Universidade de Vigo (Spain) Gender segregation in the Spanish labor market: An alternative approach Coral del Río and Olga Alonso-Villar Universidade de Vigo (Spain)

Background: Overall segregation in the case of two categories Index of dissimilarity (Duncan and Duncan, 1955): fi is the number of female workers in occupation i; mi is the number of male workers. F is the total number of female workers and M is the total number of male workers.

Characterized in terms of axioms Background: Overall segregation in the case of two categories KM index (Karmel and Maclachlan, 1988): Gini index (Silber, 1989): Hutchens’ indexes (Hutchens, 2004): Characterized in terms of axioms

Background: Local segregation in the case of two categories Moir and Selby Smith (1979) and Lewis (1982): ti is the number of workers in occupation i and T is the total number of workers

Background : Segregation in the case of multiple categories Overall Silber (1992) Karmel and Maclachlan Boisso et al. (1994) Gini Reardon and Firebaugh (2002) inequality measures/ axioms Frankel and Volij (2007): Established a set of axioms for the measurement of overall segregation Characterized the Mutual information index Alonso-Villar and Del Río (2007): Established a set of axioms for the measurement of local segregation Proposed several local measures consistent with overall measures Local

Background: Alonso-Villar and Del Río (2007): Decomposable BASIC PROPERTIES: Scale invariance Symmetry in groups Movements between groups Insensitivity to proportional divisions

Background: Alonso-Villar and Del Río (2007): Local segregation curve:

The aim of this paper: To analyze occupational segregation by gender in Spain In doing so, the local and overall indexes mentioned above are used In addition, two decompositions of the local segregation curves are proposed: One by groups of occupations Another by population subgroups These decompositions are used to go further in the empirical analysis

Our proposal: Descomposing local segregation curves i) Decomposition by subgroups of occupations: ii) Decomposition by population subgroups:

Figure 1: Local segregation curves of female and male workers. Occupational segregation in Spain: EPA, 2007, 2nd quarter Figure 1: Local segregation curves of female and male workers.

Young: 16 - 29 -- Middle-aged: 30 - 44 -- Elderly: >= 45 years old

45% 40%

3) Regarding males, segregation is higher for young workers. Conclusions 1/2 1) Female segregation explains, at least, 50% of overall gender segregation, even though the demographic weight of women in the labor force is 41%. 2) Within the female group, the young and the elderly are the ones suffering the highest occupational segregation. 3) Regarding males, segregation is higher for young workers.

Conclusions 2/2 4) Human capital increases do not necessarily reduce segregation, since for both women and men, the educational group with the lowest segregation level is that with intermediate-education. 5) The type of contract (permanent versus temporary) is more important to explain male segregation than female segregation. 6) Part-time jobs have more power to explain female segregation, since women working part-time tend to concentrate in the most feminized occupations of the economy, while for men part-time jobs are more evenly distributed across occupations.