The statistic reflects the seasonally adjusted unemployment rate in member states of the European Union in November 2024. The seasonally adjusted unemployment rate in Spain in November 2024 was 11.2 percent.The unemployment rate represents the share of the unemployed in all potential employees available to the job market. Unemployment rates in the EU The unemployment rate is an important measure of a country or region’s economic health, and despite unemployment levels in the European Union falling slightly from a peak in early 2013 , they remain high, especially in comparison to what the rates were before the worldwide recession started in 2008. This confirms the continuing stagnation in European markets, which hits young job seekers particularly hard as they struggle to compete against older, more experienced workers for a job, suffering under jobless rates twice as high as general unemployment. Some companies, such as Microsoft and Fujitsu, have created thousands of jobs in some of the countries which have particularly dire unemployment rates, creating a beacon of hope. However, some industries such as information technology, face the conundrum of a deficit of qualified workers in the local unemployed work force, and have to hire workers from abroad instead of helping decrease the local unemployment rates. This skills mismatch has no quick solution, as workers require time for retraining to fill the openings in the growing science-, technology-, or engineering-based jobs, and too few students choose degrees that would help them obtain these positions. Worldwide unemployment also remains high, with the rates being worst in the Middle East and North Africa. Estimates by the International Labour Organization predict that the problem will stabilize in coming years, but not improve until at least 2017.

The share of long-term unemployment is the share of unemployed persons since 12 months or more in the total active population, expressed as a percentage. The total active population (labour force) is the total number of the employed and unemployed population. The duration of unemployment is defined as the duration of a search for a job or as the period of time since the last job was held (if this period is shorter than the duration of the search for a job).

Among European Union countries in March 2025, Spain had the highest unemployment rate at 10.9 percent, followed by Finland at 9.4 percent. By contrast, Czechia has the lowest unemployment rate in Europe, at 2.6 percent. The overall rate of unemployment in the European Union was 5.8 percent in the same month - a historical low-point for unemployment in the EU, which had been at over 10 percent for much of the 2010s.

Unemployed persons (age 15 to 74 years - without work, available for work and actively seeking work) as a percentage of the labour force (sum of employed and unemployed persons), by NUTS 2 region. Data based on the EU Labour Force Survey.

The statistic shows the seasonally adjusted youth unemployment rate in EU member states as of November 2024. The source defines youth unemployment as unemployment of those younger than 25 years. In November 2024, the seasonally adjusted youth unemployment rate in Spain was at 26.6 percent. Youth unemployment rate in EU member states Unemployment is a crucial economic factor for a country; youth unemployment is often examined separately because it tends to be higher than unemployment in older age groups. It comprises the unemployment figures of a country’s labor force aged 15 to 24 years old (i.e. the earliest point at which mandatory school education ends). Typically, teenagers and those in their twenties who are fresh out of education do not find jobs right away, especially if the country’s economy is experiencing difficulties, as can be seen above. Additionally, it also tends to be higher in emerging markets than in industrialized nations. Worldwide, youth unemployment figures have not changed significantly over the last decade, nor are they expected to improve in the next few years. Youth unemployment is most prevalent in the Middle East and North Africa, even though these regions report high unemployment figures regardless (Zimbabwe and Turkmenistan are among the countries with the highest unemployment rates in the world, for example), and are also highly populated areas with a rather weak infrastructure, compared to industrialized regions. In the European Union and the euro area, unemployment in general has been on the rise since 2008, which is due to the economic crisis which caused bankruptcy and financial trouble for many employers, and thus led to considerable job loss, less job offerings, and consequently, to a rise of the unemployment rate. Older workers are struggling to find new jobs despite their experience, and young graduates are struggling to find new jobs, because they have none. All in all, the number of unemployed persons worldwide is projected to rise, this is not down to the economic crisis alone, but also the industrial automation of processes previously performed by workers, as well as rising population figures.

The dataset "tgs00053" has been discontinued since 20/07/2023.

As of June 2024, Spain had the highest youth unemployment rate in Europe, at 25.8 percent, with Sweden having the second-highest youth unemployment rate as of this month, at 23.8 percent. Across the 27 member states of the European Union, the overall youth unemployment rate was 14.6 percent, with Germany having the lowest youth unemployment rate of 6.8 percent.

Evolution of the number of unemployed jobseekers in the Brussels-Capital Region Annual averages since 2010, by municipality Brussels, by gender, by level of education. All basic statistics on the Unemployment is based on the number of unemployed jobseekers (IEDs). He they are persons without paid work registered as applicants employment with a public employment service. The definition is in line with provisions of Eurostat (the statistical office of the EU). In this regard, the job seeker’s file registered with Actiris serves as a base in the Brussels-Capital Region. Unemployment administrative is represented by the situation of all files at the end months, so each time it is a snapshot (and not data dynamics on unemployment inflows and outflows). IEDs are divided into three categories which are: displayed by default in the basic statistics, below the key figures. » More info: https://viewstat.actiris.brussels/viewstat_help_EN_DE_DEI.html

Youth unemployment rate by sex, age and NUTS 2 region

In order to enable international comparisons, particularly within the European Union, Eurostat has set up the Labour Force Survey (LFS). By combining a set of issues, it makes it possible to measure aggregates such as labour force, employment and unemployment in the same way in all countries and in accordance with the recommendations of the International Labour Office (ILO). This survey has been ongoing in Belgium since 1999 (before, only in spring). However, it provides reliable data only at regional level (Wallonia, Flanders, Brussels). Therefore, in order to be able to compare Belgian districts and municipalities with other areas at international level, the IWEPS calculates data calibrated on the Labour Force Survey. The totals, by sex, age and region, correspond exactly to those published by Statbel, the Belgian statistical office. These data may differ slightly from the data published by Eurostat, which reviews the whole series each year [...].

The indicator reports the number of people who are unemployed, looking for a job and available for employment in the labour force aged 15 to 64, on an annual average. It measures the imbalance between labour supply and demand.

See also: — on our website “\2” — on Statbel’s website, the Labour Force Survey ‘\2’.

Spatial reference: ETRS 1989 LAEA.

Source of the data: Eurostat. (2024). Unemployment rate by NUTS 2 regions. https://doi.org/10.2908/TGS00010. Accessed January 25, 2024.

UNR_VALUE = Unemployment rate (%).
UNR_CLASS = Unemployment rate. Seven classes: very low, low, medium to low, medium to high, high, very high, no data.

Youth unemployment rate by sex, age and NUTS 2 region Copyright notice and free re-use of data on: https://ec.europa.eu/eurostat/about-us/policies/copyright

Dataset replaced by: http://data.europa.eu/euodp/data/dataset/KnxgBMon9DXqkvGXIxcvGg

The unemployment rate in the European Union and the Euro area from 2013 to 2024 has a decreasing trend. In 2024, the average unemployment rate in the EU was 5.9 percent.

Abstract copyright UK Data Service and data collection copyright owner.The Quarterly Labour Force Survey Eurostat Datasets form the UK component of the European Union Labour Force Survey (EU LFS), and consist of a subset of core variables from the UK Quarterly Labour Force Survey (held at the UK Data Archive under GN 33246), alongside primary and secondary derived variables computed by Eurostat from the core variables supplied. The data comprise seasonal or calendar quarters, depending on the date, and are not directly comparable with the UK QLFS quarters. Annual EU LFS datasets from 1999 onwards are also available (see under GN 33399) and 'ad hoc' modules (run each year to supplement the information from the core EU LFS questionnaire) are available from 2002 onwards (see under GN 33400). Users should note that the LFS Eurostat datasets available from the UK Data Archive comprise UK data only, and no data from other EU countries are included here. Further information about the EU LFS can be found on the Eurostat EU Labour Force Survey webpage. The UK Labour Force Survey (LFS) is a unique source of articulated information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. The first LFS was conducted in 1973 and continues to be one of the reasons for carrying out the survey. Eurostat co-ordinates information from labour force surveys in the European Union (EU) member states in order to assist the EU in such matters as the allocation of the Social Fund. Between 1984 and 1991 the survey was carried out annually, and moved to a quarterly cycle (the QLFS) from May 1992. Further information may be found in the main LFS documentation (see link below). LFS Documentation (main LFS) Besides the EU LFS documentation (see below), documentation is also available to accompany the main UK LFS datasets available from the Archive. This largely consists of the latest version of each document alongside the appropriate questionnaire for the year concerned. However, LFS documentation volumes are updated periodically by ONS, so users are advised to check the ONS LFS User Guidance pages before commencing analysis. Main Topics:Topics covered include household and demographic characteristics, country and region of work, employment and self-employment, employment history, working time, occupations and occupational status, job hunting, job changing, education and training, unemployment and economic activity. See main QLFS documentation for details. Compilation or synthesis of existing material See main QLFS documentation for details of initial face-to-face and telephone interviews and methodology.

Dataset replaced by: http://data.europa.eu/euodp/data/dataset/GIdNRX8Ny4Bvkaz7lYJL4Q

Hungary - Unemployment rate was 4.20% in March of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Hungary - Unemployment rate - last updated from the EUROSTAT on August of 2025. Historically, Hungary - Unemployment rate reached a record high of 10.90% in March of 2012 and a record low of 3.20% in December of 2019.

This feature layer was created using Census 2016 data produced by the Central Statistics Office (CSO) and NUTS 3 boundary data (generalised to 100m) produced by Tailte Éireann. The layer represents Census 2016 theme 13.1, persons at work or unemployed by occupation and sex. Attributes include a breakdown of population by occupation and sex (e.g. sales and customer service occupations - males, professional occupations - females, managers, directors and senior officials - total). Census 2016 theme 13 represents Occupation. The Census is carried out every five years by the CSO to determine an account of every person in Ireland. The results provide information on a range of themes, such as, population, housing and education. The data were sourced from the CSO. NUTS 3 boundaries generalised to 100m. The Nomenclature of Territorial Units for Statistics (NUTS) were drawn up by Eurostat in order to define territorial units for the production of regional statistics across the European Union. The NUTS classification has been used in EU legislation since 1988, but it was only in 2003 that the EU Member States, the European Parliament and the Commission established the NUTS regions within a legal framework (Regulation (EC) No 1059/2003). The Irish NUTS 3 regions comprise the eight Regional Authorities established under the Local Government Act, 1991 (Regional Authorities) (Establishment) Order, 1993 which came into operation on January 1st 1994. The NUTS 2 regions, which were proposed by Government and agreed to by Eurostat in 1999, are groupings of the Regional Authorities.

Spain - Unemployment rate was 10.90% in March of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Spain - Unemployment rate - last updated from the EUROSTAT on August of 2025. Historically, Spain - Unemployment rate reached a record high of 26.30% in March of 2013 and a record low of 10.80% in December of 2024.

Description: These are research indicators of doctorate holders in Europe that were compiled from the criteria and factors of the Eurostat. This dataset consists of data in five categories (i.e. Career Development of Doctorate Holders; Labour Market - Job Vacancy Statistics; Skill-related Statistics; European and International Co-patenting in EPO Applications and Ownership of Inventors in EPO Applications). The Eurostat Research Indicators consist of (1) Doctorate holders who have studied, worked or carried out research in another EU country (%); (2) Doctorate holders by activity status (%); (3) Doctorate holders by sex and age group; (4) Employed doctorate holders working as researchers by length of stay with the same employer (%); (5) Employed doctorate holders working as researchers by job mobility and sectors of performance over the last 10 years (%); (6) Employed doctorate holders by length of stay with the same employer and sectors of performance (%); (7) Employed doctorate holders by occupation (ISCO_88, %); (8) Employed doctorate holders by occupation (ISCO_08, %); (9) Employed doctorate holders in non-managerial and non-professional occupations by fields of science (%); (10) Level of dissatisfaction of employed doctorate holders by reason and sex (%); (11) National doctorate holders having lived or stayed abroad in the past 10 years by previous region of stay (%); (12) National doctorate holders having lived or stayed abroad in the past 10 years by reason for returning into the country (%); (13) Non-EU doctorate holders in total doctorate holders (%); (14) Unemployment rate of doctorate holders by fields of science; (15) Employment in Foreign Affiliates of Domestic Enterprises; (16) Employment in Foreign Controlled Enterprises; (17) Employment rate of non-EU nationals, age group 20-64; (18) Intra-mural Business Enterprise R&D Expenditures in Foreign Controlled Enterprises; (19) Job vacancy rate by NACE Rev. 2 activity - annual data (from 2001 onwards); (20) Job vacancy statistics by NACE Rev. 2 activity, occupation and NUTS 2 regions - quarterly data; (21) Job vacancy statistics by NACE Rev. 2 activity - quarterly data (from 2001 onwards); (22) Value Added in Foreign Controlled Enterprises; (23) Graduates at doctoral level by sex and age groups - per 1000 of population aged 25-34; (24) Graduates at doctoral level, in science, math., computing, engineering, manufacturing, construction, by sex - per 1000 of population aged 25-34; (25) Level of the best-known foreign language (self-reported) by degree of urbanisation; (26) Level of the best-known foreign language (self-reported) by educational attainment level; (27) Level of the best-known foreign language (self-reported) by labour status; (28) Level of the best-known foreign language (self-reported) by occupation; (29) Number of foreign languages known (self-reported) by educational attainment level; (30) Number of foreign languages known (self-reported) by degree of urbanisation; (31) Number of foreign languages known (self-reported) by labour status; (32) Number of foreign languages known (self-reported) by occupation; (33) Population by educational attainment level, sex, age and country of birth (%); (34) Co-patenting at the EPO according to applicants’/inventors’ country of residence - % in the total of each EU Member State patents; (35) Co-patenting at the EPO: crossing inventors and applicants; (36) Co-patenting at the EPO according to applicants’/inventors’ country of residence - number; (37) EU co-patenting at the EPO according to applicants’/ inventors’ country of residence by international patent classification (IPC) sections - number; (38) EU co-patenting at the EPO according to applicants’/inventors’ country of residence by international patent classification (IPC) sections - % in the total of all EU patents; (39) Domestic ownership of foreign inventions in patent applications to the EPO by priority year; (40) Foreign ownership of domestic inventions in patent applications to the EPO by priority year; and (41) Patent applications to the EPO with foreign co-inventors, by priority year.