Gender, Race, and Class in an Intersectional Framework: Occupations and Wages in the United States

Abstract

Using family income as a class measure, this article explores whether gender and racial/ethnic gaps in hourly wages are the same across classes in the United States for 2015–2019. The study shows that the “mark of gender” extends beyond race/ethnicity and class. The conditional wages of women of any race/ethnicity are lower than those of any group of men of the same class (except that lower-class Asian women rank above lower-class Black men). Beyond differences in human capital, the wage disadvantage of Black and Hispanic workers, especially Black women, is (partially) associated with class stratification. Additionally, the study explores the role of occupations in explaining whether a group’s wage is above or below average. Black women’s wage disadvantage stems from occupational sorting, regardless of class. However, among White and Hispanic women, occupational sorting and underpayment within occupations are equally important. Occupational sorting does not seem to penalize Asian women.

HIGHLIGHTS

• Intersectional analysis shows that in the US, class shapes the labor experiences of women and men of different racial/ethnic groups.

• Class limits White women’s progress in the labor market.

• Black women are overrepresented in the lower class beyond their educational levels.

• Occupational barriers are especially strong for Black women even in the upper class.

• Racial differences in conditional wages among same-class groups of women are small.

Keywords:

• Class
• gender
• race
• ethnicity
• occupations
• earnings

JEL Codes:

• D63
• J70
• J16

ACKNOWLEDGMENTS

We also want to thank the anonymous referees and the associate editor for helpful comments.

SUPPLEMENTAL DATA

Supplemental data for this article can be accessed online at https://doi.org/10.1080/13545701.2023.2255871.

Notes

1 Eric Plutzer and John Zipp (2001) advocate for the use of “individuals in families” as the adequate unit of class analysis, taking the expression from earlier works.

2 For a review of this literature, see Joseph Altonji and Rebecca Blank (1999).

3 Our approach implies disregarding intrahousehold inequalities in well-being.

4 Stephen Rose (2020) sets the upper bound at 17.5 times the poverty line because he defines the rich as those at the top 1 percent of the income distribution.

5 Note that, when building classes based on the poverty line, we do not have to convert household income into equivalent income because there are different lines for the households depending on their sizes and compositions.

6 Although the occupational classification accounts for 458 categories, there is no employment data for thirty-two of them during the 2015–2019 period.

7 The “self-employed not incorporated” and the “unpaid family members” are not included in our sample. The workers whose wages belong to the trimmed first and 99 percentile tails mentioned earlier are also eliminated.

8 Single-person households and individuals who do not live with either a partner or relatives are considered single-person families. In theses cases, family income is strongly determined by the worker’s earnings. Our explorations suggest that the inclusion of single-person households barely affects the unconditional and conditional wages of any group in the upper and middle classes. In the lower class, the wages of Asian women and men would be lower if we restricted the analysis to households with at least two members whereas the wages of other groups would increase (White men) or remain almost the same.

9 Note that these cut-offs refer to individual equivalent income and not to family income. For a four-member family, these cut-offs are US$52,800 and US$160,000.

10 When looking at each class separately, our reference group is White men of the corresponding class.

11 We explored the conditional wages of the gender-race/ethnic groups including married/unmarried as an additional control variable, but the results barely changed.

12 The values of the charts are provided in the Online Appendix.

13 The earnings of Asian women and Hispanic men may be slightly overestimated. As Alonso-Villar and del Río (2023b) show, their earnings would be lower if, in the counterfactual distribution, we replaced the weight of each cell by the weight of the corresponding cell in the sample for White men, rather than estimating that weight using the logit model. The reason why we follow the latter approach is that it provides a decomposition of the factors involved.

14 The lower wealth/income of Black families, compared to Whites, could also be behind the position of Black men workers in earnings distribution.

15 Although these figures may be biased due to differences across classes in the earnings cut-offs that determine when adult children leave home, they are illustrative. Family class is determined here without considering these young workers’ income.

16 In Figure 2, the earning gap of this group is not the same in the actual and counterfactual distributions because, although their wages are the same, the average wage of the economy varies.

17 Something similar, but less intense, happens to Black men.

18 Although not provided in the article, if we define class based on the absolute poverty line, the results involving Figures 2–6 do not change. If we compare the twenty-four groups simultaneously, using middle-class White men as the reference group for all of them, the basic results also remain (see the Online Appendix).

19 However, if we built the counterfactual as explained in footnote 13, their wages would be below average, which suggests that the parametric counterfactual may overestimate the earnings of Asian women.

20 For an analysis of the long-term evolution of occupational segregation for Black women, see Alonso-Villar and del Río (2017).

21 Xiaoning Huang (2022) explores the role of visa programs (particularly, the H1-B program) in the increase in educational attainment and shares of highly educated STEM workers among new Asian immigrants from 1980 to 2019.

22 Among immigrant Asian women workers, who represent 77 percent of all Asian women workers, there is a high correlation between family class and birthplace. Around half of women coming from India (and Hong-Kong and Taiwan) belong to upper-class families, whereas those coming from Vietnam, Thailand, Pakistan, and Bangladesh are overrepresented in lower-class families. Unlike women coming from China, whose distribution is slightly polarized, those coming from the Philippines and Japan tend to be concentrated in the middle class.

23 The corresponding percentages are 40 and 46 percent for White and Black men, respectively.

Additional information

Funding

This work was supported by MCIN/AEI/ 10.13039/501100011033: [grant no PID2019-104619RB-C41 and PID2020-113440GB-100].

Notes on contributors

Olga Alonso-Villar

Olga Alonso-Villar is Professor of applied economics at the Universidade de Vigo, Spain. Her current research interests focus on gender and racial inequalities in the labor market (unemployment and occupational segregation), residential segregation by class, and the measurement of economic inequality. Her work has appeared in Feminist Economics, Mathematical Social Sciences, Industrial Relations, Papers in Regional Science, Review of Income and Wealth, Population, Space and Place, and Social Indicators Research, among others.

Coral del Río

Coral del Río is Professor of applied economics at the Universidade de Vigo, Spain. Her major fields include economic inequality and gender discrimination in the labor market. She has proposed indicators to quantify intermediate inequality, intertemporal poverty, unemployment, wage discrimination, and segregation, and has used them to explore the situation of various demographic groups in Europe and the United States. Her research has been published in Demography and Journal of Economic Inequality, among others. She was previously Associate Editor for Feminist Economics and Director of the Office for Equal Opportunity at the Universidade de Vigo.