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Distributional Regression Techniques in Socioeconomic Research on the Inequality of Health with an Application on the Relationship between Mental Health and Income

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  • Alexander Silbersdorff

    (Economics Faculty, Georg-August-Universität Göttingen, 37073 Göttingen, Germany)

  • Kai Sebastian Schneider

    (Department of Clinical Psychology, PFH Private University of Applied Sciences, 37073 Göttingen, Germany)

Abstract

This study addresses the much-discussed issue of the relationship between health and income. In particular, it focuses on the relation between mental health and household income by using generalized additive models of location, scale and shape and thus employing a distributional perspective. Furthermore, this study aims to give guidelines to applied researchers interested in taking a distributional perspective on health inequalities. In our analysis we use cross-sectional data of the German socioeconomic Panel (SOEP). We find that when not only looking at the expected mental health score of an individual but also at other distributional aspects, like the risk of moderate and severe mental illness, that the relationship between income and mental health is much more pronounced. We thus show that taking a distributional perspective, can add to and indeed enrich the mostly mean-based assessment of existent health inequalities.

Suggested Citation

  • Alexander Silbersdorff & Kai Sebastian Schneider, 2019. "Distributional Regression Techniques in Socioeconomic Research on the Inequality of Health with an Application on the Relationship between Mental Health and Income," IJERPH, MDPI, vol. 16(20), pages 1-28, October.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:20:p:4009-:d:278357
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    References listed on IDEAS

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