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Purpose – We propose the Information Theory of Segregation, which holds that all measures of segregation and of inequality are united within a single conceptual framework. Accepting this framework implies that all measures of inequality can also be used to measure segregation and that all measures of segregation are fundamentally based on measures of inequality.

Methodology – We state several propositions that follow from the information theory perspective, and show mathematically that many common measures of inequality and segregation satisfy the propositions.

Findings – We show that all common measures of inequality can be used to form measures of segregation and that the resulting measures can be applied to binary, polytomous, and continuous variables. Further, we develop several new measures, including a Gini Segregation Index (GS) for continuous variables and Income Dissimilarity Index (ID), a version of the Index of Dissimilarity suitable for measuring economic segregation. We show that segregation measures can easily be adapted to handle persons of mixed race, and describe the Non-Exclusive Index of Dissimilarity (NED) and the Non-Exclusive Entropy Index of Segregation (NEH). We also develop a correction for structural constraints on the value of segregation measures, comparable to capacity constraints in a communications channel, which prevent them from reaching their theoretical maximum or minimum value.

Originality – Placing inequality and segregation measures in a common framework is useful for several reasons. It highlights a common mathematical structure shared by many different segregation measures, and it suggests certain useful variants of these measures that have not been recognized previously.

Purpose – The Gini coefficient is a widely used measure of income inequality. It has also been used as a segregation measure, but only in the case of binary variables, for example race or gender. We develop a general version of the Gini Segregation Index (Gs) that can accommodate either continuous or binary variables, and discuss its relationship to existing measures.

Methodology – The Gini Index of Segregation is developed graphically and derived mathematically, illustrating the relationship between Gini's use in segregation and inequality applications.

Findings – Using the Public Use Microdata Sample for 25 U.S. metropolitan areas from the 2000 Census, we illustrate the calculation of the index and show that it is highly correlated with an existing measure of economic segregation.

Originality – This paper develops and illustrates a measure of segregation for continuous variables, a task for which there are few alternative measures.

Although the measurement of segregation by gender or ethnic group in the labor force has long been of interest to both sociologists and economists, the sociology and economics literatures on this topic have evolved in different ways and remained largely separate. This has also been the case to some extent with research on the measurement of residential segregation. Although much of the segregation measurement literature is in sociology and geography, economists have contributed to this field as well, particularly in the development of measures of residential income segregation. Again, however, the economics literature has remained largely separate from that in geography and sociology.