Data up to February 2020.
Planned article update: March 2021.
This article presents gender statistics for the European Union (EU), a selection of indicators from fields such as education, labour market, earnings and health, which are particularly important for measuring differences in the situation of women and men (i.e. gender gaps). Gender statistics constitute an area that cuts across traditional fields of statistics to identify, produce and disseminate data reflecting the realities of the lives of women and men, and policy issues relating to gender equality (Developing Gender Statistics: A Practical Tool, UNECE, 2010).
The indicators show gender gaps, together with levels achieved for the population as a whole, at EU level and across Member States (e.g. the gender employment gap with the employment rate). This approach shows gender gaps in access to resources and opportunities in the broader context of the actual resources and opportunities available. The article includes links to other articles and publications that provide a more detailed analysis of gender gaps.
One of the prominent indicators in education statistics is the proportion of persons who have attained tertiary education (i.e. who graduated from universities or other higher education institutions). This indicator belongs to the set of headline indicators used to monitor the Europe 2020 strategy for smart, sustainable and inclusive growth. In particular, one EU-level headline target is to increase the share of the population aged 30–34 having completed tertiary education to at least 40% by 2020. .
From the ‘tertiary education attainment’ indicator, a gender gap can be derived. It is defined as the proportion of men aged 30-34 that have attained tertiary education minus that of women. In 2018, this gender gap was -10.7 percentage points (p.p.) in the EU-27, meaning that the proportion of women aged 30-34 that had attained tertiary education exceeded that for men by 10.7 p.p. (see Figure 1). All Member States recorded a negative gender gap in tertiary education attainment. In 2018, that gap ranged from -0.9 p.p. in Germany (the smallest gender gap in absolute value), -5.5 p.p. in Malta, -6.4 p.p. in the Netherlands, -6.7 p.p. in Romania and -7.0 p.p. in Austria to -20.7 p.p in Lithuania, -24.6 p.p. in Latvia and -24.7 p.p. in Slovenia (the largest gender gap in absolute value).
For the population as a whole, the proportion of persons aged 30-34 that had attained tertiary education in 2018 ranged from 24.6 % in Romania to 57.6 % in Lithuania. Among the EU Member States with the largest gender gap in absolute value (above 20 p.p.), the proportion of persons with tertiary education was 42.7 % in Slovenia and Latvia, and 57.6 % in Lithuania, above the EU-27 average of 39.4 % in 2018. Among the countries with the smallest gender gap in absolute value (below 7 p.p.), the proportion of persons aged 30-34 with tertiary education in Romania (24.6 %), Malta (34.7 %) and Germany (34.9 %) was below the EU-27 average, whereas it was higher in the Netherlands (49.4 %).
For a better view of gender issues in the field of education, it is useful to take other indicators into account: upper secondary education attainment, lower secondary education, tertiary education graduates (women per 100 men), early leavers from education and training, as well as life-long-learning (see articles in Statistics Explained in the category Education and training.)
The employment rate is considered to be a key social indicator for analytical purposes when studying developments in labour markets. It is one of the headline indicators used to monitor the Europe 2020 strategy. One EU-level headline target is to raise the employment rate for women and men (aged 20–64) to 75% by 2020.
The gender gap analysed here is defined as the difference between the employment rates of men and women of working age (20-64). Across the EU-27, the gender employment gap was 11.8 p.p. in 2018, meaning that the proportion of men of working age in employment exceeded that of women by 11.8 p.p. (see Figure 2).
The gender employment gap varies significantly across Member States. In 2018, the lowest gap was reported in Lithuania (2.3 p.p.), followed by Finland (3.7 p.p.), Latvia and Sweden (both 4.2 p.p.). These four were the only EU Member States with a gender employment gap not exceeding 5 p.p. At the other end of the scale, six Member States recorded a gap above 15 p.p., namely Czechia (15.2 p.p.), Hungary (15.3 p.p.), Romania (18.3 p.p.), Italy (19.8 p.p.), Greece (21.0 p.p.), and Malta (21.9 p.p.). This is due to the lower participation of women in the labour markets in these countries.
For the population as a whole, the employment rate for persons aged 20-64 in 2018 ranged from 59.5 % to 82.4 %. Among EU Member States with the smallest gender employment gaps (below 5 p.p.), the employment rate was above the EU-27 average rate of 72.4 %. Among the countries with the largest gender employment gaps, above 15 p.p., the employment rate in Greece (59.5 %), Italy (63.0 %) and Romania (69.9 %) was below the EU average, whereas it was higher in Hungary (74.4 %), Malta (75.5 %) and Czechia (79.9 %).
For a better view of the gender issues in the field of employment, it is useful to analyse the following indicators: employment rate by highest level of education attained, employment by economic activity, self-employment, part-time employment, temporary employees, as well as unemployment and long-term unemployment (see articles in Statistics Explained in the category Labour market.)
The ‘unadjusted’ gender pay gap provides an overall picture of gender inequality in hourly pay. This gap represents the difference between the average gross hourly earnings of men and women expressed as a percentage of average gross hourly earnings of men. It is called ‘unadjusted’ as it does not take into account all of the factors that influence the gender pay gap, such as differences in education, labour market experience or type of job.
Across the EU, women earn less per hour than men do overall. For the economy as a whole, in 2018, women's gross hourly earnings were on average 14.8 % below those of men in the European Union (EU-27) and 15.9% in the euro area (EA-19). Across Member States, the gender pay gap varied by 19.7 percentage points, ranging from 3.0 % in Romania to 22.7 % in Estonia. For the rest of this section on earnings, which uses data from the last 4-yearly collection of the Structure of Earnings Survey of 2014, the comparison with other different variables is made with 2014 data. 2018 data on the gender pay gap are available in the following article Gender pay gap statistics.
In 2014, over the EU-27 as a whole, women’s gross hourly earnings were, on average, 15.7 % below those of men (see Figure 3).
The gender pay gap varies significantly across Member States. In 2014, the gender pay gap ranged from 4.5 % in Romania, 5.4 % in Luxembourg, 6.1 % in Italy, 6.6 % in Belgium, 7.0 % in Slovenia, 7.7 % in Poland and 8.7 % in Croatia, to 22.2 % in Austria, 22.3 % in Germany, 22.5 % in Czechia and 28.1% in Estonia .
Across Member States, employees’ average gross hourly earnings in 2014, expressed in purchasing power standards (PPS), varied from 34 % to 137 % of the EU-27 average. Among the countries with the smallest gender pay gap (below 10 %), earnings varied from 36 % of the EU-27 average in Romania to 131 % in Luxembourg. The countries with the largest gender pay gap (above 20 %) recorded earnings ranging from 53 % of the EU-27 average in Estonia to 121 % in Germany.
Besides the gender pay gap, based on hourly earnings, the difference between the average annual earnings of women versus men is also influenced by the higher proportion of part-time employees among women. This is shown by the ‘gender hours gap’ which represents the difference between average monthly hours paid to men and women expressed as a percentage of average hours paid to men.
In October 2014, across the EU, women were paid on average 12 % fewer hours than men per month (see Figure 4). The number of hours paid to men is broadly similar across EU countries, whereas part-time arrangements for women differ substantially. For the Netherlands, the gender hours gap stands out, at 28 %, meaning that female employees are paid on average 28 % fewer hours per month than men. At the other end of the scale, Bulgaria, Latvia and Romania recorded a gender hours gap that was 1 %.
Besides the gender pay gap and the gender hours gap, it is also useful to consider gender gaps in employment, as these also contribute to the difference in average earnings of women versus men. To give a complete picture of the gender earnings gap, a new synthetic indicator has been developed. This measures the impact of the three combined factors, namely: (1) the average hourly earnings, (2) the monthly average of the number of hours paid (before any adjustment for part-time work) and (3) the employment rate, on the average earnings of all women of working age — whether employed or not employed — compared to men.
In 2014, the gender overall earnings gap was 38.1 % in the EU-27 (see Table 1). Across Member States, the gender overall earnings gap varied significantly, from 19.2 % in Lithuania, to 47.5 % in the Netherlands (see Figure 5). Table 2 shows contributions to the gender overall earnings gap. At EU level, the gender pay gap, the gender employment gap and the gender hour's gap contributed 37.6 %, 27.7 % and 34.8 %, respectively, to the gender overall earnings gap.
For a better view of gender issues concerning earnings, it is also useful to look at the mean annual earnings by economic activity and the gender pay gap by economic activity and age (see articles in Statistics Explained in the category Wages, earnings and income).
Life expectancy at birth is one of the most frequently used indicators to measure the health status of a population. From the ‘life expectancy’ indicator, the gender gap in life expectancy at birth can be derived. This is defined as the number of years that men can expect to live (at birth) minus the number of years that women can expect to live.
In 2018, the gender gap in life expectancy at birth was -5.5 in the EU-27, meaning that life expectancy at birth was 5.5 years higher for women than for men. Life expectancy at birth was higher for women than for men in all Member States, with the negative gender gap ranging from -3.1 years in the Netherlands, -3.4 years in Sweden, -3.6 years in Ireland, -3.8 in Denmark and -3.9 years in Cyprus, to -8.7 years in Estonia, -9.6 years in Latvia and -9.8 years in Lithuania(see Figure 6).
As regards the population as a whole, life expectancy at birth varied between 75.0 and 83.5 years across Member States. Among the countries with the largest gender gap in absolute terms (8 p.p. or higher), life expectancy for the total population was 75.1 in Latvia, 76.0 years in Lithuania, 77.7 in Poland and 78.5 in Estonia, much lower than the EU-27 average of 81.0 years in 2018. Among the countries with the lowest gender gap in absolute terms (i.e. 4 years or below), life expectancy at birth for the total population was generally higher than the EU-27 average — namely 81.0 years in Denmark, 81.9 in the Netherlands, 82.3 in Ireland, 82.9 in Cyprus and 82.6 in Sweden.
For a better view of gender issues concerning health, it is also useful to look at life expectancy by highest level of education attained, causes of death and hospital discharges by diagnosis, as well as healthy life years expectancy and lifestyle characteristics, e.g. smoking (see articles in Statistics Explained in the category Health).
Source data for tables and graphs
Eurostat produces and disseminates a number of datasets that show how men and women compare in areas such as education, labour market, earnings, social inclusion and health in the EU. The most relevant and most frequently used datasets are listed in the ‘Equality’ domain. For more information on data sources and availability, see the metadata files linked to the multidimensional tables or in other relevant articles.
where GOEG means Gender overall earnings gap, Em — Mean hourly earnings of men, Hm — Mean monthly hours paid to men, ERm — Employment rate of men (aged 15-64), Ew — Mean hourly earnings of women, Hw — Mean monthly hours paid to women and ERw — Employment rate of women (aged 15-64).
Gender statistics are indispensable for identifying inequalities between women and men, and needed for the purposes of gender policy development and implementation at global, European and national levels. Four world conferences on women convened by the United Nations between 1975 and 1995 have been crucial in putting the cause of gender equality at the very centre of the global agenda. In 1995, the Fourth World Conference on Women held in Beijing adopted the Declaration and Platform for Action.
This specified critical areas of concern considered to represent the main obstacles to women’s advancement, requiring concrete action by governments and civil society. These areas are as follows: women and poverty, education and training of women, women and health, violence against women, women and armed conflict, women and the economy, women in power and decision-making, institutional mechanisms for the advancement of women, human rights of women, women and the media, women and the environment and the girl-child.
Equality between women and men is a founding value of the EU (Article 2 of the Treaty on European Union) as well as a fundamental right (Article 23 of the Charter of Fundamental Rights of the European Union). Following the 1995 conference in Beijing, the European Council requested an annual review of how EU Member States were implementing the Beijing Platform for Action. To track progress, each EU Council Presidency produces a report that covers developments in a specific critical area. Successive EU Council Presidencies have developed a set of indicators — called the Beijing indicators — covering most of the critical areas of the Beijing Platform for Action.
In March 2010, on the occasion of the 15th anniversary of the Beijing conference, the European Commission adopted the Women’s Charter. In this charter, the European Commission reiterated its ‘commitment to making equality between women and men a reality’ by strengthening the gender perspective in all its policies and by bringing forward specific measures to promote gender equality.
In December 2015, the European Commission adopted the Strategic engagement for gender equality 2016-2019. In this work programme, the Commission has reaffirmed its commitment to continue its work to promote equality between men and women. This means maintaining the focus of gender-equality policy on the five existing thematic priority areas:
- increasing female labour-market participation and the equal economic independence of women and men,
- reducing the gender pay, earnings and pension gaps and thus fighting poverty among women,
- promoting equality between women and men in decision-making,
- combating gender-based violence and protecting and supporting victims,
- promoting gender equality and women’s rights across the world.
The Commission's work programme includes a comprehensive list of indicators measuring gender equality (e.g. employment rate, gender pay gap, at-risk-of-poverty and social inclusion rate). It supports the implementation of the gender equality dimension in the Europe 2020 strategy and its headline targets.
The EU and its Member States are supported by the European Institute for Gender Equality in their efforts to promote gender equality and to raise awareness about gender equality issues. The Institute supports EU Presidencies in developing the Beijing indicators. It also developed the Gender Equality Index, which provides a synthetic measure of gender equality in EU Member States.
- The EU-level targets have been translated into national targets in each EU country, reflecting different situations and circumstances
- The GPG and ERG show a negative relationship. One possible explanation is the following: in countries where the employment rate for women is particularly low, women who still choose to work may decide so due to their higher job profile and earnings expectations. This translates into a lower (unadjusted) gender pay gap as the latter compares the average hourly earnings of all working men against all working women without correcting for the fact that working women tend to have a specific profile.