1. 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)

2. 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.

3. 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

4. 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

5. 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

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

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

8. 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

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

10. 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.

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

14. 45%
40%

15. 3) Regarding males, segregation is higher for young workers.
Conclusions /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.

16. Conclusions /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.