Unemployment statistics and beyond
Data extracted in September 2024.
Planned article update: May 2025.
Highlights
This article focuses on annual statistics on unemployment in the European Union (EU) and the European Union (EU) individual countries, as well as three EFTA countries (Iceland, Norway, and Switzerland) and three candidate countries (Bosnia and Herzegovina, Serbia and Türkiye).
A separate article on unemployment statistics presents the unemployment figures on a monthly basis. An article on labour market slack - employment supply and demand mismatch is also available, focusing on the three measures of labour market attachment that supplement the unemployment rate.
Unemployment levels and rates move in a cyclical manner, largely related to the general business cycle. However, other factors such as labour market policies and demographic changes may also influence the short and long-term development of unemployment.
Full article
Trends in the unemployment rate
In 2023, the unemployment rate in the EU for people aged 15-74 years reached a historic low of 6.1 %, marking the lowest rate since 2014 (see Figure 1). For calculating the unemployment rate, the denominator used is the labour force, which encompasses the total number of employed and unemployed people of the same age group. Over 6 consecutive years from 2014 to 2019, the unemployment rate steadily declined. This was followed by a slight increase of 0.4 percentage points (pp) in 2020 (due to the COVID-19 pandemic). Then, the EU unemployment rate decreased by 0.1 pp in 2021 and a further 0.9 pp in 2022, it decreased again by 0.1 pp in 2023.
In 2023, in the EU there were 6.7 million unemployed men and slightly fewer unemployed women, amounting to 6.5 million. Despite the lower number of unemployed women, they represented 6.4% of the female labour force, whereas unemployed men accounted for a lower percentage - at 5.8% - of the male labour force. Figure 1 above illustrates that women consistently experienced higher unemployment rates than men since 2014.
In 2023, women, in 16 out of the 27 EU countries, had higher unemployment rates than men (see Figure 2). Among these countries, Greece recorded the most significant gender difference, with a 14.3% unemployment rate for women compared with 8.5% for men (a gap of 5.8 pp). In the remaining 11 EU countries, the unemployment rate for men surpassed that of women with Latvia showing the most pronounced difference, with a male unemployment rate of 7.6% compared with 5.4% for women (a 2.2 pp gap). 5 EU countries recorded almost equal unemployment rates for men and women with 0.1 pp difference in Cyprus, Slovakia, Hungary, Slovenia and Poland.
Unemployment rate by level of education
The unemployment rate varies significantly depending on the different levels of educational attainment for people aged 25 to 74 years (see Figure 3). Generally, as educational attainment increases, the unemployment rate decreases. This is the case in the majority of countries, except for Denmark, Malta and the Netherlands, where people with a high level of education experience higher unemployment rates compared with those with a medium level.
The highest unemployment rates in the EU were recorded for those with a low level of education, reaching 34.3% in Slovakia, 18.5% in Sweden, and 17.3% in Lithuania. Conversely, the lowest rates, were found among the labour force with a high level of education in Czechia, Poland and Romania (all with 1.2%).
Unemployment rate by degree of urbanisation
Figure 4 illustrates the unemployment rate for people aged 15-74 years across different degrees of urbanisation in 2023, revealing distinct patterns among countries. The highest rates were recorded for people living in rural areas in Lithuania, Romania, Slovakia, Bulgaria, Hungary, and Poland. Conversely, other countries experienced their highest national unemployment rates in either cities or towns and suburbs. For instance, Belgium and Austria recorded substantially higher unemployment rates for people in cities compared with those residing in other areas, and in Spain, Greece, Estonia, Croatia, Cyprus and Luxembourg, the unemployment rate for those living in towns and suburbs surpassed that of residents in both, cities and rural areas.
Unemployment by age
Figure 5 shows a consistent trend in the EU, demonstrating that the unemployment rate for young people aged 15-29 years exceeded the overall unemployment rate (for people aged 15-74 years) since 2014. Conversely, the unemployment rate for people aged 55-74 years consistently remained lower than the overall unemployment rate throughout the same period.
The high unemployment rate of young people reflects the challenges they face in securing employment. However, it is important to note that this does not necessarily imply a substantial number of unemployed people aged 15 to 29 years. Many young people, unlike their older counterparts, are engaged in full-time studies and are not actively seeking employment and consequently not included in the labour force, used as a denominator to calculate the unemployment rate. To address this, an alternative indicator is calculated for analytical purposes: unemployment ratio for young people. This ratio represents the proportion of unemployed young individuals within the total young people aged 15 to 29.
Figure 6 indicates that the unemployment ratio for the young people in the EU stood at 6.3% for the year 2023. If only young people participating in the labour force are included in the denominator, the youth unemployment rate is 11.2%. For comparison, unemployed people aged 30-74 years represented 3.4% of the total population and 5.0% of the labour force of the same age group.
Across the EU countries, the unemployment ratio of young people varied from 2.4% in Czechia to 10.9% in Sweden, while the youth unemployment rate ranged from 5.0% in Germany to 21.8% in Greece.
In some countries the values of the rate and ratio are closer to each other than in others, meaning that in some instances young people in the labour force overlap more closely with the total population of the same age. For example Germany, Malta, and the Netherlands, where the difference between the youth unemployment rate and the youth unemployment ratio is less than 2 pp. By contrast, this difference exceeds 10 pp in Greece and Spain.
Long-term unemployment
The long-term unemployment rate, which represents the percentage of people unemployed for 12 months or more within the labour force, is displayed in Map 1. The age group in focus is 15-74 years old. Greece stood out with the highest long-term unemployment rate in the EU, reaching 6.2%. Spain followed with the second highest rate of 4.3%.
On the other end of the scale, Denmark, the Netherlands, Czechia, Malta and Poland reported the lowest long-term unemployment rates in the EU, with rates below 1%.
At EU level, the long-term unemployment rate was 2.1%.
Figure 7 shows the breakdown of unemployed people by unemployment duration. At EU level, about one-fifth (20.8%) have been unemployed for a period of 24 months or more (i.e. classified as very long-term unemployment). However, this average hides substantial differences between countries. Almost half (46.5%) of the unemployed people in Slovakia had been looking for a job for 24 months or more. Greece and Italy followed with relatively high percentages, respectively 37.9% and 36.7%. By contrast, less than 10% of the unemployed in Denmark, Malta, Netherlands, Poland and Estonia have been in this situation for such a period.
Previous occupation
Figure 8 provides insights into the occupation of unemployed people in their last job. Note that the data on the previous occupation is available only for those previously in employment and who left their last job within the past 8 years. The statistics reveal the percentage of each occupational group (ISCO-08) within this population at EU level. It shows that a quarter (25.0%) had been previously employed as service and sales workers, while another 22.9% had worked in elementary occupations such as cleaners, helpers, or food preparation assistants. By contrast, only 1.7% had previously been skilled agricultural, forestry and fishery workers, and 2.5% had been managers.
Significant differences between men and women are apparent. Those whose former occupation was service and sales workers constituted 16.3% of unemployed men, whereas this group made up 34.2% of unemployed women. The difference is also large but takes the opposite direction for those who had previously worked in craft and related trades: 18.8% of unemployed men held a profession in this occupational group, whereas the corresponding percentage of women was only 3.0%.
Methods to find a job
The article concludes with information on the most effective methods to find a job.
Information for the most effective method to find a job is available only for those who started their current main job within the past 8 years. In total, 29.2% of employees in the EU aged 25-74 years considered that relying on friends, relatives or other acquaintances had been the most effective method to find their current job (see Figure 9). This percentage varies a lot according to the level of education: 42.8% for those with a low level, against 19.9% for those with а high level of educational attainment.
Among the various methods, job advertisements ranked with the second highest percentage, as 24.7% considered them as the most effective to find their current main job. As opposed to the personal connections, the percentage of job advertisements was much higher among those with a high level of education (30.6%), than among those with a low level (13.7%).
The following methods were the least effective, with less than 5% considering them as the most effective to find their current main job: applying for a public competition, relying on private employment agency or public employment service and educational or training institution (including internship or previous work experience).
Source data for tables and graphs
Methods and definitions
Data sources
All figures in this article are based on the European Union Labour Force Survey (EU-LFS).
Source: The EU-LFS is the largest European household sample survey providing quarterly and annual results on labour participation of people aged 15 years and over as well as on persons outside the labour force. It covers residents in private households. Conscripts in military or community service are not included in the results. The EU-LFS is based on the same target populations and uses the same definitions in all countries, which means that the results are comparable between the countries. The EU-LFS is an important source of information about the situation and trends in the national and EU labour markets. Each quarter around 1.8 million interviews are conducted throughout the participating countries to obtain statistical information for some 100 variables. Due to the diversity of information and the large sample size, the EU-LFS is also an important source for other European statistics like Education statistics or Regional statistics.
Please note that Eurostat provides two sets of indicators linked to the annual unemployment rate, which serve different purposes and which in some cases differ from each other:
1) The LFS main indicators, which contain seasonally adjusted series. They include the labour market headline indicators used e.g. in the Macroeconomic Imbalance Procedure Scoreboard or the European Statistical Monitor and are consequently used for monitoring policy. They only have a few breakdowns and normally refer to the age group 20-64 years.
2) The detailed results, which contain series that are not seasonally adjusted. They have a large number of breakdowns and can therefore be used for more detailed analysis. For France, only one data series is published. This series contains data for metropolitan France until the fourth quarter of 2013, and from 2014 on, also the French overseas departments.
Reference period: Yearly results are obtained as averages of the four quarters in the year.
Coverage: The results from the EU-LFS currently cover all European Union countries, the EFTA countries Iceland, Norway and Switzerland, as well as the candidate countries Montenegro, North Macedonia, Serbia and Türkiye. For Cyprus, the survey covers only the areas of Cyprus controlled by the Government of the Republic of Cyprus.
European aggregates: EU and EU-27 refer to the sum of the 27 EU countries. If data are unavailable for a country, the calculation of the corresponding aggregates takes into account the data for the same country for the most recent period available. Such cases are indicated.
Country notes
In the Netherlands, the EU-LFS data remains collected using a rolling reference week instead of a fixed reference week, i.e. interviewed persons are asked about the situation of the week before the interview rather than a pre-selected week.
Definitions
The concepts and definitions used in the EU-LFS follow the resolutions of the International Conference of Labour Statisticians (ICLS) which is held every 5 years in Geneva, organized by the International Labour Organisation (ILO).
Unemployment
Eurostat publishes unemployment statistics based on a definition of unemployment for which there are three criteria, namely:
- being without work;
- actively seeking work;
- and being available for work.
Unemployed people comprise persons who were: (a) not employed according to the definition of employment above; (b) actively seeking work, i.e. had taken specific steps in the four week period ending with the reference week to seek paid employment or self-employment or who found a job to start later, i.e. within a period of at most three months from the end of the reference week; (c) currently available for work, i.e. were available for paid employment or self-employment before the end of the two weeks following the reference week.
Monthly unemployment figures are published by Eurostat as rates (as a percentage of the labour force) or levels (in thousands), by sex and for two age groups (persons aged 15 to 24 years, and those aged 25 to 74 years). The figures are available as unadjusted, seasonally adjusted and as a trend series. The time series for data for the EU and the euro area (EA-19) aggregates start in 2000; the starting point for individual EU countries varies.
Quarterly and annual unemployment figures from the EU-LFS are published with more detailed breakdowns (for example, a wider range of age groups, by nationality, or by educational attainment); there are also figures available on long-term unemployment (unemployed for more than 12 months) and very long-term unemployment (unemployed for more than 24 months).
Unemployment rates are also presented according to the educational attainment level of the population, i.e. the highest level of education successfully completed. The different levels of educational attainment are defined by the International Standard Classification of Education (ISCED 2011). Low level of educational attainment refers to ISCED levels 0-2 (lower than primary, primary and lower secondary education), medium level refers to ISCD levels 3 and 4 (upper secondary and post-secondary non-tertiary education) and high level refers to ISCED levels 5-8 (tertiary education).
Underemployment and potential additional labour force
Many persons only partially fulfil the three unemployment criteria above and are therefore not considered as unemployed. In order to provide information on people who are not unemployed, Eurostat also publishes indicators on labour market slack meaning on people who have an unmet supply of employment, so all those who are either unemployed or underemployed (i.e. those working part-time but who wish and are available to work more), or associated to the labour force because of their availability to work or their work search but who are not recorded as part of it (they meet some but not all of the criteria for unemployment).
Time series
Regulation (EU) 2019/1700 came into force on 1 January 2021 and induced a break in the EU-LFS time series for several EU countries. In order to monitor the evolution of employment and unemployment despite the break in the time series, EU countries assessed the impact of the break in their country and computed impact factors or break corrected data for a set of indicators. Break corrected data are published on the Eurostat website for the LFS main indicators.
Additional methodological information
More information on the EU-LFS can be found via the online publication EU Labour Force Survey, which includes eight articles on the technical and methodological aspects of the survey. The EU-LFS methodology in force from the 2021 data collection onwards is described in methodology from 2021 onwards. Detailed information on coding lists, explanatory notes and classifications used over time can be found under documentation.
Context
The unemployment rate is an important indicator with both social and economic dimensions. Rising unemployment results in a loss of income for individuals, increased pressure with respect to government spending on social benefits and a reduction in tax revenue. From an economic perspective, unemployment may be viewed as unused labour capacity.
Time series for unemployment are used by the European Commission, other public institutions, and the media as an economic indicator, while banks may use the data for business cycle analysis. Finally, there is interest among the general public for information concerning unemployment.
The unemployment rate is considered to be a lagging indicator. When there is an economic downturn, it usually takes several months before the unemployment rate begins to rise. Once the economy starts to pick up again, employers usually remain cautious about hiring new workers and it may take several months before unemployment rates start to fall.
Male, youth and long-term unemployment appear to be more susceptible to cyclical economic changes than overall unemployment.
Globalisation and technological developments appear to have an ever-increasing effect on daily life, and the demand for different types of labour and skills changes, sometimes at a rapid pace. While enterprises try to improve their productivity and become more competitive and innovative, they may well seek to pass on risk to the labour force through greater flexibility — both in relation to those already in employment, as well as those searching for a new job. Within the context of the European employment strategy (EES), there are a number of measures that are designed to help encourage people to remain in work or find a new job, including: the promotion of a life-cycle approach to work, encouraging lifelong learning, improving support to those seeking a job, as well as ensuring equal opportunities.
Direct access to
- Labour force survey in the EU, EFTA and candidate countries — Main characteristics of national surveys, 2020, 2022 edition
- Quality report of the European Union Labour Force Survey 2020, 2022 edition
- EU labour force survey — online publication
- European Union Labour force survey - selection of articles (Statistics Explained)
- LFS main indicators (t_lfsi)
- Unemployment - LFS adjusted series (t_une)
- LFS series - detailed annual survey results (t_lfsa)
- Unemployment rates of the population aged 25-64 years by educational attainment level (tps00066)
- LFS main indicators (lfsi)
- Unemployment - LFS adjusted series (une)
- LFS series - detailed quarterly survey results (from 1998 onwards) (lfsq)
- Total unemployment - LFS series (lfsq_unemp)
- LFS series - Detailed annual survey results (lfsa)
- Total unemployment - LFS series (lfsa_unemp)
Publications
- EU labour force survey — online publication
- Labour force survey in the EU, EFTA and candidate countries — Main characteristics of national surveys, 2020, 2022 edition
- Quality report of the European Union Labour Force Survey 2020, 2022 edition
- Statistical working papers / Manuals and guidelines
ESMS metadata files and EU-LFS methodology
- Employment and unemployment (Labour Force Survey) (ESMS metadata file — employ_esms)
- LFS main indicators (ESMS metadata file — lfsi_esms)
- LFS series - detailed annual survey results (ESMS metadata file — lfsa_esms)
- LFS series - detailed quarterly survey results (from 1998 onwards) (ESMS metadata file — lfsq_esms)
- LFS ad-hoc modules (ESMS metadata file — lfso_esms)
- Unemployment by sex and age – monthly data (ESMS metadata file — une_rt_m_esms)
- LFS regional series (ESMS metadata file — reg_lmk_esms)