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    China's Older Population with Disabiliby and Demand for Long-term Care Workforce: A Forecasting Analysis
    Zhang Wenjuan, Xue Shirui
    Population Research    2026, 50 (5): 3-19.  
    Abstract (1219)            Save
    China is ageing rapidly and is expected to become a super-aged society around 2035. As long-term care insurance expands nationwide, the coming decade will be critical for long-term care development and workforce planning. China is building a home- and community-based elderly care system with professional institutional support and medical-care integration, yet workforce shortages remain a constraint. Care needs and arrangements vary by disability level, and the two settings differ in recipient composition, service organization, and staffing mechanisms. Existing studies often treat care as homogeneous, obscuring the scale and structure of workforce demand.

    This study addresses two questions: (1) What will be the scale of demand for China's long-term care workforce (LTC workforce) from 2020 to 2035? (2) How will this demand differ between institutional and home- and community-based elderly care settings? To address these questions, data are drawn from the China Longitudinal Aging Social Survey (CLASS), the Chinese Longitudinal Healthy Longevity Survey (CLHLS), the Seventh National Population Census, World Population Prospects 2024, and the China Civil Affairs Statistical Yearbook. Disability transition probabilities are estimated from 2014 and 2018 CLASS and CLHLS panel data and combined with census and population projection data to project disabled older adults by disability level. Two scenarios are constructed: a steady-state distribution scenario and a policy development scenario. Demand for the LTC workforce is estimated using staffing ratios for institutional elderly care and service time requirements for home- and community-based elderly care.

    The results show that the number of disabled older adults will increase from 22.89 million in 2020 to 65.97 million in 2035, with older adults with mild disabilities remaining the largest group and those with severe disabilities experiencing the fastest growth. This expansion and changing composition increase LTC workforce demand, with distinct patterns across care settings. Under the medium specification, demand for the institutional LTC workforce reaches 0.68(steady-state distribution scenario)~1.53(policy development scenario)million in 2035; in the latter, care for older adults with severe disabilities accounts for more than 80% of institutional demand. Home- and community-based elderly care accounts for most LTC workforce demand, requiring 6.24(policy development scenario)~7.01(steady-state distribution scenario)million workers in 2035, with demand increasingly concentrated among older adults with mild and severe disabilities. Total demand for the LTC workforce reaches 7.69(steady-state distribution scenario)~7.78(policy development scenario)million in 2035. Although the policy development scenario raises institutional demand, the corresponding reduction in home- and community-based demand keeps the difference in total demand relatively small. Workforce supply growth lags markedly behind demand, with the supply-demand gap under the adjusted measure widening from 1.58(steady-state distribution scenario)~1.60(policy development scenario)million in 2020 to 3.12(steady-state distribution scenario)~3.16(policy development scenario)million in 2023.

    These findings show that LTC workforce pressures reflect both expanding demand and structural differentiation across disability levels and care settings. Future workforce planning should therefore balance supply expansion with structural optimization: while broadening training and employment channels and improving occupational protection to enhance supply capacity, it should also allocate human resources rationally across disability levels and care settings, and improve service efficiency through digital and intelligent technologies. By distinguishing institutional elderly care from home- and community-based elderly care and their staffing mechanisms, this study extends workforce projection from aggregate estimation to structural analysis and provides targeted empirical support for long-term care system development and workforce planning in China.

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    An Actuarial Study on the Sustainability and Fiscal Responsibility of Provincial Urban and Rural Resident Long-term Care Insurance Scheme
    Yang Hongyan, Sun Mengxin, Deng Zhiyu
    Population Research    2026, 50 (5): 20-37.  
    Abstract (1137)            Save
    Since 2026, China's long-term care insurance (LTCI) scheme has shifted from local pilots to nationwide implementation. Amid moderate population aging, nationwide LTCI is essential for equitable access to care for people with disabilities and the sustainable development of an aging society. The Urban and Rural Resident LTCI scheme covers non-employed residents and is financed by individual contributions and government subsidies. This study examines fund balances, regional disparities, and central-local fiscal responsibilities across 31 provincial-level regions in Chinese mainland during 2026-2036.

    The data and methods are as follows. First, using China's 2020 Seventh National Population Census and statistical yearbooks, the cohort-component method is employed to project population by urban-rural residence, age, and sex, accounting for urbanization and interprovincial migration. Second, using the 2018 and 2020 waves of the China Health and Retirement Longitudinal Study (CHARLS), a Markov model is constructed based on six activities of daily living (ADLs). Transition probabilities are estimated among five states—independent, mildly disabled, moderately disabled, severely disabled, and deceased—to project disability prevalence among the older population. Third, based on China's existing LTCI pilot policies, annual benefits under the low, medium, and high scenarios are set at 10%, 20%, and 30% of each province's previous-year per capita disposable income, respectively. In accordance with Chinese policies, the 31 provinces are grouped into five tiers. The central government covers 80%, 60%, 50%, 30%, and 10% of government subsidies in these tiers, respectively, with local governments covering the remainder. Fourth, national and provincial policies guide enrollment and contribution rates. Fund revenue, expenditure, balances, and government subsidies are estimated to assess provincial financial sustainability and central-local fiscal responsibilities.

    The findings are as follows. First, provincial financial sustainability under the medium-benefit scenario falls into five categories, whereas the high-benefit scenario increases the number of provinces experiencing deficits. Population aging, the size of the adult contributing population, enrollment rates, contribution rates, and benefit levels explain regional disparities. Second, central subsidies as shares of central general public budget revenue, expenditure, and outstanding central government debt peak in 2033 at 0.181%, 0.415%, and 0.046%, respectively. Tiered central subsidies alleviate local fiscal burdens but cannot eliminate structural pressures in regions experiencing advanced population aging and net population outflows.

    Policy recommendations include shortening the contribution-rate transition period or temporarily increasing contribution rates in regions with persistent deficits. For provinces with limited fiscal capacity, annual benefit caps should initially be set at 30% of residents' previous-year per capita disposable income, while benefit levels should reflect care costs and actuarial balance. Fiscal burden-sharing should account for demographic structure and fiscal constraints while strengthening provincial pooling and interregional transfers.

    This study makes three contributions. First, it extends analysis from local pilots to all provincial-level regions and identifies regional differentiation driven by demographics, financing capacity, institutional parameters, and fiscal capacity. Second, it addresses the understudied resident LTCI scheme and redefines its funding sources under current policies, aligning actuarial assumptions with institutional arrangements. Third, it develops an actuarial framework linking fund operations to fiscal responsibilities. These findings inform enrollment expansion, contribution rates, benefit levels, fiscal capacity assessment, and intergovernmental burden-sharing to promote equitable access to basic long-term care.

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    From Payment to Supply: The Impact of Long-term Care Insurance Expansion on the Growth of Elderly Care Institution Beds
    Liu Xiaoting, Wang Yanru, Ma Xinye
    Population Research    2026, 50 (5): 38-52.  
    Abstract (1074)            Save
    Against the backdrop of rapid population ageing and the rising demand for long-term care services, establishing a stable and sustainable long-term care system has become an important component of actively responding to population ageing. As an institutional arrangement designed to provide social risk-sharing protection for individuals with long-term care needs, long-term care insurance (LTCI) may not only alleviate households' financial constraints in obtaining care services but also influence the development of formal care supply. However, whether and how LTCI expansion generates supply-side responses in the elderly care service sector remains insufficiently understood. This study examines the impact of LTCI expansion on the supply of elderly care institution beds and explores the conditions under which such effects emerge.

    Using an unbalanced city-level panel dataset covering 2012-2016 and 2021-2023, this study regards the nationwide expansion of LTCI pilot programs in 2020 as a quasi-natural experiment and employs a difference-in-differences model to identify the causal effect of LTCI expansion on elderly care institution bed supply. The main sample excludes cities that had implemented LTCI before 2020 and compares cities newly included in the 2020 expansion with cities that had not introduced LTCI by 2023.

    The results show that LTCI expansion is associated with a statistically significant increase in the absolute number of elderly care institution beds. In the fully controlled specification, newly added pilot cities had, on average, about 3535 more beds during 2021-2023 relative to non-pilot cities. The results remain robust after the robustness tests including sample restrictions, inverse-probability weighting, placebo timing tests, and random reassignment of treatment status. Further analysis shows that the number of elderly care institutions increased, whereas average beds per institution did not change significantly. The expansion therefore mainly took the form of an increase in the number of institutions rather than the enlargement of existing institutions. Heterogeneity analyses show that the positive bed response is concentrated in cities with stronger pre-policy elderly care service foundations and greater fiscal capacity. Cities with higher levels of population ageing do not display a stronger response, indicating that demographic demand alone does not necessarily translate into additional institutional capacity.

    This study contributes to the literature in several ways. First, it shifts the analysis of LTCI to city-level provider capacity, providing evidence on the supply-side consequences of a demand-side social insurance program. Second, by distinguishing between increases in the number of institutions and enlargement of existing institutions, the study identifies the main form through which elderly care bed capacity expands following policy implementation. Third, the study places demographic demand and local supply-side conditions within a unified analytical framework and shows that stronger ageing pressure does not automatically translate into a larger supply response. The effectiveness of LTCI in promoting elderly care supply depends on whether local governments and service systems possess sufficient institutional foundations and fiscal capacity to absorb the increased demand generated by insurance coverage. Finally, the findings provide empirical evidence for understanding the broader supply-side effects of LTCI and offer policy implications for improving long-term care systems in the context of population ageing.

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