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Modeling and Forecasting Health Expectancy: Theoretical Framework and Application

Author

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  • Istvan Majer

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  • Ralph Stevens
  • Wilma Nusselder
  • Johan Mackenbach
  • Pieter Baal

Abstract

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

Suggested Citation

  • Istvan Majer & Ralph Stevens & Wilma Nusselder & Johan Mackenbach & Pieter Baal, 2013. "Modeling and Forecasting Health Expectancy: Theoretical Framework and Application," Demography, Springer;Population Association of America (PAA), vol. 50(2), pages 673-697, April.
  • Handle: RePEc:spr:demogr:v:50:y:2013:i:2:p:673-697
    DOI: 10.1007/s13524-012-0156-2
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    References listed on IDEAS

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    1. 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.
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    5. Kevin Dowd & David Blake & Andrew Cairns, 2010. "Facing up to uncertain life expectancy: The longevity fan charts," Demography, Springer;Population Association of America (PAA), vol. 47(1), pages 67-78, February.
    6. Anja De Waegenaere & Bertrand Melenberg & Ralph Stevens, 2010. "Longevity Risk," De Economist, Springer, vol. 158(2), pages 151-192, June.
    7. 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.
    8. 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.
    9. 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.
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    1. repec:bla:jrinsu:v:84:y:2017:i:s1:p:319-343 is not listed on IDEAS
    2. Vermeer, Niels & Mastrogiacomo, Mauro & Van Soest, Arthur, 2016. "Demanding occupations and the retirement age," Labour Economics, Elsevier, vol. 43(C), pages 159-170.

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