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A Multi-State Model of Disability for the United Kingdom: Implications for Future Need for Long-Term Care for the Elderly

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  • Rickayzen, B.D.
  • Walsh, D.E.P.

Abstract

This paper develops a multiple state model to project the number of people with disabilities in the United Kingdom over the next 35 years, thereby identifying implications for demand for long-term care for the elderly in the future. The model requires three types of data: prevalence rate data, transition rate data and trends data. Recent trends in healthy life expectancy data are used to frame the assumptions made regarding changes in the disability rates of the U.K. population in the future. Although there will be a large increase in the number of elderly people in the U.K. over the next 35 years, the projections suggest that the implications for the number of elderly people requiring long-term care could be ameliorated by a reduction in the proportion of older people who are severely disabled.

Suggested Citation

  • Rickayzen, B.D. & Walsh, D.E.P., 2002. "A Multi-State Model of Disability for the United Kingdom: Implications for Future Need for Long-Term Care for the Elderly," British Actuarial Journal, Cambridge University Press, vol. 8(2), pages 341-393, June.
    • Handle: RePEc:cup:bracjl:v:8:y:2002:i:02:p:341-393_00
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    Cited by:

    1. Carole Bonnet & Sandrine Juin & Anne Laferrère, 2019. "Private Financing of Long‑Term Care: Income, Savings and Reverse Mortgages," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 507-508, pages 5-24.
    2. Comas-Herrera, Adelina & Wittenberg, Raphael & Pickard, Linda, 2003. "Making projections of long-term care: examples and methodological issues," LSE Research Online Documents on Economics 43294, London School of Economics and Political Science, LSE Library.
    3. Guogui Huang & Fei Guo & Zhiming Cheng & Massimiliano Tani & Gong Chen, 2023. "Projections of Future Demand and Costs of Aged Care Services in China," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(4), pages 1-30, August.
    4. J. Iñaki De La Peña & M. Cristina Fernández-Ramos & Asier Garayeta, 2021. "Cost-Free LTC Model Incorporated into Private Pension Schemes," IJERPH, MDPI, vol. 18(5), pages 1-16, February.
    5. Ermanno Pitacco, 2016. "Premiums for Long-Term Care Insurance Packages: Sensitivity with Respect to Biometric Assumptions," Risks, MDPI, vol. 4(1), pages 1-22, February.
    6. 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.
    7. William Lim & Gaurav Khemka & David Pitt & Bridget Browne, 2019. "A method for calculating the implied no-recovery three-state transition matrix using observable population mortality incidence and disability prevalence rates among the elderly," Journal of Population Research, Springer, vol. 36(3), pages 245-282, September.
    8. Konstandatos, Otto, 2020. "Fair-value analytical valuation of reset executive stock options consistent with IFRS9 requirements," Annals of Actuarial Science, Cambridge University Press, vol. 14(1), pages 188-218, March.
    9. J. Iñaki De La Peña & M. Cristina Fernández-Ramos & Asier Garayeta & Iratxe D. Martín, 2022. "Transforming Private Pensions: An Actuarial Model to Face Long-Term Costs," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    10. Sandrine Juin, 2016. "Care for dependent elderly people : dealing with health and financing issues," Erudite Ph.D Dissertations, Erudite, number ph16-02 edited by Thomas Barnay.
    11. Panupong Tantirat & Repeepong Suphanchaimat & Thanit Rattanathumsakul & Thinakorn Noree, 2020. "Projection of the Number of Elderly in Different Health States in Thailand in the Next Ten Years, 2020–2030," IJERPH, MDPI, vol. 17(22), pages 1-12, November.

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