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The Persistence and Heterogeneity of Health among Older Americans

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  • Florian Heiss
  • Steven F. Venti
  • David A. Wise

Abstract

We consider how age-health profiles differ by demographic characteristics such as education, race, and ethnicity. A key feature of the analysis is the joint estimation of health and mortality to correct for the effect of mortality selection on observed age-health profiles. The model also allows for heterogeneity in individual health at a point in time and the persistence of the unobserved component of health over time. The observed component of health is based on a multidimensional index based on 27 indicators of health. Most of the key results are shown by simulations that illustrate the range of issues that can be addressed using the model. Differences in health by education and racial-ethnic group at age 50 persist throughout the remainder of life. Based on observed profiles, the health of whites is about 8 percentile points greater than the health of blacks at age 50 but by age 90 the gap is only 5 percentile points. However, when corrected for mortality selection, the health of blacks is actually declining more rapidly with age than the health of whites; the true gap widens with age. We also find that much of the difference in age-health profiles by racial-ethnic group is accounted for by differences in the levels of education between race-ethnic groups--from two-thirds to 85 percent for men and about half for women. We also simulate differences in survival probabilities by level of education and health and use these probabilities to calculate the expected present discounted value (EPDV) of an immediate annuity with first payout at age 66 for persons by gender, level of education, and health decile. The range of EPDVs is over two-fold for both men and women suggesting enormous potential for adverse selection.

Suggested Citation

  • Florian Heiss & Steven F. Venti & David A. Wise, 2014. "The Persistence and Heterogeneity of Health among Older Americans," NBER Working Papers 20306, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20306
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    References listed on IDEAS

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    1. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389.
    2. Michael Baker & Mark Stabile & Catherine Deri, 2004. "What Do Self-Reported, Objective, Measures of Health Measure?," Journal of Human Resources, University of Wisconsin Press, vol. 39(4).
    3. Heiss, Florian & Winschel, Viktor, 2008. "Likelihood approximation by numerical integration on sparse grids," Journal of Econometrics, Elsevier, vol. 144(1), pages 62-80, May.
    4. Anne Case & Christina Paxson, 2005. "Sex differences in morbidity and mortality," Demography, Springer;Population Association of America (PAA), vol. 42(2), pages 189-214, May.
    5. Paul Contoyannis & Andrew M. Jones & Nigel Rice, 2004. "The dynamics of health in the British Household Panel Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(4), pages 473-503.
    6. Florian Heiss & Axel Börsch-Supan & Michael Hurd & David A. Wise, 2009. "Pathways to Disability: Predicting Health Trajectories," NBER Chapters, in: Health at Older Ages: The Causes and Consequences of Declining Disability among the Elderly, pages 105-150, National Bureau of Economic Research, Inc.
    7. Florian Heiss, 2006. "Nonlinear State-Space Models for Microeconometric Panel Data," Computing in Economics and Finance 2006 285, Society for Computational Economics.
    8. Hernández-Quevedo, Cristina & Jones, Andrew M. & Rice, Nigel, 2008. "Persistence in health limitations: A European comparative analysis," Journal of Health Economics, Elsevier, vol. 27(6), pages 1472-1488, December.
    9. Florian Heiss, 2011. "Dynamics of self-rated health and selective mortality," Empirical Economics, Springer, vol. 40(1), pages 119-140, February.
    10. Andrew M. Jones & Xander Koolman & Nigel Rice, 2006. "Health‐related non‐response in the British Household Panel Survey and European Community Household Panel: using inverse‐probability‐weighted estimators in non‐linear models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 543-569, July.
    11. Crossley, Thomas F. & Kennedy, Steven, 2002. "The reliability of self-assessed health status," Journal of Health Economics, Elsevier, vol. 21(4), pages 643-658, July.
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    Cited by:

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    3. Watson, Dorothy & Kenny, Oona & McGinnity, Frances & Russell, Helen, 2017. "A social portrait of Travellers in Ireland," Research Series, Economic and Social Research Institute (ESRI), number RS56, June.

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    More about this item

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I19 - Health, Education, and Welfare - - Health - - - Other
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination

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