Does candidate sex matter to general election outcomes? And if so, under what conditions does sex exert an effect? Research conducted over the past 40 years has asserted an absence of a sex effect, consistently finding that women fare as well as men when they run. Nevertheless, this scholarship neglects sex-based differences in candidate valence, or non-policy characteristics such as competence and integrity that voters intrinsically value in their elected officials. If women candidates hold greater valence than men, and if women’s electoral success stems from this valence advantage, then women candidates would be penalized if they lacked the upper hand on valence. Recent research at the macro-level reports a 3 % vote disadvantage for women candidates when valence is held constant (Fulton, Political Res Q 65(2):303–314, 2012), but is based on only one general election year. The present study replicates Fulton’s (Political Res Q 65(2):303–314, 2012) research using new data from a more recent general election and finds a consistent 3 % vote deficit for women candidates. In addition, this paper extends these findings theoretically and empirically to the micro-level: examining who responds to variations in candidate sex and valence. Male independent voters, who often swing general elections, are equally supportive of women candidates when they have a valence advantage. Absent a relative abundance of valence, male independents are significantly less likely to endorse female candidates. If correct, the gender affinity effect is asymmetrical: male independent voters are more likely to support men candidates, and less likely to support women, but female independents fail to similarly discriminate.
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In this paper, I focus on character-valance, rather than an array of other candidate characteristics, such as scandals or even physical features that may or may not affect the vote decision. My analysis concentrates on character-valence attributes that voters intrinsically value in their representatives, like integrity and competence. This operationalization is consistent with most of the empirical studies using measures of candidate quality as a proxy for any valence advantage (see Adams et al. 2011; Groseclose 2001; Stokes 1963, 1992; Stone and Simas 2010).
This argument implies that an omitted variables problem biases our understanding of the effect of sex on vote-choice. An omitted variable (quality) is both correlated with an included explanatory variable (candidate sex) and influences the dependent variable (vote-choice). It appears that candidate sex exerts no independent effect on vote-choice, but this apparent null relationship is erroneous because previous models omit quality. Because candidate sex and quality are correlated—with women candidates being higher quality than men—candidate quality must be taken into account in order to get an unbiased estimate of the effect of sex. This omitted variables problem stands in contrast to an interactive effect, which implies that an explanatory variable “works differently” depending upon whether a condition is met or not. So, for instance, candidate quality has a greater (or lesser) effect on vote-choice when the candidate is a female as opposed to male. Although this is an intriguing idea that may have theoretical basis in the literature suggesting that women are more carefully scrutinized than men, this hypothesis is different from the argument about omitted variables.
Supporting Information A outlines the districts in the sample.
All analyses include a weight variable that takes into account the size of the district sample, and clusters by district.
One common criticism of this valence measure regards the potential for gender stereotypes to enter into the informants’ ratings of the candidates. For instance, due to gender norms and stereotypes [see for instance, Alexander and Anderson (1993), Huddy and Terkildsen (1993a, b), Kahn (1992, 1994, 1996)], informants may be more likely to rate female candidates more generously than males when it comes to appraising their “integrity” and “ability to work well with others.” In Supporting Information B, I replicate all the models reported in this paper with an alternative valence measure that excludes items in which women are stereotypically advantaged, and find that this alternative measure does not alter the substantive interpretations of the results reported here.
Principal components factor analysis shows that the seven items for valence form a single dimension. See Supporting Information C.
Notably, the partisan effect (mean = 1.133, p = 0.001) is much larger and more significant than the gender effect (mean = 0.068, p = 0.266).
Supporting Information D describes the variables included in the models and their coding.
I also replicate my models using a constituent-based measure of the candidates’ valence, and my results are consistent regardless of how valence is operationalized. See section below on: “Validating the Informants’ Perceptions with Alternative Measures.”.
Because the analysis excludes same-sex races, whenever there is a female Democrat running, the Republican is a male. Whenever there is a male Democrat running, the Republican is a female. 62.5% of the races featured a female Democrat and male Republican, while 37.5% of races featured a female Republican and a male Democrat.
The decision to model the dependent variable in the direction of the Democrat is arbitrary. Because all mixed-sex races are included, changing the dependent variable to the Republican candidate’s vote-share simply flips the sign of the coefficients in the model, but does not alter the coefficient’s size, significance or any of the other model statistics except for the intercept (the intercept “a” shifts up/down as “100 − a”).
Because my models include independent variables at both the district- and individual-level, I test whether my results persist using multi-level modeling. As shown in Supporting Information E, the results of the multi-level logit are consistent with the clustered models reported in the paper. All of the coefficients from the multi-level logit estimation are similarly-sized, signed and significant.
Again, the decision to model vote-choice in the direction of the Democrat is arbitrary. See footnote 11.
Democrats and Republicans include those who identify with their party as “strong” or “somewhat strong.” Independents include partisan “leaners” and “pure” independents. I code partisan leaners into the independent category for theoretical and practical reasons. Theoretically, I am interested in contrasting those with strong partisan loyalties against those with weaker attachments to party. As a practical matter, coding partisan leaners as independents ensures that there are roughly an equal number of respondents in the independent category as there are respondents in the Democratic and Republican categories.
Supporting Information D describes the variables included in the micro-models and their coding.
Captures whether there is a male candidate and a male respondent (0) or a female candidate and female respondent (1). The variables for female candidate and female respondent are the additional constituent parts required to specify all of the permutations of the interaction. See Brambor et al. (2006), Kam and Franzese (2007).
The ideology question from the CCES asked respondents to place themselves on a 5-point scale. However, a 1,000-respondent subsample of the CCES asked voters to rate their ideology using a 5-, 7-, and 100-point scale. Using the subsample, I convert the 5-point item into a 7-point item with an ordered logit model to generate the predicted probability of falling into a given ideological category. Respondents are assigned to the category with the highest probability, based on the ordered logit. This procedure is validated in Stone and Simas (2010).
The informants rated the candidates’ ideological position on a liberal (1) to conservative (7) scale. Because the voter’s ideology and the informant’s estimates of the candidates’ ideology are positioned on the same scale, I compute an “external” ideological distance variable based on the absolute difference between the respondent’s ideology and the ideology of the candidates.
Calculated from a factor analysis of voters’ attitudes towards stem cell research, the Iraq War, the minimum wage, abortion, the environment, immigration, Social Security, affirmative action, taxes and free trade, where negative values represent more liberal views, and positive values indicate more conservative issue attitudes.
Male independents are indistinguishable from the sample mean on many attitudinal and demographic markers, with a few exceptions. Compared to the sample mean, male independents are significantly more critical of President Bush, they score better on the political knowledge quiz, and report more political interest. They are more likely to be employed full-time, and are more educated and affluent. They are less white and religious than the overall sample. Supporting Information F compares male independents to the sample mean on a variety of attitudinal and demographic indicators.
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Walter J. Stone graciously provided the data used in this analysis. His guidance was instrumental to the development of this paper. I appreciate all of the feedback offered by the reviewers and editors. Their recommendations helped to strengthen this work. An earlier version of this paper was the co-winner of the Sophonisba Breckinridge Award for the best paper on the topic of women in politics at the Midwestern Political Science Association’s Annual Meeting in 2012.
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Fulton, S.A. When Gender Matters: Macro-dynamics and Micro-mechanisms. Polit Behav 36, 605–630 (2014). https://doi.org/10.1007/s11109-013-9245-1
- Voting behavior
- Candidate quality
- Independent voters