Empirical Applications of Multidimensional Inequality Analysis
This paper explores the empirical application of theoretical multidimensional inequality analysis using real household welfare distributions. The paper operationalises recent conceptual developments in multidimensional inequality theory and assesses their usefulness for measurement and policy analysis. Despite the existence of a thriving theoretical literature on multidimensional inequality, empirical applications, particularly at the individual and household levels, are few and far between. This paper compares and contrasts different methodologies for the analysis of multidimensional welfare, including multidimensional inequality indices and stochastic dominance techniques. The results strongly highlight the importance of bringing non-monetary aspects of household welfare into the forefront of inequality analysis since measurements based solely on the distribution of income variables may misrepresent the degree of overall inequality in society. Agreement over the various approaches to the measurement of multidimensional inequality entails, however, non-trivial decisions that may limit the practical usefulness of these measures. We suggest that the use of multidimensional inequality ranges and restrictive dominance criteria may open significant scope for further developments in the empirical analysis of multidimensional inequality.
Multidimensional inequality; inequality indices; income inequality; education inequality; health inequality; stochastic dominance
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