Migrant integration statistics - regional labour market indicators


Data from May 2021.

Planned article update: June 2022.

Highlights

Activity rates for citizens of other EU Member States were higher than those for nationals in a majority of the EU’s regions in 2020.

Across the EU, the highest regional employment rate in 2020 for citizens of other EU Member States was 95.6 % in Mecklenburg-Vorpommern (Germany).

In 2020, in all EU Member States except for Poland, the employment rates for people with a tertiary level of educational attainment living in cities were lower among non-EU citizens than among nationals and citizens of other Member States.


Migrants play a role in the economies of the host countries in which they settle, with their labour market participation gaining importance in many European Union (EU) Member States over recent years. Migrant integration has become a key area for policy focus in recent years.

The information presented here for regional labour market indicators supplements a more general article that provides a range of national migrant integration statistics. The present article goes into more detail by analysing statistics for NUTS regions [1] and statistics by degree of urbanisation. The information shown contrasts the situation of foreign citizens — both citizens of other EU Member States and non-EU citizens — with that of nationals (in other words citizens of the country in which they are resident). The article is divided into three main parts, each covering a key indicator: the activity rate, the employment rate and the unemployment rate [2].

All of the statistics shown relate to the working-age population, defined here as people aged 20-64 years.

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

Full article

Regional activity rates

Labour market participation can be measured through the activity rate, which provides information on the number of economically active persons (also known as the labour force) of a particular age group, expressed as a percentage of the total population of the same age group; in this article the rate has been calculated for the age group 20-64 years. This indicator is one of the key Zaragoza indicators for measuring migrant integration.

The activity rate of the working-age population living in the EU varied according to citizenship (as illustrated in Maps 1-3); note that identical classes have been used for the shading in all three maps for easier comparison. In 2020, the EU activity rate for nationals was 78.2 %, while the rate for citizens of other EU Member States was higher (80.4 %) and that for non-EU citizens was considerably lower (68.7 %).

Maps 1 to 3: Activity rates by broad groups of citizenship and NUTS 2 regions, 2020
For full-size maps please see the Excel file attached.
Source: Eurostat (lfst_r_lfp2actrtn)

In 2020, the highest regional activity rates for nationals were often recorded in the Nordic Member States or Germany. The highest regional activity rate for nationals was 90.5 % and was recorded in Stockholm, the Swedish capital region. Another Swedish region, Småland med öarna, recorded the second highest rate, 89.6 %. A total of 29 other NUTS level 2 regions recorded activity rates for nationals that were at least 85.0 %, including 17 regions of Germany, all of the other regions of Sweden, two each of Finland and the Netherlands, and the capital regions of Lithuania and Denmark. There were seven regions with activity rates for nationals below 65.0 %. Each of these was in southern Italy or an Italian island, including the lowest rate of 53.6 % for Campania. Among the six next lowest rates (at least 65.0 % but below 70.0 %), were two (overseas) French regions, one more Italian region, and one region each from Belgium, Romania and Croatia. The difference between the highest and lowest regional activity rates for nationals (recorded in Stockholm and Campania respectively) was 36.9 percentage points.

Activity rates for citizens of other EU Member States were higher than those for nationals in a majority of the EU’s regions

A similar analysis of regional activity rates is presented in Map 2, with its focus on citizens of other EU Member States. In 2020, the highest regional activity rate for this part of the population was 97.3 % recorded in Flevoland (the Netherlands). Rates of 85.0 % or more were also recorded in 52 other regions: 15 German regions (2019 data for six regions; low reliability for nine regions), seven (out of eight) Czech regions, five Swedish regions (2018 data for one region; low reliability for two regions), four regions each of Austria and Portugal (2019 data for one region), three more Dutch regions, three Danish regions, two regions each of Spain, France (2018 data with low reliability for one region), Slovenia (low reliability for one region) and Finland, as well as Malta, Latvia and Cyprus. In contrast, activity rates for citizens of other Member States were less than 60.0 % in seven Italian regions (including Basilicata which had the lowest rate (45.7 %); low reliability for one region), two Greek NUTS level 1 regions and one region of each France, Belgium and the Netherlands. The difference between the highest and lowest regional activity rates for citizens from other Member States (recorded in Flevoland and Basilicata respectively) was 51.6 percentage points.

In 2020, foreign citizens aged 20-64 years from other EU Member States were more likely to be part of the EU labour force (80.4 %) than nationals of the same age (78.2 %). A more detailed analysis reveals that this pattern was repeated in 105 of the 186 regions (56.5 %) for which data are available (including some with low reliability) across the EU. Among these regions, the largest differences between activity rates for these two parts of the population — in percentage point terms — were recorded in Malta (16.2 percentage points), Flevoland in the Netherlands (13.1 percentage points) and Centro in Portugal (13.0 percentage points) — see Figure 1.

Among the 78 regions (41.9 % of all regions for which data are available, reliable or with low reliability) where nationals recorded higher activity rates in 2020 (data for earlier years for some regions) than citizens from other EU Member States, the largest difference — in percentage point terms — was recorded in the French region of Nord-Pas-de-Calais, where the activity rate for nationals was 17.5 percentage points higher than that recorded for citizens from other EU Member States. In the Dutch regions of Friesland (low reliability) and Groningen, the gaps were 15.6 and 14.9 percentage points respectively, while in the Italian region of Basilicata it was 14.7 percentage points. There were three regions — Střední Morava in Czechia as well as Galicia and Illes Balears in Spain — where the rates were the same for these two subpopulations.

Figure 1: Largest gaps in regional activity rates for nationals and citizens from other EU Member States, by NUTS 2 regions, 2020
(percentage points difference; based on population aged 20-64 years)
Source: Eurostat (lfst_r_lfp2actrtn)

The focus of Map 3 is again the activity rate, but for non-EU citizens. The highest activity rate for this part of the population was recorded in Śląskie in Poland, where 95.0 % (2019 data; low reliability) of foreign citizens from outside the EU aged 20-64 years formed part of the labour force; the next highest activity rates (more than 85.0 %) were recorded in six of the eight Czech regions, three more Polish regions (two at NUTS level 1; low reliability), Poitou-Charentes in France, and the Lithuanian and Portuguese capital regions (Sostinės regionas and Área Metropolitana de Lisboa).

At the other end of the range, the two lowest regional activity rates for non-EU citizens — both below 38.0 % — were recorded in Prov. Hainaut and Prov. Liège in Belgium. In total, 72 regions recorded rates below 65.0 %, with these regions mainly situated in France (22 regions; 2019 data for one region; low reliability for six regions), Germany (18 regions; 2019 data for two regions; low reliability for one region), Belgium (nine regions; 2019 data for one region; low reliability for two regions), the Netherlands (eight regions; low reliability for two regions), Italy (five regions; low reliability for one region), Croatia (both regions; low reliability) and Bulgaria (national data; low reliability data for 2019). Prov. Hainaut had the lowest rate in the EU (36.2 %). Therefore, the difference between the highest and lowest regional activity rates for non-EU citizens (recorded in Śląskie in 2019 and Prov. Hainaut in 2020 respectively) was 58.8 percentage points, larger than the range for either nationals or citizens of other EU Member States.

Overall, non-EU citizens (68.7 %) were less likely to form part of the EU labour force in 2020 than nationals (78.2 %). A higher activity rate for non-EU citizens than for nationals was reported for 41 of the 204 EU regions for which data are available (including some with low reliability, for 2020 or another recent year), in other words around one fifth (20.1 %) of the total number. Among these 41 regions, the largest difference between activity rates for these two groups of the population — in percentage point terms — was recorded in the Polish region of Śląskie (23.0 percentage points; 2019 data; low reliability), followed by the Czech and Greek regions of Střední Morava (14.5 percentage points) and Dytiki Ellada (14.1 percentage points). Double-digit gaps were also observed in Campania, Sardegna (both in Italy), Małopolskie (in Poland), Dytiki Makedonia (in Greece; low reliability), Severozápad (in Czechia) and Makroregion Północno-Zachodni (NUTS level 1 region in Poland; low reliability) — see Figure 2. At the other end of the range, there were eight regions across the EU where activity rates for nationals were higher than for non-EU citizens by 30.0 percentage points or more. Two of these were French regions, namely Mayotte (which had the largest gap at 38.0 percentage points; note that results should be treated with caution) and Guyane (which had the fourth largest gap at 33.5 percentage points). In addition, there were three regions of Germany, two regions of Belgium, and one region of the Netherlands (low reliability).

Figure 2: Largest gaps in regional activity rates for nationals and citizens from outside the EU, by NUTS 2 regions, 2020
(percentage points difference; based on population aged 20-64 years)
Source: Eurostat (lfst_r_lfp2actrtn)

In 2020, regional activity rates for non-EU citizens were generally more dispersed than regional activity rates for citizens of other EU Member States (see Figure 3); regional activity rates for citizens of other Member States were generally higher than regional activity rates for non-EU citizens. Activity rates for capital regions were usually higher than the national average. This was generally the case for both foreign populations and can be seen in all Member States for which data are available (including some with low reliability) with the exception of: the Austrian and Slovenian capital regions, where both the activity rates for non-EU citizens and for citizens of other EU Member States were lower than the respective national averages; the Italian and Lithuanian capital regions, where the activity rate for citizens of other Member States was lower than the national average for citizens of other Member States; and the Czech and Croatian capital regions, where the activity rates for non-EU citizens were lower than the national averages for non-EU citizens.

Figure 3: Regional disparities in activity rates, by citizenship and NUTS 2 regions, 2020
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_lfp2actrtn)

The information presented in Figure 4 also underlines the differences in 2020 between activity rates for foreign citizens who were citizens of other EU Member States and those who were non-EU citizens. Some of the most pronounced differences were recorded in Denmark, Ireland, Austria, Slovenia and Finland where the lower regional activity rate for citizens of other EU Member States was at a higher level than the upper regional activity rate for non-EU citizens; this situation was also observed for both of the non-member countries shown in Figure 4. In Sweden, this was almost as case as these regional activity rates (the lowest for citizens of other EU Member States and the highest for non-EU citizens) were different by just 0.3 percentage points. By contrast, Czechia, Greece and Lithuania were the only EU Member States to report that their upper regional activity rate for non-EU citizens was higher than the upper regional activity rate for citizens of other EU Member States.

Figure 4: Highest and lowest regional activity rates, by citizenship and NUTS 2 regions, 2020
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_lfp2actrtn)

Activity rates by degree of urbanisation

The highest activity rates tended to be in cities

In 2020, EU activity rates for people aged 20-64 years were higher in cities than they were in towns and suburbs or rural areas. A similar pattern could be seen for all three parts of the population shown in Figure 5. For people living in EU cities, activity rates peaked at 81.2 % for citizens of other EU Member States, while the rate for nationals was 79.0 % and for non-EU citizens it was 69.5 %.

The three separate charts that make-up Figure 5 confirm some of the results already presented at a regional level, in that as activity rates tended to be higher for people from other EU Member States and for nationals than they were for non-EU citizens, although this was not the case for all degrees of urbanisation in all Member States. It is interesting to note that the activity rates varied more by degree of urbanisation for foreign citizens than for nationals in most Member States.

Focusing on the activity rates for citizens of other EU Member States analysed by degree of urbanisation, the most pronounced difference was observed in Croatia where a rate of 100.0 % was recorded for cities in 2019 compared with 68.7 % for rural areas in 2018; note that the data are of low reliability.

A similar analysis for non-EU citizens reveals that the biggest differences in activity rates by degree of urbanisation (more than 10 percentage points) were recorded in:

  • Croatia (2018 and 2019 data, low reliability) and Finland, where the highest rates were observed in rural areas;
  • Luxembourg, Portugal (2019 and 2020 data), Ireland, Malta (low reliability) and Denmark, where the highest rate was observed in cities.

In cities, the lowest activity rates were mainly recorded among non-EU citizens

In 2020, for 17 EU Member States (among those for which data are available, reliable or with low reliability, for all three subpopulations) the highest activity rates in cities were recorded for citizens of other EU Member States. Five Member States — the Netherlands, Germany, Estonia, Lithuania (low reliability) and Hungary — reported that nationals had the highest activity rates. The remaining one — France — recorded an identical rate for people living in cities among nationals and citizens of other EU Member States. Furthermore, in Luxembourg, Portugal, Malta, Greece, Poland, Italy, Czechia, Slovenia (low reliability) and Ireland the activity rates for people living in cities were higher for non-EU citizens as well as for citizens of other Member States than they were for nationals.

A similar analysis for towns and suburbs reveals that there were 14 EU Member States (out of 20 for which data are available, reliable or with low reliability) where citizens of other Member States recorded the highest activity rates, while there were five Member States where nationals recorded the highest activity rates: the Netherlands, Estonia (low reliability), Hungary (2019 and 2020 data; low reliability), Germany and Sweden. However, activity rates among non-EU citizens living in Greek towns and suburbs were higher than the rates recorded for nationals or for citizens of other Member States. In Czechia, Luxembourg and Malta, the activity rates for people living in towns and suburbs were higher among non-EU citizens as well as citizens of other Member States than they were for nationals.

In rural areas, the highest activity rates for people who were citizens of other EU Member States were recorded in eight Member States (out of 19 for which data were available, reliable or with low reliability), while there were six Member States where the highest activity rates were observed for nationals: Sweden, Belgium (low reliability), the Netherlands, France, Germany and Malta (low reliability). In Italy, the highest activity rates in rural areas were the same for people who were citizens of other Member States and for nationals. Among non-EU citizens living in rural areas of Croatia (2018 and 2020 data; low reliability), Slovenia (low reliability), Greece and Czechia, activity rates were higher than the rates recorded for nationals or for citizens of other Member States.

Figure 5: Activity rates by citizenship and degree of urbanisation, 2020
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_arednu)

Regional employment rates

The employment rate is defined as the share of the working-age population (defined here as people aged 20-64 years) who are in employment. In 2020, the EU employment rate for nationals was 73.3 %, which was 0.3 percentage points higher than the rate recorded for citizens from other EU Member States (73.0 %). By contrast, the EU employment rate for working-age people who were non-EU citizens was 57.2 % (some 16.1 percentage points lower than the average for nationals).

Maps 4-6 present regional employment rates for: nationals, citizens from other EU Member States and non-EU citizens (note that identical classes have been used for the shading in all three maps for easier comparison).

Maps 4 to 6: Employment rates by broad groups of citizenship and NUTS 2 regions, 2020
For full-size maps please see the Excel file attached.
Source: Eurostat (lfst_r_lfe2emprtn)

In 2020, the highest regional employment rates for nationals were in Germany, Finland and Sweden (see Map 4). The highest regional employment rates for nationals were recorded in the German regions of Chemnitz (87.7 %), Dresden (86.9 %), Tübingen (86.4 %) and Stuttgart (86.3 %). In the list of 13 regions with employment rates that were at least 85.0 %, these four were joined by six more German regions (mainly in the south), a Finnish region (Åland) and two Swedish regions (Stockholm and Småland med öarna).

At the other end of the range, the four regions with the lowest employment rates for nationals were all located in the south of Italy — Puglia, Calabria, Sicilia and Campania — among which three recorded rates that were less than 50.0 %. In other words, in Calabria, Sicilia and Campania it was more common for working-age adults not to have a job than to have one. This reflected a more general pattern, as many of the lowest regional employment rates for nationals were recorded in southern Europe, specifically in Italian, Spanish or Greek regions. The only regions of other EU Member States to record employment rates for nationals below 65.0 % were in Bulgaria (Severozapaden), Belgium (the capital region and Prov. Hainaut), France (three of the overseas regions) and Croatia (Jadranska Hrvatska).

The highest regional employment rates for citizens of other Member States were mainly recorded in Czechia or Germany ...

Map 5 reveals that, across the EU, the highest regional employment rates in 2020 for citizens of other EU Member States were mainly recorded in Czech or German regions, including the highest rate of all, 95.6 % in Mecklenburg-Vorpommern in Germany. There were 13 more regions where the rate was more than 85.0 %, of which five each in Czechia and Germany (data for 2019 for two regions; low reliability for two regions), two in Sweden (low reliability data for 2018 for one region) and one each in the Netherlands, Portugal, Malta, France (low reliability data for 2018) and Denmark. Nine regions recorded employment rates for citizens of other EU Member States that were below 50.0 % and again these were in southern Member States: Sardegna, Sicilia, Puglia, Campania, Basilicata, Molise(low reliability), Calabria in Italy and Voreia Ellada and Kentriki Ellada (NUTS level 1 regions) in Greece. The lowest employment rate for citizens of other EU Member States was 36.2 % in Calabria.

... while for non-EU citizens the highest rates were mainly in Czechia or Poland

The focus of Map 6 is again the employment rate, but this time for non-EU citizens. The highest employment rate for this part of the population was recorded in Střední Morava (Czechia), where 94.7 % of non-EU citizens aged 20-64 years were in employment. The next highest employment rates — which were the only other ones over 85.0 % — were in Śląskie (2019 data; low reliability) and Makroregion Północno-Zachodni (NUTS level 1; low reliability) in Poland, and in Jihovýchod, Severozápad, Střední Čechy, Severovýchod and Jihovýchod in Czechia. In 53 of the regions across the EU, less than half of non-EU citizens were in employment. Among these, there were 14 regions where the employment rate was below 40.0 % and four — the French overseas regions of Guyane and Mayotte (results should be treated with caution) as well as the Belgian regions of Prov. Hainaut and Prov. Liège — where the rate was below 30.0 %.

Figure 6 summarises the information concerning the highest and lowest regional employment rates in 2020 for citizens of other EU Member States and non-EU citizens.

Figure 6: Employment rates by citizenship for selected NUTS 2 regions, 2020
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_lfe2emprtn)

For foreign citizens, employment rates in capital regions were generally higher than national averages

In 2020, it was often the case that the employment rate for foreign citizens in capital regions was above the national average (see Figure 7). Subject to data availability, this pattern was repeated in a majority of the EU Member States, although there were several exceptions: Belgium, Czechia, Germany, Croatia, Italy and Poland, where national employment rates were higher than in the respective capital region for non-EU citizens; Lithuania and Hungary where the national employment rate was higher than in the capital region for citizens of other Member States; Austria, where national employment rates were higher than those recorded in the capital region for citizens of other Member States as well as for non-EU citizens.

Figure 7: Regional disparities in employment rates, by citizenship and NUTS 2 regions, 2020
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_lfe2emprtn)

Figure 8 confirms that regional employment rates for citizens of other EU Member States were generally higher than those recorded for non-EU citizens, while inter-regional differences were usually greater for non-EU citizens than they were for citizens of other Member States. In 2020, such inter-regional differences for non-EU citizens were particularly pronounced in France, as their employment rate ranged from a high of 68.2 % in Bourgogne, to a low of 19.5 % in Mayotte (results should be treated with caution), a gap of 48.7 percentage points; the inter-regional gap in France for citizens of other EU Member States was 24.0 percentage points. Belgium, Germany and Spain also recorded differences in employment rates in excess of 30.0 percentage points between their regions with the highest and lowest employment rates for non-EU citizens.

While the inter-regional difference for non-EU citizens was largest in France, for citizens of other EU Member States the largest gap was observed in Italy (39.9 percentage points), between 36.2 % in Calabria and 76.1 % in Friuli-Venezia Giulia. The inter-regional gap in Italy for non-EU citizens was 24.0 percentage points, therefore lower than for citizens of other EU Member States, a situation that was also observed in the Netherlands, Slovenia, Greece and Denmark.

Figure 8: Highest and lowest regional employment rates, by citizenship and NUTS 2 regions, 2020
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_lfe2emprtn)

Employment rates by degree of urbanisation

Figure 9 is composed of three separate parts that provide information on employment rates for nationals, citizens of other EU Member States and non-EU citizens; each part presents an analysis by degree of urbanisation. In 2020, the highest EU employment rate for non-EU citizens was recorded in cities (57.8 %) and this was also the case for citizens of other EU Member States (73.3 %). For nationals, there was no difference between the rates observed in cities and rural areas (both 73.5 %), while the rate for towns and suburbs was a little lower (72.9 %).

In 2020, there were 14 EU Member States (among the 23 for which data are available, reliable or low reliability) where the highest employment rates in cities were recorded for citizens of other EU Member States. In the remaining nine Member States — Greece, Estonia, Germany, Hungary, Lithuania (low reliability), Finland, Austria, Spain and the Netherlands — nationals had the highest employment rates.

A similar analysis for towns and suburbs reveals that there were 10 EU Member States (among the 20 for which data are available, reliable or low reliability) where citizens of other EU Member States recorded the highest employment rates, while there were nine Member States where employment rates among nationals living in towns and suburbs were higher than the rates recorded for non-EU citizens or for citizens of other Member States. In Czechia, the highest employment rate for people aged 20-64 years living in towns and suburbs was recorded by non-EU citizens.

In rural areas, the highest employment rate for people aged 20-64 years in nine EU Member States (among the 19 for which data are available, reliable or low reliability) was recorded for nationals. There were six Member States where the highest employment rate in rural areas was for citizens of other Member States: Cyprus, Finland, Denmark, Luxembourg, Ireland and Malta. In the remaining four Member States — Croatia, Slovenia, Czechia and Portugal —the highest employment rate for people living in rural areas was recorded for non-EU citizens.

Figure 9: Employment rates by citizenship and degree of urbanisation, 2020
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_erednu)

The analyses in Figures 10 and 11 are restricted to data covering people living in cities who had a tertiary level of educational attainment.

In 2020, in the vast majority of EU Member States the employment rates for people with high (tertiary) levels of educational attainment living in cities were lower among non-EU citizens than among nationals or citizens of other Member States

In 2020, the EU employment rate for people living in cities and who had a tertiary level of educational attainment was notably higher among nationals (85.1 %) and citizens from other EU Member States (81.5 %) than it was for non-EU citizens (65.5 %). Figure 10 reveals that, subject to data availability, in all EU Member States except for Poland the employment rate for people with a tertiary level of educational attainment living in cities was lower among non-EU citizens than among nationals or citizens of other EU Member States. In Poland, the rate for non-EU citizens was higher than that for citizens of other EU Member States.

In 2020, in a small majority of EU Members States the highest employment rate among people of working-age with a tertiary level of educational attainment living in cities was recorded for nationals, although in Lithuania (low reliability), Luxembourg, Hungary, Malta, Belgium and Portugal the highest employment rates were recorded for citizens of other Member States.

Figure 10: Employment rates for people with a tertiary level of educational attainment living in cities, by citizenship, 2020
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_erednu)

An additional analysis by sex (see Figure 11) reveals that just less than three fifths (57.2 %) of all working-age women in the EU who were non-EU citizens who had completed a tertiary level of education and lived in cities were employed, while the share for the equivalent cohort of men was three quarters (75.0 %). An analogous comparison for citizens from other EU Member States reveals a smaller gender gap, as the employment rate for men having completed a tertiary level of education and living in cities was 87.6 %, some 11.3 percentage points higher than the corresponding figure for women (76.3 %). Both of these gender gaps for foreign citizens were higher than the gap recorded among nationals, as the employment rate for male nationals with a tertiary level of educational attainment living in cities was 87.4 %, some 4.3 percentage points higher than the corresponding rate for female nationals (83.1 %).

Among the 22 EU Member States for which data are available, reliable or with low reliability (see Figure 11 for coverage), the gender gap in employment rates for non-EU citizens with a tertiary level of educational attainment living in cities was particularly pronounced in Czechia (29.8 percentage points), while gaps close to 30.0 percentage points were also recorded in Italy (28.4 points) and Sweden (27.1 points). Germany (9.9 points) was the only Member State where the employment gender gap for this subpopulation was less than 10.0 percentage points; slightly higher gaps were observed in Estonia (10.8 points) and Denmark (11.2 points).

Among the 20 EU Member States for which data are available, reliable or with low reliability (see Figure 11 for coverage), the gender gap in employment rates for citizens of other Member States with a tertiary level of educational attainment living in cities was particularly pronounced in Greece (44.4 percentage points; low reliability). In contrast, the gap was particularly small (0.3 points) in Malta, which was one of only two Member States (along with Hungary) where the rates for men and women were both over 90.0 %. Estonia stood out, as the only Member State where the employment rate for citizens of other Member States with a tertiary level of educational attainment living in cities was higher for women than for men, with a gap of 10.0 points (low reliability).

Figure 11: Employment rates for foreign citizens with a tertiary level of educational attainment living in cities, by sex, 2020
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_erednu)

Regional unemployment rates

The unemployment rate is defined as the number of unemployed persons as a share of the working-age labour force: in this article working age is defined as 20-64 years. In 2020, the EU unemployment rate for nationals was 6.3 %, which was 2.9 percentage points lower than the rate recorded for citizens from other EU Member States (9.2 %). By contrast, the EU unemployment rate for working-age people who were non-EU citizens was 16.7 % (some 10.4 percentage points higher than the average for nationals).

Maps 7-9 present regional unemployment rates for: nationals, citizens from other EU Member States and non-EU citizens (note that identical classes have been used for the shading in all three maps for easier comparison). Note also that the information presented in this section relates to NUTS level 1 regions (and hence is more geographically aggregated than the data presented above for activity and employment rates).

Maps 7 to 9: Unemployment rates by broad groups of citizenship and NUTS 1 regions, 2020
For full-size maps please see the Excel file attached.
Source: Eurostat (lfst_r_lfur2gan)

In 2020, the highest regional unemployment rates for nationals were in Spain, Greece, Italy, France and Belgium (see Map 7). In two Spanish regions the unemployment rate for nationals reached one fifth, with rates of 20.2 % recorded in Sur and 21.1 % recorded in the island region of Canarias. A total of 12 regions recorded rates of at least 10.0 % but less than 20.0 %, with these concentrated in Greece, Spain (four regions each) and Italy (two regions), with a single region each in Belgium (the capital region) and France (the Régions ultrapériphériques).

At the other end of the range, 31 regions had unemployment rates for working-age nationals that were below 4.0 %. Just over two fifths (13) of these were in Germany (2019 data for three regions; low reliability for four regions), while many of the others were in its neighbours, with six regions in Poland, four in the Netherlands, two in Austria and one region in each of Belgium and Czechia. The other regions with low unemployment rates for working-age nationals were in Hungary (two regions), Bulgaria (one region) and Malta. The lowest rate of all was 2.1 % in Bayern in southern Germany.

The highest regional unemployment rates for citizens of other Member States were recorded in Greece, Spain and Italy

Map 8 reveals that, across the EU the highest regional unemployment rates in 2020 for citizens of other EU Member States were often recorded in Greek, Spanish or Italian regions. The two highest rates of all were recorded in the Greek regions of Voreia Ellada and Kentriki Ellada, with rates of 35.5 % (low reliability) and 28.0 % (low reliability) respectively. Sur, Noreste and Canarias in Spain, Attiki and Nisia Aigaiou, Kriti (low reliability) in Greece, and Sud in Italy were the other regions where the unemployment rate for citizens of other EU Member States reached or surpassed 20.0 %. There were 13 regions where the rate was at least 10.0 % (but less than 20.0 %): the remaining four Spanish regions, four more Italian regions, three French regions (low reliability; 2017 or 2019 data), Slovenia (low reliability) and Ostösterreich in Austria.

Five regions recorded unemployment rates for citizens of other EU Member States of less than 4.0 %: Malta (low reliability), Hessen and Bayern in Germany (data for 2019), West-Nederland in the Netherlands, and Czechia (low reliability).

The highest regional unemployment rates for non-EU citizens were mainly recorded in France, Sweden, Spain and Greece

Regional unemployment rates for non-EU citizens are shown in Map 9. The highest unemployment rate for this part of the population was 39.7 %, recorded in the Régions ultrapériphériques in France. The next highest regional unemployment rates for non-EU citizens were 34.9 % in Södra Sverige (Sweden), 33.0 % in Centro (Spain), 32.0 % in Norra Sverige (Sweden), 31.2 % in Canarias (Spain) and 30.1 % in the Greek capital region, Attiki. Following on from these six regions were 20 with rates of at least 20.0 % but less than 30.0 %, comprising seven more French regions (including 2017 data for Bretagne and low reliability data for two regions), the other five Spanish regions, the other three Greek regions, two of the three Belgian regions, the remaining Swedish region, and one region each in Germany (data for 2019) and the Netherlands (low reliability data for 2019).

As for the unemployment rate for citizens of other EU Member States, Czechia had the lowest unemployment rate for non-EU citizens, its rate of 3.2 % (low reliability) being the only one below 4.0 % in 2020. Rates below 7.0 % (but of at least 4.0 %) were observed in four other regions: Bayern and Rheinland-Pfalz in Germany (2019 data), Poland (low reliability national data) and Slovenia (low reliability).

Figure 12 summarises the information concerning the highest and lowest regional unemployment rates in 2020 for citizens of other EU Member States and non-EU citizens.

Figure 12: Unemployment rates by citizenship for selected NUTS 1 regions, 2020
(% share of labour force aged 20-64 years)
Source: Eurostat (lfst_r_lfur2gan)

Unemployment rates by degree of urbanisation

Figure 13 is composed of three separate parts that provide information on unemployment rates for nationals, citizens of other EU Member States and non-EU citizens; each part presents an analysis by degree of urbanisation. In 2020, the lowest EU unemployment rates for citizens of other EU Member States and for nationals were recorded in rural areas, while for non-EU citizens the lowest rate was in towns and suburbs. The highest EU unemployment rate for non-EU citizens was in rural areas, slightly above that for cities. For citizens of other EU Member States and for nationals, there were higher unemployment rates for people living in cities than for people living in towns and suburbs. EU unemployment rates for all three degrees of urbanisation for nationals were lower than those for citizens of other Member States, which in turn were lower than those for non-EU citizens.

In 2020, Italy was the only EU Member State (among the 16 for which data are available, reliable or with low reliability) where the highest unemployment rates in cities was recorded for citizens of other EU Member States; in all other Member States, the highest unemployment rate in cities was recorded for non-EU citizens. Nationals reported the lowest unemployment rates in cities in 12 Member States, the exceptions being Cyprus, the Netherlands, Czechia (low reliability) and France where citizens of other EU Member States had the lowest unemployment rates.

A similar analysis for towns and suburbs reveals a similar situation, with Cyprus and Greece (low reliability) the only EU Member States (among the 14 for which data are available (including some with low reliability)) where citizens of other EU Member States had the highest unemployment rate; in all other Member States, the highest unemployment rate in towns and suburbs was recorded for non-EU citizens, with particularly high rates in Sweden (low reliability) and Spain. Nationals reported the lowest unemployment rates in towns and suburbs in all 14 Member States.

Data are available (including some with low reliability) for 11 EU Member States for unemployment rates in rural areas. In Slovenia (low reliability), the highest unemployment rate was recorded for citizens of other Member States, while in Italy the joint highest unemployment rates were observed for citizens of other Member States and for non-EU citizens. In the remaining nine Member States, the highest rate was for non-EU citizens. ln all 11 of the Member States for which data are available (including some with low reliability), the lowest unemployment rates in rural areas were observed among nationals.

Figure 13: Unemployment rates by citizenship and degree of urbanisation, 2020
(% share of labour force aged 20-64 years)
Source: Eurostat (lfst_r_lfur2ganu)

Data sources

The main data source for labour market statistics is the EU labour force survey (LFS). The LFS is a large quarterly sample survey that covers the resident population aged 15 years and above in private households. It covers the EU Member States, EFTA and candidate countries; note that regional analyses are not always available for non-EU Member States. The LFS is designed to provide population estimates for a set of main labour market characteristics, covering areas 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.

This article presents three key indicators:

  • the activity rate — defined as the proportion of active persons aged 20-64 years in relation to the total population aged 20-64 years; the economically active population, also referred to as the labour force, comprises employed and unemployed persons;
  • the employment rate — defined as the proportion of employed persons aged 20-64 years in relation to the total population aged 20-64 years; as such, while the denominator is the same as that used for the activity rate the numerator excludes unemployed persons;
  • the unemployment rate — defined as the proportion of unemployed persons aged 20-64 years in relation to the labour force aged 20-64 years; as such, the denominator is different from that used for the activity and employment rates in that it excludes economically inactive persons (such as retired persons, people exclusively in education as well as people who are not in the labour force for any other reason, for example caring for family members).

A set of Council, European Parliament and European Commission Regulations define how the LFS is carried out, while some countries have their own national legislation for the implementation of the survey. The key advantage of LFS data is that they come from a survey which is highly harmonised and optimised for comparability. However, there are some limitations when analysing the coverage of the LFS for various populations based on citizenship, as the survey was designed to target the whole resident population and not specific subgroups. 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 EU Member State, which results in under-coverage of the actual migrant population for LFS statistics;
  • non-response — one disadvantage of the LFS is the high proportion of non-response among migrants;
  • sample size — given that the LFS is a sample survey, it is possible that some of the results presented for labour market characteristics analysed by citizenship are unrepresentative or of low reliability, especially in EU Member States with small populations of foreign citizens; note that in cases where data are considered to be of particularly low reliability, statistics are not published.

Migrant indicators are calculated for two broad groups: the foreign population determined by place of birth and the foreign population determined by citizenship; this article presents information for the latter. It focuses on comparisons between national and foreign populations, with the latter subdivided into people who are citizens of another EU Member State and non-EU citizens. Note that while the analyses presented here are shown according to citizenship, regional labour market statistics are also available by place of birth (as published on Eurostat’s website).

In order to concentrate on people of core working-age, thereby minimising the effect of migration related to non-economic factors (for example, family reunification or retirement), the analyses focus on people aged 20-64 years.

The regional data for the activity and employment rates in the article refer to NUTS level 2 regions, but, due to the limitations of data availability, some maps or figures include NUTS level 1 (more aggregated geographical information) or national data. This approach serves to improve data coverage but has an impact on the analysis and statistical findings provided in the article. All these specific cases, where particular regions are presented using a different NUTS level in the same map or figure, are documented in footnotes.

It should also be noted that some EU Member States have a relatively small population and may therefore not be subdivided at some (or even all) of the different levels of the NUTS classification. For example, five of the Member States — Estonia, Cyprus, Latvia, Luxembourg and Malta — are each composed of a single NUTS level 2 region according to the 2016 version of the NUTS classification.

The article presents the latest results, namely for 2020. However, due to the limited availability of regional data for foreign citizens, the following approaches have been applied:

  1. when showing a single indicator in a map or figure, the gaps have been filled with the latest available data;
  2. when showing two indicators side by side or when calculating a difference between two indicators for an individual region (either in the text or in a figure/map), the latest common year for both indicators has generally been used;
  3. when showing two indicators side by side (in Figures 3 and 7) and data for an individual region are only available for a recent year for one of the two indicators, the most recent data are shown for the available indicator and the other footnoted as not available.

The use of data older than 2020 is documented in the footnotes.

Data collection for Germany during 2020 was impacted by technical issues and COVID-19 measures. The German data published for 2020 therefore show a low reliability in some regions. They are preliminary and may be revised in the future. For more information, see here.

For more information in relation to the collection of regional labour market statistics, please refer to this metadata file.

For more information in relation to methodological aspects of the LFS, please refer to this background methodological article.

Context

Successful integration of migrants into society in the host country is considered key to maximising the opportunities of legal migration and making the most of the contributions that immigration can make to EU development.

The continued development and integration of the European migration policy remains a key priority in order to meet the challenges and to harness the opportunities that migration represents globally. The integration of nationals of non-member countries legally living in the EU Member States has gained increasing importance in the European agenda in recent years.

There is a strong link between integration and migration policies since successful integration is necessary to maximise the economic and social benefits of immigration for individuals as well as societies. EU legislation provides a common legal framework regarding the conditions of entry and stay and a common set of rights for certain categories of migrants.

For more details pertaining to policy and legislative background information, please refer to this article.

Notes

  1. The regional statistics presented in the article for activity and employment rates refer to NUTS level 2 regions while the regional data shown for unemployment rates refer to NUTS level 1 regions. Due to the lack of publishable detailed regional statistics for some EU Member States, more aggregated geographical information have been included in some maps and figures, for example NUTS level 1 data (for maps and figures generally showing NUTS level 2 data) or national data (NUTS level 0). This approach serves to improve data coverage but has an impact on the analysis and statistical findings provided in the article. All of the cases where particular regions are presented using a level of NUTS that is different from the standard one are documented in the footnotes for each map or figure. It should also be noted that some EU Member States have a relatively small population and may therefore not be subdivided at some (or even all) of the different levels of the NUTS classification. For example, five of the Member States — Estonia, Cyprus, Latvia, Luxembourg and Malta — are each composed of a single NUTS level 2 region according to the 2016 version of the NUTS classification. The article presents the latest results, namely for 2020. However, due to the limited availability of regional data for foreign citizens, the following approaches have been applied when 2020 data are not complete:
    1. when showing a single indicator in a map or figure, the gaps have been filled with the most recent available data (for example, for 2019 or 2018);
    2. when showing two indicators side by side or when calculating a difference between two indicators for an individual region (either in the text or in a figure/map), the most recent common year for both indicators has generally been used;
    3. when showing two indicators side by side (in Figures 3 and 7) and data for an individual region are only available for a recent year for one of the two indicators, the most recent data are shown for the available indicator and the other is footnoted as not available.
    The use of data older than 2020 is documented in the footnotes.
  2. These indicators are based on: a set of Council conclusions from 2010 on migrant integration (the list of Zaragoza indicators that were agreed by EU Member States in Zaragoza (Spain) during April 2010); a subsequent study Indicators of immigrant integration — a pilot study from 2011; a report Using EU indicators of immigrant integration from 2013 and more recent data collection exercises.
Direct access to
Other articles
Tables
Database
Dedicated section
Publications
Methodology
Legislation
Visualisations
External links




Employment - regional series (mii_emp_r)
Activity rates (mii_act_r)
Unemployment (mii_une_r)
Employment and self-employment (mii_em_r)
LFS series - specific topics (lfst)
LFS regional series (lfst_r)
Regional population and economically active population - LFS annual series (lfst_r_lfpop)
Regional employment - LFS annual series (lfst_r_lfemp)
Regional unemployment - LFS annual series (lfst_r_lfu)
Regional labour market statistics by degree of urbanisation (lfst_r_lfurb)
LFS ad-hoc modules (lfso)
2014. Migration and labour market (lfso_14)
2008. Labour market situation of migrants (lfso_08)