A transition-based approach to measuring inequality

Abstract

The measurement of inequality is often made using observed population-based distributions, such as the distribution of income or the distribution of members of different groups across neighborhoods. Unfortunately, such population distributions confound past and present behavior. Here, we advocate measuring inequality using behavior as reflected by transitions between categories of interest (e.g. income categories) over a specified time period, and show how such measures may be obtained from frequently available data. An illustrative example is provided for the case of income inequality. The approach is then applied to analyze trends in inequality between men and women in the distribution of ages at death. Observed death distributions indicate that, since 1970, mortality in 4 Western countries experienced increases in inequality that recently leveled off. In contrast, life table death distributions, which solely reflect the implications of a given year's mortality rates, reveal a peak in inequality followed (in 3 of the 4 countries) by appreciable declines. The results are insensitive to whether inequality is measured by entropy, the Gini Index, or the Index of Dissimilarity. However, the type of population distribution analyzed - whether observed or inferred from the transitions - does make a significant difference in the results obtained. Because distributions derived from transitions reflect the inequality implications of behavior over a specified time interval, they are recommended for greater use in analyses of inequality.