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

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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