The European Commission’s 2020–2025 gender equality strategy (henceforth, the strategy) provides the current basis for coordinated action towards a gender-equal Europe. The strategy pursues a dual approach consisting of gender mainstreaming combined with specific actions, and intersectionality as a horizontal principle for its implementation.
The strategy is underpinned by a monitoring framework including a series of indicators that consider differences between women and men under each of the three main pillars of the strategy: being free from violence and stereotypes, thriving in a gender-equal economy and leading equally throughout society. Data are made available on a dedicated monitoring portal.
On 7 March 2025, a comprehensive framework to advance women’s rights and gender equality was introduced by the Commission: the EU roadmap for women’s rights.
This initiative establishes a long-term vision for gender equality and lays the groundwork for the post-2025 gender equality strategy. It demands the production of sex-disaggregated data that reflect the complexity of women’s lives across their multiple and intersecting experiences.
European Institute for Gender Equality (EIGE) defines intersectionality as an ‘analytical tool for studying, understanding and responding to the ways in which sex and gender intersect with other personal characteristics/identities, and how these intersections contribute to unique experiences of discrimination’1.
This analytical framework entails understanding how intersecting inequalities emerge from the interaction between various socio-demographic variables, such as sex, age, racial or ethnic origin, disability, religion or beliefs, country of origin, sexual orientation and gender identity, and/or socioeconomic factors such as education, household type and employment status.
Inequalities in these areas can be influenced by complex social dynamics, including historical factors and various forms of discrimination2.
When producing gender statistics, it is important to keep in mind that neither women nor men form a homogeneous group; rather, they have diverse life experiences that are shaped by a multiplicity of personal and socioeconomic factors, as outlined above.
Because of the effects of these factors, gender inequalities tend to be more severe within specific groups of the population. Therefore, gender statistics may need to be disaggregated not only by sex but also by additional variables that enable a more comprehensive understanding of disparities both between and within groups3.
The monitoring portal of the European Commission’s gender equality strategy does not have the functionality to further disaggregate data by other personal characteristics. To address this, EIGE’s Gender Statistics Database enables users to analyse indicator data from an intersectional perspective, by providing options for further disaggregation to enable the visualisation (through either charts or data tables) of how personal and socioeconomic variables affect gendered experiences.
This 'Data talk' article presents an example of an indicator from EIGE’s Gender Statistics Database that showcases the multifaceted nature of gender equality in the field of employment.
Gender gap in employment rates: more pronounced through an intersectional lens
A crucial step towards achieving gender equality is narrowing the gender gaps in the labour market, beginning with initiatives that promote the participation of women in formal employment.
This will not only benefit the EU economy as a whole, particularly as the population ages and the number of people working and paying taxes falls, but also contribute to empowering women and promoting their economic independence.
A key indicator in this respect is the difference between the employment rates of women and men – that is, the difference between the proportions of women and men (of working age) that are in employment.
In 2023, over three quarters (78.7 %) of all men aged 18–64 in the EU were working, compared with over two thirds of women (68.7 %), resulting in a gender gap of 10 percentage points (pp)4. This overall gender gap, however, conceals some substantially wider gaps when gender is combined with other characteristics (Figure 1).
As we look at the different age groups, a clear story emerges about how the gender gap in employment widens with age. Among the youngest group (aged 18–24), the gender gap is relatively small (at 5 pp), probably reflecting similar participation in education or early career stages among women and men.
However, as individuals move into the core working age population (aged 25–54), the gap widens to 10 pp. This increase suggests that gendered factors, such as childcare responsibilities, disproportionately affect women’s employment during their most active working years.
The disparity becomes even more pronounced among those aged 55–64, where the gap is 12 pp. This suggests that as women get older they start facing additional challenges, such as difficulties re-entering the workforce or staying employed as retirement approaches.
As suggested above, caregiving responsibilities remain a critical factor influencing the participation of women and men in the labour force. Prolonged absences from paid work for women not only affect their current employment status but can also lead to lower pension rights, as they have fewer years of contributions and lower lifetime earnings.
When observing the effect of level of education, there is a clear inverse relationship between the level attained and the gender employment gap.
For individuals with at most lower secondary education, the gender gap is particularly pronounced (at 20 pp), highlighting how women with lower-level qualifications are especially vulnerable to employment barriers. This vulnerability may be due to limited job opportunities, lack of skills or higher caregiving expectations.
As the level of education increases, the gender employment gap decreases. For those with upper secondary education, the gap narrows to 11 pp, and among individuals with tertiary education the disparity is the smallest, at just 5 pp.
This reflects the positive impact that higher education levels and qualifications may have in reducing gender inequalities in employment rates by providing access to higher-quality jobs and more and better career opportunities, which could also translate to improved remuneration prospects.
Focusing on household compositions, we can see how having children affects women’s employment opportunities, as evidenced by the gender employment gap across various types of households.
Among single adults without children, the gender gap is only 4 pp, suggesting that in the absence of caregiving responsibilities women and men experience more equitable employment outcomes. However, once children are involved, the gap widens considerably.
For single adults with children, the gap increases to 12 pp. The disparity is even more pronounced among adults living in couples with children, for which the gap reaches 17 pp. In contrast, among couples without children the gap narrows to 11 pp.
Traditional gender roles and the unequal sharing of childcare responsibilities, including due to limited access to affordable childcare services, affect employment dynamics of women and men, and often result in a larger gap for single parents and couples with children.
A greater work–life balance burden is placed on one partner (typically the mother), thereby affecting their ability to maintain employment or work full-time.
Moreover, the intersection of gender with age, education and household responsibilities creates a particularly significant employment gap. Among adults aged 25–54 with a low level of educational who are single parents, the gender gap is stark, at 22 pp.
This reflects the compounded effects of multiple disadvantages: caregiving responsibilities, limited educational qualifications and structural barriers that disproportionately affect women.
These intersectional gender gaps underscore how intersecting challenges significantly exacerbate gender inequalities in employment.
These data are relevant for policymakers, as they give a clear indication that efforts to boost the overall levels of employment among women and address disparities will benefit from targeted interventions focused on specific groups within society, tailored to their specific circumstances and needs.
The Gender Statistics Database also allows users to explore various intersecting variables5 to gain a deeper understanding of how gender inequality manifests across different areas, subject to data availability.
This includes examining how disabilities affect both women and men, revealing unique challenges related to healthcare access, education, employment and social inclusion. Additionally, it explores how gender disparities in educational attainment or participation vary based on factors such as age or country.
It also provides opportunities to investigate how gender inequalities present differently in urban and rural areas (particularly in access to education, employment, healthcare or social services), offering insights into geographical disparities and differences based on country of origin, among other factors.
