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The income-health gradient: Evidence from self-reported health and biomarkers using longitudinal data on income

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  • Davillas, A.; Jones, A.M.; Benzeval, M.;

Abstract

This paper adds to the literature on the income-health gradient by exploring the association between short- and long-term income and a wide set of self-reported health measures and objective nurse-administered and blood-based biomarkers as well as employing estimation techniques that allow for analysis “beyond the mean†and accounting for unobserved heterogeneity. The income-health gradients are greater in magnitude in case of long-run rather than cross-sectional income measures. Unconditional quantile regressions reveal that the differences between the long-run and the short-run income gradients are more evident towards the tails of the distributions, where both higher risk of illnesses and steeper income gradients are observed. A two-step estimator, involving a fixed-effects income model at the first stage, shows that the individual-specific selection effects have a systematic impact in the long-run income gradients in self-reported health but not in biomarkers, highlighting the importance of reporting error in self-reported health.

Suggested Citation

  • Davillas, A.; Jones, A.M.; Benzeval, M.;, 2017. "The income-health gradient: Evidence from self-reported health and biomarkers using longitudinal data on income," Health, Econometrics and Data Group (HEDG) Working Papers 17/04, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:17/04
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    Keywords

    biomarkers; health inequalities; panel data; Understanding Society;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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