Statistics Explained

Labour market statistics at regional level



Data extracted in April 2021.

Planned article update: September 2022.

Highlights

The impact of the COVID-19 pandemic was apparent insofar as the share of employed people usually working from home increased in 2020 in many regions. The latest annual increase was at least 15.0 percentage points in the capital regions of Belgium, Finland, Ireland, France and Austria.

In 2020, the highest annual increases in unemployment rates across Greece and Spain were recorded in the popular holiday regions of Kriti, Illes Balears and Ionia Nisia.

Source: Eurostat (lfst_r_lfu3rt)

The COVID-19 pandemic has had a considerable impact on all European Union (EU) labour markets. With the exception of key workers, there has generally been an increase in the number of people usually working from home. Other members of the labour force have been impacted in different ways: some were placed on furlough schemes [1], others were made unemployed and some self-employed lost their income.

Like the lockdown measures themselves, the impact of the measures varied considerably between and within EU Member States. This reflected not only the specific restrictions that were imposed, but also local economic structures and labour market conditions. The asymmetric impact of the pandemic was driven, at least in part, by the level of social contact and the feasibility of making use of technology at work. It is likely that the COVID-19 pandemic has accelerated some labour market transformations while introducing new ones: job losses have come from many activities, including some activities in long-term decline, as well as leisure and hospitality-related activities and/or among workers with precarious employment contracts. The pandemic also accelerated the introduction of digital technologies and a move towards more widespread use of flexible working arrangements.

On 4 March 2021, the European Commission set out its ambition for a stronger social EU to focus on jobs and skills, paving the way for a fair, inclusive and resilient socioeconomic recovery from the COVID-19 pandemic. The European Pillar of Social Rights Action Plan (COM(2021) 102 final) outlines a set of specific actions and headline targets for employment, skills and social protection in the EU. It includes a benchmark for the employment rate, namely that at least 78 % of people aged 20 to 64 years should be in employment by 2030.

This article analyses EU labour markets and is split into two main sections, covering:

  • regional employment, including information on employment rates, self-employment rates and a special focus on the impact of the COVID-19 pandemic, as measured by the change in the actual number of hours worked, absences from work, and changes in the proportion of people usually working from home;
  • regional unemployment rates, including a special focus on one of the groups most impacted by the COVID-19 pandemic, youths — defined here as people aged 15-24 years.

In 2020, the population of the EU aged 15-74 years numbered 332.5 million persons. The labour force — also referred to as the economically active population — was composed of 211.7 million people, while 120.8 million people in this age range were considered to be outside the labour force, in other words economically inactive. This latter cohort is largely composed of school-age children, students, pensioners, people caring for other family members, as well as volunteers and people unable to work because of long-term sickness or disability. Looking in somewhat more detail: the EU labour force aged 15-74 years was composed of 196.7 million employed persons and 15.0 million unemployed persons who were not working (but were actively seeking and available for work).

Full article

Employment

The employment rate is the ratio of employed persons (of a given age) relative to the total population (of the same age). Within this section, data are presented for a slightly narrower coverage of the working-age population, defined here as people aged 20-64 years. The choice of this age range reflects the growing proportion of young people who remain within education systems into their late teens (and beyond), potentially restricting their participation in the labour market, while at the other end of the age spectrum the vast majority of people in the EU have retired by the time they reach the age of 65 years.

Increasing the number of people in work has been one of the EU’s main policy objectives in recent decades. It has been part of the European employment strategy (EES) from its outset in 1997 and was subsequently incorporated as a target in the Lisbon and Europe 2020 strategies. The employment rate is also included as one of the indicators in the social scoreboard which is used to monitor the implementation of the European Pillar of Social Rights.

As part of its work to put in place a strong social EU that focuses on jobs and skills for the future, the European Commission has made a number of proposals to address the challenges linked to new societal, technological and economic developments, as well as the socioeconomic consequences of the COVID-19 pandemic. Alongside initiatives providing support for youth employment and adequate minimum wages, the European Commission has also provided guidance, designed to support a job-rich recovery: Commission Recommendation on an Effective Active Support to Employment following the COVID-19 crisis (EASE) (C(2021) 1372 final). The European Pillar of Social Rights Action Plan proposes three ambitious headline targets for 2030. Among these, the EU has set itself the goal whereby at least 78 % of the population aged 20-64 years should be in employment by 2030.

The EU employment rate was 72.3 % in 2020 — down compared with its peak value in 2019

The employment rate for the working-age population (20-64 years) of the EU was 72.3 % in 2020, down 0.8 percentage points compared with 2019. The outbreak of the COVID-19 pandemic therefore ended a period of six consecutive annual increases for the EU’s employment rate.

Map 1 presents the employment rate for NUTS level 2 regions: the highest rates — equal to or above the headline target for 2030 (of 78 %) — are shown in the two darkest shades of orange. In 2020, 69 out of the 240 regions for which data are available in the EU had reached or surpassed this target. These regions were principally located across much of Czechia, Germany, Estonia, the Netherlands and Sweden. Note that German data, due to a change in survey methodology in 2020, show a low level of reliability in some regions; these data are preliminary and may be revised in the future.

Rural, sparsely-populated or peripheral regions recorded some of the lowest regional employment rates in the EU. This pattern was apparent in southern Spain and southern Italy, much of Greece, the outermost regions of France, and many of the rural areas in eastern Europe (some of which remain characterised by semi-subsistence agriculture). Most of these regions were characterised by a lack of intermediate and highly-skilled employment opportunities. Former industrial heartlands that have not adapted economically make up another group of regions characterised by relatively low employment rates. Many of these have witnessed the negative impact of globalisation on traditional areas 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).

Looking in more detail, some of the highest regional employment rates in 2020 were concentrated in southern Germany, as rates of more than 84.0 % were recorded in Oberfranken, Schwaben, Tübingen and Oberbayern. However, the highest employment rate — 86.5 % — was recorded in the island region of Åland (Finland). By contrast, more than one quarter (65 out of the 240 regions for which data are available) of all EU regions had an employment rate that was below 70.0 % (as shown by the two darkest shades of blue). Among these, there were five regions — Calabria, Campania and Sicilia (in southern Italy) as well as Mayotte and Guyane (outermost regions of France) — where less than half of the working-age population was employed.

There was often a stark contrast in employment rates for capital regions

Within individual EU Member States, there were often relatively large differences in employment rates between regions. For example, in most of the multi-regional eastern and Baltic Member States it was common to find the capital region had the highest employment rate, as was the case in Bulgaria, Croatia, Lithuania, Hungary, Poland, Slovenia and Slovakia. This situation was reversed in a number of western Member States — for example, Belgium and Austria — where the capital region had one of the lowest employment rates.

Map 1: Employment rate, 2020
(%, people aged 20-64 years, by NUTS 2 regions)
Source: Eurostat (lfst_r_lfe2emprtn)

Annual change in the employment rate

The COVID-19 pandemic and its associated measures impacted EU labour markets from the end of the first quarter of 2020 onwards. Annual statistics reveal that regional employment rates (for people aged 20-64 years) fell between 2019 and 2020 in 169 out of the 240 NUTS level 2 regions for which data are available. There were however 61 regions across the EU where employment rates rose, while 10 regions recorded no change.

Figure 1 shows in more detail this mixed pattern of developments. The employment rate declined at a rapid pace in several regions characterised as some of the EU’s principal holiday destinations. For example, between 2019 and 2020 the employment rate in Notio Aigaio and Kriti (both Greece) declined by 7.3 and 5.1 percentage points, while there were reductions of 6.1 points in Illes Balears and 4.3 points in Canarias (both Spain). By contrast, regional employment rates increased across a majority of regions in Poland between 2019 and 2020, with gains of more than 2.0 percentage points in the neighbouring central regions of Łódzkie and Świętokrzyskie. However, the highest increases were recorded in Corse and Languedoc-Roussillon (both southern France), as employment rates rose by 4.5 and 3.1 percentage points respectively; note that the sample size for 2020 data for Corse was very small and that these results should therefore be treated with caution.

Figure 1: Annual change in the employment rate, 2020
(percentage points, people aged 20-64 years, by NUTS 2 regions)
Source: Eurostat (lfst_r_lfe2emprtn)

Self-employment rate

Entrepreneurship and self-employment have historically drawn the attention of policymakers as a means of promoting job creation, be it self-employed persons with employees or own-account workers. One area of discussion around self-employment concerns the motivation of individuals: do they become self-employed out of choice (being one’s own boss and accepting the risks and benefits of entrepreneurship) or out of necessity (to avoid unemployment). In recent years, contracting self-employed people has been used — by some employers — as an instrument to reduce labour costs and/or to avoid some or all aspects of labour law. For example, some Member States have experienced a growth in what is often referred to as the gig economy [2].

The self-employed form a sizeable proportion of the EU’s labour force: there were 25.8 million self-employed persons (aged 20-64 years) in 2020, representing 13.6 % of the total number of persons employed. Self-employment was particularly widespread in southern EU Member States, accounting for more than one quarter (28.0 %) of the total number of persons employed in Greece and for around one fifth (20.3 %) in Italy. At the other end of the range, the lowest self-employment rates in the EU were recorded in Germany, Denmark and Luxembourg.

Figure 2 shows those NUTS level 2 regions with the highest and lowest self-employment rates. The 12 regions with the highest self-employment rates in 2020 were exclusively located in Greece, with peaks recorded in Peloponnisos (42.4 %), Ionia Nisia (38.0 %) and Dytiki Makedonia (37.5 %). By contrast, Bucureşti-Ilfov — the capital region of Romania — had the lowest self-employment rate among EU regions, at 4.2 %. Note that aside from Vest (6.9 %), all of the remaining regions in Romania had self-employment rates that were in double-digits, with a majority of these posting rates above the EU average. The remaining regions at the lower end of the ranking were all located in Germany, with the lowest self-employment rate in Oberfranken (5.3 %).

At the start of the COVID-19 pandemic, most EU Member States introduced some form of furlough scheme in order to provide support to labour markets. However, there were considerable differences in terms of the coverage of schemes and whether or not similar schemes were implemented to protect, partially or completely, the self-employed. Figure 2 also shows how self-employment rates developed between 2019 and 2020. Looking at the regions with the lowest rates, the pandemic and its associated measures appear to have generally led to a reduction in the already low self-employment rates recorded in most German regions. On the other hand, the already high self-employment rates recorded in some Greek regions continued to rise. For example, self-employment rates rose by 4.8-6.0 percentage points between 2019 and 2020 in Notio Aigaio, Kriti and Ionia Nisia; these were the three largest gains among the 237 EU regions for which data are available.

Figure 2: Self-employment rate, 2020
(% of people in employment aged 20-64 years, by NUTS 2 regions)
Source: Eurostat (lfst_r_lfe2estat)

Focus on the impact of the COVID-19 pandemic

At the time of writing, the pandemic is still on-going. However, it is already clear that policy measures have, to some degree, cushioned the impact of the crisis on labour markets, if compared with the more rapid contraction of gross domestic product (GDP). That said, the crisis has impacted particular groups within the labour market, for example, young people, temporary employees, those in precarious employment, or those working in leisure, hospitality and transport-related activities. The final part of this section on employment looks in more detail at the impact of the COVID-19 pandemic, as measured by regional developments for the number of hours worked, absences from work, and the proportion of people usually working from home.

There was a 13.3 % reduction in the total number of hours worked in 2020

Across the EU, the total volume of work — as measured by the actual number of hours worked by each member of the labour force — fell by 13.3 % between 2019 and 2020. The vast majority of EU regions — 227 out of the 239 regions for which data are available (no information available for Mayotte in France) — recorded a fall in the actual number of hours worked between 2019 and 2020, while the overall volume of work increased in 12 regions.

Map 2 shows the annual change in actual number of hours worked for NUTS level 2 regions, with a varied patchwork of results across the individual regions of the EU. The impact of the COVID-19 pandemic and its associated measures on the actual number of hours worked between 2019 and 2020 was greatest across southern regions of the EU, whereas northern and eastern regions were generally less impacted.

Some of the largest reductions in the total volume of work between 2019 and 2020 were recorded in popular holiday destinations. This was particularly notable in Notio Aigaio, Ionia Nisia, Kriti (all in Greece), Illes Balears and Canarias (both in Spain), where the number of hours worked fell by more than 30.0 % — the biggest reductions across any of the regions in the EU. There were seven more regions where the total number of hours worked was reduced by at least 25.0 % — some of these were also popular holiday destinations — Mittelfranken, Koblenz (both Germany; note that there is a break in series), Algarve, Região Autónoma da Madeira (both Portugal), Ipeiros (Greece), Molise (Italy) and Champagne-Ardenne (France).

While the vast majority of EU regions experienced a sizeable contraction in the number of hours worked between 2019 and 2020, there were some regions where the impact of the pandemic and its associated measures was less marked. In total, there were 27 regions across the EU where the actual number of hours worked increased or fell by no more than 3.0 % (as shown by the darkest shade of orange in Map 2). These regions were located in Bulgaria (one region), Denmark (one region), Germany (10 regions; note that there is a break in series), France (two regions), the Netherlands (seven regions), Poland (three regions), Finland (two regions) and Sweden (one region).

Map 2: Annual change in the actual number of hours worked, 2020
(%, people aged 20-64 years, by NUTS 2 regions)
Source: Eurostat ad hoc extraction from labour force survey

The regions with the highest proportion of people being absent from work due to temporary lay-offs in 2020 were predominantly tourist destinations

During the COVID-19 pandemic, a large proportion of the labour force was faced with changing patterns of work. For health workers, this often meant having to work longer hours and/or in more challenging circumstances. For others it meant having to work from home or accepting a temporary lay-off, in other words having to reduce (partly or completely) their working time for technical or economic reasons (sometimes supported by government schemes designed to encourage employers to retain their workforce).

Absences due to temporary lay-off impacted just 0.2 % of employed people in the EU during 2019, a share that rose to 2.8 % in 2020. Figure 3 (left-hand side) shows the NUTS level 2 regions with the highest shares of absences from work due to temporary lay-off. In 2020, there were four regions across the EU — Canarias, Illes Balears (both in Spain), Notio Aigaio and Ionia Nisia (both in Greece) — where upwards of 1 in 10 employed persons were absent due to temporary lay-off; a peak of 14.5 % was recorded in Canarias. A number of other popular holiday destinations — Cyprus, Região Autónoma da Madeira, Algarve (both Portugal) and Cataluña (Spain) — also featured among the regions with the highest shares of absences from work due to temporary lay-off.

There was almost no change between 2019 and 2020 as regards the share of the EU workforce affected by absences due to own illness or disability; this proportion rose marginally from 2.1 % in 2019 to 2.2 % in 2020. Figure 3 (right-hand side) shows the NUTS level 2 regions that had the highest shares of absences from work in 2020 due to illness or disability. In Ciudad Autónoma de Ceuta (Spain), the proportion of the workforce that was absent from work due to illness or disability was, at 8.0 %, almost four times as high as the EU average. There were nine other Spanish and French regions where the share of absences due to illness or disability was at least twice as high as the EU average.

Figure 3: Absences from work, 2020
(% of people in employment aged 20-64 years, by NUTS 2 regions)
Source: Eurostat ad hoc extraction from labour force survey

The share of employed people working from home grew at its fastest pace in capital regions and other urban regions

In 2019, approximately 1 in 20 (5.5 %) people aged 20-64 years in the EU’s workforce usually worked from home. The impact of the COVID-19 pandemic was apparent in the latest developments for this indicator, as this share more than doubled in 2020 — increasing by 6.9 percentage points — to 12.4 %. The regional distribution was somewhat skewed, insofar as there were 94 NUTS level 2 regions where the share of the workforce usually working from home was above the EU average in 2020, compared with 134 regions that recorded lower than average shares; the propensity for employed people to work from home was also much lower than the EU average in Bulgaria (for which only national data are available).

In Helsinki-Uusimaa (the capital region of Finland), 37.0 % of employed people were usually working from home in 2020. This was the highest share across NUTS level 2 regions and was followed, at some distance, by Prov. Brabant Wallon in Belgium (26.5 %). Approximately one quarter of the workforce usually worked from home in several capital regions: Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest in Belgium (25.7 %), Eastern and Midland in Ireland (24.7 %), Wien in Austria (24.2 %), Hovedstaden in Denmark (23.6 %) and Île-de-France in France (23.4 %). There were 10 additional regions in the EU where at least one fifth of the workforce usually worked from home in 2020; these were principally urban regions and included four more capital regions, namely those of Germany, Luxembourg, the Netherlands and Portugal.

Working from home was less prevalent across many of the eastern and southern regions of the EU. In 2020, less than 5.0 % of the workforce was usually working from home in both regions of Croatia, as well as in Cyprus, Latvia and Bulgaria (only national data available). Shares of less than 5.0 % were also recorded in the vast majority of regions across Hungary and Romania (the only exceptions being the capital regions of Budapest and Bucureşti-Ilfov) as well as in a majority of the regions in Greece.

Perhaps the most striking aspect of Map 3 concerns the rapid increase in the proportion of employed people who were working from home in capital regions and several other urban regions. Overall, there were 21 regions in the EU where the annual change in the share of employed people usually working from home was at least 12.0 percentage points in 2020 (as shown by the darkest shade of orange). This share increased by 19.3 percentage points in Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest (the capital region of Belgium), by 18.8 points in Prov. Brabant Wallon (also Belgium) and by 18.7 points in Helsinki-Uusimaa (the capital region of Finland). Aside from the capital regions of Belgium and Finland, this group of 21 regions also included the capital regions of Denmark, Germany, Ireland, Spain, France, Italy, Austria and Portugal, while urban regions — such as Köln, Düsseldorf, Oberbayern, Hamburg, Karlsruhe and Stuttgart (all in Germany) — accounted for most of the remaining regions that recorded a rapid increase in homeworking. This increase in homeworking reflects, at least to some degree, the economic structure of each region, with greater homeworking opportunities for those employed in professional, financial, information and communication, education and government sectors. By contrast; there were likely to be fewer opportunities for homeworking for people employed in manual occupations such as within the agriculture, manufacturing, or distributive trades sectors.

Map 3: Annual change in the share of persons usually working from home, 2020
(percentage points, people in employment aged 20-64 years, by NUTS 2 regions)
Source: Eurostat ad hoc extraction from labour force survey

Unemployment

Unemployment can have a bearing not just on the macroeconomic performance of a country (lowering productive capacity) but also on the well-being of individuals who are without work and their families. The personal and social costs of unemployment are varied and include a higher risk of poverty and social exclusion, debt or homelessness, while the stigma of being unemployed may have a potentially detrimental impact on (mental) health.

In 2020, there were 15.0 million unemployed people (aged 15-74 years) in the EU, while the unemployment rate was 7.1 %. After six consecutive years of falling unemployment, these latest figures marked the first increase since 2013.

Map 4 shows unemployment rates across NUTS level 2 regions: the highest rates in 2020 — as shown by the darkest shade of orange — were recorded in southern and outermost regions of the EU. The lowest rates — as shown by the darkest shade of blue — were concentrated in a cluster of regions that stretched across the southern half of Germany, Czechia and the western regions of Poland and Hungary.

In 2020, regional unemployment rates of at least 16.0 % were recorded in: 11 of the 13 regions from Greece (the only exceptions being Peloponnisos and the capital region of Attiki), five regions from the southern half of Spain as well as the two island regions and two autonomous cities of Spain, four of the outermost regions of France, and three regions from the southern half of Italy. At the other end of the range, the lowest unemployment rates were recorded in: Wielkopolskie in Poland (1.8 %), Střední Čechy (1.9 %) and Jihozápad (2.0 %) in Czechia. The unemployment rate was also 2.0 % in three German regions: Niederbayern, Unterfranken and Trier (all 2019 data).

Map 4: Unemployment rate, 2020
(%, people in the labour force aged 15-74 years, by NUTS 2 regions)
Source: Eurostat (lfst_r_lfu3rt)

The EU’s unemployment rate for people aged 15-74 years increased from 6.7 % to 7.1 % between 2019 and 2020. During this period — which included the onset of the COVID-19 pandemic — a majority of the EU Member States also saw their unemployment rates rise. There were however four exceptions — Poland, France, Italy and Greece — where national unemployment rates fell between 2019 and 2020.

Figure 4 shows that in approximately 7 out of every 10 EU regions for which data are available the unemployment rate increased between 2019 and 2020. Among the 160 NUTS level 2 regions with rising unemployment rates, the labour market situation deteriorated at its most rapid pace in the Greek regions of Kriti (as the unemployment rate increased by 5.6 percentage points), Ionia Nisia (up 3.6 points) and Notio Aigaio (up 3.0 points), as well as Illes Baleares in Spain (up 4.3 points). All of these regions are popular holiday destinations which were impacted by the pandemic and its associated measures which curtailed demand for and supply of tourism-related services.

At the other end of the scale, the biggest reductions in regional unemployment rates between 2019 and 2020 were recorded in Dytiki Makedonia in Greece (down 4.9 points), three outermost regions of France — La Réunion (down 3.9 points), Guyane (down 3.2 points) and Guadeloupe (down 3.1 points) — as well as Ciudad de Melilla in Spain (down 3.3 points).

Figure 4: Annual change in the unemployment rate, 2020
(percentage points, people in the labour force aged 15-74 years, by NUTS 2 regions)
Source: Eurostat (lfst_r_lfu3rt)

Focus on youth unemployment and NEETs

One of the most pressing concerns in the area of social and employment policymaking is youth unemployment. The performance of youth labour markets is closely linked to education and training systems and reflects, at least to some degree, a mismatch between the skills obtained by young people and the skills that are required by employers (to fill job vacancies).

In recent years, several EU Member States have enacted new employment laws with the goal of liberalising labour markets, for example, by providing a wider range of possibilities for hiring staff through temporary, fixed-term or zero hours contracts. In some cases this has resulted in a division between permanent, full-time employees and those with more precarious employment contracts. The latter are often young people and/or people with relatively low levels of educational attainment. This may explain, at least to some degree, why young people in the labour market generally fare worse during economic downturns such as the global financial and economic crisis or the COVID-19 pandemic. During a downturn, employers are also less likely to recruit new workers (young people coming into the labour market) or to replace older workers who retire.

The EU’s youth unemployment rate was 16.9 %

The youth (people aged 15-24 years) unemployment rate in the EU fell from a peak of 24.6 % in 2013 to 15.1 % by 2019, before rising to 16.9 % in 2020 as the impact of the COVID-19 pandemic and its associated measures disproportionately impacted on young people. The youth unemployment rate rose by 1.8 percentage points in 2020, while the overall unemployment rate increased by 0.4 points during the same period.

Note that the youth unemployment rate is based on the same principles as the definition for the unemployment rate among the working-age population and that not every young person is in the labour market. As such, there is potential for the youth unemployment rate to be misinterpreted. For example, when the youth unemployment rate is 25 %, this does not mean that one quarter of all youths are unemployed. Rather, a quarter of those youths who are in the labour force are unemployed (and three quarters are employed), while youths outside the labour market (for example studying) are neither in the numerator nor the denominator.

Map 5 shows that around one fifth of EU regions had single-digit youth unemployment rates. The lowest youth unemployment rates were concentrated in a group of regions that covered an area from the northern half of Belgium, running through much of the Netherlands and Germany (data are for NUTS level 1 regions and often refer to 2019) into most of Austria and Czechia, as well as several Polish regions. There were also relatively low youth unemployment rates in Provincia Autonoma di Bolzano/Bozen (Italy), Közép-Dunántúl (Hungary; 2018 data) and Nord-Est (Romania). Looking in more detail, the lowest youth unemployment rates in 2020 were recorded in Bayern in Germany (4.8 %) and the capital region of Czechia, Praha (5.0 %).

High youth unemployment rates were particularly concentrated in southern Europe. There were 22 regions where more than 40 % of the labour force aged 15-24 years was unemployed in 2020 (as shown by the darkest shade of orange). This group included eight regions from Greece, seven from Spain, four from southern Italy and three outermost regions of France. At the top end of the range, there were five — largely peripheral — regions where the youth unemployment rate stood at more than 50.0 %: Ciudades Autónomas de Ceuta y Melilla (two regions) and Canarias in Spain, Sterea Ellada in Greece, and Mayotte in France.

To give some idea of the disproportionate impact of unemployment on people aged 15-24 years, the youth unemployment rate in 2020 was at least twice as high as the overall unemployment rate (for people aged 15-74 years) in 170 out of 178 NUTS level 2 regions for which data are available (note there are no regional data available for Germany). Among these 178 regions, there were eight regions where the youth unemployment rate was at least four times as high as the overall unemployment rate: three from Poland, two from Romania and a single region from each of Italy, Hungary and Portugal. The highest ratio was recorded in Bucureşti-Ilfov (the capital region of Romania), where the youth unemployment rate was 4.8 times as high as the overall unemployment rate.

Compared with 2019, youth unemployment rates increased in approximately three quarters of the 170 NUTS level 2 regions for which data are available for 2020 (again there are no regional data available for Germany). The youth unemployment rate increased by at least 10.0 percentage points in Sterea Ellada in Greece, Illes Balears, Cantabria and Ciudad de Ceuta in Spain, Poitou-Charentes in France, and Centro in Portugal. By contrast, the youth unemployment rate fell by around 10.0 percentage points between 2019 and 2020 in Attiki (the Greek capital region), as well as in Guadeloupe and Martinique (both France).

Map 5: Youth unemployment rate, 2020
(%, people in the labour force aged 15-24 years, by NUTS 2 regions)
Source: Eurostat (lfst_r_lfu3rt)

In 2020, the EU’s NEET rate was 11.1 %

The NEET rate — defined here as the share of young people (aged 15-24 years) who are not employed and not involved in further education or training — provides a useful measure for studying the vulnerability of young people in terms of their labour market and social exclusion.

The NEET rate is closely linked to economic performance and the business cycle. Having peaked at 13.1 % in 2012, the EU’s NEET rate fell slowly during seven consecutive years, to stand at 10.1 % in 2019. Following the onset of the COVID-19 pandemic, the NEET rate climbed to 11.1 % in 2020.

Figure 5 provides an analysis of the situation across NUTS level 2 regions in 2020. Some of the highest NEET rates in the EU were recorded in southern regions of Italy and the outermost regions of France, while there were also relatively high rates in several regions of Romania, Bulgaria and Greece. Looking in more detail, there were seven regions across the EU where more than one in four young people were neither in employment, nor in education or training in 2020. Four of these were located in Italy — Molise (25.5 %), Calabria (26.5 %), Campania (28.0 %) and Sicilia (29.3 %); they were joined by Severozapaden in Bulgaria (27.0 %), Voreio Aigaio in Greece (27.1 %) and Guyane in France (33.6 %), which had the highest rate.

Among the EU Member States characterised by relatively low NEET rates in 2020 it was common to find a narrow range of rates between regions; this pattern was apparent in the Nordic Member States, Austria and the Netherlands. For example, regional NEET rates in the Netherlands were within the narrow range of 3.7-5.6 %. Of the 10 NUTS level 2 regions across the EU with a NEET rate of less than 5.0 %, seven were located in the Netherlands. In 2020, the lowest regional NEET rates were recorded in Noord-Brabant (3.9 %) and Utrecht (3.7 %) in the Netherlands and Praha (the capital region of Czechia; 3.4 %).

Figure 5: Young people neither in employment nor in education or training (NEETs), 2020
(%, people aged 15-24 years, by NUTS 2 regions)
Source: Eurostat (edat_lfse_38)

Source data for figures and maps

Excel.jpg Labour market at regional level

Data sources

The information presented in this article relates to annual averages derived from the labour force survey (LFS). Eurostat compiles and publishes labour market statistics for the EU, the individual EU Member States, as well as the EU regions. In addition, data are also available for several EFTA (Iceland, Norway and Switzerland) and candidate (Montenegro, North Macedonia, Serbia and Turkey) countries and their regions. The LFS population generally consists of persons aged 15 years and over living in private households, with definitions aligned with those provided by the International Labour Organization (ILO).

The collection of LFS data up to and including reference year 2020 was conducted by national statistical authorities in accordance with Council Regulation (EEC) No 577/98 of 9 March 1998; there is a new legal basis for LFS data from 2021 onwards.

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 second job, time-related underemployment, the search for employment, education and training, previous work experience of persons not in employment, their situation one year before the survey, their main labour status and their income. These statistics are aggregated by region and are generally published down to NUTS level 2. That said, some regional labour market statistics are compiled/transmitted for NUTS level 3 regions, although this is on a voluntary basis.

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

It is important to note that changes in the survey methodology have led to a break in German data for 2020. Estimates for 2020 can therefore not be compared directly with those of previous years. In addition, data collection during 2020 was impacted by technical issues and COVID-19 measures. The German data published therefore show a low degree of reliability for some regions. They should be considered as preliminary data and may be revised in the future. For more information, see here .

Note also that the actual net sample for Corse is too small to have reliable regional results and that Mayotte is covered by a specific annual survey. As a result, data for these two French regions for 2020 should also be treated with caution.

Indicator definitions

Employment rate

The employment rate is the percentage of employed persons in relation to the comparable total population. For the overall employment rate, the comparison is made with the population of working-age (defined in this publication as people aged 20-64 years). However, employment rates can also be calculated for a particular age group and/or gender in a specific geographical area — for example, males aged 15-24 years.

Self-employment rate

In the LFS, persons in employment (employed persons) are classified to one of three categories: (paid) employees, self-employed and unpaid family workers. Self-employed persons include employers and own-account (independent) workers. The self-employment rate measures the share of self-employed persons in relation to the comparable population of employed persons. For the purpose of this publication, the self-employment rate is defined in relation to employed persons aged 20-64 years.

Average number of actual weekly hours in main job

The number of hours actually worked is defined as the sum of all periods spent on direct and ancillary activities. This includes all hours worked including overtime, regardless of whether they were paid, and short breaks (such as for a drink). It excludes travel time between home and the workplace, as well as main meal breaks (normally taken at midday). The number of hours actually worked may be contrasted with the number of hours usually worked (which is collected with respect to a period of between four weeks and three months prior to the survey).

Absences from work

The notion of a temporary absence from work refers to situations in which a period of work is interrupted by a period of absence. This implies that the temporary absence relates to employed persons who had already worked at their current activity and were expected to return to work after a period of absence.

People who are absent from work due to ‘temporary lay-off’ are those whose written or unwritten contract of employment, or activity, has been suspended but have an assurance of return to work within a period of three months or receive at least 50 % of their wage or salary from their employer. These absences are also referred to as ’slack work for technical or economic reasons’. People both without an assurance of return to work within a period of three months and not receiving at least 50 % of their wage or salary from their employer, are not considered as employed people temporarily absent from work. Alternatively, absences from work may be classified as resulting from ‘own illness or disability’ (illness, injury or temporary disability), due to holidays, or in a residual category of ‘other’ (absences due to bad weather, labour disputes, education or training, maternity leave, parental leave, compensation leave and other personal or family reasons).

Persons usually working from home

Working from home means doing any productive work related to a person’s current job(s) at home; this concept also covers self-employed people, who work wholly or partly at home (for example, in a part of their living accommodation set aside for the purpose). In this context, persons ‘usually’ working from home, should be interpreted to mean those who worked at home at least half of the total number of days worked in a reference period of four weeks preceding the end of the reference week for the LFS.

Unemployment rate

Eurostat‘s unemployment statistics are based on ILO guidelines. An unemployed person is defined as someone aged 15 to 74 years (16 to 74 years in Italy, Spain and Iceland) who is without work, but who has actively sought employment in the previous four weeks and is available to begin work within the next two weeks (or has already found a job to start within the subsequent three months). The unemployment rate is defined as the number of unemployed persons expressed as a percentage of the total labour force (the economically active population).

Youth unemployment rate

The youth unemployment rate is defined as the number of unemployed people aged 15-24 years expressed in relation to the total labour force of the same age. It is important to note that a relatively high proportion of people aged 15-24 years are outside the labour force as they study full-time.

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

The share of people who are neither in employment nor in education and training, abbreviated as NEETs, 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 four weeks preceding the survey). The numerator of the indicator refers to persons meeting these two 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 15-24 years.

Context

There are six European Commission priorities for 2019-2024, including the creation of ‘An economy that works for people’, whereby the EU seeks to create a more attractive investment environment, and growth that creates quality jobs, especially for young people and small businesses. Some of the principal challenges outlined by President von der Leyen include: fully implementing the European Pillar of Social Rights; ensuring that workers have at least a fair minimum wage; promoting a better work-life balance; tackling gender pay gaps and other forms of workplace discrimination; getting more disabled people into work; and protecting people who are unemployed.

Since the end of 2019, the European Commission has contributed to the implementation of the social pillar principles with, among other initiatives, the following.

At the beginning of March 2021, the European Commission outlined the European Pillar of Social Rights Action Plan. It provides specific actions to implement the principles of the European Pillar of Social Rights through the active involvement of social partners and civil society. Furthermore, it proposes a number of employment, skills and social protection targets to be achieved by 2030. One of the headline targets relates specifically to labour markets, namely that at least 78 % of people aged 20 to 64 years should be in employment by 2030.

Also early in March 2021, the European Commission presented a Recommendation (EU) 2021/402 of 4 March 2021 on an effective active support to employment following the COVID-19 pandemic (EASE) (C(2021) 1372 final). This seeks to provide guidance on policy measures that are backed by EU funding to encourage job creation and job transitions in the aftermath of the COVID-19 pandemic from declining towards expanding sectors, notably within the green and digital economy. Measures outlined in the recommendation are eligible for support from the Recovery and Resilience Facility (RRF), as well as a number of other EU funds including the European Social Fund Plus (ESF+), the European Regional Development Fund (ERDF), the JUST transition fund, and the European Globalisation Adjustment Fund (EGF).

The European Social Fund Plus (ESF+) is the EU’s main instrument dedicated to investing in people. It aims to build a more social and inclusive EU, supporting EU Member States in tackling the crisis caused by the COVID-19 pandemic. It also aims to encourage high employment levels, fair social protection and a skilled and resilient workforce ready for the transition to a green and digital economy. In January 2021, the European Parliament and the Council reached a political agreement on a proposed regulation for this key financial instrument for implementing the European Pillar of Social Rights, providing support for post-pandemic recovery. The ESF+ has a total budget of EUR 88.0 billion (in 2018 prices) and will support people by creating and protecting job opportunities, promoting social inclusion, fighting poverty and developing the skills needed for the digital and green transition, with ambitious goals for investing in young people and addressing child poverty.

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Regional labour market statistics (t_reg_lmk)
Employment rate of the age group 20-64 by NUTS 2 regions (tgs00102)
Unemployment rate by NUTS 2 regions (tgs00010)
LFS series - Specific topics (t_lfst)


Regional labour market statistics (reg_lmk)
LFS series - detailed annual survey results (lfsa)
Employment - LFS series (lfsa_emp)
Employment rates - LFS series (lfsa_emprt)
Self-employed - LFS series (lfsa_empself)
Working time - LFS series (lfsa_wrktime)
Total unemployment - LFS series (lfsa_unemp)
LFS series - Specific topics (lfst)
LFS regional series (lfst_r)
Regional employment - LFS annual series (lfst_r_lfemp)
Regional unemployment - LFS annual series (lfst_r_lfu)


Manuals and further methodological information

Metadata

Notes

  1. Also known by other names, such as temporary lay-off or technical unemployment. In a furlough scheme, for a fixed or open-ended period of time employees are not required to work, but are not made unemployed. Depending on the details of specific schemes: the workers may receive full, reduced or no pay; the employers may receive full, partial or no financial support from public authorities. Furlough schemes allow employers to retain employees during economically difficult times, with the intention of the employees returning to work for the same employer at the end of the scheme.
  2. In the gig economy, people — referred to by various names such as freelancers/self-employed/contractors — have a service contract/agreement to work on a specific task or project for a client, rather than a more traditional employment contract to do the same or similar work. Such working practices have always been common in some activities, such as within creative, arts and entertainment activities, but have grown in importance in other activities, such as information technology services, passenger transport services, and some professional and support services.

Maps can be explored interactively using Eurostat’s statistical atlas (see user manual).

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