Decomposition Analysis of Segregation

• In Event: 472 - Section on Methodology Paper Session. Innovative Methodological Applications to Data Analysis

Abstract

Although substantive studies on segregation, such as residential or school segregation by race and occupational segregation by gender, are many in sociology, the analytical methodology is almost exclusively focused on measurement issues related to segregation. This paper introduces a set of new statistical methods for the decomposition analysis of segregation that will permit researchers to analyze segregation from a new methodological angle. These methods can be regarded as a tool to analyze whether one dimension of racial or gender inequality is related to another dimension of inequality, because they can assess, for example, the extent to which gender differences in human capital are related to gender segregation in occupation. One of the new methods is a simple extension of the DiNardo-Fortin-Lemiuex decomposition method of inequality, and another modifies it to incorporate an important macrosocial constraint on positional status attainment, but both methods rely on Rubin’s conception of modeling counterfactual outcomes and inverse-probability weighting based on propensity score. An application focuses on gender segregation in occupation in Japan and will lead to a paradoxical result: equalizing human capital characteristics between men and women increases, rather than decreases, gender segregation in occupation. Although the underlying behavioral mechanism for gender differences in occupational choice remains to be investigated, the analysis clarifies at least demographically why segregation increases under the counterfactual situation.

Author

• Kazuo Yamaguchi, University of Chicago