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The Evolution of Occupational Segregation in the United States, 1940–2010: Gains and Losses of Gender–Race/Ethnicity Groups


The aim of this article is twofold: (1) to descriptively explore the evolution of occupational segregation of women and men of different racial/ethnic groups in the United States during 1940–2010, and (2) to assess the consequences of segregation for each group. For that purpose, in this article, we propose a simple index that measures the monetary loss or gain of a group derived from its overrepresentation in some occupations and underrepresentation in others. This index has a clear economic interpretation. It represents the per capita advantage (if the index is positive) or disadvantage (if the index is negative) of the group, derived from its segregation, as a proportion of the average wage of the economy. Our index is a helpful tool not only for academics but also for institutions concerned with inequalities among demographic groups because it makes it possible to rank them according to their segregational nature.

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  1. This index has been used to quantify segregation in the United States (Alonso-Villar et al. 2012, 2013).

  2. For studies applying these measures to explore occupational segregation by race/ethnicity and/or gender in the United States, see Watts (1995) and Gradín et al. (2015).

  3. This average wage actually coincides with the average wage of the economy because the wage of each occupation is determined by the average wage of the individuals working there.

  4. This per capita earning gap ratio is the difference between the average wage of the group and the average wage of the economy, expressed as a proportion of the latter.

  5. See

  6. The residual category “other race” is different each year. In particular, multiple-race responses were allowed since 2000. Regarding Hispanic origin, there is a break between 1970 and 1980; before 1980, the origin was imputed by IPUMS.

  7. We have trimmed the tails of the hourly wage distribution to prevent data contamination from outliers. Thus, we computed the trimmed average in each occupation eliminating all workers whose wage is either 0 or situated below the first or above the ninety-ninth percentile of positive values in that occupation.

  8. Hegewisch et al. (2010) found a similar evolution when analyzing whites, blacks, and Hispanics separately, although in this case, no further progress is observed between mid-1990s and 2009. Asians, however, do improve at the beginning of the 2000s.

  9. This evolution is in line with that obtained by Watts (1995) for the period 1983–1992 using the I p index proposed by Silber (1992) and considering 6 rather than 12 groups.

  10. The rise in segregation by gender between 1940 and 1960—as documented by Blau and Hendricks (1979) for 1950–1960 and shown in Fig. 1—seems to be mainly due to a rise in the segregation of white men—who accounted for more than 60 % of workers—and also of black men because the segregation of white women—who accounted for almost 30 % of workers—and that of other minority women and men actually fell during this period.

  11. The evolution of the segregation of black women reported in Fig. 2 was previously shown by Alonso-Villar and Del Río (2013), who undertook an in-depth analysis of this particular group.

  12. Queneau (2009) also documented a decrease in the segregation between blacks and nonblacks between 1983 and 2002, although this study did not distinguish between women and men.

  13. The demographic weights are given in Table 2 in the appendix.

  14. This percentage had been increasing since 1980 (when it was 54 %) because the reduction in the earning gap of white women due to segregation has been larger than the reduction in their salary disadvantage within occupations. Petersen and Morgan (1995) documented the important role of occupational segregation in explaining the wage gap of women in the early 1980s, although they did not distinguish women by race.

  15. As we mention earlier, this index responds only to those wage disparities that arise from working in different occupations, ignoring wage disparities or discrimination within occupations. In fact, as Fig. 4 shows, the situation of black and Hispanic women is worse when these wage disparities are taken into account (their per capita earning gap ratios are –21 and –32, respectively). Conrad (2005) documented the widening wage gap for black women with respect to white women between 1980 and 2000 derived from the persistent discrimination as well as the racial gap in education that still remains.

  16. The proportion of Asian Indians who have a bachelor’s degree or higher education is more than twice as much as that of Vietnamese (Allard 2011). Kim and Mar (2007) also documented wide differences among Asian groups in terms of poverty and unemployment rates.

  17. The earnings gap for this subgroup is mainly explained by the within component (Fig. 6), which suggests that although they are not particularly concentrated in bad occupations, they are penalized within them.


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We gratefully acknowledge financial support from the Ministerio de Economía y Competitividad (ECO2013-46516-C4-2-R, ECO2010-21668-C03-03 and ECO2011-23460), Xunta de Galicia (CN2012/178), and FEDER. We also want to thank the anonymous referees for helpful comments.

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Correspondence to Olga Alonso-Villar.



Table 1, 2, 3, and 4

Table 1 Local segregation of gender–race/ethnicity groups (Φ g1 ), 1940–2010
Table 2 Demographic weight of gender–race/ethnicity groups, 1940–2010
Table 3 Decomposition of the per capita earning gap ratio of each group (EGap × 100) in terms of segregation (Γ ×100) and within-occupation wage disparities (Δ × 100), 2008–2010
Table 4 Gains and losses of the gender–race/ethnicity groups (Γ × 100), 1940–2010

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del Río, C., Alonso-Villar, O. The Evolution of Occupational Segregation in the United States, 1940–2010: Gains and Losses of Gender–Race/Ethnicity Groups. Demography 52, 967–988 (2015).

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  • Occupational segregation
  • Local segregation
  • Race
  • Gender
  • Wages