Demography

, Volume 48, Issue 4, pp 1377–1400 | Cite as

Differential Survival in Europe and the United States: Estimates Based on Subjective Probabilities of Survival

Article

Abstract

Cross-country comparisons of differential survival by socioeconomic status (SES) are useful in many domains. Yet, to date, such studies have been rare. Reliably estimating differential survival in a single country has been challenging because it requires rich panel data with a large sample size. Cross-country estimates have proven even more difficult because the measures of SES need to be comparable internationally. We present an alternative method for acquiring information on differential survival by SES. Rather than using observations of actual survival, we relate individuals’ subjective probabilities of survival to SES variables in cross section. To show that subjective survival probabilities are informative proxies for actual survival when estimating differential survival, we compare estimates of differential survival based on actual survival with estimates based on subjective probabilities of survival for the same sample. The results are remarkably similar. We then use this approach to compare differential survival by SES for 10 European countries and the United States. Wealthier people have higher survival probabilities than those who are less wealthy, but the strength of the association differs across countries. Nations with a smaller gradient appear to be Belgium, France, and Italy, while the United States, England, and Sweden appear to have a larger gradient.

Keywords

Differential survival Differential mortality Subjective probabilities Cross-country comparison 

Supplementary material

13524_2011_66_MOESM1_ESM.doc (822 kb)
ESM 1 (DOC 822 kb)

References

  1. Adams, P., Hurd, M., McFadden, D., Merrill, A., & Ribeiro, T. (2003). Healthy, wealthy, and wise? Tests for direct causal paths between health and socioeconomic status. Journal of Econometrics, 112, 3–56.CrossRefGoogle Scholar
  2. Attanasio, O., & Emmerson, C. (2003). Differential mortality in the UK. Journal of the European Economic Association, 1, 821–850.CrossRefGoogle Scholar
  3. Attanasio, O. P., & Hoynes, H. W. (2000). Differential mortality and wealth accumulation. Journal of Human Resources, 35, 1–29.CrossRefGoogle Scholar
  4. Bloom, D., Canning, D., Moore, M., & Song, Y. (2007). The effect of subjective survival probabilities on retirement and wealth in the United States. In R. Clark, A. Mason, & N. Ogawa (Eds.), Population aging, intergenerational transfers and the macroeconomy (pp. 67–100). Northampton, MA: Elgar Press.Google Scholar
  5. Bommier, A., Magnac, T., Rapoport, B., & Roger, M. (2006). Droit a la retraite et mortalite differentielle [Pension entitlement and differential mortality]. Économie et Prévision, 168, 1–16.Google Scholar
  6. Börsch-Supan, A., & Jürges, H. (Eds.). (2005). The survey of health, aging, and retirement in Europe – methodology. Mannheim, Germany: Mannheim Research Institute for the Economics of Aging.Google Scholar
  7. Börsch-Supan, A., & Mariuzzo, F. (2005). Our sample: 50+ in Europe. In A. Börsch-Supan, A. Brugiavini, H. Jürges, J. Mackenbach, J. Siegrist, & G. Weber (Eds.), Health ageing and retirement in Europe: First results from the survey of health, ageing and retirement in Europe (pp. 30–34). Mannheim, Germany: Mannheim Research Institute for the Economics of Aging.Google Scholar
  8. Bruine de Bruin, W., Fischhoff, B., Millstein, S., & Halpern-Felsher, L. (2000). Verbal and numerical expressions of probability. “It’s a fifty-fifty chance.” Organizational Behavior and Human Decision Processes, 81, 115–131.CrossRefGoogle Scholar
  9. Deaton, A., & Paxson, C. (2001). Mortality, education, income, and inequality among American cohorts. In D. Wise (Ed.), Themes in the economics of aging (pp. 129–147). Chicago, IL: Chicago University Press for NBER.Google Scholar
  10. Deaton, A., & Paxson, C. (2004). Mortality, income, and income inequality over time in Britain and the US. In D. Wise (Ed.), Perspectives in the economics of aging (pp. 247–286). Chicago, IL: University of Chicago Press.Google Scholar
  11. Delavande, A., & Willis, R. J. (2008). Managing the risk of life (Michigan Retirement Research Center Working Paper No. 2007–167). Ann Arbor: Michigan Retirement Research Center, University of Michigan.Google Scholar
  12. Desplanques, G. (1991). Les cadres vivent plus vieux [Executives live longer]. INSEE Premieres, 158, 1–4.Google Scholar
  13. Duleep, H. (1986). Measuring the effect of income on adult mortality using longitudinal administrative record data. Journal of Human Resources, 21, 238–251.CrossRefGoogle Scholar
  14. Duleep, H. (1989). Measuring socioeconomic mortality differentials over time. Demography, 26, 345–351.CrossRefGoogle Scholar
  15. Elder, T. E. (2007). Subjective survival probabilities in the Health and Retirement Study: Systematic biases and predictive validity (Michigan Retirement Research Center Working Paper No. 2007–159). Ann Arbor: Michigan Retirement Research Center, University of Michigan.Google Scholar
  16. Feldman, J., Makuc, D., Kleinman, J., & Cornoni-Huntley, J. (1989). National trends in educational differences in mortality. American Journal of Epidemiology, 129, 919–933.Google Scholar
  17. Hill, D., Perry, M., & Willis, R. J. (2006). Estimating Knightian uncertainty from survival probability questions on the HRS (Working paper). Ann Arbor: Department of Economics, University of Michigan.Google Scholar
  18. Hoffmann, R. (2005). Does the socioeconomic mortality gradient interact with age? Evidence from US survey data and Danish register data (MPIDR Working Paper WP 2005–020). Rostock, Germany: Max Planck Institute for Demographic Research.Google Scholar
  19. Huisman, M., Anton, K., Andersen, O., Bopp, M., Borgan, J. K., Borrell, C., . . . Mackenbach, J. P. (2004). Socioeconomic inequalities in mortality among elderly people in 11 European populations. Journal of Epidemiology and Community Health, 58, 468–475.Google Scholar
  20. Hurd, M., & McGarry, K. (1995). Evaluation of the subjective probabilities of survival in the health and retirement study. Journal of Human Resources, 30, S268–S292.CrossRefGoogle Scholar
  21. Hurd, M., & McGarry, K. (2002). The predictive validity of the subjective probabilities of survival. The Economic Journal, 112, 966–985.CrossRefGoogle Scholar
  22. Hurd, M., Rohwedder, S., & Winter, J. (2005). Subjective probabilities of survival: An international comparison (Unpublished manuscript). Santa Monica, CA: RAND.Google Scholar
  23. Hurd, M., Smith, J., & Zissimopoulos, J. (2004). The effects of subjective survival on retirement and Social Security claiming. Journal of Applied Econometrics, 19, 761–775.Google Scholar
  24. Juster, F. T., & Suzman, R. (1995). An overview of the health and retirement study. Journal of Human Resources, 30, S7–S56.CrossRefGoogle Scholar
  25. Kunst, A., & Mackenbach, J. (1994a). International variation in the size of mortality differences associated with occupational status. International Journal of Epidemiology, 33, 742–750.CrossRefGoogle Scholar
  26. Kunst, A., & Mackenbach, J. (1994b). The size of mortality differences associated with educational level in nine industrialized countries. American Journal of Public Health, 84, 932–937.CrossRefGoogle Scholar
  27. Lillard, L., & Willis, R. J. (2002). Cognition and wealth: The importance of probabilistic thinking (Michigan Retirement Research Center Working Paper UM00-04). Ann Arbor: Michigan Retirement Research Center, University of Michigan.Google Scholar
  28. Lleras-Muney, A. (2005). The relationship between education and adult mortality in the United States. The Review of Economic Studies, 72, 189–221.CrossRefGoogle Scholar
  29. Mackenbach, J., Bos, V., Andersen, O., Cardano, M., Costa, G., Harding, S., . . . Kunst, A. (2003). Widening socioeconomic inequalities in mortality in six western European countries. International Journal of Epidemiology, 32, 830–837.Google Scholar
  30. Mackenbach, J., Kunst, A., Cavelaars, A., Groenhof, F., Geurts, J., & the EU Working Group on Socioeconomic Inequalities in Health. (1997). Socioeconomic inequalities in morbidity and mortality in Western Europe. Lancet, 349, 1655–1659.CrossRefGoogle Scholar
  31. Manski, C. F. (2004). Measuring expectations. Econometrica, 72, 1329–1376.CrossRefGoogle Scholar
  32. Marmot, M. (1999). Multi-level approaches to understanding social determinants. In L. Berkman & I. Kawachi (Eds.), Social epidemiology (pp. 349–367). Oxford, UK: Oxford University Press.Google Scholar
  33. Martikainen, P. (1995). Socioeconomic mortality differentials in men and women according to own and spouse’s characteristics in Finland. Sociology of Health & Illness, 17, 353–375.CrossRefGoogle Scholar
  34. Nelissen, J. H. M. (1999). Mortality differences related to socioeconomic status and the progressivity of old-age pensions and health insurance: The Netherlands. European Journal of Population, 15, 77–97.Google Scholar
  35. Papke, L. E., & Wooldridge, J. M. (1996). Econometric methods for fractional response variables with an application to 401(k) plan participation rates. Journal of Applied Econometrics, 11, 619–632.CrossRefGoogle Scholar
  36. Perozek, M. (2008). Using subjective expectations to forecast longevity: Do survey respondents know something we don’t know? Demography, 45, 95–113.CrossRefGoogle Scholar
  37. Rantanen, T., Guralnik, J. M., Foley, D., Masaki, K., Leveille, S., Curb, J. D., & White, L. (1999). Midlife hand grip strength as a predictor of old age disability. Journal of the American Medical Association, 281, 558–560.Google Scholar
  38. Siegel, M., Bradley, E. H., & Kasl, S. (2003). Self-rated life expectancy as a predictor of mortality: Evidence from the HRS and AHEAD surveys. Gerontology, 49, 265–271.CrossRefGoogle Scholar
  39. Smith, K., Taylor, D., & Sloan, F. (2001). Longevity and expectations: Can people predict their own demise? The American Economic Review, 91, 1126–1134.CrossRefGoogle Scholar
  40. St. Clair, P., Blake, D., Bugliari, D., Chien, S., Hayden, O., Hurd, M., . . . Zissimopoulos, J. (2008). RAND HRS Data Documentation, Version H. Santa Monica, CA: RAND Labor and Population and RAND Center for the Study of Aging.Google Scholar
  41. Valkonen, T., Martikainen, P., Jalovaara, M., Koskinen, S., Martelin, T., & Mäkelä, P. (2000). Changes in socioeconomic inequalities in male mortality during economic boom and recession in Finland. European Journal of Public Health, 10, 274–280.CrossRefGoogle Scholar
  42. Winter, J. (2008). Expectations and attitudes. In A. Börsch-Supan, A. Brugiavini, H. Jürges, A. Kapteyn, J. Mackenbach, J. Siegrist, & G. Weber (Eds.), First results from the Survey of Health, Ageing and Retirement in Europe 2004–2007 (pp. 306–311). Mannheim, Germany: Mannheim Research Institute for the Economics of Aging.Google Scholar

Copyright information

© Population Association of America 2011

Authors and Affiliations

  1. 1.RAND Corporation and Nova School of Business and Economics and University of EssexEssexUK
  2. 2.RAND Corporation and NETSPARSanta MonicaUSA

Personalised recommendations