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Draft Submission to B.J.Pol.S. XX, X–XX Cambridge University Press, 2018
doi:doi:10.1017/XXXX
The Cultural Sources of the Gender Gap in Voter Turnout
Ruth Dassonneville and Filip Kostelka
Recent publications argue that the traditional gender gap in voting has decreased or reversed in many democracies.
However, this decrease in the gender gap may apply only to some types of elections. Building on the existing literature, we
hypothesise that although women participate at the same or higher rates than men in national elections, they participate
less in supranational elections. We investigate this possibility empirically by analyzing the evolution of gender gap in voter
turnout in elections to the European parliament (EP). We make three important contributions. First, we show the presence
and stability of the traditional gender gap in EP elections. Second, we find that gender differences in political interest are
the main source of this gender gap. Third, these gender differences in political interest are, in turn, context-dependent.
They are strongly associated with cultural gender differences, which we capture through differences in boys’ and girls’
maths scores.
Keywords: gender gap, voter turnout, European Parliament elections, descriptive representation, cultural gender differences
Introduction
Classic studies on electoral participation reported that women were less likely to turn out to vote
compared to men.
1
Lower turnout rates among women were interpreted as a logical consequence
of late female enfranchisement and inequalities in resources.
2
However, gender patterns in voter
turnout in established democracies seem to have changed in recent decades. More recent studies
3
argue either that there are no observable differences in men’s and women’s likelihood to turn out
or that women are slightly more likely to vote than men.
4
Having performed a meta-analysis of
published papers on the individual-level determinants of turnout, Smets and van Ham
5
conclude
that the effect of gender on the vote is mostly not significant and close to zero. In addition, they
find that ‘when gender is found to be significant it is usually women that turn out at higher rates,
not men’.
6
The current scientific consensus thus holds that men and women turn out to about the
same extent.
In this paper, we refine these findings and show that it is too early to conclude that the
traditional gender gap in voter turnout has vanished. Employing hierarchical regression models
and an original dataset integrating individual-level data from the European Election Studies
project, which covers all elections to the European Parliament (EP) that have been held to date,
we make three important contributions to the literature.
First, we show the presence of a traditional gender gap in EP elections. This gap has passed
largely unnoticed in the scientific literature, even though we show that it has been systematically
present and fairly stable since the first direct elections to the European Parliament in 1979.
1Almond and Verba 1963; Tingsten 1937; Verba and Nie 1972.
2Verba and Nie 1972; Schlozman, Burns, and Verba 1994; Norris 2002; Mayer 2010.
3Childs 2004a; Inglehart and Norris 2003; Mayer 2010; Beauregard 2017.
4
A traditional gender gap in voter turnout is still observed in new democracies (Desposato and Norrander 2009;
Córdova and Rangel 2017) and also in Switzerland (Engeli, Ballmer-Cao, and Giugni, n.d.; Stadelmann-Steffen and
Koller, n.d.) where women were enfranchised at the federal level as late as in 1971.
5Smets and van Ham 2013.
6p. 348.
2The Cultural Sources of the Gender Gap in Voter Turnout
Second, to explain the presence of this gender gap, we draw on classic political science
theories that underline the importance of psychological engagement in politics for participation in
less mobilizing contexts.
7
EP elections are typical low-turnout second-order contests
8
. That is,
elections that are not held for the main political arena in a country, and where ‘less is at stake’. In
such low-stake elections, turnout is lower, and electoral participation requires higher levels of
political interest. We find that when we control for the well-established finding that women are
less interested in politics9, the gender gap in EP turnout even reverses.
Third, having identified political interest as the main culprit, we focus on variation in this
– causally proximate – factor to investigate the deep causes of the persistent gender gap in
participation in EP elections. Exploring country-level variation in the gender gap in political
interest, we find that women’s political representation may somewhat reduce the differences
between men and women. However, a more powerful predictor of gender differences in political
interest is the gender culture of a country, which we demonstrate using evidence from two distinct
and independent sources. These results have important implications for a better understanding of
gender inequalities in political participation.
Gender, Turnout, and Second-Order Elections
The earliest publications on gender differences in voter turnout have pointed out that women are
less likely to vote than men.
10
This finding has been referred to as ‘the traditional gender gap’.
The traditional gender gap, however, is by no means conventional wisdom among scholars of
turnout and gender. For multiple decades already, it is argued that the gender gap in turnout
should not be exaggerated,
11
that the gender gap has diminished or is absent
12
or that women vote
more than men.13 Summarizing the state of the art on the individual-level determinants of voter
turnout, Smets and van Ham14 conclude that gender differences are essentially zero.
The absence of a gender gap in turnout – or a reversal of the traditional gap (i.e., women
voting more) – is surprising, because it contrasts with patterns of persistent gender differences for
other variables. First, when studying political interest, political knowledge, or other precursors
of voter turnout, scholars find that the gender gap in these motivational factors for participation
has persisted.
15
Second, there is substantial evidence of a gender gap in other institutionalised
forms of political participation, such as campaign activities, working for a party, or being member
of a party.
16
In summary, while women’s position in society has improved – as evident from
the growth in women’s employment
17
and a reversal of the gender gap in higher education
18
–
women are still and consistently found to be less politically engaged and to participate less in
non-institutionalised ways.
7Campbell et al. 1960; Campbell 1960; Kostelka, Blais, and Gidengil 2019.
8Reif and Schmitt 1980.
9Thomas 2012.
10Almond and Verba 1963; Duverger 1955; Verba and Nie 1972.
11Norris 1991.
12Childs 2004a; Bennett and Bennett 1991.
13Inglehart and Norris 2003.
14Smets and van Ham 2013.
15Dassonneville and McAllister 2018; Fraile and Gomez 2015; Thomas 2012.
16Beauregard 2014; Carreras 2017; Marien, Hooghe, and Quintelier 2010.
17Fagan, Rubery, and Smith 2003.
18Schwartz and Han 2014.
The Cultural Sources of the Gender Gap in Voter Turnout 3
We argue here that the gender gap in voter turnout is still present, even in established European
democracies where gender equality is fairly high. However, the size of the gender gap in voter
turnout will depend on the level of turnout – and the election type (i.e., the importance of the
election). In particular, building on the work of Kostelka et al.
19
, we expect to find that women
participate less than men in the context of second-order elections, such as EP elections. Elections
for the European Parliament are a prototypical example of elections of second order, there is
‘less at stake’
20
in these elections and turnout is generally rather low. When turnout is low,
psychological involvement in politics matters more for participation
21
and inequalities in voter
turnout are stronger. Several studies have reported that social inequalities in participation are
larger under low turnout,22 which is in line with Tingsten’s law of dispersion.23
Focusing on EP elections, we therefore expect to find indications of a traditional gender gap,
with women voting less than men.
Hypothesis 1 In the context of EP elections, women vote significantly less than men.
Further, we expect that the gender gap in EP turnout will be driven by differential degrees
of psychological involvement in politics, which can be captured by citizens’ level of interest in
politics.
Hypothesis 2
The gender gap in EP elections turnout is driven by different levels of interest in
politics.
While the traditional gender gap in political interest remains on average quite large, its
magnitude varies across European democracies.
24
If hypothesis 2 is correct, this should also
reflect in the variation in the magnitude of the gender gap in voter turnout. In those countries
where the traditional gender gap in political interest is strong, we should observe a large traditional
gender gap in voter turnout. Conversely, in those countries where the traditional gender gap
in political interest is weak, the traditional gender gap in voter turnout is likely to be small to
insignificant or, if there are other personality or attitudinal differences between men and women,
even reversed.25
Political, Societal, and Cultural gender inequalities
Psychological involvement in politics is, of course, a causally proximate factor to political
behaviour. To provide a causally deeper explanation of the potential gender differences in electoral
participation, it is necessary to look further in the chain of causality and investigate the sources of
the gender differences in political interest. Building on the existing literature, we consider three
19Kostelka, Blais, and Gidengil 2019.
20Reif and Schmitt 1980, p. 9.
21Campbell et al. 1960; Campbell 1960.
22Armingeon and Schädel 2015; Dassonneville and Hooghe 2017; Gallego 2009.
23Tingsten 1937.
24Fraile and Gomez 2017.
25
For instance, Carreras (2018) found that women have a higher sense that voting is a civic duty and that this accounts
for a reversed gender gap in voter turnout in some first-order elections. In countries with a small traditional gender gap in
political interest, the same mechanism could lead to a reversed gender gap even in second-order elections.
4The Cultural Sources of the Gender Gap in Voter Turnout
possible competing explanations: women’s representation in politics, the overall degree of gender
equality in society, and cultural gender inequalities.26
First, a number of recent studies argue that an increased representation of women in elected
offices has strong effects on women’s political engagement, interest and knowledge.
27
The effects
of women’s descriptive representation on women’s political attitudes and behavior appear to be
especially strong among adolescents and young adults,
28
which has been argued to be a result of
the fact that contextual effects are of most importance during the formative years, when political
attitudes are formed.29
Several causal mechanisms have been proposed to explain a causal link between the presence
of women in politics and women’s political engagement. Women elected politicians or political
leaders can serve as role models for other women. The presence of female politicians could
thus be symbolic, weakening the stereotypical association of politics as a masculine domain
30
and increasing the legitimacy of the political system for women.
31
A number of publications
have offered suggestive evidence of the important role of symbolic representation for women.
For instance, the political engagement of adolescent girls is positively affected by an increased
representation of women in politics
32
and women are more likely to run for politics when more
women are elected in high-profile offices.
33
In addition, women’s political representation could be
important for substantive reasons, if women elected politicians give greater attention to issues that
improve women’s equality in society.
34
For all these reasons, we expect that gender differences in
political interest will be smaller in settings with a stronger political representation of women.
Hypothesis 3
The gender gap in political interest reflects how women are represented in elected
offices.
The second explanation posits that the gender differences in political engagement reflect
broader (and not exclusively political) social patterns. From this perspective, gender inequality in
the political sphere results from inequalities in other areas of human activity. The more women
have to bear the burden of household and family life, the less likely they are to have time and
energy for politics.
35
By contrast, the more traditional gender inequalities are attenuated or even
eliminated through public policies, the smaller the gender gap in political engagement. In line
with this interpretation, Fraile and Gomez
36
have recently found that an index measuring gender
equality across a broad range of areas is positively associated with weaker gender differences in
political interest.
Hypothesis 4
The gender gap in political interest reflects the effective overall level of gender
equality.
26
A fourth possible explanation pertains to gender inequality in resources such as education or workforce participation
(Norris 1991; Verba and Nie 1972). However, a number of authors have recently noted that a reduction in these inequalities
did not diminish the gender gap in political engagement (e.g., Kittilson 2016; Fraile and Gomez 2017). We thus include
education and employment status only as control variables in all of our analyses.
27Campbell and Wolbrecht 2006; Carreras 2017; Dassonneville and McAllister 2018; Fraile and Gomez 2015.
28Campbell and Wolbrecht 2006; Dassonneville and McAllister 2018; Wolbrecht and Campbell 2007.
29Dassonneville and McAllister 2018.
30Karp and Banducci 2008.
31Mansbridge 1999.
32Campbell and Wolbrecht 2006; Wolbrecht and Campbell 2007.
33Ladam, Harden, and Windett 2018.
34Greene and O’Brien 2016; Lovenduski and Norris 2003.
35Fraile and Gomez 2017.
36Fraile and Gomez 2017.
The Cultural Sources of the Gender Gap in Voter Turnout 5
Finally, the third account is similar to the second in that it does not consider the gender gap in
political engagement as a specifically political phenomenon. However, instead of public policies,
it focuses on socialisation processes that reproduce traditional gender roles and stereotypes.
37
From this perspective, several studies found that cultural obstacles are the main causes of women’s
underrepresentation in elected offices.
38
Sartori, Tuorto and Ghigi
39
study a massive dataset of
Italian households and find that the gender gap in political participation – in contrast to social and
leisure activities – persists even when contributions to domestic work are controlled for. They
attribute this result to cultural barriers. As regards political interest, Bennett and Bennett
40
found
that general sex role socialisation explains better the gender gap than situational or structural
accounts.
We build on these findings and suggest that what matters for gender equality in political
interest is the general cultural perception of men’s and women’s social roles. The more society
adheres to the traditional norms and stereotypes, the more politics is considered as the domain
of men. According to this interpretation, the elite level (e.g., women’s political representation)
and public policies (e.g., availability of child care facilities) are only some of the factors that
may gradually affect society’s cultural norms. And it is, in fine, these general cultural norms that
drive men’s and women’s everyday behaviour and attitudes. The less individuals’ social role are
predetermined by their sex, the weaker should be the traditional gender gap in political interest
and, by the same token, in political participation.
Hypothesis 5 The gender gap in political interest reflects cultural norms and stereotypes.
Hypotheses 4 and 5 are inspired by a rich literature that has pointed out the important roles
of gender equality and sex role socialisation for explaining gender differences in attitudes and
behaviour. However, recent studies seemingly challenge such work, and find that, in more
gender equal societies, men and women differ more strongly in terms of personality traits than
in less gender equal societies.
41
While these findings are important, they do not rule out the
potentially positive effect of gender equality on reducing the gender gap in political interest (and
participation). First, in the existing literature, the association between personality traits and
political interest is rather weak. The only personality trait that is consistently related to political
interest is openness, with more open individuals being more interested in politics.
42
Second,
focusing on the personality trait of openness, it is important to note that women are, on average,
more open than men. This difference can be observed in less gender equal societies, but it is
stronger in more gender equal societies.
43
As a result, it is very unlikely that the traditional gender
gap in political interest is a result of gender differences in personality. If anything, the role of
other factors such as gender unequal policies (Hypothesis 4) or gender unequal social norms
(Hypothesis 5) on political interest is probably attenuated by their effect on personality traits.
37Bennett and Bennett 1989; Norris and Inglehart 2001; Inglehart and Norris 2003; Paxton and Kunovich 2003.
38Bennett and Bennett 1989; Paxton and Kunovich 2003; Glatte and Vries 2015.
39Sartori, Tuorto, and Ghigi 2017.
40Bennett and Bennett 1989.
41Falk and Hermle 2018; Giolla and Kajonius 2018.
42See Cawvey et al. (2017) for an overview.
43Giolla and Kajonius 2018.
6The Cultural Sources of the Gender Gap in Voter Turnout
Data and Methods
We first explore variation in the gender gap over time and across countries via a series of
regressions of individual voter turnout on a dummy variable Female and year and country
control dummies. Subsequently, we analyse this variation by incorporating individual-level
variables. These comprise classic predictors of voter turnout
44
: socio-demographic indicators
of resources (continuous age and dummies for education, employment status, and perceived
class status), correlates of political mobilization (dummies for closeness to a political party,
trade union membership, and weekly attendance of religious services) and an indicator of
psychological involvement in politics (4-point scale of political interest).
45
Given the specific
nature of European elections,
46
we also include a measure of support for European integration
(dummies for considering EU membership as a good, neither good nor bad, or bad thing).
We rely on survey-data, with self-reported turnout rates, to study the determinants of electoral
participation. When doing so, it is important to be aware of the limitations of such data. In
particular, it is well-known that this leads to an overestimation of actual turnout rates, both because
voters tend to be overrepresented in surveys and because non-voters misreport having voted.
47
While we acknowledge this limitation, we have no reason to believe that this over-reporting will
be systematically correlated with gender. Karp and Brockington
48
studied over-reporting in five
countries and did not find differences between men and women. More recently, Morin-Chassé
et al.
49
conducted an experimental study on the consequences of using a face-saving option to
measure turnout. They found that men and women respond similarly to this option – suggesting
that their likelihood of over-reporting turnout when such an option is not available, is comparable.
To quantify the contributions to the gender gap in voter turnout more explicitly, we complement
the regression analyses with a linear decomposition.
50 51
The decomposition technique is a standard
method for the study of differences and inequalities in terms of gender or race.
52
It decomposes
the effect of a binary variable in a regression analysis (i.e., the difference in an outcome variable
between two groups) into two parts: explained and unexplained (see Equation 1). The explained
part amounts to the group difference in endowments with the independent variables (e.g., education
attainment) and the unexplained part to the group differences in the effects of these endowments
(e.g., a different regression coefficient of education for each group) and, more generally, to
unobserved factors.
Gender gap in turnout =
[E(XM) − E(XW)]0β∗
| {z }
Explained part
+[E(XM)0(βM−β∗) − E(XW)0(β∗−βW)]
| {z }
Unexplained part
(1)
44Blais 2000; Geys 2006; Smets and van Ham 2013; Stockemer 2017.
45
We rescale the political interest variable to run from 0 to 1. The question wording of the political item in the EES
surveys can be found in the Supplementary Materials.
46Flickinger and Studlar 2007.
47Selb and Munzert 2013.
48Karp and Brockington 2005.
49Morin-Chassé et al. 2017.
50Oaxaca 1973; Blinder 1973.
51
For consistency with the rest of the analysis (i.e., the use of linear probability models, see below), we apply a linear
decomposition technique. The use of a non-linear decomposition (Fairlie 2005) leads to similar substantive results, which
we display in the Supplementary Materials. We executed the two decompositions using software developped by Jann
(2006, 2008).
52Dow 2009; Kim 2010.
The Cultural Sources of the Gender Gap in Voter Turnout 7
Note:
XM
and
XW
denote vectors with men’s and women’s endowments in terms of independent variables.
β∗
,
βM
,
and βWare regression coefficients for the pooled sample, men, and women respectively.
The decomposition analysis allows us to test more directly whether the gender gap in voter
turnout in European elections is, in line with Hypothesis 2, mostly driven by a gender gap in
political interest. The two general components the decomposition technique estimates (i.e., the
explained and unexplained parts) are, in fact, simple aggregates of the contributions of individual
factors (such as political interest). The explained part is the sum of the differences in individual
endowments multiplied by the associated regression coefficients (see Equation 2). Importantly,
the individual contributions can be expressed as shares of the estimated total gender gap (see
Equation 3).
53
We can thus estimate which part of the gender gap in voter turnout is a consequence
of the fact that, on average, women and men are not equally interested in politics.
Explained part =
(¯
XM−¯
XW)0ˆ
β=(¯
XAgeM−¯
XAgeW)ˆ
βAge
| {z }
Contribution: Age
+(¯
XPostsecondaryM−¯
XPostsecondaryW)ˆ
βPostsecondary
| {z }
Contribution: Postsecondary education
+
(¯
XUnemployed M−¯
XUnemployedW)ˆ
βUnemployed
| {z }
Contribution: Unemployment
+(¯
XNot workingM−¯
XNot workingW)ˆ
βNot working
| {z }
Contribution: No formal employment
+
(¯
XMiddle classM−¯
XMiddle classW)ˆ
βMiddle class
| {z }
Contribution: Share of Middle Class
+(¯
XUpper classM−¯
XUpper classW)ˆ
βUpper class
| {z }
Contribution: Share of Upper Class
+
(¯
XEU neitherM−¯
XEU neitherW)ˆ
βEU neither
| {z }
Contribution: Indifferent attitude to EU membership
+(¯
XEU goodM−¯
XEU goodW)ˆ
βEU good
| {z }
Contribution: Positive attitude to EU membership
+
(¯
XTrade unionM−¯
XTrade unionW)ˆ
βTrade union
| {z }
Contribution: Trade union membership
+(¯
XReligiousM−¯
XReligiousW)ˆ
βReligious
| {z }
Contribution: Attendance of religious services
+
(¯
XPartyM−¯
XPartyW)ˆ
βParty
| {z }
Contribution: Closeness to a party
+(¯
XInterestM−¯
XInterestW)ˆ
βInterest
| {z }
Contribution: Interest in politics
+
(¯
XCountry iM−¯
XCountry iW)ˆ
βCountry i
| {z }
Contribution: Country dummies (i=1, ..., I)
+(¯
XElection jM−¯
XElection jW)ˆ
βElection j
| {z }
Contribution: Election dummies (j=1, ..., J)
(2)
53
Like the original contributions, these shares can be positive or negative. This depends on the distribution of the
given endowment (e.g., whether men or women are better off) and on the direction of the regression coefficient (e.g.,
whether the given factor fosters or hampers participation in elections). For instance, political interest exerts a positive
effect on participation (i.e., its regression coefficient is positive). Consequently, were women on average more interested
in politics than men, the contribution of political interest to the gender gap, defined as the difference between men’s and
women’s participation, would be negative. This would mean that political interest attenuates the observed gender gap
and that this gender gap is due to other factors. In reality, given that women are less interested in politics than men, the
contribution of political interest is likely to be positive and thus (at least partly) responsible for the observed gender gap in
voter turnout. It should also be noted that, as negative and positive contributions cancel out, the magnitude of individual
contributions can, in some cases, exceed the magnitude of the gender gap. In other words, some factors may exert a very
strong positive (or negative) effect, which is attenuated by other factors. Without these other factors, the observed gender
gap would probably be much larger (when the strong contribution is positive) or, on the contrary, totally reversed (when
the strong contribution is negative).
8The Cultural Sources of the Gender Gap in Voter Turnout
Note: The group means
¯
XM
and
¯
XW
are used as estimates of the endowments
E(XM)
and
E(XW)
from Equation 1.
ˆ
β
are estimates of the pooled regression coefficients β∗.
Contribution of political interest as share of the gender gap =
(¯
XInterestM−¯
XInterestW)ˆ
βInterest
(¯
XVoter turnoutM−¯
XVoter turnoutW)
(3)
Note: ¯
XVoter turnoutMand ¯
XVoter turnoutWare men’s and women’s average voting rates respectively.
We subsequently explore the cross-country variation in the gender gap in political interest.
We employ three sets of macro-indicators.
The first set captures the impact of women’s political representation (Hypothesis 3). In
particular, We test the impact of the percentage of women in the legislature. This is probably
the indicator that has been used most extensively in research on the effects of women’s political
representation.
54
Information on the percent of women in parliament comes from Paxton et
al.
55
and has been complemented with data on recent years from the Inter-Parliamentary Union
website.
56
In addition, we verify the impact of the percent of women in parliament when a citizen
entered the electorate, hence taking into account the possibility that the impact of women’s
descriptive representation is long-term.57
Second, to measure the overall level of gender inequality in society (Hypothesis 4), we follow
Fraile and Gomez
58
and employ an index produced by the European Institute for Gender Equality
(EIGE).
59
The EIGE’s gender equality index draws on 37 indicators and spans 6 areas: work,
money, knowledge, time, power, and health. The index is available between 2005 and 2015
and ranges from 0 (full gender inequality) to 100 (full gender inequality). We enter it in our
analyses in two versions. The variable EIGE corresponds to a time-series indicator available for
the EP elections of 2004, 2009, and 2014.
60
The variable EIGE (2005-2015 average) contains an
time-invariant average for the 2005-2015 period.
Third, to operationalise the degree of cultural gender inequality in society (Hypothesis 5),
we do not rely on explicit survey data.
61
Instead, we employ gender differences in mathematical
54Beauregard 2017; Fortin-Rittberger 2016; Fraile 2014; Karp and Banducci 2008.
55Paxton, Green, and Hughes 2008.
56Inter-Parliamentary Union 2016.
57Dassonneville and McAllister 2018.
58Fraile and Gomez 2017.
59The data and further information about the index is available at https://eige.europa.eu/.
60We use the values of the index from the most proximate available years: 2005, 2010, and 2015 respectively.
61
Using explicit survey items on gender roles as the main operationalisation represents a risky empirical strategy as
responses to these items tend to be strongly affected by the social desirability bias (Streb et al. 2008; Setzler, forthcoming;
Walter 2018). Scholars who specialise in gender and survey methodology even argue that “unfortunately, it is almost
impossible to assess the true gender role attitudes of respondents” (Walter 2018). When performing a cross-national
comparison, the use of survey items on gender attitudes is particularly problematic as, especially among men, attitudes on
gender tend to follow elites’ cues (Morgan and Buice 2013). Consequently, survey responses may conform to incumbent
(liberal or conservative) elites’ expectations and only weakly reflect cultural norms and mass behaviour that characterise
the population at large. Furthermore, in face-to-face surveys, which represent the best survey mode for population
representativeness (Malhotra and Krosnick 2007; Baker et al. 2010), the desirability bias is also influenced by the
interviewer’s gender (Huddy et al. 1997). Finally, in addition to the external pressure to give socially desirable responses,
there is typically a gap even between sincere conscious attitudes on gender roles, and, in part unconscious, real-world
patterns of thought and behaviour (Chiao, Bowman, and Gill 2008; Mo 2015). In sum, explicit survey items on gender
roles are fragile tools and, in many situations, it may be preferable to employ suitable alternatives.
The Cultural Sources of the Gender Gap in Voter Turnout 9
performance.
62
A large number of studies
63
have shown that this indicator is positively associated
with explicit survey measures of gender inequality. That is, in countries where women are the
most emancipated, young female students perform as well or even better than men in maths.
By contrast, in societies where respondents adhere to the traditional gender roles, boys perform
significantly better in maths than girls.
We use data from two distinct cross-nationals studies: the Program for International Student
Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS).
Both studies provide a comprehensive assessment of mathematical skills: the PISA data for
15-year-old students and the TIMSS study for approximately 10-year-old students. In both cases,
we calculated the gender gap for country ias the difference between women’s and men’s average
scores, standardised by the country’s average score (see Equation 4). These data are available only
for the periods 2000-2015 (PISA)
64
and 1995-2015 (TIMSS).
65
During these time-spans, neither
measure exhibits a time-trend and the country-level differences remain stable. This supports the
idea, suggested in the aforementioned studies, that the gap in mathematical performance reflects
long-term and durable cultural traits that pertain to gender. In the following analyses, we thus
enter the PISA and TIMSS measures as time-invariant country-level averages. This produces
more reliable measures (i.e., measures less affected by idiosyncratic measurement errors) and
also allows us to cover the whole period under study.66
Gender gap in mathsi=
Women’s average scorei−Men’s average scorei
Country averagei
(4)
Descriptive statistics of all variables included in the analyses are reported in the Supplementary
Materials.
The European Election Studies data have a nested structure, with individual respondents
nested in election-years and in countries. In addition, we are interested in analysing how
contextual-level variables (indicators of political, societal, and cultural gender inequalities)
moderate individual-level differences in political interest. We take into account the data structure
and estimate hierarchical random intercept models. We also specify random slopes for gender.
67
To ease the interpretation of the effects (and the estimation), we present the results of linear
probability models.
62
We prefer to rely on math scores to capture cultural gender differences. However, it is important to point out that
these math scores correlate with survey-based measures of cultural gender differences in society—suggesting both tap into
a same latent construct. We also show in the Supplementary Materials that using explicit survey data from the European
Value Survey instead leads to similar results. That is, the results of these analyses still support Hypothesis 5.
63
Dickerson, McIntosh, and Valente 2015; Guiso et al. 2008; Hyde and Mertz 2009; Nollenberger, Rodrìguez-Planas,
and Sevilla 2016; Nosek et al. 2009; Rai 2018.
64The PISA study was conducted in 2000, 2003, 2006, 2009, 2012, and 2015.
65The TIMSS study was conducted in 1995, 2003, 2007, 2011, and 2015.
66
It should be noted that the scores are not available for East Germany (both PISA and TIMSS), Estonia (TIMSS), and
Luxembourg (TIMSS). Because of data constraints, we use pan-German scores for West Germany (both PISA and TIMSS)
and, in the case of the TIMSS, the scores of England for the United Kingdom and the score of the Flanders for Belgium.
67Gelman and Hill 2007.
10 The Cultural Sources of the Gender Gap in Voter Turnout
Results
Tenacity of the Traditional Gender Gap in Voter Turnout
Figure 1 displays the over-time evolution of the gender gap in voter turnout in supranational
elections.
68
We distinguish two groups of countries. The first comprise only those countries that
had become EU member states by 1979 and, therefore, the related estimates are not affected by
successive EU enlargements. The other group include all EU member states in the given election
year and its estimates thus indicate an average value of the gender gap for the whole European
Union.
Figure 1: Evolution of Gender Gap in Voter Turnout
−.06
−.04
−.02
0
.02
Gender gap in the probability to vote
1979 1984 1989 1994 1999 2004 2009 2014
All Member States 1979 Member States
Note: Negative values mean that women participate at lower rates. 90 % confidence intervals. EES data 1979-2014. The
2004 estimate does not include Belgium and Lithuania for which the voter turnout variable is not available.
The two types of indicators point systematically in the same direction. In line with Hypothesis
1, they confirm that women tend to vote at lower rates than men in EP elections. This inequality
in electoral participation is strikingly stable in time and generally oscillates between two and
three percentage points. The effect of EU enlargements on the overall magnitude of the gender
gap appears to be negligible.
Although the gender gap in voter turnout remains stable in time, it varies strongly between
countries. This is shown in Figure 2, which plots the gender gap by country in both EP and
68
The figure draws on average marginal effects (AME) from linear probability models of voter turnout including the
dummy variable female and country controls as predictors.
The Cultural Sources of the Gender Gap in Voter Turnout 11
national elections.
69
The traditional gender gap in EP elections can be observed in approximately
two thirds of EU member states and reaches almost 7 percentage points in Poland and Croatia. In
contrast, in mostly North European countries (but also Malta), the gap is reversed and women
vote at higher rates than men by up to 5 percentage points. Nearly in all cases, the traditional gap
is weaker (i.e., less unfavorable to women) in national elections than in EP elections.
70
In fact,
on average, women do not vote less than men in national elections. This discrepancy between
EP elections and national elections corroborates the findings of Kostelka et al.
71
At the same
time, it should be noted that, although the sex differences in participation vary in magnitude,
they are correlated across election types. In countries where the EP gap is reversed, women also
participate at higher rates than men in national elections. Conversely, where the traditional gap is
strong in EP elections, there seems to be a mild gap also in national elections. This suggests that
sex differences in voting rates reflects some more general societal patterns that are unrelated to
the specificity of supranational elections.
Explaining the Gender Gap in Voter Turnout
Having shown indications of a traditional gender gap – with women turning out at lower rates
than men – in a large majority of countries in the EES dataset, we now turn to investigating the
sources of the gender gap in voter turnout in EP elections.
In a first step, we examine which individual-level factors account for this gender gap in voter
turnout. In Table 1, we present the estimates of a series of hierarchical models explaining turnout
in EP elections. We present five models. The first is a baseline model in which we only control
for respondents’ gender. In Model 2 and 3 we add the socio-demographic variables and attitudes
towards the EU respectively. In a fourth model, we additionally control for correlates of political
mobilisation, while the fifth and final model also accounts for the role of political interest.
The results of Model 1 in Table 1 offer evidence of a significant gender gap in turnout in the
pooled dataset. The effect of gender, that is estimated to be about 1.7 percentage points (pp.),
appears to be largely unaffected by the addition of socio-demographics control variables in Model
2. Even though each of these control variables is significantly – and in expected ways – related
to turnout in EP elections, these variables do not seem to account for gender differences in this
sample of elections.
Additionally controlling for respondents’ attitudes towards the European Union (in Model 3)
reduces the estimated gender gap in EU turnout somewhat. Though women are still estimated to
turn out less than men.
In Model 4 we add a set of variables that captures the impact of mobilization agents on turnout.
The estimates of this model confirm the impact of mobilization, as trade union members, those
who regularly attend religious service and individuals who are close to a party are all more likely
to turn out to vote. Accounting for these variables, however, only marginally affects the gender
gap.
The picture radically changes when additionally controlling for respondents’ reported level of
interest in politics (Model 5). A higher level of interest in politics is positively and significantly
associated with the probability of participation in EP elections. Importantly, adding political
69The figure displays AME from country-specific regressions including year dummies.
70
There are a few exceptions, but these are probably the result of a less accurate estimation for national elections as
the question on national turnout was asked only three EES waves (1989, 1994 and 2014). Most of the countries where the
national gap appears stronger than the EP gap joined the European Union only in 2004 and the participation rates in
national elections hence draw on a single EES sample (of 2014).
71Kostelka, Blais, and Gidengil 2019.
12 The Cultural Sources of the Gender Gap in Voter Turnout
Figure 2: Gender Gap in Voter Turnout by Country
Lithuania
Estonia
Latvia
Malta
Sweden
Finland
East Germany
Austria
Belgium
Ireland
Slovenia
Netherlands
Spain
Hungary
Greece
United Kingdom
Denmark
Slovakia
Luxembourg
Cyprus
Bulgaria
Italy
France
Romania
West Germany
Czech Rep.
Portugal
Croatia
Poland
−.12 −.1 −.08 −.06 −.04 −.02 0 .02 .04 .06 .08 .1 .12
Gender gap in the probability to vote
EP Elections National Elections
Note: Negative values mean that women participate at lower rates. 90 % confidence intervals. EES data 1979-2014.
Information on national elections is available only for 1989, 1994 and 2014.
interest to the model leads to a reversal of the gender gap in turnout (the coefficient for female
is now positive and significant). These results suggest that when we account for the fact that
The Cultural Sources of the Gender Gap in Voter Turnout 13
women are generally less interested in politics
72
women appear to turn out more than men. This
reversed gender gap may be due to other persisting personality and/or attitudinal differences
between men and women, as documented by recent research.
7374
One factor in particular that
might lead women to turn out more is civic duty. Indeed, Carreras
75
has found that women have a
stronger feeling that voting is a civic duty (but see Galais and Blais76 for a critical assessment).
72Thomas 2012; Kostelka, Blais, and Gidengil 2019.
73Falk and Hermle 2018; Giolla and Kajonius 2018.
74
Caution is, of course, needed in the interpretation of our result as, to some extent, it is based on an extrapolation.
Yet, Figure 2 shows that, at least in some North European countries, the reversed gender gap is real.
75Carreras 2018.
76Galais and Blais 2018.
14 The Cultural Sources of the Gender Gap in Voter Turnout
Table 1: Explaining Turnout in EP Elections, Individual-Level Determinants
(1) (2) (3) (4) (5)
Female -0.017∗∗∗ -0.014∗∗∗ -0.007∗∗ -0.005∗0.019∗∗∗
(0.003) (0.003) (0.003) (0.003) (0.003)
Age 0.006∗∗∗ 0.006∗∗∗ 0.005∗∗∗ 0.004∗∗∗
(0.000) (0.000) (0.000) (0.000)
Postsecondary 0.086∗∗∗ 0.070∗∗∗ 0.065∗∗∗ 0.040∗∗∗
(0.003) (0.003) (0.003) (0.003)
Unemployed (ref: working) -0.031∗∗∗ -0.032∗∗∗ -0.028∗∗∗ -0.028∗∗∗
(0.003) (0.003) (0.003) (0.003)
Not working (ref: working) -0.057∗∗∗ -0.050∗∗∗ -0.045∗∗∗ -0.039∗∗∗
(0.005) (0.005) (0.005) (0.005)
Middle class (ref: working class) 0.062∗∗∗ 0.049∗∗∗ 0.046∗∗∗ 0.032∗∗∗
(0.003) (0.003) (0.003) (0.003)
Upper class (ref: working class) 0.095∗∗∗ 0.073∗∗∗ 0.067∗∗∗ 0.040∗∗∗
(0.005) (0.005) (0.005) (0.005)
Eu membership neither good nor bad (ref: bad) 0.015∗∗∗ 0.019∗∗∗ 0.026∗∗∗
(0.004) (0.004) (0.004)
Eu membership good (ref: bad) 0.138∗∗∗ 0.125∗∗∗ 0.103∗∗∗
(0.004) (0.004) (0.004)
TU member 0.047∗∗∗ 0.035∗∗∗
(0.004) (0.004)
Attendance of religious services at least once a week 0.069∗∗∗ 0.069∗∗∗
(0.004) (0.003)
Closeness to a party 0.180∗∗∗ 0.137∗∗∗
(0.003) (0.003)
Interest in politics 0.302∗∗∗
(0.004)
Constant 0.654∗∗∗ 0.312∗∗∗ 0.238∗∗∗ 0.152∗∗∗ 0.084∗∗∗
(0.026) (0.027) (0.026) (0.024) (0.023)
σ2countries 0.017 0.018 0.016 0.014 0.013
σ2elections 0.008 0.008 0.007 0.007 0.006
(N) countries 29 29 29 29 29
(N) elections 119 119 119 119 119
(N) individuals 119610 119610 119610 119610 119610
Note: Coefficients of random intercept linear probability models, random slope specified for gender. Standard errors in parentheses. Significance levels:
*p<0.05, ** p<0.01, *** p<0.001.
The Cultural Sources of the Gender Gap in Voter Turnout 15
To investigate the contributions to the gender gap in voter turnout more explicitly, Table
2 displays the results of the linear decomposition. It reveals that the gap is entirely due to
differences in the levels of the independent variables (i.e., the explained part). In fact, differences
in regression coefficients (and unobserved factors, i.e., the unexplained part) moderate the gap and
without them, the gap is nearly 1.8 pp. larger.
77
By far, political interest represents the strongest
contribution and, on its own, it accounts for the observed gap. The other, significantly weaker
contributions largely cancel out. Moreover, the two strongest of these contributions – closeness
to a party (22.6 %) and considering EU membership as a good thing (20.9 %) – are themselves
strongly associated with political interest and, therefore, their contributions may partly reflect
political interest’s indirect effects.
78
In short, the decomposition analysis provides strong support
for Hypothesis 2.
Table 2: Linear Decomposition of the Gender Gap in Voter Turnout
Observations 119610
Probability to vote: Men 0.660
Probability to vote: Women 0.632
Gender gap 0.027
Explained 0.046
Unexplained -0.018
Factor Contribution Share of the gap
(explained part)
Age -0.002∗∗∗ -8.0 %
Postsecondary 0.001∗∗∗ 4.5 %
Unemployed 0.003∗∗∗ 12.4 %
Not working 0.000 -0.2 %
Middle class -0.001∗∗∗ -3.2 %
Upper class 0.001∗∗∗ 2.9 %
EU membership neither good nor bad -0.002∗∗∗ -5.8 %
EU membership good 0.006∗∗∗ 20.9 %
Trade union member 0.002∗∗∗ 7.1 %
Attendance of religious services -0.004∗∗∗ -15.8 %
Closeness to a party 0.006∗∗∗ 22.6 %
Interest in politics 0.028∗∗∗ 102.9 %
28 country dummies (total contribution) 0.007 25.4 %
7 election dummies (total contribution) 0.001 1.8 %
Note: Significance levels: * p<0.05, ** p<0.01, *** p<0.001.
77
In Table 2, the magnitude of the gender gap appears larger than in Table 1. This is because, in the estimation
procedure, the initial regression of turnout on gender does not control for country and year dummies. These controls are
incorporated only in the decomposition stage and their contributions jointly account for the difference between Tables 2
and 1.
78
In additional analyses, we found that among the variables included in our data set, political interest is the strongest
predictor of closeness to a political party and of considering EU membership as a good thing. Of course, our data do not
allow us to establish the direction of causality in these cases. However, it is likely that, at least in some instances, interest
in politics made respondents adhere to a political party or appreciate the benefits of European integration.
16 The Cultural Sources of the Gender Gap in Voter Turnout
Summarizing the results from this section, we find evidence of a traditional gender gap in
turnout in EP elections. This gender gap, it appears, is to a large extent a reflection of women’s
lower level of interest in politics. When we account for differential levels of political interest,
women turn out more than men.
These results align well with our expectations; not only is there evidence that women turn out
less than men in EP elections (Hypothesis 1), we also find political interest to be a key cause
of this gender gap in EP turnout (Hypothesis 2). Having identified political interest as the main
reason for women’s lower propensity to turn out in EP elections, in the next section we seek to
gain insights in what leads women to be less interested in politics – with particular attention for
the role of contextual factors.
Explaining the Gender Gap in Political Interest
To explore the origins of the gender gap in voter turnout, we leverage over-time and cross-country
variation in political interest. We aim to identify factors that may explain why, in some countries,
women are more interested in politics and, thereby, participate at higher rates in European
elections.
In Table 3, we present the results of a series of mixed linear regression models to explain
political interest.
79
In a first step, we explicitly demonstrate the presence of a gender gap in
political interest. The results confirm that in our EU-wide 1979-2014 dataset, women are on
average significantly less interested in politics than men even when accounting for a set of
individual-level predictors of political interest. By and large, the effects of these individual-level
variables are in line with theoretical expectations; being older, higher educated, employed, a
member of a higher social class and feeling close to a party all increase reported levels of political
interest.
The main goal of the analyses that are reported in Table 3, however, is to explain between-
country variation in the gender gap in political interest—which we found to be the key to
understanding the presence of a traditional gender gap in EP turnout. For doing so, we include in
Models 3 to 8 in Table 3 interactions between respondents’ sex and six different macro variables.
We investigate the role of women’s political representation (the percent of women in parliament
at the time of the survey, and when the respondent was 18-21 years old), societal gender equality
(EIGE and EIGE (2005-2015 average)) and cultural gender equality (by means of differences in
maths between boys’ and girls’ according to PISA and TIMSS).
First, a stream of recent publications has argued that women’s descriptive representation
can play a crucial role in increasing women’s political engagement, in this way reducing gender
gaps. Models 3 and 4 test these claims for political interest. The results consistently show the
expected positive interaction effect between women’s political representation and respondent’s
gender. However, this effect falls short of significance when focusing on the percent of women in
the legislature at the time of the survey. The results of Model 4 are more encouraging, as they
suggest that a higher percentage of women in the legislature during respondents’ formative years
(18 to 21) is associated with a significantly smaller gender gap in political interest. These results
are in line with earlier work, that has argued that if there is an effect of women’s descriptive
representation, it works through the mechanism of political socialisation.80
79
As evident from the results in the Supplementary Materials, our results are substantively the same when we estimate
ordered logit models to take into account the categorical nature of the dependent variable (with four answer options).
80Dassonneville and McAllister 2018.
The Cultural Sources of the Gender Gap in Voter Turnout 17
Table 3: Explaining Political Interest, Contextual-Level Factors
(1) (2) (3) (4) (5) (6) (7) (8) (9)
Female -0.094∗∗∗ -0.086∗∗∗ -0.094∗∗∗ -0.094∗∗∗ -0.076∗∗∗ -0.072∗∗∗ -0.066∗∗∗ -0.070∗∗∗ -0.073∗∗∗
(0.002) (0.002) (0.006) (0.004) (0.023) (0.020) (0.005) (0.005) (0.006)
Age 0.002∗∗∗ 0.002∗∗∗ 0.003∗∗∗ 0.002∗∗∗ 0.002∗∗∗ 0.002∗∗∗ 0.002∗∗∗ 0.003∗∗∗
(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)
Postsecondary 0.095∗∗∗ 0.095∗∗∗ 0.094∗∗∗ 0.089∗∗∗ 0.094∗∗∗ 0.089∗∗∗ 0.090∗∗∗ 0.088∗∗∗
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Unemployed -0.009∗∗∗ -0.009∗∗∗ -0.008∗∗∗ -0.007∗∗∗ -0.009∗∗∗ -0.007∗∗∗ -0.008∗∗∗ -0.008∗∗∗
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Not working -0.030∗∗∗ -0.029∗∗∗ -0.030∗∗∗ -0.029∗∗∗ -0.028∗∗∗ -0.029∗∗∗ -0.029∗∗∗ -0.029∗∗∗
(0.003) (0.003) (0.003) (0.004) (0.003) (0.004) (0.004) (0.004)
Middle class 0.056∗∗∗ 0.056∗∗∗ 0.055∗∗∗ 0.053∗∗∗ 0.056∗∗∗ 0.053∗∗∗ 0.052∗∗∗ 0.053∗∗∗
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Upper class 0.101∗∗∗ 0.102∗∗∗ 0.100∗∗∗ 0.095∗∗∗ 0.102∗∗∗ 0.098∗∗∗ 0.096∗∗∗ 0.098∗∗∗
(0.003) (0.003) (0.003) (0.004) (0.003) (0.004) (0.004) (0.004)
Close to a political party 0.152∗∗∗ 0.154∗∗∗ 0.151∗∗∗ 0.154∗∗∗ 0.153∗∗∗ 0.152∗∗∗ 0.154∗∗∗ 0.151∗∗∗
(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002)
Women in parliament (survey year) 0.001
(0.001)
Female ×Women in parliament(sur vey year) 0.000
(0.000)
Women in parliament (18-21) 0.001∗∗∗ 0.001∗∗∗
(0.000) (0.000)
Female ×Women in parliament(18-21) 0.001∗∗ 0.000
(0.000) (0.000)
EIGE 0.001
(0.001)
Female ×EIGE -0.000
(0.000)
EIGE (2005-2015 average) 0.003∗
(0.001)
Female ×EIGE (2005-2015 average) -0.000
(0.000)
PISA -0.672 -0.802
(0.956) (0.977)
Female ×PISA 0.863∗∗∗ 0.717∗∗∗
(0.210) (0.215)
TIMSS 0.820
(1.490)
Female ×TIMSS 1.076∗∗∗
(0.327)
Constant 0.535∗∗∗ 0.254∗∗∗ 0.221∗∗∗ 0.226∗∗∗ 0.196∗∗ 0.067 0.238∗∗∗ 0.256∗∗∗ 0.204∗∗∗
(0.014) (0.013) (0.020) (0.013) (0.074) (0.087) (0.021) (0.021) (0.022)
σ2countries 0.005 0.004 0.003 0.004 0.003 0.003 0.003 0.004 0.004
σ2elections 0.003 0.003 0.003 0.003 0.002 0.003 0.002 0.002 0.002
σ2female 0.000 0.000 0.000 0.000 0.000 0.000 0.000
(N) countries/elections 29/119 29/119 29/113 29/119 28/75 28/114 28/90 26/84 28/90
(N) individuals 123398 123398 116198 118649 88512 117996 98358 93357 96327
Note: Coefficients of random intercept linear regression models, random slope specified for gender. Standard errors in parentheses. Significance levels:
*p<0.05, ** p<0.01, *** p<0.001.
18 The Cultural Sources of the Gender Gap in Voter Turnout
By contrast, the level of overall societal gender equality does not find support in our data (see
Models 5 and 6). The interaction between the EIGE’s index and Female (both in the time-variant
and time-invariant versions) does not have the expected sign and is statistically insignificant. This
invalidates Hypothesis 4.
Finally, Models 7 and 8 in Table 3 test cultural explanations. For doing so, we interact
respondent’s sex with country-level differences in boys’ and girls’ results on maths scores.
81
The estimates in Table 3 suggest that cultural differences matter a great deal for explaining the
gender gap in political interest. The effect of the two indicators is in the expected direction, highly
significant, and of roughly the same size for both data sources.
Furthermore, the estimates of Model 9 indicate that when considering both political and
cultural factors simultaneously, it is the latter that matter more. That is, when accounting
for differences in boys’ and girls’ maths scores, the long-term impact of women’s descriptive
representation is no longer significant at conventional levels. The effect of culture, in contrast,
seems largely unaffected when we account for the role of women’s descriptive representation.
To ease the interpretation of the interaction effects in Table 3, we present in Figure 3 the
average marginal effect of gender (using the observed values of the other variables) for different
values of the macro-indicators. Looking at the marginal effects plots clarifies that the political
and cultural macro-variables have the expected effect: as women’s political representation (upper
graphs) or cultural gender equality (bottom graphs) increases, the gender gap in political interest
tends to be smaller. The strongest impact, however, and the only contextual factor that seems
to have the potential to reduce the gender gap in interest significantly, is culture. To be more
precise, as the difference between boys’ and girls’ maths scores in the PISA tests moves from
the minimum to the maximum value, the gender gap in political interest is nearly halved. This
suggests that if societies curb stereotypical perceptions about gender-specific social roles, i.e.,
they stop considering that maths and politics are more for boys than girls, this may reduce or even
fully eliminate the traditional gender gap in voter turnout.82
Discussion
The scientific literature on gender and turnout generally finds few indications of different turnout
rates among men and women. In contrast to what holds for attitudinal variables such as political
interest or non-institutional forms of participation, the gender gap in turnout appears to have
diminished or even reversed.
As we have shown here, however, this conventional wisdom does not apply to low turnout
elections, such as elections to the European Parliament. In a large majority of the countries in our
dataset, women are less likely to turn out than men for EP elections, while there is no such a gap
for elections to the national parliament. This gender gap, furthermore, is remarkably stable over
time, despite patterns of growing gender equality in other domains.
81
A different way of gauging the association between the gender gap in political interest and gender differences in
math scores is to plot–in a bivariate way–the random effects of the female-coefficient over the math score differentials. As
evident from the Supplementary Materials, such a simple graphical representation already shows the positive correlation
between both. That is, settings where girls do better than boys on math tests also tend to report positive gender gaps in
political interest and vice versa.
82
Our first analysis demonstrates that, at the same level of political interest, women tend to vote more than men.
Therefore, to eliminate the gender gap in voter turnout, the level of political interest does not even need to be the same.
A substantial reduction in the difference between men and women may suffice. Of course, caution is needed in the
extrapolation of these results as the variation we observe in our data is mostly cross-sectional.
The Cultural Sources of the Gender Gap in Voter Turnout 19
Figure 3: Marginal Effects of Female on Political Interest, Conditional on Macro-Level Factors
Women’s Political Representation
−.04
−.06
−.08
−.1
−.12
AME Female
4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46
Percentage of women in parliament
0
5
10
Percentage of observations
−.04
−.06
−.08
−.1
−.12
AME Female
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46
Percentage of women in parliament (18−21)
0
5
10
Percentage of observations
Societal Gender Equality
−.04
−.06
−.08
−.1
−.12
AME Female
45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83
Societal gender equality (EIGE)
0
5
10
Percentage of observations
−.04
−.06
−.08
−.1
−.12
AME Female
45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83
Societal gender equality (EIGE − 2005−2015 average)
0
5
10
Percentage of observations
Cultural Norms & Stereotypes
−.04
−.06
−.08
−.1
−.12
AME Female
−.04 −.035 −.03 −.025 −.02 −.015 −.01 −.005 0 .005 .01
Gender gap in math (PISA)
0
5
10
Percentage of observations
−.04
−.06
−.08
−.1
−.12
AME Female
−.025 −.02 −.015 −.01 −.005 0 .005 .01
Gender gap in math (TIMSS)
0
5
10
Percentage of observations
Note: Estimates and 90% confidence intervals come from Models 3 to 8 in Table 3.
Why is the gender gap in turnout for EP elections so persistent, while the traditional gender
gap in national parliament elections has diminished or disappeared? Our results suggest that
attitudinal factors, and political interest more specifically, are key. A large number of studies
20 The Cultural Sources of the Gender Gap in Voter Turnout
have shown that gender differences in such attitudinal variables are large and stable
83
and these
indicators of psychological engagement with politics have even more weight in low turnout
elections.
84
Hence, once we account for these attitudes, and women’s overall lower level of interest
in politics, women actually turn out more than men in EP elections.
Our results give insights in the reasons for gendered patterns of political participation in
European Parliament Elections. We focused on elections to the European Parliament because they
are the textbook example of elections of second-order, that is, elections where voters perceive
there to be ‘less at stake’.
85
But to what extent do our results generalize to other low turnout
elections? First, regarding the presence of a gender gap in turnout it is important to stress that not
all sub- or supranational elections are truly elections of second order. On this topic, Kostelka et
al.
86
have shown that its direction and size of the gender turnout gap varies depending on the
second-order character of an election. For example, they find no evidence of a gender gap in
turnout in subnational elections in Québec and Catalonia, because of the high saliency of these
elections. Second, it is possible that the mechanisms that we have identified do not apply to local
elections, even when they are clearly low-turnout elections.
87
In particular, Coffé
88
has shown that
– in contrast to what holds for national or international politics – there is no evidence of a gender
gap in interest in local politics. In line with this finding, studies from the early 2000s
89
did not
observe the traditional gender gap in voter turnout in British local elections. By contrast, Kostelka
et al.
90
found the traditional gender gap in the 2014 French municipal elections. Unfortunately,
the lack of a large comparative dataset of local election surveys prevents us from evaluating
directly whether our results hold for local elections as well. We hope that our results spur further
research on this topic, with specific attention for second-order elections of different degrees.
Our analyses suggest that the deep cause of the gender gap in voter turnout, acting through
political interest, lie in the cultural perceptions of men’s and women’s roles. Full gender equality
in voting and, presumably, other forms of political participation, is likely to be achieved only when
these resilient perceptions evolve. Our results support the idea that better women’s representation
in politics may help in this respect but we do not find a direct link between overall gender equality
in society and political interest. To be effective, public policies aiming at greater gender equality
in politics should thus target more directly cultural representations and stereotypes. Future
research should help identify effective methods for overcoming these long-lasting impediments to
genuinely gender-equal politics.
Acknowledgement
Both authors contributed to this manuscript equally. A previous draft of this manuscript received
the 2019 Marian Irish Award from the Southern Political Science Association. Early versions of
the manuscript benefited from comments and suggestions of the participants at the 2018 Annual
83Dassonneville and McAllister 2018; Thomas 2012.
84Kostelka, Blais, and Gidengil 2019.
85Reif and Schmitt 1980.
86Kostelka, Blais, and Gidengil 2019.
87
Most authors who have studied the second-order character of local elections conclude that these elections are not
‘really’ second-order. Instead, local elections seem to be situated somewhere in-between national-level first-order elections
and supranational second-order elections. Scholars have used the term ‘one and three-quarters order’ elections to describe
local elections (Heath et al. 1999; Marien, Dassonneville, and Hooghe 2015).
88Coffé 2013.
89Childs 2004b; Norris and Inglehart 2001.
90Kostelka, Blais, and Gidengil 2019.
REFERENCES 21
Meeting of the Southern Political Science Association in New Orleans; the “Journée d’études
de Sciences Po Quanti” conference in Grenoble; the “Institutions in context: gender equality
and policy” conference at the University of Tampere; and the 2018 Annual Conference of the
European Political Science Association in Vienna. We are particularly grateful to James Garand,
Debra Leiter, Nicolas Sauger, and Mariken van der Velden for their feedback. We would also like
to thank three anonymous reviewers and the BJPS editorial team for their constructive assessment
and their guidance. Any remaining errors and imperfections are our own.
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