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Modeling and Forecasting Health Expectancy: Theoretical Framework and Application

  • Istvan Majer

    ()

  • Ralph Stevens
  • Wilma Nusselder
  • Johan Mackenbach
  • Pieter Baal
Registered author(s):

    Life expectancy continues to grow in most Western countries; however, a major remaining question is whether longer life expectancy will be associated with more or fewer life years spent with poor health. Therefore, complementing forecasts of life expectancy with forecasts of health expectancies is useful. To forecast health expectancy, an extension of the stochastic extrapolative models developed for forecasting total life expectancy could be applied, but instead of projecting total mortality and using regular life tables, one could project transition probabilities between health states simultaneously and use multistate life table methods. In this article, we present a theoretical framework for a multistate life table model in which the transition probabilities depend on age and calendar time. The goal of our study is to describe a model that projects transition probabilities by the Lee-Carter method, and to illustrate how it can be used to forecast future health expectancy with prediction intervals around the estimates. We applied the method to data on the Dutch population aged 55 and older, and projected transition probabilities until 2030 to obtain forecasts of life expectancy, disability-free life expectancy, and probability of compression of disability. Copyright Population Association of America 2013

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    File URL: http://hdl.handle.net/10.1007/s13524-012-0156-2
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    Article provided by Springer in its journal Demography.

    Volume (Year): 50 (2013)
    Issue (Month): 2 (April)
    Pages: 673-697

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    Handle: RePEc:spr:demogr:v:50:y:2013:i:2:p:673-697
    Contact details of provider: Web page: http://www.springer.com/economics/journal/13524

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    1. Richard MacMinn & Patrick Brockett & David Blake, 2006. "Longevity Risk and Capital Markets," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(4), pages 551-557.
    2. Eileen Crimmins & Mark Hayward & Aaron Hagedorn & Yasuhiko Saito & Nicolas Brouard, 2009. "Change in disability-free life expectancy for Americans 70 years old and older," Demography, Springer, vol. 46(3), pages 627-646, August.
    3. Hyndman, Rob J. & Shahid Ullah, Md., 2007. "Robust forecasting of mortality and fertility rates: A functional data approach," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4942-4956, June.
    4. De Waegenaere, A.M.B. & Melenberg, B. & Stevens, R., 2010. "Longevity risk," Other publications TiSEM fa89b4b3-82f5-4c65-8c2c-b, Tilburg University, School of Economics and Management.
    5. Manton, Kenneth G. & Stallard, Eric & Singer, Burt, 1992. "Projecting the future size and health status of the US elderly population," International Journal of Forecasting, Elsevier, vol. 8(3), pages 433-458, November.
    6. Andrew J. G. Cairns & David Blake & Kevin Dowd, 2006. "A Two-Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(4), pages 687-718.
    7. Anja De Waegenaere & Bertrand Melenberg & Ralph Stevens, 2010. "Longevity Risk," De Economist, Springer, vol. 158(2), pages 151-192, June.
    8. repec:ner:tilbur:urn:nbn:nl:ui:12-4578387 is not listed on IDEAS
    9. Kevin Dowd & David Blake & Andrew Cairns, 2010. "Facing up to uncertain life expectancy: The longevity fan charts," Demography, Springer, vol. 47(1), pages 67-78, February.
    10. Wolfgang Lurz & Anne Goujon, 2001. "The World's Changing Human Capital Stock: Multi-State Population Projections by Educational Attainment," Population and Development Review, The Population Council, Inc., vol. 27(2), pages 323-339.
    11. Nan Li & Ronald Lee, 2005. "Coherent mortality forecasts for a group of populations: An extension of the lee-carter method," Demography, Springer, vol. 42(3), pages 575-594, August.
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