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Measurement of Health, the Sensitivity of the Concentration Index, and Reporting Heterogeneity

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  • Nicolas R. Ziebarth

Abstract

Using representative survey data from the German Socio-Economic Panel Study (SOEP) for 2006, we show that the magnitude of such health inequality measures as the concentration index (CI) depends crucially on the underlying health measure. The highest degree of inequality is found when dichotomized subjective health measures like health satisfaction or self-assessed health (SAH) are employed. Measures of medical care usage like doctor visits result in substantially lower concentration indices. Moreover, with the use of SF12, a generic health measure, the inequality indicator is reduced by a factor of ten. Scaling SAH by means of the SF12 leads to similar results to those with the pure SF12 measure. Employing generic health measures used with other populations like the Canadian HUI-III or the Finish 15D to cardinalize SAH has a significant impact on the degree of inequality measured. Finally, by contrasting the physical health component of the SF12 to the unambiguously objective grip strength measure, we provide evidence of the presence of income-related reporting heterogeneity in generic health measures.

Suggested Citation

  • Nicolas R. Ziebarth, 2009. "Measurement of Health, the Sensitivity of the Concentration Index, and Reporting Heterogeneity," Discussion Papers of DIW Berlin 916, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp916
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    Cited by:

    1. Pfarr, Christian & Schmid, Andreas & Schneider, Udo, 2011. "Reporting Heterogeneity in Self-Assessed Health among Elderly Europeans: The Impact of Mental and Physical Health Status," MPRA Paper 29900, University Library of Munich, Germany.
    2. Schneider, Julia & Beblo, Miriam, 2010. "Health at work - indicators and determinants : a revised literature and data review for Germany," IAB-Discussion Paper 201017, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    3. Nicolas R. Ziebarth & Joachim R. Frick, 2010. "Revisiting the Income-Health Nexus: The Importance of Choosing the "Right" Indicator," SOEPpapers on Multidisciplinary Panel Data Research 274, DIW Berlin, The German Socio-Economic Panel (SOEP).
    4. Udo Schneider & Christian Pfarr & Brit Schneider & Volker Ulrich, 2012. "I feel good! Gender differences and reporting heterogeneity in self-assessed health," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(3), pages 251-265, June.
    5. Will Davis & Alexander Gordan & Rusty Tchernis, 2021. "Measuring the spatial distribution of health rankings in the United States," Health Economics, John Wiley & Sons, Ltd., vol. 30(11), pages 2921-2936, November.
    6. Müller, Bettina & Bähr, Sebastian & Gundert, Stefanie & Teichler, Nils & Unger, Stefanie & Wenzig, Claudia, 2020. "PASS Scales and Instruments Manual," FDZ Methodenreport 202007_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

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    Keywords

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    JEL classification:

    • D30 - Microeconomics - - Distribution - - - General
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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