How the Growing Gap in Life Expectancy May Affect Retirement Benefits and Reforms

  • Alan J. Auerbach
  • Kerwin K. Charles
  • Courtney C. CoileEmail author
  • William Gale
  • Dana Goldman
  • Ronald Lee
  • Charles M. Lucas
  • Peter R. Orszag
  • Louise M. Sheiner
  • Bryan Tysinger
  • David N. Weil
  • Justin Wolfers
  • Rebeca Wong


Older Americans have experienced dramatic gains in life expectancy in recent decades, but an emerging literature reveals that these gains are accumulating mostly to those at the top of the income distribution. We explore how growing inequality in life expectancy affects lifetime benefits from Social Security, Medicare and other programmes and how this phenomenon interacts with possible programme reforms. We first project that life expectancy at age 50 for males in the two highest income quintiles will rise by seven to eight years between the 1930 and 1960 birth cohorts, but that the two lowest income quintiles will experience little to no increase over that time period. This divergence in life expectancy will cause the gap between average lifetime programme benefits received by men in the highest and lowest quintiles to widen by US$130,000 (in US$2009) over this period. Finally, we simulate the effect of Social Security reforms such as raising the normal retirement age and changing the benefit formula to see whether they mitigate or enhance the reduced progressivity resulting from the widening gap in life expectancy.


demographic trends inequality government expenditures social security 



This paper draws on a report produced by the National Academies of Sciences’ Committee on the Long-Run Macroeconomic Effects of the Aging U.S. Population—Phase II, of which Lee and Orszag were co-chairs and the other authors were Members (except Tysinger, on staff at the Roybal Center). The authors thank Staff Director Kevin Kinsella for his support of the Committee’s work and staff at the Roybal Center for Health Policy Simulation, Leonard D. Schaeffer Center for Health Policy and Economics, University of Southern California for assistance with the Future Elderly Model simulations. Computation for the work described in this paper was supported by the University of Southern California’s Center for High-Performance Computing (


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Copyright information

© The International Association for the Study of Insurance Economics 2017

Authors and Affiliations

  • Alan J. Auerbach
    • 1
  • Kerwin K. Charles
    • 2
  • Courtney C. Coile
    • 3
    Email author
  • William Gale
    • 4
  • Dana Goldman
    • 5
  • Ronald Lee
    • 1
  • Charles M. Lucas
    • 6
  • Peter R. Orszag
    • 7
  • Louise M. Sheiner
    • 4
  • Bryan Tysinger
    • 5
  • David N. Weil
    • 8
  • Justin Wolfers
    • 9
  • Rebeca Wong
    • 10
  1. 1.University of CaliforniaBerkeleyUSA
  2. 2.University of ChicagoChicagoUSA
  3. 3.Department of EconomicsWellesley CollegeWellesleyUSA
  4. 4.Brookings InstitutionWashingtonUSA
  5. 5.University of Southern CaliforniaLos AngelesUSA
  6. 6.Osprey Point ConsultingDeer IsleUSA
  7. 7.LazardNew YorkUSA
  8. 8.Brown UniversityProvidenceUSA
  9. 9.University of MichiganAnn ArborUSA
  10. 10.University of TexasGalvestonUSA

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