An algorithm to reduce the occupational space in gender segregation studies.

Abstract

This paper presents an algorithm based on the bootstrap to select an admissible aggregation level, that is, the minimum number of occupational categories that yield a gender segregation value not significantly smaller than that obtained from the large number of occupational categories usually available in any data set. The approach is illustrated using labour force survey data for Spain for the comparison of gender segregation in 1977 and 1992, as well as 1994 and 2000. To measure gender segregation, an additively decomposable segregation index based on the entropy concept is used. Despite a substantial simplification in the size of the occupation space, the decrease in the segregation index is very small and not significant, regardless of the year. Consequently, intertemporal changes in gender segregation can be studied using a greatly reduced classification of occupations that permits an easier interpretation of results.