IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i8p3144-d345271.html
   My bibliography  Save this article

Prediction the Contribution Rate of Long-Term Care Insurance for the Aged in China Based on the Balance of Supply and Demand

Author

Listed:
  • Liangwen Zhang

    (State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361102, China
    Key Laboratory of Health Technology Assessment of Fujian Province University, School of Public Health, Xiamen University, Xiamen 361102, China
    School of Economics, Xiamen University, 422 Siming South Road, Xiamen 361005, China)

  • Sijia Fu

    (State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361102, China
    Key Laboratory of Health Technology Assessment of Fujian Province University, School of Public Health, Xiamen University, Xiamen 361102, China)

  • Ya Fang

    (State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361102, China
    Key Laboratory of Health Technology Assessment of Fujian Province University, School of Public Health, Xiamen University, Xiamen 361102, China)

Abstract

There are a large number of disabled elderly people in China, which results in huge care and financial burdens to their families and society. However, China has not yet launched a unified long-term care insurance (LTCI) system. This study aims to predict the contribution rate of LTCI in China from 2020 to 2050 based on the long-term care (LTC) cost of the disabled elderly, aged 65 and over, in order to provide strong evidence for the establishment of a unified and sustainable national LTCI system in China. The simulations are based on data from the population census data, the Chinese statistical yearbook, and the Chinese Longitudinal Healthy Longevity Survey (CLHLS) database. Based on the International Labor Organization (ILO) financing model from the perspective of fund balance, an overall simulation model and a Monte Carlo simulation are used to estimate the contribution rate of LTCI for disabled elderly from 2020 to 2050 in China. The total financial demands will increase sharply from 538.0 billion yuan in 2020 to 8530.8 billion yuan in 2050. Of that total, 80.2% will be required in urban areas. In addition, the per capita financial demands of care in urban and rural areas in 2050 will be approximately six times and 11 times higher than in 2020, respectively. The predicted results show that the overall contribution rate of LTCI in China will increase sharply from 1.46% in 2020 to 5.14% in 2050, an increase of about 3.5 times. By comparison, the contribution rate in 2020 will be close to 1.33% in Japan in 2015 and 1.40% in Germany in 2010. According to the 1:1 payment proportion between employer and employee, each side bears 0.68% of the insurance premium. From 2020 to 2050, the financial demands of long-term care for disabled elderly in China will increase, especially in urban areas, and the burden of per capita financial demands in rural areas will increase significantly. The overall contribution rate of LTCI will increase linearly and the payment burden of policyholders will increase year by year. This study provides evidence of the need for the establishment of a sustainable financing mechanism for multiple financial supplies.

Suggested Citation

  • Liangwen Zhang & Sijia Fu & Ya Fang, 2020. "Prediction the Contribution Rate of Long-Term Care Insurance for the Aged in China Based on the Balance of Supply and Demand," Sustainability, MDPI, vol. 12(8), pages 1-12, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3144-:d:345271
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/8/3144/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/8/3144/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Karlsson, Martin & Mayhew, Les & Plumb, Robert & Rickayzen, Ben, 2006. "Future costs for long-term care: Cost projections for long-term care for older people in the United Kingdom," Health Policy, Elsevier, vol. 75(2), pages 187-213, January.
    2. Fengyue Li & Junko Otani, 2018. "Financing elderly people's long‐term care needs: Evidence from China," International Journal of Health Planning and Management, Wiley Blackwell, vol. 33(2), pages 479-488, April.
    3. Yumei Zhu & August Österle, 2019. "China's policy experimentation on long‐term care insurance: Implications for access," International Journal of Health Planning and Management, Wiley Blackwell, vol. 34(4), pages 1661-1674, October.
    4. Chang, Shuang & Yang, Wei & Deguchi, Hiroshi, 2020. "Care providers, access to care, and the Long-term Care Nursing Insurance in China: An agent-based simulation," Social Science & Medicine, Elsevier, vol. 244(C).
    5. Xiaocang Xu & Linhong Chen, 2019. "Projection of Long-Term Care Costs in China, 2020–2050: Based on the Bayesian Quantile Regression Method," Sustainability, MDPI, vol. 11(13), pages 1-13, June.
    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. Eva Boj del Val & M. Mercè Claramunt Bielsa & Xavier Varea Soler, 2020. "Role of Private Long-Term Care Insurance in Financial Sustainability for an Aging Society," Sustainability, MDPI, vol. 12(21), pages 1-21, October.

    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. Liangwen Zhang & Sijia Fu & Ya Fang, 2020. "Prediction of the Number of and Care Costs for Disabled Elderly from 2020 to 2050: A Comparison between Urban and Rural Areas in China," Sustainability, MDPI, vol. 12(7), pages 1-13, March.
    2. Wang, Qun & Abiiro, Gilbert Abotisem & Yang, Jin & Li, Peng & De Allegri, Manuela, 2021. "Preferences for long-term care insurance in China: Results from a discrete choice experiment," Social Science & Medicine, Elsevier, vol. 281(C).
    3. Xueqin Deng & Jiaxin Liao & Rong Peng & Jiahao Chen, 2022. "The Impact of Long-Term Care Insurance on Medical Utilization and Expenditures: Evidence from Jingmen, China," IJERPH, MDPI, vol. 19(19), pages 1-18, September.
    4. Ruth Hancock & Marcello Morciano & Stephen Pudney & Francesca Zantomio, 2015. "Do household surveys give a coherent view of disability benefit targeting?: a multisurvey latent variable analysis for the older population in Great Britain," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 815-836, October.
    5. Boqin Xie & Chenjuan Ma & Junqiao Wang, 2020. "Independent and Combined Relationships of Perceived Neighborhood Social Cohesion and Physical Frailty on Functional Disability in Community-Dwelling Older Adults," IJERPH, MDPI, vol. 17(16), pages 1-12, August.
    6. Feng, Xinzhen & Zhou, Dequn & Hussain, Tufail, 2024. "An investigation of fintech governance, natural resources and government stability on sustainability: Policy suggestions under the SDGs theme," Resources Policy, Elsevier, vol. 96(C).
    7. Les Mayhew, 2017. "Means Testing Adult Social Care in England," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 42(3), pages 500-529, July.
    8. Miaoxi Zhao & Yanliu Lin & Huiqin Wang, 2022. "Locational Differences of Collective Land and Their Socioeconomic Effects on the Rural Elderly in China’s Pearl River Delta," Land, MDPI, vol. 11(5), pages 1-16, April.
    9. Joan Costa-Font & Martin Karlsson & Henning Øien, 2015. "Informal Care and the Great Recession," CINCH Working Paper Series 1502, Universitaet Duisburg-Essen, Competent in Competition and Health, revised Feb 2015.
    10. Run-Ping Che & Mei-Chun Cheung, 2022. "Community-Dwelling Older Adults’ Intended Use of Different Types of Long-Term Care in China and Its Associated Factors Based on the Andersen Behavioral Model," IJERPH, MDPI, vol. 19(18), pages 1-16, September.
    11. Kwon Hyuk-Sung & Lee Chang-Soo & Hur Jun-Soo, 2012. "Projecting the Cost of Long-Term Care Insurance in Korea," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 7(1), pages 1-22, December.
    12. Wenna Wang & Yulin Zhang & Beilei Lin & Yongxia Mei & Zhiguang Ping & Zhenxiang Zhang, 2020. "The Urban-Rural Disparity in the Status and Risk Factors of Health Literacy: A Cross-Sectional Survey in Central China," IJERPH, MDPI, vol. 17(11), pages 1-12, May.
    13. Schünemann, Johannes & Strulik, Holger & Trimborn, Timo, 2022. "Optimal demand for medical and long-term care," The Journal of the Economics of Ageing, Elsevier, vol. 23(C).
    14. Hong Mi & Zhenzhen Yang & Tiantian Zhang, 2012. "Factors influencing Chinese long-term care," International Journal of Public Policy, Inderscience Enterprises Ltd, vol. 8(1/2/3), pages 31-42.
    15. Xiaodong Di & Lijian Wang & Xiuliang Dai & Liu Yang, 2020. "Assessing the Accessibility of Home-Based Healthcare Services for the Elderly: A Case from Shaanxi Province, China," IJERPH, MDPI, vol. 17(19), pages 1-16, September.
    16. Xiaotian Zhang & Xiaoyun Liu & Yang Wang & Lulin Zhou & Xiaoran Cheng, 2022. "Sustainable Development of China’s Maternity Insurance System in the Context of Population Policy Changes: Using a Grounded Theory Approach," Sustainability, MDPI, vol. 14(4), pages 1-19, February.
    17. Brunton, Margaret & Jordan, Claire & Fouche, Christa, 2008. "Managing public health care policy: Who's being forgotten?," Health Policy, Elsevier, vol. 88(2-3), pages 348-358, December.
    18. Bo Hu & Javiera Cartagena-Farias & Nicola Brimblecombe & Shari Jadoolal & Raphael Wittenberg, 2024. "Projected costs of informal care for older people in England," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(6), pages 1057-1070, August.
    19. Linhong Chen & Yue Zhuo & Zhiming Xu & Xiaocang Xu & Xin Gao, 2019. "Is Carbon Dioxide (CO 2 ) Emission an Important Factor Affecting Healthcare Expenditure? Evidence from China, 2005–2016," IJERPH, MDPI, vol. 16(20), pages 1-14, October.
    20. Li, Yan, 2022. "Social care for disabled elderly women in urban China: The roles of the community," Social Science & Medicine, Elsevier, vol. 314(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:gam:jsusta:v:12:y:2020:i:8:p:3144-:d:345271. 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.