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What Determines End-of-Life Assets? A Retrospective View

In: Insights in the Economics of Aging

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  • James M. Poterba
  • Steven F. Venti
  • David A. Wise

Abstract

We consider assets when individuals were last observed prior to death in the Health and Retirement Study (HRS) and trace assets backwards to the age when these individuals were first observed. For most individuals, assets in the last year observed (LYO) were very similar to assets in the first year observed (FYO). In particular, most of those who were last observed with very low asset levels also had low assets when first observed. We also estimate the relationship between an individual’s asset change between the first and last date of observation, that individual’s education and health status when first observed, and that individual’s within-sample changes in health and family composition. We obtain estimates for HRS respondents who were 51 to 61 in 1992 and for AHEAD respondents who were age 70 and over in 1993.
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Suggested Citation

  • James M. Poterba & Steven F. Venti & David A. Wise, 2015. "What Determines End-of-Life Assets? A Retrospective View," NBER Chapters, in: Insights in the Economics of Aging, pages 127-157, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:13629
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    References listed on IDEAS

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    1. James Smith, 2005. "Consequences and Predictors of New Health Events," NBER Chapters, in: Analyses in the Economics of Aging, pages 213-240, National Bureau of Economic Research, Inc.
    2. Samuel Marshall & Kathleen McGarry & Jonathan S. Skinner, 2011. "The Risk of Out-of-Pocket Health Care Expenditure at the End of Life," NBER Chapters, in: Explorations in the Economics of Aging, pages 101-128, National Bureau of Economic Research, Inc.
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    5. Poterba, James M. & Venti, Steven F. & Wise, David A., 2017. "The asset cost of poor health," The Journal of the Economics of Ageing, Elsevier, vol. 9(C), pages 172-184.
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    Cited by:

    1. Huang, H. & Milevsky, M.A. & Salisbury, T.S., 2017. "Retirement spending and biological age," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 58-76.
    2. Huaxiong Huang & Moshe A. Milevsky & Thomas S. Salisbury, 2018. "Retirement spending and biological age," Papers 1811.09921, arXiv.org.
    3. Gale, William & Gelfond, Hilary & Fichtner, Jason, 2018. "How Will Retirement Saving Change by 2050? Prospects for the Millennial Generation," MPRA Paper 99196, University Library of Munich, Germany.
    4. Joelle Saad-Lessler & Teresa Ghilarducci & Gayle Reznik, 2017. "Defined Contribution Wealth Inequality: Role of Earnings Shocks, Portfolio Choice, and Employer Contributions," SCEPA working paper series. SCEPA's main areas of research are macroeconomic policy, inequality and poverty, and globalization. 2017-09, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    5. Teresa Ghilarducci & Joelle Saad-Lessler & Gayle Reznik, 2017. "Relative Wages in Aging America: Defined Contribution Wealth Inequality: Role of Earnings Shocks, Portfolio Choice, and Employer Contributions," SCEPA working paper series. SCEPA's main areas of research are macroeconomic policy, inequality and poverty, and globalization. 2017-06, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.

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    More about this item

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination

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