Abstract
This paper focuses on the measurement of socioeconomic inequality of health between countries and its evolution over time, by means of population-weighted indicators. We show that rank-dependent indicators of inequality can be highly sensitive to small changes in the socioeconomic variable when estimating inequality in samples consisting of countries with large differences in population weights. Since larger countries count more than smaller countries, changes in the former tend to have bigger effects than changes in the latter. When using rank-dependent indicators, however, the sensitivity to small changes in the variable which is used for ranking can be so extreme, that the indicator may suggest trend reversals in inequality which do not really exist. An empirical study shows that this is not a freak case. The use of rank-dependent indicators may therefore produce misleading results when it comes to the measurement of population-weighted between-country inequality. We propose a simple diagnostic test to check how sensitive rank-dependent indices are to small changes in the variable used for ranking.
Highlights
High-income countries are richer, but in general healthier than low-income countries
This note shows that rank-dependent indices of socioeconomic inequality of health may behave oddly when they are used to measure the evolution of cross-country inequality over time
When rank-dependent indices such as the Concentration index are applied to samples in which some observations have very large sample weights, they are liable to overreact to small changes in the socioeconomic distribution which involve the largest countries, i.e. the observations with the largest sample weights
Summary
High-income countries are richer, but in general healthier than low-income countries. By far the most popular indicator when it comes to the measurement of income-related health inequality is the Concentration index, a rank-dependent indicator which is closely related to the Gini coefficient It has been used for the measurement of income-related inequality of health both between regions of the world (Reidpath and Allotey, 2007) and between countries of a region (Hajizadeh et al, 2014). In some studies of global inequality a case is made for unweighted, or “Concept 1” inequality (see, e.g., Decancq, Decoster and Schokkaert, 2009), we deal exclusively with population-weighted inequality This means that we use the weighted version of the Concentration index (O’Donnell et al, 2008: Chapter 8), which resembles the weighted version of the Gini coefficient (Lerman and Yitzhaki, 1989; Creedy, 2015). What we learn from this comparison is that the sensitivity problem identified here can be seen as the outcome of an explosive combination of rank-dependency and population weighting in the measurement of incomerelated inequality of health
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