Intersectional Occupational Crowding: Labor Market Stratification Amongst Women Workers in New Orleans

Abstract

This descriptive paper examines racial and gender patterns of employment in New Orleans Louisiana using the 2018 American Communities Survey microdata in the context of the post-Katrina economy, with a focus on women workers. This paper reviews the literature on occupational crowding, and then uses a simple measure of crowding to analyze the local labor market focusing on an intersectional lens to examine patterns by race and ethnicity, gender, as well as additionally important dimensions of citizenship and age. A review of the literature shows the proliferation of these low-wage service occupations as associated with the redevelopment trajectory of New Orleans, as well as broader trends in the service economy. This paper then discusses how such a case study in the context of the “New New Orleans” can help to pose further research questions about occupational crowding, including methodologies for measurement, the relationship between crowding patterns and changes in service work, and how specific local and regional policy and redevelopment decisions shape crowding patterns.

Keywords:

• occupational crowding
• labor market stratification
• low-wage work

Acknowledgments

The author would like to thank the team at the Insight Center for Community Economic Development including Jacob Denny, Aisa Villarosa, Anne Price, and Jhumpa Bhattacharya for support, collaboration, and feedback on portions related to this project. The author also thanks participants in the ASE at ASSA 2021 session on Stratification Economics, Social Policy, and Low-Wage Workers for helpful discussion and feedback. All errors are my own.

Notes

1 We use the term intersectional drawing on Crenshaw (1989)’s theory of intersectionality which states that overlapping forms of oppression, discrimination, exploitation and so on must be understood in tandem. Drawing on this concept, we use the term intersectional to describe our analyses that overlay categories such as race and gender, race, gender and age, and so on. See further: (Crenshaw, 1989)

2 Here we focus specifically on healthcare support occupations, rather than healthcare practitioners and technical occupations since healthcare support occupations are predominately low-wage work according to (“Occupational Employment and Wages in New Orleans–Metairie – May 2019 : Southwest Information Office : U.S. Bureau of Labor Statistics” 2020)

3 Estimates of percentages of workers of each group within sub-occupations use the occ2010 variable in the ACS 2018 microdata for Orleans Parish. Due to sampling, these should be interpreted as only estimates, especially as the sub-occupation categories draw on a smaller number of responses.