Sick of Inequality?
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Sick of Inequality?

An Introduction to the Relationship between Inequality and Health

Andreas Bergh, Therese Nilsson and Daniel Waldenström

There is a clear trend in rich countries that despite rising incomes and living standards, the gap between rich and poor is widening. What does this mean for our health? Does increasing income inequality affect outcomes such as obesity, life expectancy and subjective well-being? Are rich and poor groups affected in the same ways? This book reviews the latest research on the relationship between inequality and health. It provides the reader with a pedagogical introduction to the tools and knowledge required to understand and assess the issue. Main conclusions from the literature are then summarized and discussed critically.
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Chapter 8: Searching for the inequality effect: which tools are appropriate?

Andreas Bergh, Therese Nilsson and Daniel Waldenström


One of the main conclusions of our survey of the empirical literature in Chapter 7 is that there is no uniform effect of inequality on individual health. In the cases when such an effect is found to exist, it seems to be contingent on various factors. One of these is the selected inequality measure. In this chapter, we discuss how and why the measurement of inequality dimensions can affect the interpretation of the results in this literature. Our review of the current research in the previous chapter showed that a large majority of the studies in this field use the Gini coefficient as a statistical measure of income inequality. This measure indeed has a number of tractable theoretical and empirical features, but most reviewed studies do not seem to have chosen it based on an informed discussion of the mechanisms involved or the best way to capture the type of inequality that is expected to be at work. On the contrary, it is our impression that the Gini coefficient is often selected as the inequality measure for conventional reasons rather than because it is the most appropriate measure for a specific context. As we argue in this chapter, an unreflective use of the Gini coefficient risks not only missing important variation in the data but may also add to the confusion of interpreting the results in the literature.

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