Advertisement

Demography

, Volume 45, Issue 1, pp 95–113 | Cite as

Using subjective expectations to forecast longevity: do survey respondents know something we don’t know?

  • Maria Perozek
Article

Abstract

Old-age mortality is notoriously dif cult to predict because it requires not only an understanding of the process of senescence—which is influenced by genetic, environmental, and behavioral factors—but also a prediction of how these factors will evolve. In this paper, I argue that individuals are uniquely qualified to predict their own mortality based on their own genetic background, as well as environmental and behavioral risk factors that are often known only to the individual. Given this private information, individuals form expectations about survival probabilities that may provide additional information to demographers and policymakers in their challenge to predict mortality. From expectations data from the 1992 Health and Retirement Study (HRS), I construct subjective, cohort life tables that are shown to predict the unusual direction of revisions to U.S. life expectancy by gender between 1992 and 2004: that is, for these cohorts, the Social Security Actuary (SSA) raised male life expectancy in 2004 and at the same lowered female life expectancy, narrowing the gender gap in longevity by 25% over this period. Further, although the subjective life expectancies for men appear to be roughly in line with the 2004 life tables, the subjective expectations of women suggest that female life expectancies estimated by the SSA might still be on the high side.

Keywords

Survival Probability Life Table Survivor Function Subjective Expectation Female Life Expectancy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bassett, W. and R. Lumsdaine. 2001.“Probability Limits—Are Subjective Assessments Adequately Accurate?” Journal of Human Resources 36:327–63.CrossRefGoogle Scholar
  2. Bell, F., A. Wade, and S. Goss. 1992. “Life Tables for the United States Social Security Area 1900-2080.” Actuarial Study No. 107, U.S. Department of Health and Human Services, Social Security Administration, Office of the Actuary.Google Scholar
  3. Bernheim, B.D. 1989. “The Timing of Retirement: A Comparison of Expectations and Realizations.” Pp. 335–55 in The Economics of Aging, edited by D. Wise. Chicago: The University of Chicago Press.Google Scholar
  4. — 1990. “How do the Elderly Form Expectations: An Analysis of Responses to New Information.” Pp. 259–83 in Issues in the Economics of Aging, edited by D. Wise. Chicago: The University of Chicago Press.Google Scholar
  5. Cutler, D. and E. Meara. 2004. “Changes in the Age Distribution of Mortality Over the Twentieth Century.” Pp. 333–65 in Perspectives on the Economics of Aging, edited by D. Wise. Chicago: The University of Chicago Press.Google Scholar
  6. Dominitz, J. 1998. “Earnings Expectations, Revisions, and Realizations.” The Review of Economics and Statistics 80:374–88.CrossRefGoogle Scholar
  7. Dominitz, J. and C. Manski. 1997. “Using Expectations Data to Study Subjective Income Expectations.” Journal of the American Statistical Association 2:855–62.CrossRefGoogle Scholar
  8. Economos, A. 1982. “Rate of Aging, Rate of Dying, and the Mechanism of Mortality.” Archives of Gerontological Geriatrics 1:3–27.CrossRefGoogle Scholar
  9. Gan, L., M. Hurd, and D. McFadden. 2003. “Individual Subjective Survival Curves.” NBER Working Paper 9480. National Bureau of Economic Research, Cambridge, MA.Google Scholar
  10. Hamermesh, D. 1985. “Expectations, Life Expectancy, and Economic Behavior.” Quarterly Journal of Economics 100(2):389–408.CrossRefGoogle Scholar
  11. Hurd, M. and K. McGarry. 1995. “Evaluation of the Subjective Probabilities of Survival in the Health and Retirement Study.” Journal of Human Resources 30(Suppl.):S268-S292.CrossRefGoogle Scholar
  12. — 2002. “The Predictive Validity of Subjective Probabilities of Survival.” The Economic Journal 112:966–85.CrossRefGoogle Scholar
  13. Juster, F.T. and R. Suzman. 1995. “An Overview of the Health and Retirement Study.” Journal of Human Resources 30(Suppl.):S7-S56.CrossRefGoogle Scholar
  14. Lawless, J.F. 1982. Statistical Models and Methods for Lifetime Data. New York: John Wiley & Sons.Google Scholar
  15. Lee, R. 2003. “The Demographic Transition: Three Centuries of Fundamental Change.” Journal of Economic Perspectives 17(4):167–90.CrossRefGoogle Scholar
  16. Leveille, S.G., B.W.J.H. Penninx, D. Melzer, G. Izmirlian, and J.M. Guralnik, 2000. “Sex Differences in the Prevalence of Mobility Disability in Old Age: The Dynamics of Incidence, Recovery, and Mortality.” Journal of Gerontology: Social Sciences 55B(1):S41-S50.Google Scholar
  17. Manski, C. 1990. “The Use of Intentions Data to Predict Behavior: A Best Case Analysis.” Journal of the American Statistical Association 85:934–40.CrossRefGoogle Scholar
  18. —. 2004. “Measuring Expectations.” Econometrica 72:1329–76.CrossRefGoogle Scholar
  19. Manton, K.G., E. Stallard, and H.D. Tolley. 1991. “Limits to Human Life Expectancy: Evidence, Prospects, and Implications.” Population and Development Review 17:603–37.CrossRefGoogle Scholar
  20. National Center for Health Statistics (NCHS). 2004. “Health, United States, 2004.” Hyattsville, MD: NCHS. Available online at http://www.cdc.gov/nchs/hus.htmGoogle Scholar
  21. Oeppen, J. and J. Vaupel. 2002. “Broken Limits to Life Expectancy,” Science 296:1029–31.CrossRefGoogle Scholar
  22. Olshansky, S.J. and B.A. Carnes. 2001. The Quest for Immortality: Science at the Frontiers of Aging. New York: W.W. Norton and Co.Google Scholar
  23. Pollard, A.H., F. Yusuf, and G.N. Pollard. 1990. Demographic Techniques. New York: Pergamon Press.Google Scholar
  24. Vaupel, J., A. Baudisch, M. Dolling, D. Roach, and J. Gampe. 2004.“The Case for Negative Senescence.” MPIDR Working Paper 2004-02. Max Planck Institute for Demographic Research, Rostock, Germany.Google Scholar
  25. Vaupel, J. and H. Lundstrom. 1994. “Longer Life Expectancy? Evidence From Sweden of Reductions in Mortality Rates at Advanced Ages.” Pp. 79–94 in Studies in the Economics of Aging, edited by D. Wise. Chicago: The University of Chicago Press.Google Scholar
  26. Wilson, D. 1994. “The Analysis of Survival (Mortality) Data: Fitting Gompertz, Weibull and Logistic Functions.” Mechanisms of Ageing and Development 74(1994):15–33.CrossRefGoogle Scholar

Copyright information

© Population Association of America 2008

Authors and Affiliations

  • Maria Perozek
    • 1
  1. 1.Federal Reserve Board of GovernorsNW

Personalised recommendations