Labour market statistics at regional level

Data extracted in May 2025.

Planned article update: September 2026.

Highlights

In 2024, the lowest employment rates across the EU were recorded in southern Italy – Calabria (48.5%) and Campania (49.4%) were the only regions where less than half of all people aged 20 to 64 years were in employment.

In 2024, the Czech regions of Praha and Střední Čechy and the Dutch regions of Noord-Brabant and Utrecht recorded the lowest long-term unemployment rates in the EU; in all 4 regions, 0.4% of the labour force aged 15 to 74 years had been unemployed for 12 months or more.

Source: Eurostat (lfst_r_lfsd2pwn)

On 4 March 2021, the European Commission set out its ambition to build a stronger, more social EU by focusing on jobs and skills, paving the way for a fair, inclusive and resilient socioeconomic recovery from the COVID-19 crisis. The European Pillar of Social Rights Action Plan (COM(2021) 102 final) outlines specific actions and headline targets to improve employment, skills and social protection across the EU. One of the principal targets is to have, by 2030, an employment rate of at least 78% among people aged 20 to 64 years.

Employment and social policies offer a broad range of practical benefits for people living in the EU, including employment support, mobility within the labour market, skills development, social protection and inclusion, as well as range of different rights at work. In 2024, there were 260.6 million people aged 20 to 64 years in the EU (those considered to be of core working age); see the infographic above. Of these, the labour force was composed of 197.6 million employed people and 11.9 million unemployed people who were actively seeking and available for work. There were 51.1 million people outside the labour force – in other words, economically inactive – for example, students, retired people (if under the age of 65), people caring for other family members, volunteers and those unable to work due to a long-term illness or disability.

Among NUTS level 2 regions, the Finnish archipelago of Åland recorded the highest share of employed people within the core working-age population, at 86.4% in 2024. By contrast, less than half of this subpopulation was employed in the southern Italian regions of Calabria (48.5%) and Campania (49.4%).

This chapter examines employment and unemployment patterns across EU regions, offering a detailed analysis of regional labour markets, with a focus on qualifications and skills. It highlights key indicators such as employment rates, unemployment rates and the structure of labour markets, offering insights into regional disparities within the EU.

Employment

More about the data: employment rate targets in the European Pillar of Social Rights

The employment rate is the percentage of employed people (of a given age) relative to the total population (of the same age).

The EU prioritises increasing the number and share of people in work as 1 of its key policy objectives. This goal has been central to EU employment policies since the launch of the European employment strategy in 1997; it was subsequently integrated into the Lisbon and Europe 2020 strategies.

The employment rate is a key indicator in the social scoreboard, which monitors the implementation of the European Pillar of Social Rights. By 2030, the EU aims to have an employment rate of at least 78% among people aged 20 to 64 years. This age range reflects the growing share of young people who remain within education into their late teens and beyond, potentially limiting early labour market participation, while most EU residents retire by the age of 65.

Individual EU countries have different employment rate targets. To achieve the overall EU target of a 78% employment rate by 2030, EU countries presented and agreed national targets in June 2022. These are generally higher for countries that already had relatively high rates. For example, the target for Hungary has been set at 85.0%, for Malta at 84.6% and for Germany at 83.0%.

The employment rate is included in the EU’s sustainable development goals (SDGs) indicator set. Goal 8 seeks to promote sustained, inclusive and sustainable economic growth, through full and productive employment and decent work for all.

In 2024, the EU’s employment rate was 2.2 percentage points below its 2030 target

Prior to the COVID-19 crisis, the EU’s employment rate for the core working-age population (20 to 64 years) increased steadily for 6 consecutive years, reaching 73.1% by 2019. This upward development was interrupted in 2020 when the pandemic contributed to a fall of 0.9 percentage points. However, the employment rate rebounded in 2021, nearly returning to its pre-pandemic levels, and continued to rise in subsequent years, with a particularly sharp increase in 2022 (up 1.6 points). By 2024, the EU’s employment rate had climbed to a historical high of 75.8%, which was 2.2 points below the target for 2030, as set by the European Pillar of Social Rights Action Plan.

Map 1 shows the employment rate in 2024 for NUTS level 2 regions. Almost half (46.5%) of all EU regions – 113 out of the 243 regions for which data are available – had already reached or surpassed the EU’s target of 78.0% by 2024 (those regions shown in shades of teal). These 113 regions were found in clusters, with high concentrations in Czechia (all 8 regions), Denmark (all 5 regions), Germany (35 out of 38 regions; the exceptions being Bremen, Düsseldorf and Berlin), Ireland (all 3 regions), the Netherlands (all 12 regions), Slovakia (3 out of 4 regions) and Sweden (all 8 regions); this group included Estonia, Cyprus and Malta too.

At the top end of the distribution, the highest employment rates among NUTS level 2 regions in 2024 – and the only regions to record rates of more than 85.0% – were:

the archipelago of Åland in Finland (86.4%)
Warszawski stołeczny, the Polish capital region (86.2%)
Bratislavský kraj, the Slovak capital region (85.4%)
Budapest, the Hungarian capital region (85.3%)
Utrecht in the Netherlands (85.3%)
Praha, the Czech capital region (85.1%).

Aside from the 6 regions mentioned above, an additional 22 regions recorded employment rates of at least 83.5% (as shown by the darkest shade of teal in Map 1). Almost half of them were located in Germany, while the others were exclusively from the Netherlands, Hungary or Sweden – including the capital regions of Noord-Holland (the Netherlands; 84.4%) and Stockholm (Sweden; 83.7%).

In 2024, all multi-regional northern, eastern and southern EU countries reported that their capital region had a higher employment rate than their national average. For example, Romania’s capital region of Bucureşti-Ilfov had an employment rate of 81.1%, which was 11.6 percentage points above the national average of 69.5%. A similar pattern was observed in the western EU countries of Ireland, France and the Netherlands. By contrast, the pattern was reversed in Belgium, Germany and Austria, where capital regions recorded lower employment rates than their respective national averages. Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest and Wien registered the lowest regional employment rates across the whole of Belgium and Austria, at 64.1% and 70.6%, respectively.

In 2024, the southern Italian regions of Calabria, Campania and Sicilia recorded the lowest employment rates in the EU

Many of the regions with relatively low employment rates were rural, sparsely populated, or regions on the periphery of the EU. This pattern was particularly apparent in southern regions of Spain and Italy, much of Greece, some regions in Romania, and the outermost regions of France. These areas typically experienced limited employment opportunities, especially for individuals with intermediate and high skill levels.

Another group of regions characterised by relatively low employment rates are former industrial heartlands that have not adapted economically. Some of these have witnessed the negative impact of globalisation on traditional sectors of their economies (such as coal mining, steel or textiles manufacturing). Examples include a band of regions running from north-east France into the Région wallonne (Belgium).

Approximately 1 in 4 (65 out of the 243 regions for which data are available) EU regions had an employment rate that was below 73.5% in 2024 (as shown by the 2 darkest shades of gold in Map 1). This group included:

2 regions in southern Italy where less than half of the core working-age population was employed – Calabria (48.5%) and Campania (49.4%)
the island region of Sicilia (also in southern Italy), where employment covered just over half of the working-age population (50.7%), the 3rd lowest rate in the EU
the capital regions of Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest in Belgium (64.1%), Lazio in Italy (69.0%), Wien in Austria (70.6%) and Attiki in Greece (71.0%).

Map 1: Employment rate
Source: Eurostat (lfst_r_lfe2emprtn)

In 2024, Italy had the highest regional disparity for employment rates

Several EU countries face considerable labour market disparities across their regions, with labour shortages in some regions contrasted against persistently high unemployment in others. A population-weighted coefficient of variation provides a means to analyse these inter-regional disparities. Figure 1 shows that, in 2024, Italy had the highest regional disparities in employment rates, with a coefficient of variation of 15.6%. Broadly, there was a north-south split: the Alpine region of Provincia Autonoma di Bolzano/Bozen recorded the highest employment rate (79.9%), while the southern regions of Calabria and Campania had the lowest rates (48.5% and 49.4%).

Belgium (8.1%), Romania (7.6%) and Spain (6.5%) had the next highest coefficients of variation for regional employment rates in 2024:

in Belgium, the highest regional employment rates were generally recorded in Vlaams Gewest, while lower rates were observed in Région wallonne and particularly in the capital region
in Romania, the highest regional employment rate was in the capital region of Bucureşti-Ilfov (81.1%), with notably lower rates observed in all other regions, in particular, Sud-Est (62.6%) and Sud-Vest Oltenia (63.5%)
in Spain, the highest regional employment rates were generally recorded in northern and eastern regions, as well as the capital city region; lower rates were observed in peripheral, southern and western regions.

At the other end of the range, the lowest regional disparities in employment rates – with a coefficient of variation of 2.0% or less – were recorded in the Nordic EU countries and the Netherlands.

Figure 1 shows that regional employment rates converged to some degree across the EU between 2014 and 2024. The coefficient of variation for the EU as a whole fell from 13.0% to 9.5%. In 15 (out of 17) EU countries for which data are available, inter-regional employment rate disparities narrowed. The largest falls – in relative terms – occurred in Finland, the Netherlands, Czechia, Portugal and Spain, as regional disparities decreased by at least 40%. By contrast, Romania and Austria were the only EU countries to report an increase in regional disparities, rising 8.6% and 2.0%, respectively.

Figure 1: Regional disparities in employment rates
Source: Eurostat (lfst_r_lmder)

The EU’s gender employment gap was 10.0 percentage points in 2024

The gender employment gap is included in the EU’s SDGs indicator set. Goal 5 seeks to achieve gender equality by, among other actions, ending all forms of discrimination, violence, and any harmful practices against women and girls, while promoting women’s social and economic empowerment.

Long-standing challenges related to female participation in the labour force are reflected in persistent gender gaps in employment and pay. These gaps exist for a variety of reasons, including:

women often bear a disproportionate share of unpaid care and household chores that may limit their availability for paid employment
gender bias and discrimination when hiring, promoting and paying women
fewer women in leadership positions to draw attention to gender-related policies or to mentor more junior female staff
a lack of affordable childcare and support for working parents
disincentives in tax and benefit system that can lead to 2nd earners bearing a higher tax burden when they choose to participate in the labour market
occupational segregation, with women often concentrated in specific activities that are characterised by lower wages and/or fewer opportunities for career development.

In 2024, the EU employment rate for men aged 20 to 64 years was 80.8%, while the corresponding rate for women of the same age was considerably lower, at 70.8%. This resulted in a gender employment gap – defined here as the difference between male and female employment rates – of 10.0 percentage points. As part of its broader target to increase the overall employment rate to 78% by 2030, the European Pillar of Social Rights Action Plan also includes a subgoal to halve the gender employment gap. This implies reducing the gap to 5.6 percentage points by 2030 – equivalent to an average annual decrease of 0.5 points from 2019 onwards.

In 2024, there were 4 regions across the EU where employment rates for women were higher than those for men

In 2024, 59 out of the 243 NUTS level 2 regions for which data are available reported a gender employment gap that was 5.6 percentage points or lower – in other words, meeting the subgoal for the European Pillar of Social Rights Action Plan; they are shown in different shades of teal in Map 2. This group of 59 regions was mainly concentrated in Germany (13 regions), France (10 regions), Sweden (7 out of 8 regions), Portugal (6 out of 9 regions) and Finland (all 5 regions); it also included the Baltic regions and Luxembourg. Those regions with relatively small gender employment gaps were often characterised by high overall employment rates.

In 2024, there were only 4 regions within the EU that reported a higher employment rate for women (than for men):

the Finnish regions of Åland, Etelä-Suomi and Pohjois- ja Itä-Suomi
the Croatian capital region of Grad Zagreb.

Despite some progress made in reducing the gender employment gap, female employment rates continue to lag behind male rates in the vast majority of EU regions. Many of the regions with relatively large gender employment gaps were characterised by high unemployment rates and a greater share of women outside the labour force. In 2024, there were 24 NUTS level 2 regions that reported gender employment gaps of at least 17.5 percentage points (as shown by the darkest shade of gold in Map 2). The regions composing this group were concentrated in southern and eastern EU countries:

11 out of 13 regions in Greece, the exceptions being Attiki and Ipeiros
8 regions in central/southern Italy, including the capital region of Lazio
4 regions in Romania
Ciudad de Ceuta in Spain.

Sterea Elláda (Greece; 31.2 percentage points in 2024) had the largest gender employment gap in the EU, followed by the Italian regions of Puglia (29.8 points), Campania (29.1 points) and Basilicata (28.1 points).

Map 2: Gender employment gap
Source: Eurostat (lfst_r_lfe2emprtn)

Employment – focus on qualifications and skills

Young people neither in employment nor in education and training (NEET)

More about the data: young people neither in employment nor in education and training (NEET)

The share of young people (aged 15 to 29 years) who are neither in employment nor in education and training (NEET) provides a useful measure for studying the vulnerability of young people in terms of their labour market participation and social exclusion.

The NEET rate is expressed relative to the total population of the same age (15 to 29 years); the numerator includes not only young people who are unemployed but also young people who are outside the labour force for reasons other than education or training (for example, because they are caring for family members, volunteering or travelling, or unable to work for health reasons).

The NEET rate is included in the EU’s SDG indicator set. Goal 8 seeks to promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all.

Economic crises tend to impact young people disproportionately, as they are more likely to work under temporary and other atypical contracts that are easier to terminate. The NEET rate helps assess the share of young people who have not transitioned from education or training to employment. It is generally seen as a more comprehensive measure than the unemployment rate, as it more closely reflects young people’s risk of social and labour market exclusion.

Within the European Pillar of Social Rights Action Plan, the EU has set a policy target whereby the NEET rate should decrease to less than 9% by 2030. Having peaked at 16.1% in 2013, the EU’s NEET rate subsequently fell during 6 consecutive years. With the onset of the COVID-19 crisis, it climbed to 13.8% in 2020, after which a downward pattern of development returned. In 2024, the EU’s NEET rate stood at 11.0%.

In 2024, the 4 EU regions with the lowest NEET rates were all located in the Netherlands

In 2024, 89 NUTS level 2 regions reported a NEET rate of less than 9.0% (the EU’s policy target to be reached by 2030); they are shown in teal shades within Map 3. This group was concentrated in northern Belgium (all 5 regions of Vlaams Gewest), Czechia (6 out of 8 regions), Ireland (all 3 regions), north-western Hungary (4 regions), the Netherlands (all 12 regions), Austria (7 out of 9 regions), Slovenia (both regions), Slovakia (3 out of 4 regions) and Sweden (all 8 regions); it also included Malta.

Looking more closely at the data, 26 regions across the EU recorded a NEET rate below 6.5% in 2024 (as shown by the darkest shade of teal in Map 3). This group included several capital regions, notably those of Bulgaria, Czechia, Denmark, Croatia, Hungary, the Netherlands and Sweden. The lowest NEET rates in the EU were observed in the Netherlands, with Utrecht recording the lowest share, at 4.4%, followed by the capital region of Noord-Holland (4.5%), Noord-Brabant and Overijssel (both 4.7%). Praha, the Czech capital region, had the lowest rate outside the Netherlands, at 4.8% – a share that was also recorded in the Dutch region of Zuid-Holland.

As noted above, some of the lowest NEET rates in the EU were recorded in capital regions. More broadly, capital regions generally reported lower NEET rates than the national average. In 2024, there were only 4 exceptions – among multi-regional EU countries – where the share of young people neither in employment nor in education or training was higher in the capital region than the national average:

Wien in Austria (12.7%), where the NEET rate was 3.5 percentage points higher than the national average (9.2%)
Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest in Belgium (13.1%), where the rate was 3.2 points higher than the national average (9.9%)
Berlin in Germany (11.1%), where the rate that was 2.6 points higher than the national average (8.5%)
Eastern and Midland in Ireland (7.7%), where the rate was marginally higher than the national average (7.6%).

By contrast, Bucureşti-Ilfov – the capital region of Romania – had a NEET rate in 2024 that was 9.9 percentage points lower than the national average. This broadly reflected the pattern observed across most eastern EU countries, with the capital regions of Bulgaria (6.5 points), Hungary (5.4 points), Slovakia (also 5.4 points; 2022 data) and Croatia (5.0 points) also recording considerably lower rates than their respective national averages.

In 2024, 24 out of the 240 NUTS level 2 regions for which data are available recorded NEET rates of at least 18.0% among young people aged 15 to 29 years (these regions are shaded in the darkest 2 shades of gold in Map 3). The highest NEET rates were generally observed in predominantly rural regions of southern and eastern EU countries, as well as in the French outermost regions. At the upper end of the distribution, 5 regions had NEET rates of at least 25.0%:

the Italian regions of Sicilia (25.7%) and Calabria (26.2%)
the Romanian regions of Sud-Vest Oltenia (25.0%) and Sud-Est (29.9%)
the French outermost region of Guyane had the highest rate, at 34.4%.

Map 3: Young people neither in employment nor in education and training
Source: Eurostat (edat_lfse_22)

In 2024, the EU’s NEET rate was 2.1 percentage points higher among young females than young males

Across the EU, 12.1% of young females aged 15 to 29 years were neither in employment nor in education and training in 2024. This figure was 2.1 percentage points higher than the corresponding rate for young males (10.0%). Across NUTS level 2 regions, nearly 3 out of 4 regions had a higher NEET rate among young females. The gender gaps were most pronounced in regions located across eastern and southern EU countries, where cultural, economic and societal factors may hinder some young females’ from entering the workforce.

Figure 2 confirms the highest NEET rates among young females in 2024 were recorded in the Romanian regions of Sud-Est (37.7%), Centru (32.7%) and Sud-Vest Oltenia (30.6%), as well as the French outermost region of Guyane (33.7%). This may reflect, at least in part, persistent structural and societal barriers disproportionately affecting young women in accessing education, training and employment. For young males, the highest NEET rate, by far, was observed in Guyane, at 35.1%; this was followed by Severozapaden in Bulgaria (25.7%).

A closer analysis of the data for regions with the highest NEET rates among young females and males in 2024 reveals some notable gender differences. For instance:

Sud-Muntenia in Romania (28.7%), Észak-Magyarország in Hungary (26.7%) and Anatoliki Makedonia, Thraki in Greece (24.7%) had some of the highest NEET rates for young females, but did not feature among those regions with the highest overall NEET rates
Notio Aigaio in Greece (22.6%) and Guadeloupe in France (21.1%) had some of the highest NEET rates for young males, but similarly did not feature among those regions with the highest overall NEET rates.

In 2024, the lowest overall NEET rates in the EU were concentrated in the Netherlands, Germany and Czechia, particularly across economically developed and urbanised regions that may make labour market integration for young people easier.

The lowest female NEET rate was recorded in Grad Zagreb (the Croatian capital region; 4.6%), while Budapest (the capital region of Hungary; 5.2%) and Östra Mellansverige (Sweden; 5.5%) were the only other regions from outside of the Netherlands to feature among those with the lowest rates.
The lowest male NEET rates were recorded in the neighbouring Czech regions of Praha (2.4%) and Střední Čechy (2.5%). There were 4 other regions from Czechia that featured among those with the 12 lowest rates, alongside 5 regions from the Netherlands (the lowest rate was in Utrecht; 3.6%) and Oberbayern in Germany (4.2%).

Figure 2: Young people neither in employment nor in education and training
Source: Eurostat (edat_lfse_22)

Employment rates by educational attainment

More about the data: employment rates by educational attainment

An individual’s level of educational attainment can play a key role when seeking employment. People with a tertiary level of educational attainment (as defined by the international standard classification of education (ISCED 2011 levels 5 to 8)) generally enjoy the most success when trying to find work. They also tend to be better shielded from the risks of unemployment than their peers with lower levels of educational attainment.

The data presented in this section concern people aged 25 to 64 years, as this represents a cohort of individuals who have generally completed their education or training and are most likely to be actively participating in the labour market. As such, it excludes younger individuals who may still be studying, as well as older individuals who may be in retirement.

In 2024, 184.7 million people aged 25 to 64 years were employed across the EU. The largest share of this cohort consisted of people with an upper secondary or post-secondary non-tertiary education (ISCED levels 3 to 4; 44.4%), followed by those with a tertiary level of educational attainment (ISCED levels 5 to 8; 40.6%). A relatively small share of the EU workforce had no more than a lower secondary education (ISCED levels 0 to 2; 14.8%). The strong links between educational attainment and employment opportunities are reflected in the latest employment rates:

59.2% for people with no more than a lower secondary education (hereafter referred to as a low level of education)
78.3% for people with an upper secondary or post-secondary non-tertiary education (a medium level of education)
87.8% for people with a tertiary level of education (a high level of education).

Map 4 presents employment rates in 2024 for people aged 25 to 64 years according to these 3 different levels of educational attainment.

There were 46 NUTS level 2 regions where fewer than half of all people with a low level of education were in employment. By contrast, employment rates for people with medium or high levels of education exceeded 50.0% in every region of the EU.
There were 71 NUTS level 2 regions where at least 90.0% of all people with a high level of education were in employment. By contrast, employment rates for people with a low level of education remained consistently below 90.0% across every region of the EU, while Åland in Finland was the only region to report an employment rate of at least 90.0% for people with a medium level of education.

In 2024, Východné Slovensko in Slovakia had the lowest employment rate among people with a low level of education …

The 1st part of Map 4 shows employment rates for people aged 25 to 64 years with a low level of education. In 2024, there were 46 NUTS level 2 regions with employment rates below 50.0% for this cohort. These 46 regions were mainly concentrated in eastern EU countries (excluding Czechia, Hungary and Slovenia), as well as in southern Belgium and southern Italy; among others, this group also included the capital regions of Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest (Belgium), Attiki (Greece) and Wien (Austria). The lowest employment rate was recorded in Východné Slovensko – the easternmost region of Slovakia – where 27.7% of people with a low level of education were in employment. There were 4 other regions that recorded employment rates below 35.0%: Guyane (France; 31.8%), Centru (Romania; 33.4%), Stredné Slovensko (Slovakia; 34.4%) and Severozapaden (Bulgaria; 34.7%).

… while 3 regions in southern Italy had the lowest employment rates for people with a medium level of education

The 2nd map shows employment rates for people aged 25 to 64 years with a medium level of education. In 2024, there were 8 NUTS level 2 regions that recorded an employment rate of at least 87.0% for this cohort. They included 3 regions in Czechia (among them the capital region of Praha), Bratislavský kraj (the capital region of Slovakia), Malta, Közép-Dunántúl (Hungary), as well as the island regions of Região Autónoma dos Açores (Portugal) and Åland (Finland). Åland recorded the highest employment rate for people with a medium level of education, at 90.1%.

At the lower end of the distribution, there were 3 regions within the EU where fewer than 60.0% of people with a medium level of education were in employment. All 3 were located in southern Italy: Calabria (53.2%), Campania (58.2%) and Sicilia (59.8%). The next lowest employment rate was recorded in the Belgian capital region – Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest – at 60.9%.

In 2024, Região Autónoma dos Açores in Portugal recorded the highest proportion of tertiary-educated people in employment

The 3rd map shows employment rates for people aged 25 to 64 years with a high level of education. In 2024, there were 71 NUTS level 2 regions across the EU that recorded employment rates of at least 90.0% for this cohort. These regions were clustered across Bulgaria, Lithuania, Hungary, the Netherlands, Poland, Portugal, Romania and Slovenia; Malta had a similarly high level too. The highest proportion of tertiary-educated people in employment was recorded in the Portuguese island region of Região Autónoma dos Açores (93.9%), while employment rates of at least 93.0% were also observed in Småland med öarna (Sweden), Centru (Romania), Pest (Hungary) and Bratislavský kraj (Slovakia).

In 2024, employment rates for people aged 25 to 64 years with a tertiary level of education were generally higher in capital regions than their respective national averages. This may reflect the ability of capital regions to attract highly qualified individuals, exerting considerable ‘pull effects’ through the diverse educational, employment and social/lifestyle opportunities that they offer. This pattern was particularly evident in Greece, where the employment rate for tertiary-educated people in the capital region of Attiki was 3.1 percentage points above the national average. A similar although less pronounced situation was observed in Slovakia, Spain, Czechia, Bulgaria, Croatia and Poland, where the gap between these 2 rates exceeded 1.0 points. By contrast, in the western EU countries of Belgium, Austria and Germany, the national employment rate for this cohort was at least 3.2 points higher than that for the capital region. This gap was particularly wide in Belgium, as the employment rate for tertiary-educated people in Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest was 6.0 points below the national average.

There were 10 NUTS level 2 regions where, in 2024, the employment rate for people aged 25 to 64 years with a high level of education was below 78.5%. These regions were exclusively located in the southern EU countries of Italy (5 regions), Greece (4 regions) and Spain (1 region, Ciudad de Ceuta). Almost all of these regions were predominantly rural, characterised by relatively large agricultural sectors and limited opportunities for highly skilled workers. The southern Italian region of Calabria had the lowest rate for this cohort, at 71.1%.

Map 4: Employment rate by educational attainment
(%, people aged 25–64 years, by NUTS 2 regions, 2024)
Source: Eurostat (lfst_r_lfe2eedu) and (lfst_r_lfsd2pop)

Highly skilled people

A recent communication from the European Commission, Harnessing talent in Europe’s regions (COM(2023) 32 final), highlighted the issue of increasing global competition for talent, as many developed world economies are expected to face shrinking populations in the years ahead. The communication identified demographic transformation as a cause for concern in several EU regions, where shrinking working-age populations and the potential departure of young and skilled workforces to other regions/territories could result in a ‘talent development trap’.

More about the data: highly skilled people

The International Classification of Occupations (ISCO) provides statisticians with a framework for internationally comparable data about occupations (a set of tasks and duties performed, or meant to be performed, by 1 person, including for an employer or in self-employment). The current version of the classification was published in 2008 (its 4th iteration) and is known as ISCO-08. It is based on a hierarchical classification made-up of 10 major groups, denoted by 1-digit codes.

For the purpose of this publication, highly skilled employed people are defined as people aged 25 to 64 years in the following occupations:

managers (ISCO 1)
professionals (ISCO 2)
technicians and associate professionals (ISCO 3).

In 2024, there were 84.2 million highly skilled people aged 25 to 64 years employed within the EU; they accounted for 45.8% of the total number of employed people of the same age. Map 5 shows that the regional distribution of highly skilled people across NUTS level 2 regions was somewhat skewed: 106 out of 243 regions for which data are available – or 43.6% of all regions – reported a share of highly skilled employed people that was above the EU average.

Capital regions attract highly qualified talent

There were 21 NUTS level 2 regions across the EU where, in 2024, at least 60.0% of all employed people aged 25 to 64 years were considered highly skilled. Of these, 13 were capital regions, which tend to attract highly qualified individuals by offering a wide array of job prospects in dynamic sectors of the economy, as well as diverse cultural and social opportunities.

Stockholm, the Swedish capital region, recorded the highest share, with 72.7% of employed people considered highly skilled.
In the capital regions of Czechia, Poland, Hungary, the Netherlands and Denmark, more than 2 out of 3 employed people were considered highly skilled; the same was true for Luxembourg.
The capital regions of France, Croatia, Belgium, Slovakia, Finland, Lithuania and Germany also reported shares of highly skilled employed people that were above 60.0%.
Luxembourg recorded a share of 71.7%.
Non-capital regions with shares over 60.0% included:
- the Dutch regions of Utrecht (72.0%), Zuid-Holland (63.8%) and Groningen (60.6%)
- the Belgian Prov. Brabant Wallon (68.2%)
- the Swedish regions of Sydsverige (63.5%) and Östra Mellansverige (60.7%)
- the German region of Hamburg (61.4%).

In 2024, there were 20 NUTS level 2 regions where highly skilled employed people accounted for less than 30.0% of total employment among those aged 25 to 64 years (these regions are denoted by a yellow shade in Map 5). This group was concentrated in the south-east of the EU, comprising 11 regions in Greece and 7 regions in Romania. The other 2 regions were both located in Spain: the central region of Castilla-La Mancha and the island region of Canarias.

Looking in more detail, the lowest share of highly skilled employed people was recorded in the Greek region of Sterea Elláda (18.5% in 2024); it was the only region across the EU where fewer than 1 in 5 employed people were highly skilled. The next lowest shares were observed in Romania – Sud-Muntenia (22.5%) and Nord-Est (22.7%); these were followed by 3 more Greek regions, namely, Anatoliki Makedonia, Thraki (23.3%), Voreio Aigaio (24.4%) and Peloponnisos (24.8%).

Map 5: Highly skilled employed people
Source: Eurostat (labour force survey)

People frequently using digital devices at work

Technology has become integral to many job functions, from administrative tasks to complex decision-making processes. In capital regions, where economies are often more service-oriented and knowledge-driven, the adoption of digital tools is particularly high. As technology advances, digital literacy becomes essential for maintaining productivity and competitiveness. In 2022, just over 2 out of 5 (40.3%) employed people in the EU aged 20 to 64 years reported using digital devices for at least half of their time at work. Such devices encompass computers, tablets, phablets and smartphones for work-related tasks; phone calls are excluded.

In 2022, approximately 3 out of 4 employed people in Stockholm used digital devices for at least half of their working time

Map 6 shows the regional distribution of employed people aged 20 to 64 years who, in 2022, spent at least half of their working time using digital devices. Among the 234 NUTS level 2 regions for which data are available, 127 reported shares above the EU average of 40.3%. Within this group, 50 regions reported that at least half of all employed people spent at least 50% of their working time using digital devices (as shown by the 2 darkest shades of blue).

Looking in more detail, the map highlights the top decile of the distribution – regions where at least 54.5% of employed people used digital devices for at least half of their working time (shown by the darkest shade of blue in Map 6). In 2022, 25 NUTS level 2 regions were in this category, almost all of them located in western and Nordic EU countries. This group included all 8 Swedish regions and 7 out of the 10 Dutch regions for which data are available. The remainder comprised:

the capital regions of France, Finland, Austria, Germany, Denmark and Ireland
2 other predominantly urban German regions – Oberbayern and Stuttgart
Luxembourg
the Polish capital region of Warszawski stołeczny, the only region outside western and Nordic EU countries.

The Swedish capital region of Stockholm recorded, by far, the highest share of employed people using digital devices for at least half of their working time in 2022 (75.9%). The next highest share was reported in Sydsverige (also Sweden; 65.2%), followed by 3 capital regions: Noord-Holland (the Netherlands; 64.9%), Ile-de-France (France; 63.5%), and Helsinki-Uusimaa (Finland; 62.0%).

At the lower end of the distribution, there were 25 NUTS level 2 regions where less than 24.0% of employed people used digital devices for at least half of their working time (as shown by the lightest shade of yellow in Map 6). These regions were concentrated across southern and eastern EU countries:

5 out of 6 regions in Bulgaria, with the exception of the capital region, Yugozapaden
11 out of 13 regions in Greece, with the exceptions of the capital region of Attiki and the island region of Notio Aigaio
7 out of 8 regions in Romania, with the exception of the capital region, Bucureşti-Ilfov
the remaining 2 regions in this group were both located in Hungary – Nyugat-Dunántúl and Észak-Magyarország.

The central Greek mainland region of Sterea Elláda recorded the lowest share of employed people using digital devices for at least half of their working time, at 11.6% in 2022. The next lowest shares were reported in Peloponnisos and Dytiki Elláda (also Greece; both 13.0%), followed by Severozapaden (Bulgaria; 14.3%) and Ipeiros (Greece; 14.8%).

Map 6: Frequent use of digital devices at work
Source: Eurostat (labour force survey) and (lfso_22dmsc01)

Unemployment

Unemployment can impact not only the macroeconomic performance of a country or a region, for example lowering productive capacity, but also the well-being of individuals and their families. Rising unemployment results in a loss of income for individuals, increased pressure on government spending for social benefits and a reduction in tax revenues. Additionally, the personal and social costs of unemployment are varied and include a higher risk of poverty, social exclusion, debt or homelessness, while the stigma of being unemployed may have a potentially detrimental impact on (mental) health.

More about the data: the unemployment rate

Within this section, data are presented for people aged 15 to 74 years; this is the standard age range employed by Eurostat and the International Labour Organization (ILO) for studying unemployment rates within the labour force.

Contrary to what may be thought, the unemployment rate is not the direct opposite of the employment rate, since the 2 measures do not have the same denominator; the unemployment rate uses the labour force as a denominator, while the employment rate uses the population.

In 2024, there were 13.1 million unemployed people aged 15 to 74 years across the EU. When expressed as a share of the labour force (of the same age), the EU’s unemployment rate was 5.9%. These figures – the overall number of unemployed people and the unemployment rate –represent the lowest levels recorded since the start of the time series in 2002.

Looking more closely at recent developments, the EU’s unemployment rate fell from a peak of 11.4% in 2013, declining over 6 consecutive years to 6.7% by 2019. With the onset of the COVID-19 crisis, the rate increased 0.4 percentage points in 2020 and remained unchanged the following year as the pandemic continued to affect much of the EU economy. After a marked decrease in unemployment during 2022 – when labour shortages became apparent in certain sectors – unemployment continued to fall in 2023 and 2024, albeit at a relatively modest pace.

The Czech region of Střední Čechy had the lowest regional unemployment rate in 2024

Map 7 presents unemployment rates (for people aged 15 to 74 years) across NUTS level 2 regions. In 2024, the distribution of regional unemployment rates was relatively balanced: of the 204 NUTS level 2 regions for which data are available, 100 had rates above the EU average of 5.9%, while 102 reported rates below the average; Nordjylland (Denmark) and Sostinės regionas (the capital region of Lithuania) had the same unemployment rate as the EU average. The highest regional unemployment rates were generally concentrated in southern EU countries and in several of France’s outermost regions, while the lowest rates were primarily found across eastern EU countries.

In 2024, there were 21 regions across the EU that reported unemployment rates of at least 10.5%, as shown by the darkest 2 shades of blue in Map 7. The Spanish autonomous cities of Ceuta and Melilla were the only regions with rates exceeding 20.0%. Leaving these 2 regions and the French outermost regions aside, the highest rates in the EU were reported by Andalucía (16.5%) and Extremadura (15.5%) in south-western Spain, Ionia Nisia (16.2%) in western Greece, and Campania (15.6%) in southern Italy.

At the lower end of the distribution, there were 10 regions with unemployment rates below 2.5% in 2024; they are shown with a yellow shade in Map 7. A majority of these 10 regions were located in Czechia and Poland, while Provincia Autonoma di Bolzano/Bozen (northern Italy), Zeeland (the Netherlands), Bucureşti-Ilfov (the capital region of Romania) and Bratislavský kraj (the capital region of Slovakia) also recorded such low rates. The neighbouring Czech regions of Střední Čechy and Praha (the former surrounds the latter), recorded the lowest unemployment rates in the EU, at 1.3% and 1.8%, respectively.

Unemployment rates in the capital regions of multi-regional eastern and Baltic EU countries were consistently lower than their national averages. In 2024, this pattern was particularly notable in Romania and Slovakia, as their national unemployment rates were at least twice as high as those recorded in the capital regions of Bucureşti-Ilfov and Bratislavský kraj. By contrast, the capital regions of Belgium, Denmark, Germany, Ireland, France, the Netherlands, Austria and Finland reported higher unemployment rates than their respective national averages. Indeed, in 6 of these 8 countries – with France and the Netherlands as exceptions – the capital region recorded the highest unemployment rate of any region (in Finland, Etelä-Suomi had a rate identical to that recorded in Helsinki-Uusimaa). This pattern was especially striking in Belgium, as Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest had an unemployment rate that was more than double the national average.

Unemployment rates vary considerably as a function of age. In 2024, EU-wide unemployment rates were highest among young people aged 15 to 24 years (14.9%) and lowest among people aged 45 to 54 and 55 to 64 years (both 4.4%). Subject to data availability, young people systematically faced the highest unemployment rates in every NUTS level 2 region of the EU. In 6 regions, the unemployment rate of young people was at least 5 times as high as the regional average (for people aged 15 to 74 years):

Corse in France (6.4 times as high)
Nord-Vest in Romania (5.7)
Praha, the capital region of Czechia (5.4)
Prov. Oost-Vlaanderen and Prov. West-Vlaanderen in Belgium (5.3 and 5.2, respectively)
Molise in Italy (5.0).

Map 7: Unemployment rate
Source: Eurostat (lfst_r_lfu3rt)

An analysis by age – covering people aged 15 to 24, 25 to 34, 35 to 44 and 45 to 54 years – reveals the highest regional unemployment rates across all EU regions were mainly found in Spanish and French regions (see Map 8):

the autonomous Spanish regions of Ciudad de Ceuta and Ciudad de Melilla featured across all 4 age groups
the French island region of Corse and the French outermost regions of Guadeloupe and Guyane also featured multiple times
Ionia Nisia (Greece) had a particularly high rate for people aged 25 to 34 years.

Conversely, the lowest regional unemployment rates by age group were primarily recorded in Czechia and Hungary:

Střední Čechy (Czechia) featured across all 4 age groups
Praha, Jihovýchod and Jihozápad (all in Czechia) also recorded several particularly low rates
Pest and Budapest (both Hungary) had particularly low rates for people aged 25 to 34 years and people aged 35 to 44 years, respectively
Bayern (Germany) and Zeeland (the Netherlands) had particularly low rates for people aged 15 to 24 years
Prov. Oost-Vlaanderen in Belgium and Gelderland in the Netherlands had particularly low rates for people aged 45 to 54 years.

Map 8: Unemployment rate
(% of labour force, by NUTS 2 regions, 2024)
Source: Eurostat (lfst_r_lfu3rt)

The EU’s long-term unemployment rate was 1.9% in 2024

Long-term unemployment is a major challenge in the EU, affecting both individual well-being and social cohesion. High rates often signal structural issues in the labour market, skill mismatches, or economic stagnation, leading to income loss, social exclusion and increased pressure on public welfare systems and community well-being. In March 2024, the European Commission presented an action plan to tackle labour and skills shortages driven by demographic changes, emerging skill demands and poor working conditions. Building on existing initiatives – including the European Pillar of Social Rights Action Plan – it supports training, mobility and attracting talent – 1 of its key measures is the financing of new projects aimed at achieving zero long-term unemployment.

In 2024, 4.2 million people across the EU had been unemployed for more than a year. The long-term unemployment rate – which is defined as the share of the labour force (aged 15 to 74 years) that has been unemployed for 12 months or more – stood at 1.9%. As such, around 1 in 3 unemployed people in the EU had been jobless for more than a year.

Map 9 shows long-term unemployment rates (for people aged 15 to 74 years) across NUTS level 2 regions. Of the 195 regions for which data are available, 82 recorded rates above the EU average, while 106 had rates below, and 7 had the same rate. As with the overall unemployment rate, some of the highest long-term unemployment rates were observed in southern EU countries and several of France’s outermost regions.

The autonomous Spanish regions of Ciudad de Melilla (16.3%) and Ciudad de Ceuta (15.8%) had, by far, the highest rates.
The French outermost region of Guadeloupe (11.4%) was the only other region in the EU with a double-digit rate, while another French outermost region – La Réunion (8.2%) – also had a relatively high rate.
There were 3 other regions across the EU that had long-term unemployment rates of at least 8.0%, each of them located in southern Italy – Campania (9.9%), Calabria (8.3%) and Sicilia (8.0%).

In 2024, there were 52 regions across the EU where the long-term unemployment rate was below 1.0% (as shown by the lightest 2 shades in Map 9). These regions were mainly concentrated in northern Belgium, Czechia, Denmark (all 5 regions), north-western Hungary, the Netherlands (all 10 regions for which data are available), Austria and Poland; Malta also recorded a rate below 1.0%. The lowest rate across the EU – 0.4% – was observed in 4 regions:

the neighbouring Czech regions of Praha and Střední Čechy
Utrecht and Noord-Brabant in the Netherlands.

Map 9: Long-term unemployment rate
Source: Eurostat (lfst_r_lfu2ltu)

Source data for figures and maps

Regional labour market statistics

Data sources

The information presented in this chapter relates to annual averages derived from the European Union’s labour force survey (EU-LFS). Eurostat compiles and publishes labour market statistics for the EU, individual EU countries, as well as EU regions. In addition, data are also available for several EFTA countries – Iceland, Norway and Switzerland – and candidate countries – Bosnia and Herzegovina, Montenegro, North Macedonia, Serbia and Türkiye – and their statistical regions. The EU-LFS population generally consists of people aged 15 years or over living in private households; definitions are aligned with those provided by the International Labour Organization (ILO).

EU-LFS microdata are collected through a survey to obtain information on an individual’s demographic background, labour status, employment characteristics of their main job, hours worked, employment characteristics of their 2nd job (if relevant), time-related underemployment, the search for employment, education and training, previous work experience of people not in employment and their income. These statistics are aggregated by region and are generally published down to NUTS level 2. Some regional labour market statistics are compiled/transmitted for NUTS level 3 regions, although this is on a voluntary basis.

When evaluating regional information from the EU-LFS, it is important to bear in mind that the information presented relates to the region where the respondent has their permanent residence and that this may be different to the region where their place of work is situated as a result of commuter flows.

The collection of EU-LFS data up to and including reference year 2020 was conducted by national statistical authorities in accordance with Council Regulation (EEC) No 577/98. A new legal basis was introduced for EU-LFS data from 2021 onwards: Regulation (EU) 2019/1700 establishing a common framework for European statistics relating to persons and households, based on data at individual level collected from samples. Furthermore, Commission Implementing Regulation (EU) 2019/2240 specifies the technical items of the dataset, establishing the technical formats for transmission of information and specifying the detailed arrangements and content of the quality reports on the organisation of the sample survey in the labour force domain. This change in legal basis implies a break in series between 2020 and 2021; results obtained before and after 1 January 2021 are consequently not fully comparable.

Some countries/regions have other quality concerns that may impact geographical comparability.

Spain and France use slightly different definitions to those provided by the regulation.
Changes in survey methodology led to a break in series for German data in 2020. Therefore, data for Germany from 2020 onwards should not be compared directly with those for previous years. In addition, data collection during 2020 was impacted by technical issues and COVID-19 measures and hence there is a low degree of reliability for some regions.
The labour force survey sample for Corse (in France) was too small to have reliable regional results, while Mayotte (also France) is covered by a specific annual survey. As a result, data for these 2 regions should also be considered with caution.

For more information please refer the online methodological publication for the EU’s labour force survey.

Indicator definitions

Employed people

In the context of the EU-LFS, employed people include those aged 15 to 89 years who, during the reference week, performed work – even if just for 1 hour – for pay, profit or family gain. Alternatively, the person was not at work, but had a job or business from which they were temporarily absent due to illness, holiday, maternity or paternity leave, job-related training or short or paid parental leave. This definition follows guidelines of the International Labour Organization (ILO). Within this publication, most labour force indicators are for a narrower definition of core working-age people, namely people aged 20 to 64 years.

Employment rate

The employment rate is the percentage of employed people in relation to the comparable total population. For the overall employment rate, the comparison is generally made within the population of core working-age people (defined within this publication as people aged 20 to 64 years). Employment rates may also be calculated for a specific age group and/or sex – for example, males aged 15 to 29 years.

The gender employment gap is defined as the employment rate of men minus the employment rate of women among people aged 20 to 64 years. In a similar vein, employment rates may also be calculated for other cohorts according to a range of socioeconomic criteria, for example, employment rates by level of educational attainment. Within this publication, the employment rate of people with different levels of educational attainment concerns people aged 25 to 64 years who had completed:

no more than a lower secondary education (as defined by the international standard classification of education (ISCED) levels 0 to 2)
an upper secondary or post-secondary non-tertiary education (as defined by ISCED levels 3 to 4)
a tertiary level of education (as defined by ISCED levels 5 to 8) – in other words, people who had completed a short-cycle tertiary education, bachelor’s, master’s or doctoral (PhD) degree.

Highly skilled employed people

The most commonly used approaches for measuring the demand for skills include making use of data on qualifications (educational attainment) or occupations. Both of these datasets are available from within the EU-LFS.

Data on occupations provide indications of the type of jobs undertaken by people in employment. Occupations are considered to be a good indirect measure for skills demand and their distribution across an economy. The international standard classification of occupations (ISCO) allocates jobs to occupations, based on a description that takes into account the level of qualifications and the types of tasks to be carried out. Highly skilled employed people are defined as people employed as managers (ISCO 1), professionals (ISCO 2), technicians and associate professionals (ISCO 3).

To have consistency with the age classes presented for alternative indicators about qualifications and skills and to exclude younger people who may not have had the prospect/opportunity of getting a job requiring a high-skill level, the data for this indicator are shown for people aged 25 to 64 years. The indicator used in this publication is defined as the share of highly skilled employed people in the total number of employed people (among those aged 25 to 64 years); it excludes people who gave no response when asked about their occupation.

Labour force

The labour force includes all people who were either employed or unemployed during the reference week. This aggregate includes all people offering their work capacity on the labour market: as such it reflects the supply side of the market.

People using digital devices at least half of their working time

The 2022 EU-LFS included a module on job skills, examining the skills use, task autonomy and task repetitiveness. One of the 11 variables collected focused on time spent using digital devices – defined as the use of computers, tablets, phablets or smartphones for work purposes; telephone calls without video were excluded. This variable was designed to capture the active use of digital devices only for work tasks (therefore, excluding personal use). Relevant activities included web browsing, video calls, e-mail, messaging and the use of software or apps. Respondents estimated the use they made of digital devices at work on a 5-point scale, from ‘all or most of the time’ to ‘none of the time’.

This publication presents results for the cohort of core working-age people (aged 20 to 64 years) in EU countries, Norway and Switzerland, focusing on the share of employed people who used digital devices for at least half of their working time.

Regional disparities in labour force indicators

Regional labour market disparities are based on the population-weighted coefficient of variation. Calculations are only made for those countries that have more than 4 level 2 regions. As such, data are not presented for Estonia, Ireland, Croatia, Cyprus, Latvia, Lithuania, Luxembourg, Malta, Slovenia, Slovakia, Iceland, Bosnia and Herzegovina, Montenegro, North Macedonia or Serbia. The coefficient of variation for the whole of the EU includes all regions in the EU, not just those of EU countries that have more than 4 NUTS level 2 regions.

Unemployment and long-term unemployment

Eurostat‘s unemployment statistics are based on guidelines provided by the ILO. Unemployed people are defined as those aged 15 to 74 years who are without work, but who have actively sought employment in the 4 weeks preceding the reference week (or have already found a job to start within the subsequent 3 months) and are available to begin work within the following 2 weeks.

Long-term unemployment refers to the number of people who are out of work and have been actively seeking employment for at least a year.

Unemployment rate

The unemployment rate is defined as the number of unemployed people expressed as a percentage of the total labour force.

In a similar vein, the long-term unemployment rate is defined as the number of unemployed people who have been out of work and actively seeking employment for at least a year expressed as a percentage of the total labour force.

Young people neither in employment nor in education or training (NEET)

The share of young people who are neither in employment nor in education and training, abbreviated as NEET, corresponds to the share of the population (of a given age group and sex) that is not employed and not involved in further (formal or non-formal) education or training during the 4 weeks preceding the survey. The numerator refers to people meeting these 2 conditions, while the denominator is the total population (of the same age group and sex), excluding those respondents who did not answer the question in the survey about participation in regular (formal) education and training. For the purpose of this publication, the share of young people neither in employment nor in education or training relates to those aged 15 to 29 years.

Context

Promoting gender equality in the labour market

The European Commission’s Gender Equality Strategy 2020–25 aims to counter gender stereotypes, close gender gaps in the labour market and promote women’s participation in decision-making.

In March 2023, the European Commission launched a campaign to challenge gender stereotypes, targeting biases that influence, among other aspects, career choices, caregiving roles and representation in leadership positions.

More recently, the European Commission adopted A Roadmap for Women’s Rights (COM(2025) 97 final) in March 2025. This addresses emerging gender equality challenges, including technology-facilitated discrimination through a ‘Declaration of principles for a gender-equal society’ as an annex to the Communication.

Safeguarding jobs and ensuring fair working conditions

Since late 2019, the European Commission has introduced several initiatives to support labour market resilience in line with the European Pillar of Social Rights.

Council Regulation (EU) 2020/672 established the European instrument for temporary support to mitigate unemployment risks in an emergency (SURE) to protect jobs and protect income during the COVID-19 crisis.
The Youth Employment Support initiative enhanced the Youth Guarantee, supporting vocational training, apprenticeships, and entrepreneurship opportunities for young people.
The Just Transition Fund helps communities manage the socioeconomic costs/effects of the shift to a climate-neutral economy.
Directive (EU) 2022/2041 on adequate minimum wages in the European Union promotes fair minimum wages, strengthens collective bargaining and supports upward social convergence across EU countries.

Investing in people: funding and skills development

The European Social Fund Plus (ESF+) is the EU’s main financial instrument for investing in people. With a budget of €99.3 billion allocated for 2021 to 2027, it supports employment, social inclusion, poverty reduction and youth investment. The ESF+ is central to advancing the European Pillar of Social Rights and the post-pandemic recovery.

To align with changing demands in labour markets – especially due to green and digital transitions – the EU has set out a range of strategic skills development priorities, including:

A New Skills Agenda for Europe (COM(2016) 381 final)
the European Skills Agenda for sustainable competitiveness, social fairness and resilience (COM(2020) 274 final)
the European Year of Skills, launched in 2023 and extended into 2024, further promoted upskilling and reskilling initiatives to improve the quality of jobs, workforce adaptability, SME competitiveness and talent attraction in strategic sectors
European Commission – The Union of Skills (COM(2025) 90 final) has 3 principal objectives
ensure that everyone in the EU is empowered to build solid skills foundations and engage in lifelong upskilling and reskilling, through equal opportunities
support enterprises to be competitive and resilient, making it easier for employers and particularly for SMEs to find people with the skills they need to create sustainable growth and quality jobs
work to make skills and qualifications – regardless of where they are acquired – transparent, trusted and mutually recognised, so individuals may exercise their right to free movement and employers may recruit effectively across borders.

Towards a fair and inclusive future labour market

Labour markets across the EU are adapting to technological progress, demographic change and sustainability goals. Policymakers have introduced measures to improve employment access for underrepresented groups at risk of exclusion – such as young people, older workers and people with disabilities – while, at the same time, supporting regional adaptation to structural change and reducing skill mismatches.

The rise of (digital) platform work and other non-standard employment models underscores the importance of ensuring fair working conditions for all. By fostering adaptable and inclusive labour markets, the EU seeks to leave no group or region behind in the transition to a competitive and sustainable economy. Key initiatives include

Labour and skills shortages in the EU: an action plan (COM(2024) 131 final) that was published in March 2024, which sets out a comprehensive response by aiming to:
- increase the participation of underrepresented groups
- advance skills development, training and education
- improve working conditions in critical sectors
- facilitate fair intra-EU mobility
- attract international talent.
As part of the European Semester spring package, the European Commission proposed updated employment guidelines in June 2024 to:
- address skills and labour shortages
- strengthen basic and digital skills
- assess the impact of new technologies, including AI
- focus on (digital) platform work, the social economy and affordable housing.
In March 2025, the European Commission and cross-industry social partners signed a new Pact for European Social Dialogue, reaffirming the role of social partners in shaping labour market, employment and social policies.

This article forms part of Eurostat’s annual flagship publication, the Eurostat regional yearbook.

You can explore the maps interactively using Eurostat’s Statistical Atlas.

Explore further

Database

Regional statistics by NUTS classification (reg), see

Regional labour market statistics (reg_lmk)

Employment and unemployment (Labour force survey) (employ), see

LFS series - detailed annual survey results (lfsa)

Employment – LFS series (lfsa_emp)

Employment rates – LFS series (lfsa_emprt)

Total unemployment – LFS series (lfsa_unemp)

LFS series – Specific topics (lfst)

LFS regional series (lfst_r)

Regional population and economically active population – LFS annual series (lfst_r_lfpop)

Regional employment – LFS annual series (lfst_r_lfemp)

Regional unemployment – LFS annual series (lfst_r_lfu)

Regional labour market disparities – LFS series and LFS adjusted series (lfst_r_lmd)

LFS ad-hoc modules (lfso)

2022. Job skills (lfso_22)

Thematic section

Publications

Paper and PDF publications

Eurostat regional yearbook – 2025 edition

Online publications

Selected datasets

Regional statistics (t_reg), see

Regional labour market statistics (t_reg_lmk)

Unemployment rate by NUTS 2 regions (tgs00010)

Employment and unemployment (Labour force survey) (t_employ), see

LFS main indicators (t_lfsi)

LFS series – detailed annual survey results (t_lfsa)

LFS series – Specific topics (t_lfst)

Methodology

Manuals and further methodological information

Metadata

Regional labour market statistics (ESMS metadata file – reg_lmk_esms)

External links

Visualisation