IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2022i1p175-d1012053.html
   My bibliography  Save this article

The Impact of Health Insurance Policy on the Fertility Intention of Rural Floating Population in China: Empirical Evidence from Cross-Sectional Data

Author

Listed:
  • Yiqing Xing

    (School of Politics and Public Administration, Wuhan University, Wuhan 430072, China)

  • Clifford Silver Tarimo

    (College of Public Health, Zhengzhou University, Zhengzhou 450001, China
    Department of Science and Laboratory Technology, Dares Salaam Institute of Technology, Dar es Salaam P.O. Box 2958, Tanzania)

  • Weicun Ren

    (School of Politics and Public Administration, Wuhan University, Wuhan 430072, China)

  • Liang Zhang

    (School of Politics and Public Administration, Wuhan University, Wuhan 430072, China)

Abstract

Declining total fertility rates pose a severe challenge to the economy, society, culture, and politics of any region. Low fertility rates among China’s rural floating population with strong fertility are aggravating these challenges. Previous research has confirmed the relationships between health insurance and fertility intention. However, it is still unclear whether the existing association is favorable or not. Moreover, the majority of existing studies in China employ data from either urban or rural populations, whereas evidence from rural floating populations remains scarce. Based on the “China Migrants Dynamic Survey (CMDS)” in 2016, the current study used the logistic regression model to explore the impact of health insurance policy on the fertility intention of the rural floating population in China. Propensity Score Matching (PSM) was used to address potential selection bias. Three important findings were observed: Firstly, participating in the Basic Medical Insurance System (BMISUR) significantly improved rural floating populations’ fertility intentions in China. Secondly, the association between age and the fertility intention of the floating population was “inverted u-shaped” with the highest fertility intention among those aged 25 to 34. There was also a positive correlation between personal income and fertility intention, and it was found between local housing purchase, formal employment, the co-residents scale, and the fertility intention in the rural floating population in China. Interprovincial mobility was positively associated with the fertility intention among rural migrants. Thirdly, the impact of health insurance policies on the fertility intention of the rural migrant population varies by gender, age, and inflow areas. The aforementioned findings can guide the Chinese government in its efforts to improve the fertility intention of the rural floating population, reform the social security system with a focus on “targets”, and implement differentiated welfare policies aimed at promoting the equalization of basic public services, thereby contributing to China’s population structure and long-term development.

Suggested Citation

  • Yiqing Xing & Clifford Silver Tarimo & Weicun Ren & Liang Zhang, 2022. "The Impact of Health Insurance Policy on the Fertility Intention of Rural Floating Population in China: Empirical Evidence from Cross-Sectional Data," IJERPH, MDPI, vol. 20(1), pages 1-16, December.
    • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:175-:d:1012053
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/1/175/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/1/175/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yingying Meng & Junqiang Han & Siqi Qin, 2018. "The Impact of Health Insurance Policy on the Health of the Senior Floating Population—Evidence from China," IJERPH, MDPI, vol. 15(10), pages 1-17, October.
    2. Letizia Mencarini & Daniele Vignoli & Tugba Zeydanli & Jungho Kim, 2018. "Life satisfaction favors reproduction. The universal positive effect of life satisfaction on childbearing in contemporary low fertility countries," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-19, December.
    3. William A. V. Clark & Daichun Yi & Xin Zhang, 2020. "Do House Prices Affect Fertility Behavior in China? An Empirical Examination," International Regional Science Review, , vol. 43(5), pages 423-449, September.
    4. Akira Yakita, 2001. "Uncertain lifetime, fertility and social security," Journal of Population Economics, Springer;European Society for Population Economics, vol. 14(4), pages 635-640.
    5. Qiang He & Xin Deng & Chuan Li & Zhongcheng Yan & Yanbin Qi, 2022. "The Impact of Rural Population Mobility on Fertility Intention under the Comprehensive Two-Child Policy: Evidence from Rural China," IJERPH, MDPI, vol. 19(12), pages 1-17, June.
    6. Larry E. Jones & Alice Schoonbroodt & Michèle Tertilt, 2010. "Fertility Theories: Can They Explain the Negative Fertility-Income Relationship?," NBER Chapters, in: Demography and the Economy, pages 43-100, National Bureau of Economic Research, Inc.
    7. Maloney, William F, 1999. "Does Informality Imply Segmentation in Urban Labor Markets? Evidence from Sectoral Transitions in Mexico," The World Bank Economic Review, World Bank, vol. 13(2), pages 275-302, May.
    8. Liu, Jing & Xing, Chunbing & Zhang, Qiong, 2020. "House price, fertility rates and reproductive intentions," China Economic Review, Elsevier, vol. 62(C).
    9. Xiaojie Wang & Wenjie Nie & Pengcheng Liu, 2020. "Son Preference and the Reproductive Behavior of Rural-Urban Migrant Women of Childbearing Age in China: Empirical Evidence from a Cross-Sectional Data," IJERPH, MDPI, vol. 17(9), pages 1-12, May.
    10. Christakis, Nicholas A. & Iwashyna, Theodore J., 2003. "The health impact of health care on families: a matched cohort study of hospice use by decedents and mortality outcomes in surviving, widowed spouses," Social Science & Medicine, Elsevier, vol. 57(3), pages 465-475, August.
    11. Liu, Jun & Liu, Taoxiong, 2020. "Two-child policy, gender income and fertility choice in China," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 1071-1081.
    12. Tom S. Vogl, 2016. "Differential Fertility, Human Capital, and Development," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(1), pages 365-401.
    13. Jean Drèze & Mamta Murthi, 2001. "Fertility, Education, and Development: Evidence from India," Population and Development Review, The Population Council, Inc., vol. 27(1), pages 33-63, March.
    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. Qiang He & Xin Deng & Chuan Li & Zhongcheng Yan & Yanbin Qi, 2022. "The Impact of Rural Population Mobility on Fertility Intention under the Comprehensive Two-Child Policy: Evidence from Rural China," IJERPH, MDPI, vol. 19(12), pages 1-17, June.
    2. Matthias Doepke & Anne Hannusch & Fabian Kindermann & Michèle Tertilt, 2022. "The Economics of Fertility: A New Era," NBER Working Papers 29948, National Bureau of Economic Research, Inc.
    3. Chen, Nana & Xu, Hangtian, 2021. "Why has the birth rate relatively increased in China's wealthy cities?," MPRA Paper 105960, University Library of Munich, Germany.
    4. Michael Bar & Moshe Hazan & Oksana Leukhina & David Weiss & Hosny Zoabi, 2018. "Why did rich families increase their fertility? Inequality and marketization of child care," Journal of Economic Growth, Springer, vol. 23(4), pages 427-463, December.
    5. Alfano, Marco, 2017. "Daughters, dowries, deliveries: The effect of marital payments on fertility choices in India," Journal of Development Economics, Elsevier, vol. 125(C), pages 89-104.
    6. Remi Jedwab & Dietrich Vollrath, 2019. "The Urban Mortality Transition and Poor-Country Urbanization," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(1), pages 223-275, January.
    7. Takuya Obara & Yoshitomo Ogawa, 2020. "Optimal Taxation in an Endogenous Fertility Model with Non-Cooperative Couples," Discussion Paper Series 211, School of Economics, Kwansei Gakuin University, revised Jan 2021.
    8. Tuna Dökmeci & Carla Rainer & Alyssa Schneebaum, 2023. "Economic Security and Fertility: Evidence from the Mincome Experiment," Department of Economics Working Papers wuwp332, Vienna University of Economics and Business, Department of Economics.
    9. Abebe HAILEMARIAM, 2024. "Income and differential fertility: evidence from oil price shocks," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 90(1), pages 31-54, March.
    10. Ermanno Affuso & Khandokar Istiak & James Swofford, 2022. "Interest Rates, House Prices, Fertility, and the Macroeconomy," JRFM, MDPI, vol. 15(9), pages 1-17, September.
    11. Jorge Alberto Charles Coll & Elizabeth Lizeth Mayer Granados & Nazhle Faride Cheín Schekaiban, 2018. "Desigualdad en el ingreso y crecimiento económico de los municipios mexicanos: el efecto natalidad - capital humano\Income inequality and economic growth in Mexican municipalities: The fertility - hu," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 33(2), pages 195-217.
    12. Roozbeh Hosseini & Larry E. Jones & Ali Shourideh, 2009. "Risk Sharing, Inequality and Fertility," NBER Working Papers 15111, National Bureau of Economic Research, Inc.
    13. Michael F. Lovenheim & Kevin J. Mumford, 2010. "Do Family Wealth Shocks Affect Fertility Choices? Evidence from the Housing Market Boom and Bust," Purdue University Economics Working Papers 1228, Purdue University, Department of Economics.
    14. Albertini, Julien & Terriau, Anthony, 2019. "Informality over the life-cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 105(C), pages 182-202.
    15. Flórez, Luz A., 2017. "Informal sector under saving: A positive analysis of labour market policies," Labour Economics, Elsevier, vol. 44(C), pages 13-26.
    16. Mathan Satchi & Jonathan Temple, 2006. "Growth and labour markets in developing countries," Bristol Economics Discussion Papers 06/581, School of Economics, University of Bristol, UK.
    17. Mathilde Bouvier & François Roubaud & Mireille Razafindrakoto & Roberta Teixeira, 2022. "Labour market transitions in the time of Covid-19 in Brazil:a panel data analysis," Working Papers DT/2022/02, DIAL (Développement, Institutions et Mondialisation).
    18. Calderón, Valentina & Marinescu, Ioana, 2011. "The Impact of Colombia's Pension and Health Insurance Systems on Informality," IDB Publications (Working Papers) 3831, Inter-American Development Bank.
    19. George‐Levi Gayle & Limor Golan & Mehmet A. Soytas, 2018. "Estimation of dynastic life‐cycle discrete choice models," Quantitative Economics, Econometric Society, vol. 9(3), pages 1195-1241, November.
    20. Thomas Baudin & David de la Croix & Paula E. Gobbi, 2015. "Fertility and Childlessness in the United States," American Economic Review, American Economic Association, vol. 105(6), pages 1852-1882, June.

    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:jijerp:v:20:y:2022:i:1:p:175-:d:1012053. 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.