Not Tough Enough? Gender Stereotypes and Vote Choice in Switzerland

Figures & data

Figure 1. Distribution of Gender Stereotypes in Switzerland.

Source: Selects (2022), own calculations and depiction.

Table 1. Logistic Regression Models.

	(1)	(2)	(3)	(4)	(5)
Male trait stereotype	-0.036 (0.053)				-0.026 (0.063)
Female trait stereotype		-0.017 (0.044)			-0.030 (0.055)
Male issue stereotype			-0.070 (0.051)		-0.129* (0.058)
Female issue stereotype				0.051 (0.045)	0.126* (0.055)
Gender (female)	0.154* (0.075)	0.156* (0.075)	0.142 (0.076)	0.157* (0.075)	0.132 (0.076)
Age	-0.000 (0.002)	-0.000 (0.002)	-0.001 (0.002)	-0.001 (0.002)	-0.001 (0.002)
Secondary education	0.005 (0.094)	0.006 (0.095)	0.003 (0.095)	0.003 (0.095)	0.001 (0.095)
Tertiary education	0.173 (0.101)	0.172 (0.101)	0.166 (0.101)	0.175 (0.101)	0.171 (0.101)
Income	0.021* (0.010)	0.021* (0.010)	0.020* (0.010)	0.021* (0.010)	0.020* (0.010)
Left-right self-placement	-0.002 (0.019)	-0.002 (0.019)	0.002 (0.020)	-0.001 (0.019)	0.008 (0.020)
Political interest	-0.058 (0.060)	-0.058 (0.060)	-0.059 (0.060)	-0.059 (0.060)	-0.059 (0.060)
Incumbency	-5.776*** (0.228)	-5.777*** (0.229)	-5.775*** (0.228)	-5.777*** (0.229)	-5.787*** (0.229)
Position of candidate’s party	-0.044*** (0.002)	-0.044*** (0.002)	-0.044*** (0.002)	-0.044*** (0.002)	-0.044*** (0.002)
Constant	0.836** (0.256)	0.833** (0.255)	0.876*** (0.258)	0.784** (0.256)	0.854*** (0.259)
N	4861	4861	4861	4861	4861

Note: For education, the baseline category is “primary education.” Regarding the position of the candidate’s party, a lower value means a position further to the left and a higher value means a position further to the right. Models are estimated with cantonal fixed effects. Standard errors in parentheses. * p < 0.05, ** p < 0.01, *** p < 0.001. Source: Selects (2022), Lehmann et al. (2022), own calculations.

Selects. 2022. “Data From: Selects 2019 Panel Survey (Waves 1-5) (Dataset).” SwissUbase. June 8. www.selects.ch1048573/f2dg-9v33

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Lehmann, Pola, Tobias Burst, Theres Matthieß, Sven Regel, Andrea Volkens, Bernhard Weßels, and Lisa Zehnter. 2022. “Data From: The Manifesto Data Collection.” Manifesto Project (MRG/CMP/MARPOR). Version 2022a“(dataset), Wissenschaftszentrum Berlin für Sozialforschung (WZB). doi:10.25522/manifesto.mpds.2022a.

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