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Pathways to Disability: Predicting Health Trajectories

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  • Florian Heiss

    ()

  • Axel Börsch-Supan

    ()

  • Michael Hurd
  • David Wise

    (Munich Center for the Economics of Aging (MEA))

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.

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Bibliographic Info

Paper provided by Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy in its series MEA discussion paper series with number 07131.

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Date of creation: 03 Jul 2007
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Handle: RePEc:mea:meawpa:07131

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Postal: Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy, Amalienstraße 33, 80799 München, Germany
Phone: +49/89/38602.442
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Web page: http://www.mea.mpisoc.mpg.de/

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References

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  1. Axel H. Boersch-Supan, 2001. "Incentive Effects of Social Security under an Uncertain Disability Option," NBER Chapters, in: Themes in the Economics of Aging, pages 281-310 National Bureau of Economic Research, Inc.
  2. Michaud, Pierre-Carl & van Soest, Arthur, 2008. "Health and wealth of elderly couples: Causality tests using dynamic panel data models," Journal of Health Economics, Elsevier, vol. 27(5), pages 1312-1325, September.
  3. 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.
  4. Jonathan Meer & Douglas L. Miller & Harvey S. Rosen, 2003. "Exploring the Health-Wealth Nexus," NBER Working Papers 9554, National Bureau of Economic Research, Inc.
  5. Gruber, Jonathan & Wise, David A. (ed.), 1999. "Social Security and Retirement around the World," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226310114.
  6. Florian Heiss, 2006. "Nonlinear State-Space Models for Microeconometric Panel Data," Computing in Economics and Finance 2006 285, Society for Computational Economics.
  7. Michael Hurd & Daniel McFadden & Angela Merrill, 1999. "Predictors of Mortality Among the Elderly," NBER Working Papers 7440, National Bureau of Economic Research, Inc.
  8. Michael Hurd & Arie Kapteyn, 2003. "Health, Wealth, and the Role of Institutions," Journal of Human Resources, University of Wisconsin Press, vol. 38(2).
  9. James P. Smith, 2004. "Unravelling the SES health connection," IFS Working Papers W04/02, Institute for Fiscal Studies.
  10. 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.
  11. Adda, Jerome & Chandola, Tarani & Marmot, Michael, 2003. "Socio-economic status and health: causality and pathways," Journal of Econometrics, Elsevier, vol. 112(1), pages 57-63, January.
  12. Paul Contoyannis & Andrea M Jones, . "Socioeconomic Status, Health and Lifestyle," Discussion Papers 01/19, Department of Economics, University of York.
  13. Borg, Vilhelm & Kristensen, Tage S., 2000. "Social class and self-rated health: can the gradient be explained by differences in life style or work environment?," Social Science & Medicine, Elsevier, vol. 51(7), pages 1019-1030, October.
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Cited by:
  1. Florian Heiss, 2006. "Nonlinear State-Space Models for Microeconometric Panel Data," Computing in Economics and Finance 2006 285, Society for Computational Economics.
  2. 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.
  3. 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.
  4. 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.
  5. Florian Heiss, 2011. "Dynamics of self-rated health and selective mortality," Empirical Economics, Springer, vol. 40(1), pages 119-140, February.

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