Motivation

Gender inequality remains a universal phenomenon. Even in relatively egalitarian societies, women are often disadvantaged in economic, political, and social life. To cite just a few examples, women’s labor force participation is almost universally lower than men’s (United Nations Development Programme 2020), and women’s median earnings are also consistently lower (Organization for Economic Cooperation and Development 2021). Many women face significant household burdens, including the threat of domestic violence (World Health Organization 2013). And in 2021, there were only three countries in the world where a (slight) majority of politicians are women (Inter-Parliamentary Union 2021). So, regardless of the many details and differences, the general existence of gender inequality is undeniable.

For our purposes, however, the relevant question is whether these inequalities extend to and potentially have their roots in political representation. That is, are the policy preferences of women generally ignored by policymakers compared to the preferences of men?

The relevance of this question is threefold. First, and as mentioned earlier, potential gender-based inequality in policy representation is inherently important in a normative sense. It violates the democratic principle of political equality, under which all adult citizens should have equal opportunities and capabilities to influence their government and see their preferences reflected in policy (Ingham Reference Ingham2022; Kolodny Reference Kolodny2014). Second, unequal policy representation would add to the relevance of other expressions of gender inequality, for instance in labor market participation, earnings, and political participation, as this suggests that these factors have political inequality as one of their consequences. And third, unequal representation could in turn reproduce or even reinforce other gender inequalities by suppressing policies that would benefit women.

Approach and Contribution

As mentioned earlier, our research question brings us to the intersection of two kinds of literature in the field of representation. On the one hand, there is research on the link between public opinion and policy (Canes-Wrone Reference Canes-Wrone2015; Erikson Reference Erikson2015; Shapiro Reference Shapiro2011). For our purposes, the most relevant studies are related to inequality in this opinion-policy link on the basis of income (e.g., Gilens and Page Reference Gilens and Page2014). On the other hand, we have research focusing on women’s substantive representation (Childs and Krook Reference Childs and Krook2006; Lawless Reference Lawless2015; Wängnerud Reference Wängnerud2009). Here, relevant studies include those that consider the conditions affecting whether women’s interests are reflected in policy.

We will say more about the findings of these sets of studies later, but we mention them here to emphasize that we take inspiration from both research lines. Specifically, we combine the themes of the second literature with the research design of the first. We focus on the substantive representation of women and men, but measure representation as the correspondence between opinion and implemented policy. We do not make any assumptions about which policies are in the interest of women or men. Some studies have for instance argued that expanding reproductive rights are in women’s interest, and implementation of such policy, therefore, constitutes the representation of women (e.g., Franceschet and Piscopo Reference Franceschet and Piscopo2008). Following the standard approach in the field, we instead consider citizens better represented when policies are implemented that are consistent with their stated preferences.

It should be noted that our approach is subject to potential criticism. First, there is skepticism about the ability of average citizens to develop informed preferences. One consequence of this is that the link between opinion and policy would at best pick up the adaptation of opinions to policy cues, rather than the other way around (Achen and Bartels Reference Achen and Bartels2016, 313). Second, and more specific to our topic, scholars studying women’s representation often point out that citizens’ interests can be “uncrystallized” at any point in time (Mansbridge Reference Mansbridge1999). It is in the process of representation that people develop an understanding of their interests, so the argument goes (Celis and Childs Reference Celis and Childs2012; Saward Reference Saward2010). Both criticisms question the value of citizens’ policy preferences and their impact on actual policy.

Space limitations prevent us from doing justice to these views and their own critics, but we mention a few considerations here that we believe justify our approach. First, we acknowledge the limitations of public opinion and its measurement through surveys (Berinsky Reference Berinsky2017). At the same time, many studies show that aggregate opinion is stable, coherent, and capable of influencing policy (Erikson, Mackuen, and Stimson Reference Erikson, Mackuen and Stimson2002; Hakhverdian Reference Hakhverdian2010). Second, interests and preferences certainly change over time, but survey questions also measure the outcome of a process of “constructing” interests in the period before the survey (Converse Reference Converse1987). Moreover, while preferences may be updated and refined over time, they are highly unlikely to reverse completely in the short to medium term, especially at the aggregate level (Page and Shapiro Reference Page and Shapiro1992). Thus, we believe that citizens’ preferences are a meaningful (though imperfect) indicator of their interests.

The main alternative—identifying women’s interests by assumption—also has major limitations. It is often unclear how “women’s issues” or “women’s interests” are established, and who has the authority to decide on them. In practice, different actors often have different understandings of women’s issues (Celis et al. Reference Celis, Childs, Kantola and Krook2014). More broadly, this approach simultaneously assumes too much by implying that all women have the same interests and assumes too little by implying that women do not have any interests beyond a relatively narrow set of women’s issues.

We may add that we do not consider public opinion to be a fully exogenous force in the policy process (Celis et al. Reference Celis, Childs, Kantola and Krook2008). In general, we know surprisingly little about opinion formation, and why men and women develop different preferences. However, it is likely that this is affected by their different experiences and social positions. In addition, to some extent preferences might be a product of men and women following different parties and taking up cues from their different platforms, given the general evidence for cue-taking among the public (Boudreau and Mackenzie Reference Boudreau and Mackenzie2014; Slothuus and Bisgaard Reference Slothuus and Bisgaard2020). Hence, while it is meaningful to ask whether policy reflects women’s and men’s preferences, we should simultaneously acknowledge the more complicated links between the two sides.

To our knowledge, few studies connect women’s and men’s preferences with policy (or other outcomes) in this way. And to the limited extent that previous studies have addressed this question, they have arrived at different answers. Some authors conclude that political outcomes are more consistent with men’s preferences than women’s (Homola Reference Homola2019; Kopkin and Roberts Reference Kopkin and Roberts2022; Reher Reference Reher2018; Weber Reference Weber2020), while others find that women are not significantly underrepresented (Bernauer, Giger, and Rosset Reference Bernauer, Giger and Rosset2015; Dingler, Kroeber, and Fortin-Rittberger Reference Dingler, Kroeber and Fortin-Rittberger2019; Ferland Reference Ferland2020; Griffin, Newman, and Wolbrecht Reference Griffin, Newman and Wolbrecht2012). Thus, further analysis that includes more data is needed to clarify this debate. We aim to contribute to this effort.

As briefly mentioned in the introduction, we make several (empirical) improvements over these studies of political representation by gender. To begin with, compared to previous analyses, our data cover many more countries, years, and policy issues, allowing us to draw more comprehensive conclusions about the extent of unequal representation. This larger dataset also provides a better opportunity to examine the contextual factors that moderate gender inequality in representation.

An additional contribution comes from the fact that representation is measured in terms of policy changes. Since government policies are what ultimately affect citizens the most, they are “arguably the ultimate metric of representation” (Caughey and Warshaw Reference Caughey and Warshaw2018, 250). In contrast, most previous studies use party positions as their dependent variable (exceptions include Kopkin and Roberts Reference Kopkin and Roberts2022; Reher Reference Reher2018). However, this is an imperfect proxy for actual policy outcomes, especially since party stances come at a much earlier stage in the policy process. Some studies of the descriptive-substantive link have argued that women’s interests are often hampered at later stages of the policy process (Franceschet and Piscopo Reference Franceschet and Piscopo2008; Volden, Wiseman, and Wittmer Reference Volden, Wiseman and Wittmer2018). To the extent that this is true, analysis of party positions understates any inequality in substantive representation.

A final, important element of our approach relates to the meaning of policy representation. Here, we follow previous literature by theoretically distinguishing between congruence and responsiveness (Bartels Reference Bartels2021; Beyer and Hänni Reference Beyer and Hänni2018). Congruence reflects who gets what in purely descriptive terms, while responsiveness is a causal process and captures whether policy adapts to changes in public opinion. Both concepts fall under the broader notion of substantive representation.Footnote ¹

It is important to add that while the distinction between congruence and responsiveness is an important one, we are limited in how far we can apply it empirically. Responsiveness implies a causal effect of preferences, but causality is very difficult to establish with the observational data usually employed in studies like this one. Still, one important distinction is whether to analyze the correspondence between opinion and policy for different groups independently from each other, or together. For instance, to establish congruence between women’s preferences and policy, we need only to compare the two. But to get at responsiveness, we should expect to see correspondence even when controlling for the preferences of men, that is, also when men and women disagree. While an analysis that controls each group’s preferences for the others still falls short of a causal interpretation, it provides a useful contrast to the bivariate analysis of congruence and goes some way towards measuring responsiveness. We return to this issue in the data section.

Theoretical Expectations and Hypotheses

Turning to our hypotheses, can we assume that women’s political representation is generally weaker than men’s? Several factors suggest that this is indeed the case, at least in terms of responsiveness, each of which is closely related to the broader manifestations of gender inequality noted earlier.

First, women are politically underrepresented almost everywhere in descriptive terms. Given that politicians’ backgrounds often affect whose viewpoints they know, understand, heed, and ultimately advocate (Butler Reference Butler2014; Phillips Reference Phillips1995), it is likely that the lack of female politicians leads to unequal responsiveness. This is supported by many studies documenting a link between women’s descriptive and substantive representation (Chattopadhyay and Duflo Reference Chattopadhyay and Duflo2004; Lawless Reference Lawless2015; Lowande, Ritchie, and Lauterbach Reference Lowande, Ritchie and Lauterbach2019; Volden, Wiseman, and Wittmer Reference Volden, Wiseman and Wittmer2018).

At the same time, this link has been shown to be more contingent and probabilistic than suggested by earlier research (cf. Weldon Reference Weldon2002). For example, Wängnerud argues that “substantial change—whatever that means—cannot be taken for granted just because a group, such as women, is taking part in decision making to a larger extent than before” (Wängnerud Reference Wängnerud2009, 59). According to the idea of “politics of presence”, representatives are likely to put forward the policy agenda and preferences of the group that they represent, but only if there are conditions where they can actively participate and have their perspectives and interests considered (Höhmann Reference Höhmann2020; Phillips Reference Phillips1995). This is further illustrated by Childs and Krook (Reference Childs and Krook2009), who show that, beyond the sheer presence of female representatives, it also matters to what extent they can work in the interests of women, and to what extent they manage to form alliances with men with a similar policy agenda. They even suggest that “a lower proportion of women may be more effective than a higher number because female legislators may be able to specialize in women’s concerns without appearing to undermine male domination” (Childs and Krook Reference Childs and Krook2009, 129).

Second, studies consistently find that female voters have lower levels of political knowledge than men (Delli Carpini and Keeter Reference Carpini, Michael and Keeter1996, 135–77; Fraile Reference Fraile2014). This likely makes it more difficult for women to assert their political demands and influence policy (Adams and Ezrow Reference Adams and Ezrow2009). Having said this, measurement issues make it hard to say exactly how large this gap is and research has found that to some extent the gap can be explained by men being more likely to guess (Mondak and Anderson Reference Mondak and Anderson2004). Studies have also shown that the knowledge gap is not as large when applying a more expansive view on political knowledge that includes, for example, practical aspects of the welfare state system (Stolle and Gidengil Reference Stolle and Gidengil2010).

Third, women generally participate less in political activities (Burns, Schlozman, and Verba Reference Burns, Schlozman and Verba2001; Ondercin and Jones-White Reference Ondercin and Jones-White2011), which is in turn related to household power relations and bargaining power (Iversen and Rosenbluth Reference Iversen and Rosenbluth2006). Political participation, too, is an important prerequisite for steering politics in one’s preferred direction (Griffin and Newman Reference Griffin and Newman2005). A qualification here is that these inequalities are largest when it comes to voting, and smaller for other forms of participation (Kittilson Reference Kittilson2016). Scholars working on gender and participation also disagree over whether the differences have to do with differences in resources, gender roles, or the political context. As Kittilson (Reference Kittilson2016) puts it, “to date, no single explanatory factor accounts for gender gaps across all types of participation, nor across different types of women. Certainly, these sets of explanation are interrelated and likely interact in complex (and to date largely untested) ways.”

Fourth and finally, women tend to have lower incomes than men. As mentioned earlier, many studies have tested whether higher levels of income correspond to better policy representation, and though there is no consensus on this point (Elkjær and Iversen Reference Elkjær and Iversen2020), most analyses find that affluence buys influence (Bartels Reference Bartels2016; Elsässer, Hense, and Schäfer Reference Elsässer, Hense and Schäfer2021; Gilens and Page Reference Gilens and Page2014; Persson and Sundell Reference Persson and Sundell2023).

To be clear, these four factors do not exhaust the mediating factors affecting gender-based inequality in policy representation.Footnote ² Naturally, the way that citizens’ input is processed depends on formal rules and elite actors, including the incumbent government (Annesley, Engeli, and Gains Reference Annesley, Engeli and Gains2015; Htun and Weldon Reference Htun and Weldon2010). As we have also seen, all potential drivers of unequal representation come with qualifications. Overall, however, they suggest that both the input from citizens and the response to it from governments will tend to be biased against the views of women.

At the same time, this expectation of political inequality is somewhat weaker when we turn from responsiveness to congruence, since this presupposes differences in policy preferences. If, to take the extreme case, only men have a say in the political process but push for policies that women also support, the latter happen to get what they want (Enns Reference Enns2015). Consistent with this hypothetical scenario, gender is generally not among the strongest predictors of policy preferences (Häusermann and Kriesi Reference Häusermann, Kriesi, Beramendi, Häusermann, Kitschelt and Kriesi2015). Nevertheless, gender does affect these preferences in significant ways. For example, women generally prefer more egalitarian and progressive policies than men. Women are also more in favor of reproductive rights and stringent environmental policies, while they are less in favor of tough-on-crime measures (Shapiro and Mahajan Reference Shapiro and Mahajan1986; Yildirim Reference Yildirim2022). In line with this, previous studies have suggested that women’s interests tend to be better represented by left ideologies (Erzeel and Celis Reference Erzeel and Celis2016).

Summarizing the preceding considerations, our first hypothesis is the following:

But we also assume that unequal representation is more pronounced for the latter than for the former. In other words, women are likely to have limited political power compared to men, even if the consequences for the overall direction of policy will remain modest.

A natural follow-up question is: What macro-level factors moderate women’s political voice? In this second part of our analysis, we consider four sets of contextual factors that largely overlap with the mechanisms discussed earlier. First, and perhaps most obviously, we examine whether women’s substantive representation is improved when women have high levels of descriptive representation. As noted at the outset, a substantial body of research has argued and shown that a greater proportion of women in decision-making positions leads to better representation of women’s interests. At the same time, some previous studies incorporating public opinion have not found that women’s policy preferences gain more weight as the number of female parliamentarians increases (Dingler, Kroeber, and Fortin-Rittberger Reference Dingler, Kroeber and Fortin-Rittberger2019; Reher Reference Reher2018). While this makes our expectations somewhat uncertain, most of the evidence still suggests a link between descriptive and substantive representation. Hence our second hypothesis is the following:

The second set of factors is socioeconomic and based on known class differences in representation (Erikson Reference Erikson2015; Peters Reference Peters2018). Here, the reasonable expectation is that women are better represented in contexts where they are higher on the socioeconomic ladder in terms of income, education, and status. This leads to our third hypothesis:

Third, we consider political behavior. Assuming that “politicians and officials are not compelled to pay much attention to classes and groups of citizens who do not vote” (Key Reference Key1949, 527), political inequality may be mitigated by widespread and equal political participation (Leighley and Oser Reference Leighley and Oser2018). Hence our fourth hypothesis is:

Fourth and finally, it is plausible that cultural conventions moderate women’s substantive representation (Matland Reference Matland1998). That is, if the importance of women’s views in the political process is less constrained by public opinion or law, we would expect those views to carry more weight. Thus, our fifth and final hypothesis is the following:

Data

To measure the policy representation of men and women, we combine existing survey data from 43 countries with hand-coded information on the implementation of policy proposals asked about in the surveys. The survey questions were taken from cross-country survey instruments from the Eurobarometer, the International Social Survey Program, the European Social Survey, the European Values Study, the Comparative Study of Electoral Systems, and the World Values Survey. To be considered, a question had to concern a specific policy proposal and be answerable in an appropriate manner regarding its implementation or lack thereof. The questions needed to be clear enough to allow coders to know what information to look for to check implementation. Questions relating to priorities, importance, or conditions were not included. Nevertheless, inquiries could encompass absolute changes (such as joining NATO or shutting down all nuclear power plants) or relative changes (increasing or decreasing spending in various domains). These questions could pertain to new propositions or already implemented policies (the status quo).

In total, we use 152 unique questions from these surveys, covering a wide range of topics including redistribution, public spending, abortion, and immigration. Each of these questions is asked in multiple countries, and many are asked at multiple points in time. Therefore, at the aggregate level, our dataset consists of 4,758 observations that are survey questions nested in countries and years. The dataset contains information on 43 countries, 40 years, and nearly two million respondents who answered an average of 5.6 questions. Fifty-three percent of respondents are women. The distribution of countries, years, and sources in our data is shown in figures A1-A2 and table A1 of the online appendix, while table A2 provides more information on the policy areas covered by our survey questions.

Variables

The dependent variable in our analysis is dichotomous and indicates whether a particular policy was changed or not. To determine this, a team of research assistants checked whether the policy was implemented after five years. The variables were coded 1 if a government decision was made or a proposed outcome occurred. If there was no change, if a decision was made in the opposite direction, or if no information was found after thorough research, the proposal was classified as not implemented (0). In cases where the official implementation of the policy differed from actual implementation, the team relied on official factual data (de jure). For relative change statements, the team looked at differences between the level in the survey year and the level five years later. If there was a relative change in the direction of the policy proposal, the implementation variable was coded 1; otherwise, it was coded 0.

The coders received clear instructions to code whether the policy proposal was implemented at the specified time points. To determine implementation, coders had to consult various sources based on the type of policy. For instance, if a survey question specifically asked about policy decisions, the team referred to the national parliament minutes. On the other hand, for questions that focused on proposal implementation, the team referred to relevant sources for the topic in question, such as budgets, administrative files, or documentation on closure of nuclear power plants or infrastructure projects.

Our main independent variables are the proportion of men or women who favor a policy change on a survey question. We include all respondents in this calculation, instead of, say, only voters. Many questions ask respondents about the status quo; in these cases, we treat opposition to existing policy as support for policy change. For example, in 2003, 66% of men and 61% of women supported EU membership in France. In this case, our independent variables are equal to 0.34 and 0.39, respectively.Footnote ³

Overall, male and female support for proposals is highly correlated in our data with r = 0.97 (within each country, the correlation is the same). The distribution of support for policy change is shown in figure 1. This shows that women tend to prefer more policy change than men, though the average difference between the distributions is small (0.7 percentage points).

Figure 1

Density plot of support for policy change among men and women

Although these correlations are quite striking, they should not be too surprising for several reasons. First, this pattern of high agreement between men and women has already been found in other studies (Schakel and Van der Pas Reference Schakel and Van der Pas2021). Second, gender does not stratify preferences as broadly and strongly as, say, social class. Accordingly, previous studies have found somewhat more modest correlations between preferences of different income groups within and across countries (Elsässer, Hense, and Schäfer Reference Elsässer, Hense and Schäfer2021; Schakel Reference Schakel2021). Third, it is important to note that much of this correlation, which undoubtedly reflects a “true” overlap in preferences, also could be inflated by correlated measurement error arising from the fact that men’s and women’s preferences are based on the same survey questions. For example, some questions may be worded or arranged to elicit strong agreement among all respondents in the survey, while other questions elicit predominantly disagreement, regardless of the topic. Thus, like most other studies of unequal representation, our data somewhat underestimate differences in preferences.

Figure 2 shows the distribution of the simple average difference in support for the proposals in our dataset, across all countries and years, with points to the right being more supported by men, on average, and points to the left more supported by women. The vertical position in the graph does not signify anything. The proposal with the largest gender difference (averaged across all years and countries) is support for nuclear power. Men are also more in favor of joining the European currency and the European Union itself, whereas women are more supportive of gay couples’ right to adopt and a proposal to limit imports. On the classical left-right issue of supporting progressive taxation, women and men are equally supportive. To reiterate, an analysis such as ours that builds on actual preference differences among genders will thus potentially give different results than one that looks at the implementation of proposals assumed to be in the interest of women.

Figure 2

Beeswarm plot of differences in support for policy proposals

In the second part of the analysis, we introduce several potential moderators of gender inequality in representation, all measured at the time of the survey. First, descriptive representation is measured as the proportion of female parliamentarians (Inter-Parliamentary Union 2021) or female ministers (Teorell et al. Reference Teorell, Sundström, Holmberg, Rothstein, Pachon and Dalli2021) in each country-year. Second, the socioeconomic indicators included in the analysis are the proportion of women who are in the labor market and have a college degree (Teorell et al. Reference Teorell, Sundström, Holmberg, Rothstein, Pachon and Dalli2021). Third, political participation is measured as voter turnout (Teorell et al. Reference Teorell, Sundström, Holmberg, Rothstein, Pachon and Dalli2021), since turnout becomes more equal—less skewed—among groups the more widespread it is, and as women’s civic participation, using expert surveys from the Varieties of Democracy (V-Dem) project (Coppedge et al. Reference Coppedge2021). Fourth and finally, we measure cultural conventions using survey data from the World Values Survey (WVS) and the European Values Survey (EVS) or, more specifically, as an index of citizens’ views on the justifiability of abortion, divorce, and homosexuality.Footnote ⁴ We also consider here women’s civil liberties (including their right to freedom of movement and property), again based on V-Dem data.

Measures

Using the (dichotomous) policy change indicator and (continuous) indicators of support for policy change, we construct several measures of congruence and responsiveness.

Starting with congruence, the simplest strategy to measure this is to assess whether the majority preference in a subgroup is congruent with implemented policy. Returning to the example of French EU membership, this dichotomous congruence measure would equal one for both women and men, since France did not leave the EU in subsequent years and hence a majority of both groups (61% and 66%, respectively) got what they wanted. However, a limitation of this measure is that it ignores anything above or below the 50% threshold (for example, it does not distinguish between 51% and 100% agreement), and it may exaggerate small differences around this threshold that are likely to be affected by sampling and measurement error. Therefore, we also use a second approach, suggested by Bartels (Reference Bartels2021), which uses a continuous measure that assesses the proportion of women and men who got what they wanted for each policy. This measure equals 0.61 for women and 0.66 for men in this example.

To measure responsiveness, we regress policy changes on the preferences of men and women in the same model. We also include fixed effects for countries and years to alleviate some omitted variable bias (however, results are not substantively affected by their exclusion). Following the recommendations of the econometric literature, we estimate our dependent variable using linear probability models with heteroskedastic consistent standard errors (Angrist and Pischke Reference Angrist and Pischke2008). While we are limited in our ability to make causal inferences, as noted before, this is a complementary approach to the entirely descriptive congruence approach and gives some indication of the relative influence of the two groups. A second specification is similar to the first, but here we regress policy change on the non-absolute difference in preferences between men and women while controlling for the average level of support. Positive differences indicate that men are more in favor of policy change than women, while negative differences indicate the opposite. This variable is particularly useful to test whether responsiveness is significantly stronger for one group relative to the other, since a positive (negative) coefficient points to biased representation in favor of men (women).