A behaviorally-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. (ProQuest: ... denotes formulae omitted.) 1. Introduction Social inequalities are important indicators of social stratification, social cohesion, and individual well-being. As a result, ways to measure the ex^sub t^ent of inequality in a population have received a great deal of methodological attention in the social sciences. Introductions to the large literature on the topic can be found in Cowell (1995), Jenkins (1991), and Sen (1997). A number of different measures, each with its own set of strengths and weaknesses, have been used in a variety of analyses. For the most part, inequality measures have been based on population distributions observed at a given time with respect to a particular characteristic of interest. For example, measures of income inequality examine how members of different groups are distributed with regard to their level of income, while measures of residential segregation reflect how members of different groups are distributed with regard to place of residence. That approach is straightforward and reasonable, but such population-based measures for a given year (or period) do not reflect behavior at or near that time. Instead, they reflect the complex interplay of current and past behavior that produced the given year's population distribution. In short, conventional measures do not reflect the inequality implications of behavior at any readily identifiable time period. If the objective of an analysis is to do so, conventional approaches are inappropriate and can produce misleading measures of inequality levels and trends. This paper provides a way to examine inequality based on transitions during a given period, i.e. on how persons move from one category of the characteristic of interest to another, rather than on the population distributions produced by past and present patterns of movement. Such transition rates or proportions reflect behavior during the given period, independent of previous behavior. Those transition values can be used to measure inequality because they imply a unique, long term population distribution. Thus the behavior of a given period can yield a theoretical population distribution that can be used with standard measures of inequality to calculate the inequality implied by behavior during that period. The following sections describe how to calculate such transition-based measures of inequality. …