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The Evolution of Health over the Life Cycle

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  • Roozbeh Hosseini

    (University of Georgia)

  • Kai Zhao

    (University of Connecticut)

  • Karen Kopecky

    (Federal Reserve Bank of Atlanta)

Abstract

Recent studies have identified health dynamics and health shocks as major sources of risk over the life cycle. Health has implications for many economic variables includ- ing asset accumulation, labor supply, and income and wealth inequality. Despite the importance of health in economic studies, there is no unified objective measure of health status. In this paper we propose such a measure: frailty, defined as the cumulative sum of all adverse health indicators observed for an individual. There is overwhelming evidence in the gerontology literature that this simple measure is a strong predictor of mortality and other health outcomes. We construct a frailty index for individuals in the PSID, HRS and MEPS separately and make the following three observations. One, our constructed frailty index is remarkably consistent across the three datasets in terms of persistence, and dynamics of its distribution. This is in contrast to the most commonly used measure of health, self-reported health status. Two, individuals’ health decays at a substantially faster pace over the lifecycle when measured by frailty as opposed to self-reported health status. Three, health status is more persistent when measured by frailty as opposed to self reported health status. We estimate a dynamic process for frailty over the life cycle and show that an important driver of increasing inequality in health with age is dispersion in growth rates of frailty across individuals. Our frailty measure and dynamic process can be used by economists to study the evolution of health status over the life cycle and its implications.

Suggested Citation

  • Roozbeh Hosseini & Kai Zhao & Karen Kopecky, 2018. "The Evolution of Health over the Life Cycle," 2018 Meeting Papers 977, Society for Economic Dynamics.
  • Handle: RePEc:red:sed018:977
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    Cited by:

    1. Tianxu Chen, 2019. "Can Health Savings Account Reduce Health Spending?: Evidence from China," Working papers 2019-08, University of Connecticut, Department of Economics.
    2. Umesh Ghimire, 2020. "The Impact of Health on Wealth: Empirical Evidence," Working papers 2020-19, University of Connecticut, Department of Economics.
    3. Johannes Schünemann & Holger Strulik & Timo Trimborn, 2021. "Optimal Demand for Medical and Long-Term Care," Economics Working Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    4. Dragone, Davide & Strulik, Holger, 2020. "Negligible senescence: An economic life cycle model for the future," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 264-285.
    5. Abeliansky, Ana & Strulik, Holger, 2020. "Health and aging before and after retirement," Center for European, Governance and Economic Development Research Discussion Papers 397, University of Goettingen, Department of Economics.
    6. Strulik, Holger, 2021. "Intertemporal choice with health-dependent discounting," Mathematical Social Sciences, Elsevier, vol. 111(C), pages 19-25.
    7. Abeliansky, Ana Lucia & Erel, Devin & Strulik, Holger, 2019. "Aging in the USA: Similarities and disparities across time and space," Center for European, Governance and Economic Development Research Discussion Papers 384, University of Goettingen, Department of Economics.

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    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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