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Reconsidering the income‐health relationship using distributional regression

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  • Alexander Silbersdorff
  • Julia Lynch
  • Stephan Klasen
  • Thomas Kneib

Abstract

We reconsider the relationship between income and health taking a distributional perspective rather than one centered on conditional expectation. Using structured additive distributional regression, we find that the association between income and health is larger than generally estimated because aspects of the conditional health distribution that go beyond the expectation imply worse outcomes for those with lower incomes. Looking at German data from the Socio‐Economic Panel, we find that the risk of bad health is roughly halved when doubling the net equivalent income from 15,000 to 30,000€. This is more than tenfold of the magnitude of change found when considering expected health measures. A distributional perspective thus highlights another dimension of the income–health relation—that the poor are in particular faced with greater health risk at the lower end of the health distribution. We therefore argue that when studying health outcomes, a distributional approach that considers stochastic variation among observationally equivalent individuals is warranted.

Suggested Citation

  • Alexander Silbersdorff & Julia Lynch & Stephan Klasen & Thomas Kneib, 2018. "Reconsidering the income‐health relationship using distributional regression," Health Economics, John Wiley & Sons, Ltd., vol. 27(7), pages 1074-1088, July.
  • Handle: RePEc:wly:hlthec:v:27:y:2018:i:7:p:1074-1088
    DOI: 10.1002/hec.3656
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    File URL: https://doi.org/10.1002/hec.3656
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    References listed on IDEAS

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    1. DIARRA, Setou & LEBIHAN, Laetitia & MAO TAKONGMO, Charles Olivier, 2018. "Polygyny, Child Education, Health and Labour: Theory and Evidence from Mali," MPRA Paper 88518, University Library of Munich, Germany.

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