Migrant integration statistics - employment conditions


Data extracted in June 2020.

Planned article update: June 2021.

Highlights

In the EU-27, the share of persons born outside the EU that were self-employed was 11.8 % in 2019, compared with 11.5 % for persons born in a different EU Member State and 13.9 % for the native-born population.

In the EU-27, more than one fifth (21.8 %) of employees born outside the EU were temporary employees in 2019, compared with 13.0 % for native-born employees and 15.2 % for employees born in a different EU Member State.

In the EU-27, nearly one quarter (24.6 %) of persons employed who were born outside the EU worked part-time in 2019, compared with 16.9 % for native-born persons in employment and 22.4 % for persons employed who were born in a different EU Member State.

Development of the share of self-employed persons in total employment for the population aged 20-64 years, EU-27, 2009-2019

This article presents EU statistics for a range of employment characteristics, contrasting the situation of migrants with the native-born population; the information may be used as part of an on-going process to monitor and evaluate migrant integration policies. The indicators presented are based on: a set of Council conclusions from 2010 on migrant integration; a subsequent study Indicators of immigrant integration — a pilot study from 2011; and a report titled Using EU indicators of immigrant integration from 2013. The article analyses information from the list of Zaragoza indicators that were agreed by EU Member States in Zaragoza (Spain) in April 2010, alongside additional information derived from the 2013 report on migrant integration. More specifically, it presents statistical data on the following:

This article forms part of an online Eurostat publication — Migrant integration statistics.

Full article

Self-employment

In 2019, the EU-27 self-employment share for people aged 20 to 64 years was 11.8 % for those born outside the EU, 11.5 % for those born in another EU Member State and 13.9 % for the native-born population

Between 2009 and 2019 there was almost no change in the share of self-employment in the EU-27 for working-age persons who were non-EU-born (in other words, born outside the EU); in 2019, the EU-27 self-employment share for persons born outside the EU was 11.8 %, which was 0.2 percentage points lower than the share recorded in 2009 (see Figure 1). However, this share did increase between 2011 and 2015 by 1.4 points before falling rapidly in 2017 (down 1.7 points) and thereby reversing all of the increase of the previous years. The share of self-employed persons was also lower in 2019 than it had been in 2009 in both of the other parts of the population, with a fall for EU-born persons (in other words, those born in a different EU Member State from the one in which they were living) of 1.0 points, while for the native-born population there was a fall of 1.4 points.

Figure 1 also shows an alternative analysis, namely by citizenship. The share of self-employed persons in total employment among non-EU citizens in the EU-27 was 0.9 percentage points higher in 2019 (11.2 %) than it had been in 2009 (10.3 %). This share for non-EU citizens in 2019 was the same as for citizens of other EU Member States, both of which were lower than the share for nationals (13.8 %). The share for nationals was 1.3 points lower in 2019 than it had been in 2009, while for citizens of other EU Member States the share in 2019 was 1.7 points lower than 10 years earlier.

Figure 1: Development of the share of self-employed persons in total employment for the population aged 20-64 years, EU-27, 2009-2019
(%)
Source: Eurostat (lfsa_esgacob), (lfsa_esgan), (lfsa_pgacws) and (lfsa_pganws)

In absolute terms, about 26.1 million persons of working-age were self-employed in the EU-27 in 2019. Around 23.2 million of these were native-born, while 2.9 million were foreign-born persons (with a higher share coming from outside the EU). Among the EU Member States, Italy had the largest self-employed population (4.6 million working-age persons), accounting for 17.7 % of all self-employed people in the EU-27, followed by Germany (3.5 million), France (3.0 million), Spain (2.9 million) and Poland (2.8 million).

In relative terms, there was little difference between self-employment shares in the EU-27 when analysing the results for 2019 by country of birth. The share for the native-born working-age population was 13.9 %, while those for foreign-born were lower, at 11.8 % for persons born outside the EU and 11.5 % for those born in a different EU Member State. Among the EU Member States, by far the highest self-employment share for persons born outside the EU was recorded in Czechia (33.2 %), with the next highest shares in Malta (18.7 %), Hungary (17.4 %), the Netherlands (16.7 %), Portugal (16.6 %) and Poland (16.2 %) — see Figure 2. By contrast, the lowest shares were recorded in Sweden (8.7 %), Germany (8.6 %), Austria (7.2 %) and Luxembourg (6.4 %).

For persons born in a different EU Member State, the highest self-employment share in 2019 was recorded in Slovakia (23.7 %), followed by Malta (21.6 %), Greece (18.4 %) and the Netherlands (18.3 %). At the other end of the range, the lowest self-employment shares for persons born in a different EU Member State were registered in Sweden (7.8 %), Cyprus (7.3 %), Luxembourg (7.2 %) and Ireland (6.5 %).

Comparing self-employment shares between the native-born and migrant populations (subject to data availability), there was a mixed pattern across the EU Member States in 2019 (see Figure 2). Czechia reported the largest gap when analysing the self-employment shares for persons born outside the EU and those for the native-born population, with the share for the latter being 17.7 percentage points lower; the next largest gaps in this direction were 7.3 points in Hungary and 5.1 points in Malta. The largest gap for the opposite situation was observed in Greece, where the self-employment share recorded for the native-born population was 17.5 points higher than it was for persons born outside the EU; again this was far larger than the next largest gap, 7.5 points in Italy.

A similar comparison between self-employment shares for the native-born population and persons born in a different EU Member State reveals that there were seven Member States with a higher share recorded for the native-born population. Among these, the largest gaps were observed in Greece (10.9 percentage points difference) and Italy (10.0 points), while relatively large gaps were also observed in Ireland (7.5 points) and Cyprus (5.7 points). By contrast, the native-born population recorded lower self-employment shares in 12 Member States, with the gap exceeding 3.0 points in Croatia (3.7 points), Malta (8.0 points) and Slovakia (8.9 points).

Figure 2: Share of self-employed persons in total employment for the population aged 20-64 years, by country of birth, 2019
(%)
Source: Eurostat (lfsa_esgacob) and (lfsa_pgacws)

Figure 3 presents an analysis of self-employed persons within the EU-27 by country of birth and according to their working status, with the self-employed split into two distinct groups: self-employed persons with employees (in other words, employers) and self-employed persons without employees (also known as own-account workers or sole proprietors). People working on their own account are typically people running their own business, farm or professional practice.

In 2019, more than two thirds (69.3 %) of self-employed persons aged 20-64 years in the EU-27 were own account workers, with the remainder being employers. When analysed by country of birth, the share was marginally higher (69.4 %) for the native-born population and slightly higher still (69.8 %) for people born in other EU Member States. The corresponding share of own account workers among people born outside the EU was somewhat lower, at 67.3 %.

Figure 3: Analysis of the total number of persons self-employed for the population aged 20-64 years, by country of birth and working status, EU-27, 2019
(%)
Source: Eurostat (lfsa_esgacob)

Temporary employment

The share of foreign-born persons in the EU who were temporary employees in 2019 was lower than in 2009, while for the native-born population it was almost unchanged

In the EU-27, temporary employees accounted for a 13.0 % share of the total number of native-born employees in 2019. This was the lowest share since 2009 when it had been 0.1 percentage points lower (see Figure 4). The corresponding shares for foreign-born populations were somewhat higher, as 15.2 % of employees born in another EU Member State were employed on a temporary basis, while the share among persons born outside the EU was 21.8 %.

Figure 4: Development of the share of temporary employees in the total number of employees for the population aged 20-64 years, EU-27, 2009-2019
(%)
Source: Eurostat (lfsa_etpgacob) and (lfsa_etpgan)

In 2019, the gap between the share of native-born and foreign-born employees aged 20-64 years in the EU-27 who worked on a temporary basis was 6.6 percentage points (see Table 1).

In 2019, the share of temporary employees in the total number of native-born employees peaked in Spain (23.8 %), followed by Poland (21.1 %), Portugal (19.4 %) and Croatia (18.0 %). Among the foreign-born population, the share of temporary employees in the total number of employees was close to half (47.9 %) in Poland, while more than one third of the total number of foreign-born employees in Spain (35.4 %) were employed on a temporary basis, as were more than a quarter in Portugal (27.5 %).

Among the 23 EU Member States for which comparable 2019 data are available, the share of temporary employees was higher for the foreign-born population than it was for the native-born population in all but three. The largest difference was observed in Poland (a gap of 26.8 percentage points); the next highest gaps were recorded in Cyprus (13.0 points), Sweden (12.3 points), Spain (11.6 points) and Greece (11.0 points). Estonia, Ireland and Croatia were the only exceptions, as their share of temporary employees in the total number of employees was lower for the foreign-born population than it was for the native-born population; this gap was 0.4 points in Estonia and Ireland and 4.1 points in Croatia.

There are limited data available for comparing the share of temporary employees between persons born in another EU Member State and persons born outside the EU. For 18 out of the 20 EU Member States for which data are available, the share of temporary employees was higher among persons born outside the EU than it was for persons born in another Member State. The biggest gap (24.0 percentage points) was recorded in Cyprus, where one third (32.7 %) of all employees born outside the EU were employed on a temporary basis, compared with less than one tenth (8.7 %) of their peers who had been born in another Member State. The next largest gaps were recorded in Sweden (11.6 points) and Spain (9.5 points). By contrast, in Greece, the share of temporary employees was higher among people born in another EU Member State than it was for those born outside the EU, while in Malta the share was the same for both of these populations.

Table 1: Share of temporary employees in the total number of employees, by country of birth and age group, 2019
(%)
Source: Eurostat (lfsa_etpgacob)

Figure 5 presents an analysis of the share of temporary employees in the total number of employees by country of birth and by sex. In 2019, the share of temporary employees in the total number of employees in the EU-27 was higher among women than men for both the native-born population and the population born in another EU Member State; by contrast, the opposite situation existed when comparing the difference between the shares recorded for men and women born outside the EU.

Figure 5: Share of temporary employees in the total number of employees for the population aged 20-64 years, by country of birth and sex, 2019
(%)
Source: Eurostat (lfsa_etpgacob)

Youth temporary employment

The final two figures within this section on temporary employment provide an analysis of the share of temporary employees in the total number of employees for young people (aged 15-29 years). Figure 6 shows the development of this share in the EU-27 during the period 2009-2019. Among the native-born population aged 15-29 years, the share of temporary employees in the total number of employees increased from 33.1 % in 2009 to reach a peak of 37.2 % in 2017 before falling to 35.5 % in 2019; during this period there were annual falls in 2012, 2018 and 2019. For young persons born outside the EU, the share of temporary employees in the total number of employees fluctuated between 37.1 % and 38.1 % between 2009 and 2014. Thereafter it rose each year to reach 43.1 % by 2018 and remained more or less at this level (43.0 %) in 2019. For young persons born in another EU Member State, the development was less regular but the share remained in a relatively narrow range, between 30.9 % (observed in 2013) and 33.3 % (observed in 2011 and again in 2017). The share of young employees born in another EU Member State who worked on a temporary basis was 1.0 percentage points higher in 2019 than in 2009. Throughout the period shown in Figure 6, the share was lowest for young people born in other Member States and was highest among young persons born outside of the EU. In 2019, the gap between the shares for young persons born outside of the EU and the young native-born population was 7.5 points, while between the young native-born population and young people born in other Member States it was 3.5 points.

Figure 6: Development of the share of temporary employees in the total number of employees for the population aged 15-29 years, by country of birth, EU-27, 2009-2019
(%)
Source: Eurostat (yth_empl_050)

An analysis by EU Member State shows that it was quite common for a relatively large proportion of employees aged 15-29 years to be working on a temporary basis; this was most notably the case in Spain, Portugal and Italy, where around half of all employees aged 15-29 years worked on a temporary basis in 2019: 55.4 % in Spain, 49.4 % in Portugal and 48.1 % in Italy. Among the young persons born outside the EU, the share of temporary employees in the total number of employees (regardless of sex) was the highest in Poland, Portugal, Spain and the Netherlands. In the case of Poland the share for young men was 61.8 % while for women it was 71.9 % (see Figure 7). More than half of young women born outside the EU working as employees in Slovenia, Sweden and Cyprus also worked on a temporary basis. Among young men born in another EU Member State, in the Netherlands a majority (50.4 %) worked on a temporary basis. Among the native-born population, a majority of young employees in Spain worked on a temporary basis, 54.4 % for young men and 57.8 % for young women. Furthermore, at least half of young, native-born, female employees worked on a temporary basis in Italy, Portugal and Slovenia.

Figure 7: Share of temporary employees in the total number of employees for the population aged 15-29 years, by country of birth and sex, 2019
(%)
Source: Eurostat (yth_empl_050)

Part-time employment

The share of the workforce aged 20-64 years working on a part-time basis rose faster between 2009 and 2019 among the foreign-born population than among the native-born population

The share of part-time employment in total employment increased steadily in the EU-27 during the most recent 10 year period. This pattern was most apparent among foreign-born populations, with the fastest pace of increase recorded for persons born outside the EU. Figure 8 shows that nearly one quarter (24.6 %) of the EU-27 workforce who had been born outside the EU worked on a part-time basis in 2019, while the corresponding share for persons born in another EU Member State was 22.4 % and that for the native-born workforce was lower at 16.9 %. A comparison between 2018 and 2019 reveals that the downturn that started the year before continued in 2019 for foreign-born persons working on a part-time basis (both for persons born in another EU Member State and persons born outside the EU). By contrast, there was a more stable (small increase) development for the share of part-time employment among the native-born workforce, following on from modest reductions in each of the previous four years.

Figure 8: Development of the share of part-time employment in total employment for the population aged 20-64 years, EU-27, 2009-2019
(%)
Source: Eurostat (lfsa_eppgacob) and (lfsa_eppgan)

This pattern of a higher share of part-time employment among foreign-born persons — particularly those born outside the EU — was repeated in most of the EU Member States in 2019 (see Table 2). However, Luxembourg, the Netherlands, Ireland, Croatia, Slovenia, Malta and Belgium reported higher shares of part-time employment among their native-born (rather than foreign-born) workforces; the difference was highest in in Luxembourg (5.9 percentage points) and the Netherlands (4.4 points). On the other hand, the share of part-time employment among the foreign-born workforce was 7.1 points higher than the share recorded for the native-born workforce in Greece and 7.0 points higher in Italy; the next largest differences between these two populations were observed in Spain (5.8 points) and Finland (5.1 points).

In 2019, the share of part-time employment was higher for women compared with men for all population groups

In 2019, the share of part-time employment was higher among women than it was among men. For the native-born workforce (aged 20-64 years), the highest gender gaps in the proportion of people working on a part-time basis were recorded in the Netherlands (51.6 percentage points), Austria (39.2 points) and Germany (37.2 points). The difference between the sexes regarding the propensity to be employed on a part-time basis was generally lower in EU Member States where the overall propensity to employ on a part-time basis was below the EU-27 average; the gap between the sexes was less than 1.0 points in Bulgaria and Romania (where relatively few people worked on a part-time basis).

A similar analysis for the foreign-born workforce (aged 20-64 years) shows that the migrant population living in the Netherlands, Germany and Austria had a similar pattern as that observed for the native-born workforce, insofar as they recorded the largest gender gaps for shares of part-time employment. The share of part-time employment among foreign-born persons was higher among women (than among men) in each of the 23 EU Member States for which data are available (note: no data or only partial data available for Bulgaria, Poland, Romania and Slovakia), with the gap between women and men reaching 42.1 percentage points in the Netherlands, 39.6 points in Germany, 35.1 points in Austria, 31.7 points in Belgium and 30.2 points in Italy. By contrast, the lowest gender gaps were recorded for Hungary (where the share of part-time employment for the foreign-born workforce was 2.9 points higher among women than among men), Croatia (3.5 points), Latvia (4.0 points), Lithuania (4.7 points) and Cyprus (5.3 points).

Table 2: Share of part-time employment in total employment for the population aged 20-64 years, by country of birth and sex, 2019
(%)
Source: Eurostat (lfsa_eppgacob)

An analysis by age suggests that older persons (aged 55-64 years) tended to have a higher propensity to work on a part-time basis. Among the native-born population the share of persons aged 55-64 years working on a part-time basis in the EU-27 (19.9 %) was 4.6 percentage points higher than the share recorded for those aged 25-54 years (15.3 %). This pattern was repeated for the foreign-born workforce when considering persons born in other EU Member States, as the share of part-time employment among older workers was 4.3 points higher than the share recorded for those aged 25-54 years. For the workforce born outside the EU a smaller difference (2.0 points) was observed: the share of part-time employment recorded for people aged 55-64 years was 25.8 % compared with 23.8 % for people aged 25-54 years. It is interesting to note that among the workforce born outside the EU, the share of part-time employment was lower for older people (than for those aged 25-54 years) in Austria, Lithuania and Italy.

Table 3: Share of part-time employment in total employment, by country of birth and age group, 2019
(%)
Source: Eurostat (lfsa_eppgacob)

Youth part-time employment

The share of part-time employment for young people (aged 15-29 years) in the EU-27 as a percentage of total employment was higher in 2019 than in 2009, regardless of the country of birth. However, the propensity to employ on a part-time basis was falling or stabilising for some groups of young people during the last few years.

Despite falling since 2014, the share of part-time employment among young people born outside the EU was 5.2 percentage points higher across the EU-27 in 2019 than it had been in 2009. While there were also increases over this period for the other two populations, their rates of change were somewhat less marked, as the proportion of part-time employment rose by 3.5 points for young people born in another EU Member State and by 4.2 points for young native-born people.

Across the whole of the EU-27, in 2019 the share of part-time employment for young people born outside the EU was 28.9 %, compared with shares of 22.4 % for those who were native-born and 23.1 % for those born in another EU Member State. These aggregate figures (for both sexes) disguise the gender imbalance that exists in relation to part-time employment (see Figure 9), with a higher proportion of young women (than men) in part-time employment. The share of part-time employment among young women born in another EU Member State stood at 32.5 %, which was 17.6 percentage points higher than the corresponding share among young men born in another EU Member State. The differences for the other populations were almost as large, as the share of part-time employment among young women born outside the EU was 38.0 % (15.5 points higher than for young men) and the share for young women who were native-born was 29.8 % (13.7 points higher). For both sexes, the highest shares of part-time employment were recorded for young persons born outside the EU. By contrast, the shares of part-time employment among young people who were native-born and young people who were born in another EU Member State were quite closely matched in recent years, particularly for young men. The proportion of young men born in another EU Member State who worked on a part-time basis (14.9 %) was somewhat lower than the corresponding share for young men who were native-born (16.1 %), whereas for young women the difference was slightly broader: 29.8 % of the native-born population worked on a part-time basis compared with 32.5 % of young women born in another EU Member State.

Figure 9: Development of the share of part-time employment in total employment for the population aged 15-29 years, by country of birth and sex, EU-27, 2009-2019
(%)
Source: Eurostat (yth_empl_060)

Data sources

The main data source for employment characteristics is the EU labour force survey (EU-LFS). The EU-LFS is a quarterly sample survey that covers the resident population aged 15 years and above in private households; it provides data for the EU Member States, the United Kingdom, EFTA (except Liechtenstein) and candidate countries. The survey is designed to provide population estimates for a set of main labour market characteristics, covering subjects such as employment, unemployment, economic inactivity and hours of work, as well as providing analyses for a range of socio-demographic characteristics, such as sex, age, educational attainment, occupation, household characteristics and region of residence.

A set of Council, European Parliament and European Commission regulations define how the EU-LFS is carried out, whereas some countries have their own national legislation for the implementation of the survey. The key advantage when using EU-LFS data is that they come from a survey which is highly harmonised and optimised for comparability. However, there are some limitations when considering the coverage of the EU-LFS for migrant populations, as the EU-LFS was designed to target the whole resident population and not specific subgroups, such as migrants. The following issues should be noted when analysing migrant integration statistics:

  • recently arrived migrants — this group of migrants is missing from the sampling frame in every host Member State, which results in under-coverage of the actual migrant population for EU-LFS statistics;
  • non-response — one disadvantage of the EU-LFS is the high percentage of non-response that is recorded among migrant populations which may reflect: language difficulties; misunderstanding concerning the purpose of the survey; difficulties in communicating with the survey interviewer; or fear concerning the negative impact that participation in the survey could have (for example, damaging a migrants chances of receiving the necessary authorisation to remain in the host Member State);
  • sample size — given the EU-LFS is a sample survey, it is possible that some of the results presented for labour market characteristics of migrants are unrepresentative, especially in those EU Member States with small migrant populations (note that for cases where data are considered to be of particularly low reliability, statistics are not published).

This article focuses on comparisons between national and migrant populations. The results for the migrant population are usually disaggregated into migrants from other EU Member States and migrants from outside the EU; in some cases an additional analysis by age or by sex is presented. Migrant indicators are calculated for two broad groups: the foreign population determined by country of birth and the foreign population determined by citizenship. Although providing some main indicators for the latter, this article focuses on information for migrant integration by country of birth (this subgroup of the population is generally somewhat larger and therefore allows a more complete and robust data set to be presented). That said, results by country of birth are generally representative of those by citizenship.

The following analyses are presented:

For the population by country of birth

  • Native-born — the population born in the reporting country;
  • foreign-born — the population born outside the reporting country; subdivided into:
    • EU-born — the population born in the EU, except the reporting country; and
    • non-EU-born — the population born in non-EU countries.

For the population by citizenship

  • Nationals — the population of citizens of the reporting country;
  • foreign citizens — the non-nationals; subdivided into:
    • EU citizens — the citizens of EU Member States, except the reporting country;
    • non-EU citizens — the citizens of non-EU countries.

For the population by age

  • 15-29 years — this age cohort represents the youth population;
  • 20-64 years — this cohort has been selected because it is relevant to one of the targets included within the Europe 2020 strategy, namely, that the employment rate of persons aged 20-64 years should reach 75 % by 2020;
  • 25-54 years — this cohort is considered as the most appropriate group for an analysis of the situation of core working-age migrants, as it minimises the effects of migration related to non-economic reasons (for example, educational studies, training or early retirement), while forming a homogenous group that is large enough to produce reliable results;
  • 55-64 years — this cohort focuses on older migrants.

The indicators in this article use the definitions of the Zaragoza indicators. Note the age groups above may not be the same as presented in Eurostat’s labour market statistics; for this reason results may differ from other results disseminated by Eurostat.

Tables in this article use the following notation:

Value in italics     data value is forecasted, provisional or estimated and is therefore likely to change;
: not available, confidential or unreliable value.

Context

There is a strong link between integration, migration and employment policies since successful integration is necessary for maximising the economic and social benefits of immigration for EU societies and economies. The importance of integration of nationals of non-member countries living legally in the EU Member States and the establishment of policies for a secure labour environment for migrants underwent a considerable development in 2000 when the Racial Equality Directive (2000/43/EC) and the Employment Equality Directive (2000/78/EC) were adopted in order to prohibit discrimination in employment, occupation, social protection education and access to public goods on the grounds of religion or belief, disability, age, or sexual orientation, race and ethnic origin. In 2010, Europe 2020, a strategy for smart, sustainable and inclusive growth (COM(2010) 2020 final) was set as a foundation for all people, including migrants, to achieve the objective of ‘an inclusive high employment society’, setting a target of reaching a 75 % employment rate by 2020. In July 2011, the European Commission proposed a European agenda for the integration of third-country nationals [1] focusing on actions to increase economic, social, cultural and political participation by migrants. The agenda highlighted challenges that need to be addressed if the EU is to benefit fully from the potential offered by migration and the value of diversity. It also explored the role of countries of origin in the integration process.

With regard to the measurement of migrant integration, the Stockholm Programme for the period 2010-2014 embraced the development of core indicators for the monitoring of the results of integration policies in a limited number of relevant policy areas including employment, education and social inclusion. Through the 2010 Zaragoza Declaration (and the subsequent Council conclusions) Member States identified a number of common indicators (the so-called Zaragoza indicators) and called upon the European Commission to undertake a pilot study examining proposals for common integration indicators and reporting on the availability and quality of the data for a range of harmonised sources necessary for the calculation of these indicators. The proposals in the pilot study were examined and developed in a report published by the European Commission’s Directorate-General for Migration and Home Affairs Using EU indicators of immigrant integration.

In July 2015, the European Commission released jointly with the OECD a report on indicators of immigrant integration Settling in — 2015. While in the thematic chapters of this report the analysis is focused on the foreign-born population, there is a specific chapter dealing with the situation of non-EU citizens in the EU, aimed specifically at monitoring the Zaragoza indicators. A second edition of the report was released in 2018.

On 7 June 2016, the European Commission adopted an Action Plan on the integration of third-country nationals. The plan aims to support the integration process of nationals of non-member countries in the EU, including the specific challenges faced by refugees. The actions target key policy priorities such as pre-departure/pre-arrival measures and access to basic services (education, vocational training, labour market integration, health-care and housing).

Notes

  1. ‘Third-countries’ is a synonym for non-member countries, in other words countries outside of the EU.
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Employment (mii_emp)
Unemployment (mii_une)
Long-term unemployment (12 months or more) as a percentage of the total unemployment, by sex, age and citizenship (%) (lfsa_upgan)
Long-term unemployment (12 months or more) as a percentage of the total unemployment, by sex, age and country of birth (%) (lfsa_upgacob)
Employment and self-employment (mii_em)
Employment rates by sex, age and citizenship (%) (lfsa_ergan)
Employment rates by sex, age and country of birth (%) (lfsa_ergacob)
Part-time employment as percentage of the total employment, by sex, age and citizenship (%) (lfsa_eppgan)
Part-time employment as percentage of the total employment, by sex, age and country of birth (%) (lfsa_eppgacob)
Self-employment by sex, age and citizenship (1 000) (lfsa_esgan)
Self-employment by sex, age and country of birth (1 000) (lfsa_esgacob)
Temporary employees as percentage of the total number of employees, by sex, age and citizenship (%) (lfsa_etpgan)
Temporary employees as percentage of the total number of employees, by sex, age and country of birth (%) (lfsa_etpgacob)