Abstract
We offer a theory that links sexism to economic threat from immigrants and immigration-related policy preferences. Sexism has generally been associated with vote choice and other policy preferences but has not been studied in the context of immigration. We argue that because sexists are concerned with maintaining gender hierarchies, they tend to be threatened by the perceived effects of immigrants on jobs, which can upset native men’s breadwinning ability and social status. Therefore, we expect that individuals scoring high on sexism are more likely to believe that immigrants are an economic threat and to support policies that make immigration harder and thus alleviate such a threat. We specify regression analyses and lagged dependent variable (LDV) models using data from two national datasets, the 2016 ANES, and the 2016–2018 Voter Study Group (VSG) panel. We find that controlling for known predictors, sexism is a significant driver of immigrant economic threat and support for immigration restrictions among white Americans. Results among nonwhites are mixed but tend to support our theory. We also find that the effect of sexism is not conditional upon the respondent’s gender. Lagged dependent variable models further strengthen our inferences, alleviating endogeneity concerns. Our analyses suggest a link between sexism and immigrant economic threat, suggesting that sexist Americans may perceive immigration as a threat to the economic status of men.
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Data availability
Data will be available through Harvard dataverse. Filindra, Alexandra, 2023, “The Breadwinner and “the Other”: Sexism, Immigrant Economic Threat, and Support for Immigration Restriction in American Public Opinion”, https://doi.org/https://doi.org/10.7910/DVN/WLSWRT.
Notes
A total of 22.54% of respondents show missing values in the ideology question. We used the mean value to impute missing cases as this is a conservative approach to imputation. We also use the mean values of prejudice toward Hispanics and sexism to impute missing cases given that a total of 15.5% and 14.13% of respondents had missing values respectively. Imputing missing values allows us to preserve the base, especially among nonwhite respondents. Results with and without imputations are very similar and using models with imputations does not alter our inferences.
The results are robust when we conduct seemingly unrelated regression models.
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Filindra, A., Nassar, R.L. The breadwinner and “the other”: sexism, immigrant economic threat, and support for immigration restriction in American Public Opinion. SN Soc Sci 4, 23 (2024). https://doi.org/10.1007/s43545-023-00826-0
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DOI: https://doi.org/10.1007/s43545-023-00826-0