedo & Óscar Afonso & Sandra T. Silva, 2017. "Endogenous Growth and Intellectual Property Rights: A North–South Modelling Proposal with Population Ageing," Australian Economic Papers, Wiley Blackwell, vol. 56(1), pages 72-94, March.
    16. Lee, R., 2016. "Macroeconomics, Aging, and Growth," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 59-118, Elsevier.
    17. Davis, Colin & Hashimoto, Ken-ichi & Tabata, Ken, 2022. "Demographic structure, knowledge diffusion, and endogenous productivity growth," Journal of Macroeconomics, Elsevier, vol. 71(C).
    18. Sulekha Hembram & Sushil Kr. Haldar, 2019. "Beta, sigma and club convergence: Indian experience from 1980 to 2015," Indian Economic Review, Springer, vol. 54(2), pages 343-366, December.
    19. Xinxin Wang & Jingjing Hong & Pengpeng Fan & Shidan Xu & Zhixian Chai & Yubo Zhuo, 2021. "Is China’s urban–rural difference in population aging rational? An international comparison with key indicators," Growth and Change, Wiley Blackwell, vol. 52(3), pages 1866-1891, September.
    20. Maik T. Schneider & Ralph Winkler, 2021. "Growth and Welfare under Endogenous Lifetimes," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(4), pages 1339-1384, 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:14:y:2022:i:17:p:10573-:d:896804. 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.