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Purpose – To develop measures of segregation that are appropriate when either the groups or the organizational units are defined by ordered categories. These methods allow the measurement of segregation among groups defined by ordered educational attainment categories or among ordered occupational categories, for example.

Approach – I define a set of desirable properties of such measures, develop a general approach to constructing such measures, derive three such measures, and show that these measures satisfy the required properties.

Originality – Traditional methods of measuring segregation focus on the measurement of segregation among groups defined by nominal categorical variables (e.g., race and gender) among organizational units also defined by nominal categorical units (e.g., schools and neighborhoods). Such methods are not appropriate to the measurement of occupational segregation, for example. The methods developed here are widely applicable and appropriate for such cases.

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.

This article axiomatically derives a class of numerical indices of integration (equality) in the distribution of different types of workers across occupations. The associated segregation (inequality) indices parallel one form of multidimensional generalized Gini inequality indices. A comparison is made with the other Gini-related segregation indices. A numerical illustration of the family of indices is also provided using US occupational data.

I want to thank Paul Jargowsky for his comment. I take it as a serious comment by a thoughtful scholar. I admit, however, that I cannot make sense of much of it.

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 – This paper considers methods for decomposing indexes that incorporate economic disadvantage into a measure of segregation. According to such indexes, segregation in high-economic-status occupations is worse than similar segregation in low-economic-status occupations. The paper presents three decompositions of these indexes.

Methodology/Approach – The paper first characterizes a class of segregation indexes that include economic disadvantage in the index. It then develops mathematical methods for decomposing a change in such an index. The change is decomposed into two or more components: components that indicate either the effect of changes in economic disadvantage or the effect of changes in a standard measure of segregation – a measure that essentially ignores economic disadvantage. The paper then implements the decompositions using data on U.S. occupational segregation by gender between 1970 and 2000.

Findings – The primary finding is that a segregation index that incorporate economic disadvantage can be decomposed in interesting ways. A secondary finding is that such indexes indicate reduced segregation between 1970 and 2000. The dominant forces associated with the reduction were (a) the convergence of occupational gender ratios and (b) the movement of women out of less advantaged occupations and into the comparatively well-compensated professional and managerial occupations.

Research limitations/Implications – The 1970–2000 results are mainly illustrative. They are based on three broad occupational categories for which there were compatible earnings data, and the analysis could quite feasibly be done with more detailed occupational categories.