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Survival expectations, subjective health and smoking: evidence from SHARE

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  • Silvia Balia

Abstract

This article aims to assess how the risk perceptions of smokers affect survival expectations and subjective health. Data from the Survey of Health, Ageing and Retirement in Europe, which include a numerical measure of subjective survival probability, are used to estimate a joint recursive system of equations that describe the relationships among survival expectations, subjective health status and smoking duration. A finite mixture model is used to address endogeneity and unobservable heterogeneity. This approach allows for two types of individuals with different observable characteristics to be identified in the examined population. We find that only in the population of the first type, current and former smokers incorporate the effects of smoking duration into their assessments of survival probabilities. For both types, quitting smoking affects current perceptions of smoking risks, causing the overestimation of both survival probability and subjective health. Copyright Springer-Verlag Berlin Heidelberg 2014

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  • Silvia Balia, 2014. "Survival expectations, subjective health and smoking: evidence from SHARE," Empirical Economics, Springer, vol. 47(2), pages 753-780, September.
    • Handle: RePEc:spr:empeco:v:47:y:2014:i:2:p:753-780
    DOI: 10.1007/s00181-013-0750-1
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    3. Juergen Jung, 2022. "Estimating transition probabilities between health states using US longitudinal survey data," Empirical Economics, Springer, vol. 63(2), pages 901-943, August.
    4. Sunde, Uwe, 2023. "Age, longevity, and preferences," The Journal of the Economics of Ageing, Elsevier, vol. 24(C).
    5. Frank A. Sloan, 2024. "Subjective beliefs, health, and health behaviors," Journal of Risk and Uncertainty, Springer, vol. 69(2), pages 105-144, October.
    6. Adeline Delavande & Jinkook Lee & Seetha Menon, 2017. "Eliciting Survival Expectations of the Elderly in Low-Income Countries: Evidence From India," Demography, Springer;Population Association of America (PAA), vol. 54(2), pages 673-699, April.
    7. Timothy Riffe & Pil H. Chung & Jeroen J. A. Spijker & John MacInnes, 2015. "Time-to-death patterns in markers of age and dependency," MPIDR Working Papers WP-2015-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    8. Lin, Wanchuan & Sloan, Frank, 2015. "Risk perceptions and smoking decisions of adult Chinese men," Journal of Health Economics, Elsevier, vol. 39(C), pages 60-73.
    9. Apostolos Papachristos & Georgia Verropoulou & George Ploubidis & Cleon Tsimbos, 2020. "Factors incorporated into future survival estimation among Europeans," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(2), pages 15-56.
    10. Manish Kumar & Shobhit Srivastava & T. Muhammad & Priya Saravanakumar, 2022. "Examining the association between health status and subjective life expectancy among older Indian adults based on the mindsponge approach," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.
    11. Dimiter Philipov & Sergei Scherbov, 2020. "Subjective length of life of European individuals at older ages: Temporal and gender distinctions," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-14, March.

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    More about this item

    Keywords

    Survival expectations; Subjective health; Risk perception; Smoking; EM algorithm; I12; C0; C30; C41;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • C0 - Mathematical and Quantitative Methods - - General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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