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What do we mean by inequality comparisons? If the rich just get richer and the poor get poorer, the answer might seem easy. But what if the income distribution changes in a complicated way? Can we use mathematical or statistical techniques to simplify the comparison problem in a way that has economic meaning? What does it mean to measure inequality? Is it similar to National Income? Or a price index? Is it enough just to work out the Gini coefficient?Measuring Inequality tackles these questions and examines the underlying principles of inequality measurement and its relation to welfare economi

The emerging literature on experimental methods in connection with economic inequality has shed fresh light on how to think about inequality, how important issues of equality are in comparison with other economic objectives and how individuals incorporate criteria of equality and fairness into their own decisions. This volume covers a wide range of topics in the field of income distribution and extends the approach to related issues such as mobility and attitudes to risk. The selection of papers includes both participatory experiments - where individuals respond to economic incentives - and questionnaire experiments designed to investigate the extent to which individuals' values and attitudes conform to the way that economists and others conventionally model inequality and welfare.

The standard theory of inequality measurement assumes that the equalisand is a cardinal quantity, with known cardinalization. However, one often needs to make inequality comparisons where either the cardinalization is unknown or the underlying data are categorical. We propose an alternative approach to inequality analysis that is rigorous, has a natural interpretation, and embeds both the ordinal data problem and the well‐known cardinal data problem. We show how the approach can be applied to the inequality of happiness and of health status.