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Gender and Presidential Vote Choice in Latin America

Published online by Cambridge University Press:  26 December 2025

Catherine Reyes-Housholder*
Affiliation:
Pontificia Universidad Católica de Chile, Santiago, Chile
Leslie A. Schwindt-Bayer
Affiliation:
Department of Political Science, Rice University, Houston, TX, USA
*
Corresponding author: Catherine Reyes-Housholder; Email: creyeshousholder@uc.cl
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Abstract

Why do women and men vote differently in presidential elections? Much research on gender and vote choice has focused on the United States and Western Europe, with less attention to the Global South. We develop a theory of sex gaps in presidential voting, which shows how ideology, feminism, and gendered personalities may help explain them. To test this, we designed and fielded surveys for presidential elections in Chile in 2021, Brazil in 2022, and Argentina in 2023. Results show that ideology and feminism largely explain men’s and women’s divergent votes for presidential candidates. Leftists, self-identified feminists, and respondents with more feminist attitudes were more likely to vote for Gabriel Boric instead of José Antonio Kast, Luiz Inácio Lula da Silva over Jair Bolsonaro, and Sergio Massa rather than Javier Milei. Unlike in the United States, Latin Americans’ gendered personalities do not seem to influence their vote choice.

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Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. A theory of sex gaps in vote choice.

Figure 1

Figure 2. Sex gaps in Chile, Brazil, and Argentina.Note: panels show the predicted gap in each variable from regression models controlling for socio-economic status, age, political interest, and education (where available). All other variables are held at their means * p < 0.1, ** p < 0.05, *** p < 0.01.

Figure 2

Figure 3. Explanations for sex gaps in voting for Boric versus Kast in Chile.Note: each panel shows estimated logit coefficients from a different statistical model. Models control for socio-economic status, age, and political interest. Horizontal lines denote 95 per cent confidence intervals.

Figure 3

Figure 4. Full models for sex gaps in Boric versus Kast vote.Note: the figure shows estimated logit coefficients predicting vote for Boric instead of Kast with all variables in the same model. Models control for socio-economic status, age, and political interest. Horizontal lines denote 95 per cent confidence intervals.

Figure 4

Figure 5. Feminism and predicted probabilities of Boric versus Kast vote.Note: each panel presents predicted probabilities of voting for Boric compared to Kast for feminists calculated from the analyses presented in Figure 3 and show 95 per cent confidence intervals. The left panel shows probabilities when feminism is measured as self-identified feminists; the right panel is for feminist attitudes. Models control for socio-economic status, age, and political interest.

Figure 5

Figure 6. Explanations for sex gaps in Lula versus Bolsonaro vote in Brazil.Note: each panel shows estimated logit coefficients from different statistical models. Models control for socio-economic status, education, age, and political interest. Horizontal lines denote 95 per cent confidence intervals.

Figure 6

Figure 7. Full models for sex gaps in Lula versus Bolsonaro vote.Note: the figure shows estimated logit coefficients predicting vote for Lula compared to Bolsonaro with all variables in the same model. Models control for socio-economic status, education, age, and political interest. Horizontal lines denote 95 per cent confidence intervals.

Figure 7

Figure 8. Feminism and predicted probabilities of voting for Lula versus Bolsonaro.Note: each panel presents predicted probabilities of support for Lula compared to Bolsonaro calculated from the analyses presented in Figure 6. The left panel shows probabilities when feminism is measured as self-identified feminists; the right panel is for feminist attitudes. Models control for socio-economic status, age, and political interest. We report 95 per cent confidence intervals.

Figure 8

Figure 9. Explanations for sex gaps Massa versus Milei vote in Argentina.Note: each panel shows estimated logit coefficients from a different statistical model. Models control for socio-economic status, education, age, and political interest. Horizontal lines denote 95 per cent confidence intervals.

Figure 9

Figure 10. Full models of sex gaps in Massa versus Milei vote.Note: the figure shows estimated logit coefficients predicting vote for Massa compared to Milei with all variables in the same model. Models control for socio-economic status, education, age, and political interest. Horizontal lines denote 95 per cent confidence intervals.

Figure 10

Figure 11. Feminism and predicted probabilities of Massa versus Milei vote.Note: each panel presents predicted probabilities of support for Massa compared to Milei calculated from the analyses of Figure 9. The left panel shows probabilities when feminism is measured as self-identified feminists; the right panel corresponds to feminist attitudes. Models control for socio-economic status, age, and political interest. We report 95 per cent confidence intervals.

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