Concepts of inequality and their measurement

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Submission Summary
Inequality measurements are widely used by scientists and policy makers. Social scientists use them to analyze the global distribution of income and trends over time. In policymaking, inequality measurements contribute to inform redistributive policies at national level, and to set the agenda for international development and foreign aid. Inequality measurements are expected to objectively arbitrate in the design, selection and implementation of policy in these areas. The measurement of inequality, however, is far from straightforward, and scientists disagree about what is the best way to conceptualize inequality and what is the most appropriate method for measuring it. As a result, the policies based on these measurements are also called into question. One of the main questions is what exactly should be measured. While measurements typically focus on income or wealth inequality, there is increasing awareness that inequality is multidimensional and that other aspects of people’s well-being (like health, education, and political freedoms) should be measured too. Moreover, scientists have stressed the importance of measuring the inequality of opportunities rather than looking merely at the inequality of outcomes, and highlighted the relevance of investigating people’s subjective perception of economic disparities for designing successful inequality-reducing policies. The problem is that no measurement can take into account all aspects of inequality at the same time, and scientists disagree about which aspects should be taken into account and why. Measurement practice requires scientists to find context-dependent compromises between conceptual and procedural desiderata. As a consequence, scientific practice relies on a variety of narrow, contextual concepts, but this raises questions for using the outcomes of these measurements outside the narrow scope for which they were initially designed. This paper investigates how these narrow concepts of inequality are related to each other, and to the broader and multidimensional notions implementers are interested in. By looking in particular at the relations between subjective and objective measurements of inequality, I highlight the challenges that arise when investigating the relations between inequality parameters that are measured using different methodologies. However, I also defend the idea that conceptual analogies can be used to establish high-order relations between distinct dimensions of inequality. While inequality is measured differently across contexts, there is a sense in which these are all related to a common underlying concept of inequality, which can provide the basis for comparison and aggregation. This highlights the need for deeper theoretical understanding of how multiple dimensions are related to each other.
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University of Cambridge

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