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Measuring Inequality in Health

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Advances in Economic Measurement

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Abstract

The burden of poor health is greater among poorer social groups throughout the world. Measuring inequalities in health and understanding their origins are a prerequisite for implementing an efficient policy aiming at reducing inequalities. In this chapter, we present the literature on the measurement of health inequalities, distinguishing between cardinal and ordinal health variables and between the univariate and bivariate approaches. A number of empirical illustrations from the recent literature, which highlight important factors that could serve as targets to improve equality, is also presented.

We dedicate this paper to the memory of Adam Wagstaff who was a pioneer in the study of health inequality and who passed away prematurely in May 2020.

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Notes

  1. 1.

    According to Erreygers and Van Ourti (2011a), there are different types of measurement scales (ordinal, cardinal, ratio-scale, and fixed). Authors also distinguish between bounded and unbounded variables. In this perspective, while body temperature or the HUI are measured on a cardinal scale, health care expenditures and body length are ratio-scale variables, and the number of chronic conditions or of doctor visits are measured on a fixed scale.

  2. 2.

    This wording of the question is recommended by the WHO Regional Office for Europe and provides a basis for comparisons of self-assessed health across countries.

  3. 3.

    Note that Erreygers and Van Ourti (2011a) present a matrix indicating which inequality index may be used for each type of health variables, making a distinction between ordinal, cardinal, ratio-scale, and fixed measurement scales.

  4. 4.

    Note that the Gini coefficient and the concentration index give information on health attainment (Apouey & Silber, 2016).

  5. 5.

    Some features of social dispersion in health are not taken into account by inequality measures but may be better captured by polarization approaches. For this reason, building on the literature on bivariate health inequality (the concentration index) and univariate polarization (for cardinal variables), Apouey (2010) develops measures of bivariate polarization in health (for cardinal data). Like the concentration index, these measures can be decomposed into factors using a regression approach.

  6. 6.

    Such an inequality index should vary between 0 and 1, which, for example, is not the case of the so-called Theil (1967) indices.

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Authors and Affiliations

  1. Paris School of Economics—CNRS, Paris, France

    Bénédicte Apouey

  2. Bar-Ilan University, Ramat Gan, Israel

    Jacques Silber

Authors
  1. Bénédicte Apouey
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  2. Jacques Silber
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Correspondence to Jacques Silber .

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  1. Caulfield, VIC, VIC, Australia

    Duangkamon Chotikapanich

  2. St Lucia, QLD, Australia

    Alicia N. Rambaldi

  3. Southport, QLD, Australia

    Nicholas Rohde

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Apouey, B., Silber, J. (2022). Measuring Inequality in Health. In: Chotikapanich, D., Rambaldi, A.N., Rohde, N. (eds) Advances in Economic Measurement. Palgrave Macmillan, Singapore. https://doi.org/10.1007/978-981-19-2023-3_7

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