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Pathways to disability : predicting health trajectories

Author

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  • Heiss, Florian
  • Börsch-Supan, Axel
  • Hurd, Michael D.
  • Wise, David A.

Abstract

The paper considers transitions in the health and disability status of persons as they age. In particular, we explore the relationship between health and disability at younger ages (say 50) and health and disability in future ages. We consider for example, the future health path of persons who are in good health at age 50 compared to the future health path of persons who are in poor health at age 50. To do this, we develop a model that jointly considers health and mortality. The key feature of the model is the assumption of underlying “latent” health that determines both mortality and self-reported responses to categorical health and disability questions. Latent health allows for heterogeneity among individuals and allows for correlation of health status over time, thus allowing for state dependence as well as heterogeneity. The model also allows for classification errors in self-reported response to categorical health and disability questions. All of these are important features of health and disability data, as we show with descriptive data. The model accommodates the strong relationship between self-reported health status and mortality, which is critical to an understanding of the paths of health and disability of the survivors who are observed in panel data files. Our empirical analysis is based on all four cohorts of the Health and Retirement Study (HRS) -- the HRS, AHEAD, CODA and WB cohorts). We find that self-reported health and self-reported disability correspond very closely to one another in the HRS. We find that both self-reported health and disability are strong predictors of mortality. Health and disability at younger ages are strongly related to future health and disability paths of persons as they age. There are important differences in health and disability paths by education level, race, and gender.

Suggested Citation

  • Heiss, Florian & Börsch-Supan, Axel & Hurd, Michael D. & Wise, David A., 2006. "Pathways to disability : predicting health trajectories," Papers 07-30, Sonderforschungsbreich 504.
  • Handle: RePEc:mnh:spaper:2536
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    References listed on IDEAS

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    1. Börsch-Supan, Axel, 2001. "Incentive Effects of Social Security Under an Uncertain Disability Option," Sonderforschungsbereich 504 Publications 01-42, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
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    5. Florian Heiss, 2006. "Nonlinear State-Space Models for Microeconometric Panel Data," Computing in Economics and Finance 2006 285, Society for Computational Economics.
    6. Balia, Silvia & Jones, Andrew M., 2008. "Mortality, lifestyle and socio-economic status," Journal of Health Economics, Elsevier, vol. 27(1), pages 1-26, January.
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    8. Peter Adams & Michael D. Hurd & Daniel L. McFadden & Angela Merrill & Tiago Ribeiro, 2004. "Healthy, Wealthy, and Wise? Tests for Direct Causal Paths between Health and Socioeconomic Status," NBER Chapters, in: Perspectives on the Economics of Aging, pages 415-526, National Bureau of Economic Research, Inc.
    9. Meer, Jonathan & Miller, Douglas L. & Rosen, Harvey S., 2003. "Exploring the health-wealth nexus," Journal of Health Economics, Elsevier, vol. 22(5), pages 713-730, September.
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    11. Michael D. Hurd & Daniel McFadden & Angela Merrill, 2001. "Predictors of Mortality among the Elderly," NBER Chapters, in: Themes in the Economics of Aging, pages 171-198, National Bureau of Economic Research, Inc.
    12. James Smith, 2004. "Unravelling the SES health connection," IFS Working Papers W04/02, Institute for Fiscal Studies.
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    15. repec:ran:wpaper:191 is not listed on IDEAS
    16. Jonathan Gruber & David A. Wise, 1999. "Social Security and Retirement around the World," NBER Books, National Bureau of Economic Research, Inc, number grub99-1.
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    Cited by:

    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. Florian Heiss, 2011. "Dynamics of self-rated health and selective mortality," Empirical Economics, Springer, vol. 40(1), pages 119-140, February.
    3. Heiss, Florian, 2006. "Nonlinear State-Space Models for Microeconometric Panel Data," Discussion Papers in Economics 1157, University of Munich, Department of Economics.
    4. Joanna N. Lahey, 2017. "Understanding Why Black Women Are Not Working Longer," NBER Chapters, in: Women Working Longer: Increased Employment at Older Ages, pages 85-109, National Bureau of Economic Research, Inc.
    5. Florian Heiss & Daniel McFadden & Joachim Winter, 2010. "Mind the Gap! Consumer Perceptions and Choices of Medicare Part D Prescription Drug Plans," NBER Chapters, in: Research Findings in the Economics of Aging, pages 413-481, National Bureau of Economic Research, Inc.
    6. Paul L. Latreille, 2009. "Disability, Health and the Labour Market: Evidence from the Welsh Health Survey," Local Economy, London South Bank University, vol. 24(3), pages 192-210, May.
    7. Florian Heiss & Daniel McFadden & Joachim Winter, 2008. "Mind the Gap! Consumer Perceptions and Choices," MEA discussion paper series 08156, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    8. 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.

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