Abstract

In this study, I assess the relationship between various types of demographic variables, including individual, partner, and family-level information, and the likelihood of mothers staying at home. Using nationally representative data from the 2019,2021, and 2023 waves of the Annual Social and Economic Supplement (ASEC) to the Current Population Survey to account for differences across the COVID-19 pandemic, this analysis examines the likelihood of becoming a stay-at-home mother (SAHM) across three separate regression models. From the variables analyzed, I find that various individual, family, and partner demographic characteristics are significantly associated with the likelihood of becoming a SAHM. These results provide necessary information for an updated understanding of the types of individuals most likely to belong to this social group.

Degree

MS

College and Department

Family, Home, and Social Sciences; Sociology

Rights

https://lib.byu.edu/about/copyright/

Date Submitted

2025-06-24

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd13721

Keywords

stay-at-home mother, gender, division of labor, COVID-19, demographic predictors

Language

english

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