Migrant integration statistics - regional labour market indicators


Data from June 2020.

Planned article update: June 2021.

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 2019.

Across the EU, the highest regional employment rate in 2019 for citizens of other EU Member States was 92.7 % in Flevoland (the Netherlands).

In 2019, in all EU Member States except for Greece 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.

Activity rates by broad groups of citizenship and NUTS 2 regions, 2019
Source: Eurostat (lfst_r_lfp2actrtn)

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 age group has been selected because it is relevant to one of the targets included within the Europe 2020 strategy, namely, that the EU employment rate for persons aged 20-64 should be at least 75 % by 2020. This article forms part of an online Eurostat publication — Migrant integration statistics.

Full article

Regional activity rates

Labour market participation may 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-27 varied according to citizenship (as illustrated in Maps 1-3); note that identical classes have been used for the shading in all three maps so they may be more easily compared. In 2019, the EU-27 activity rate for nationals was 78.6 %, while the rate for citizens of other EU Member States was higher (82.0 %) and that for non-EU citizens was considerably lower (70.2 %).

Maps 1 to 3: Activity rates by broad groups of citizenship and NUTS 2 regions, 2019
For full-size maps please see the Excel file attached.
Source: Eurostat (lfst_r_lfp2actrtn)

In 2019, 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 90.4 % and was recorded in Stockholm, the Swedish capital region. Two other Swedish regions, Småland med öarna and Västsverige, recorded the second and third highest rates, at 90.0 % and 89.4 % respectively. A total of 28 other NUTS level 2 regions recorded activity rates for nationals that were at least 85.0 %, including 18 regions from Germany, all of the other regions from Sweden, two from Finland and one each from Lithuania, the Netherlands and Denmark. There were four regions with activity rates for nationals below 60.0 %. Each of these was in southern Italy, including the lowest rate of 55.1 % for the island region of Sicilia. Among the 10 next lowest rates (at least 60.0 % but below 70.0 %), were three more Italian regions, three Romanian regions, two Belgian regions (including the capital region), one French and one Croatian region. The difference between the highest and lowest regional activity rates for nationals (recorded in Stockholm and Sicilia respectively) was 35.3 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 2019, the highest regional activity rate for this part of the population was 96.5 % recorded in Övre Norrland (Sweden). Shares of 90.0 % or more were also recorded in nine other regions: a second Swedish region, two Czech regions and one region each from Germany, Spain, France (2018 data, low reliability), Malta, the Netherlands and Portugal. By contrast, activity rates for citizens of other Member States were less than 60.0 % in two Italian regions (including Basilicata, which had the lowest rate (56.6 %)), one Greek NUTS level 1 region and one French region. The difference between the highest and lowest regional activity rates for citizens from other Member States (recorded in Övre Norrland and Basilicata respectively) was 39.9 percentage points.

In 2019, foreign citizens aged 20-64 years from other EU Member States were more likely to be part of the EU-27 labour force (82.0 %) than nationals of the same age (78.6 %). A more detailed analysis reveals that this pattern was repeated in 105 of the 181 regions (58.0 %) for which data are available (reliable or with limited 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 (13.4 percentage points), Croatia (13.0 percentage points; national data, low reliability) and the Spanish Región de Murcia (12.1 percentage points) — see Figure 1.

Among the 73 regions (40.3 % of all regions for which data are available, reliable or with limited reliability) where nationals recorded higher activity rates in 2019 than citizens from other EU Member States, the largest difference — in percentage point terms — was recorded in the Dutch region of Friesland (2018 data, low reliability), where the activity rate for nationals was 17.6 percentage points higher than that recorded for citizens from other EU Member States. In the Greek NUTS level 1 region of Voreia Ellada, the gap was 16.0 percentage points and in the French region of Nord-Pas-de-Calais it was 14.4 percentage points. There were three regions —Koblenz and Sachsen-Anhalt in Germany as well as the Finnish capital region (Helsinki-Uusimaa) — 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, 2019
(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 this time for non-EU citizens. The highest activity rate for this part of the population was recorded in Slaskie in Poland, where 95.0 % (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 90.0 %) were recorded in the Lithuanian capital region (Sostines regionas) and the Czech regions Severozápad and Jihovýchod. At the other end of the range, the six lowest regional activity rates for non-EU citizens — all below 45.0 % — were recorded in Prov. Liège and Prov. Hainaut in Belgium, the French overseas regions of La Réunion (low reliability) and Guyane, the Spanish Ciudad Autónoma de Ceuta (low reliability) and Drenthe in the Netherlands (low reliability). The Prov. Liège had the lowest rate in the EU (36.4 %). As such, the difference between the highest and lowest regional activity rates for non-EU citizens (recorded in Slaskie and Prov. Liège respectively) was 58.6 percentage points, larger than the range for either nationals or citizens of other EU Member States.

Overall, non-EU citizens (70.2 %) were less likely to form part of the EU-27 labour force than nationals (78.6 %). In 2019, a higher activity rate for non-EU citizens than for nationals was reported by 40 of the 205 EU regions for which data are available (reliable or with limited reliability), in other words around one fifth (19.5 %) of the total number. Among these 40 regions, the largest differences between activity rates for these two parts of the population — in percentage point terms — were recorded in the Polish region of Slaskie (23.0 percentage points, low reliability) and the Italian region of Campania (16.7 percentage points), while double-digit gaps were also observed in: Sicilia and Sardegna in the island regions of Italy; the Greek region of Dytiki Ellada; Malopolskie (low reliability) and the NUTS level 1 regions of Makroregion Poludniowo-Zachodni and Makroregion Pólnocno-Zachodni in Poland (low reliability), and in the Czech region of Severozápad (low reliability) — see Figure 2. At the other end of the range, there were six 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 Dutch regions, namely Drenthe (which had the largest gap at 40.0 percentage points, low reliability) and Friesland (which had the second largest gap at 35.2 percentage points, low reliability). In addition, there was one region each from Belgium, Spain, France and Germany.

Figure 2: Largest gaps in regional activity rates for nationals and citizens from outside the EU, by NUTS 2 regions, 2019
(percentage points difference; based on population aged 20-64 years)
Source: Eurostat (lfst_r_lfp2actrtn)

Figure 3 confirms that, in 2019, regional activity rates for non-EU citizens were generally more dispersed than regional activity rates for citizens of other EU Member States. It also shows that regional activity rates for citizens of other Member States were generally higher than regional activity rates for non-EU citizens; at an aggregated level this pattern could be observed for national data in all of the Member States except for Greece, Lithuania and Poland. A third pattern that is apparent when analysing the information presented in Figure 3 is that activity rates for capital regions were usually higher than the national averages. This was generally the case for both foreign groups of the population and was repeated in all of the Member States for which data are available (reliable or with limited reliability) with the exceptions of: the Austrian and Polish capital regions, where both the activity rates for non-EU citizens and for citizens of other EU Member States were lower than their respective national averages; the Italian and Slovenian 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. In Sweden, the activity rate observed for citizens of other Member States in the capital region was the same as the national average.

Figure 3: Regional disparities in activity rates, by citizenship and NUTS 2 regions, 2019
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_lfp2actrtn)

The information presented in Figure 4 also confirms the differences in 2019 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, Germany, Ireland, Austria, Slovenia and Finland where the lowermost regional activity rate for citizens of other EU Member States was at a higher level than the uppermost regional activity rate for non-EU citizens; among the non-member countries shown in Figure 4 this situation was also observed for Swiss regions. In Sweden, this situation nearly occurred as these regional activity rates (the lowest for citizens of other EU Member States and the highest for non-EU citizens) were the same. By contrast, Greece was the only EU Member States to report that its uppermost regional activity rate for non-EU citizens was higher than the uppermost regional activity rate for citizens of other EU Member States, while among the non-member countries the equivalent rates in the United Kingdom were the same.

Figure 4: Highest and lowest regional activity rates, by citizenship and NUTS 2 regions, 2019
(% 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 2019, EU-27 activity rates for people aged 20-64 were somewhat higher in cities than they were in towns and suburbs or rural areas. This pattern was almost repeated for all three parts of the population shown in Figure 5 although the activity rate for people living in cities was the same as for towns and suburbs among citizens of other EU Member States. Activity rates for citizens of other EU Member States peaked at 82.2 % in cities as well as in towns and suburbs, while the highest activity rates for nationals (79.3 %) and for non-EU citizens (71.0 %) were recorded for those subpopulations living in the most-densely populated areas, in other words in cities.

The three separate charts that make-up Figure 5 confirm some of the results already presented at a regional level, insofar 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 far from being 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 differences were observed in Croatia (2018 data) and Slovenia where a rate of 100.0 % was recorded in cities compared with 68.7 % for rural areas in Croatia and 81.3 % for rural areas in Slovenia (all data with 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:

  • Lithuania, where the highest rate was observed in rural areas (low reliability);
  • Croatia (2018 data, low reliability), Malta, Denmark and Poland, where the highest rates were observed in cities;
  • Belgium, where the highest rate was observed in towns and suburbs.

In cities, the lowest activity rates tended to be recorded among non-EU citizens

In 2019, there were 14 EU Member States (among those for which data are available, reliable or with limited reliability, for all three subpopulations) where the highest activity rates in cities were recorded for citizens of other EU Member States. Six Member States — Germany, Estonia, France, Latvia (2016 data for citizens of other Member States), the Netherlands and Austria — reported that nationals had the highest activity rates. The remaining four — Greece, Lithuania, Malta and Poland — recorded their highest rates for people living in cities among non-EU citizens. Furthermore, in Czechia, Spain, Croatia (2018 data for citizens of other EU Member States and for non-EU citizens), Italy, Malta, Poland and Portugal, 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 15 EU Member States (out of 20 for which data are available, reliable or with limited reliability) where citizens of other Member States recorded the highest activity rates, while there were four Member States where nationals recorded the highest activity rates: Belgium, Hungary, the Netherlands 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, Italy, Malta and Portugal, 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 12 Member States (among those for which data were available, reliable or with limited reliability), while there were five Member States where the highest activity rates were observed for nationals: France, Hungary (2018 data for non-EU citizens), the Netherlands, Finland and Sweden. Among non-EU citizens living in rural areas of Greece, Croatia (2018 data for citizens of other EU Member States and for non-EU citizens), and Portugal, 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, 2019
(% 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 2019, the EU-27 employment rate for nationals was 73.8 %, which was 1.7 percentage points lower than the rate recorded for citizens from other EU Member States. By contrast, the EU-27 employment rate for working-age people who were non-EU citizens was 59.8 % (some 14.0 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 so they may be more easily compared).

Maps 4 to 6: Employment rates by broad groups of citizenship and NUTS 2 regions, 2019
For full-size maps please see the Excel file attached.
Source: Eurostat (lfst_r_lfe2emprtn)

In 2019, the highest regional employment rates for nationals were in Sweden, Germany and Finland (see Map 4). As was the case for the activity rate, the highest regional employment rates for nationals were recorded in the Swedish regions of Småland med öarna (87.4 %) and Stockholm (86.4 %). In the list of eight regions with employment rates that were at least 85.0 %, these two were joined by four regions in southern Germany (Oberbayern, Stuttgart, Tübingen and Freiburg), a Finnish region (Åland) and another Swedish region (Västsverige).

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, Campania and Sicilia — among which three recorded rates that were less than 50.0 %. In other words, in Calabria, Campania and Sicilia it was more common for working-age adults not to have a job than it was for them 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 from other 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 often recorded in Czechia or Germany ...

Map 5 reveals that, in 2019, across the EU the highest regional employment rates for citizens of other EU Member States were often recorded in Czech or German regions, although the highest rate of all was recorded in the Dutch region, Flevoland (92.7 %). There were 13 more regions where the rate was more than 85.0 %, among which four each in Czechia and Germany and one each in Sweden, France (2018 data, low reliability), Malta, Austria and Portugal. Five regions recorded employment rates for citizens of other EU Member States that were below 50.0 % and again these were in southern Member States: three of these regions were in Italy (Puglia, Molise (low reliability) and Calabria) and two were in Greece (Voreia Ellada (low reliability) and Attiki, NUTS level 1 regions).

... while for non-EU citizens 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 Slaskie (Poland), where 91.6 % (low reliability) 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 Severozápad, Jihovýchod, Jihozápad (all in Czechia), Sostines regionas (the capital region of Lithuania) and Malopolskie (also in Poland, low reliability data). A further 14 regions reported rates of at least 75.0 % but less than 85.0 %, including four more regions from each of Czechia and Poland, two regions from Portugal and single regions from each of Malta (one region at this level of detail), Romania (national data; 2018 data), the Netherlands and Slovenia. In 46 of the regions, less than half of non-EU citizens were in employment. Among these, there were 17 regions where the employment rate was below 40.0 % and four — the French overseas regions of La Réunion (low reliability), Guyane and Mayotte as well as the Belgian region of Prov. Liège — where the rate was below 30.0 %.

Figure 6 summarises the information concerning the highest and lowest regional employment rates in 2019 for citizens of other EU Member States and non-EU citizens.

Figure 6: Employment rates by citizenship for selected NUTS 2 regions, 2019
(% 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 2019, it was usually 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 and Poland, where national employment rates were higher than in the respective capital region for non-EU citizens; Germany, Italy and Slovenia, where the national employment rate was higher than in the capital region for citizens of other Member States; Austria and Greece, 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, 2019
(% 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 2019, such inter-regional differences for non-EU citizens were particularly pronounced in the Netherlands, as their employment rates ranged from a high of 76.5 % in Flevoland, down to a low of 36.3 % (low reliability) in Drenthe, a gap of 40.2 percentage points; for citizens of other Member States the gap was 29.2 points. France, Belgium, Spain and Germany 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 the Netherlands, for citizens of other EU Member States the largest gap was observed in Italy (37.3 percentage points), between 42.6 % in Puglia and 79.9 % in the Provincia Autonoma di Bolzano/Bozen. The inter-regional gap in Italy for non-EU citizens was 22.8 percentage points, therefore lower than for citizens of other EU Member States, a situation that was also observed in Greece, Portugal, France and Austria among the Member States as well as in the United Kingdom.

Figure 8: Highest and lowest regional employment rates, by citizenship and NUTS 2 regions, 2019
(% 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 2019, the highest EU-27 employment rates for non-EU citizens was recorded in cities (60.5 %), while for citizens of other EU Member States the highest rate was for towns and suburbs (76.1 %). For nationals there was almost no difference between the rates observed in cities, towns and suburbs and rural areas (73.9 %, 73.7 %, 73.7 % respectively).

In 2019, there were 17 EU Member States (among the 24 for which data are available, reliable or with limited reliability) where the highest employment rates in cities were recorded for citizens of other EU Member States, while six Member States — Germany, Greece, France, Hungary, the Netherlands and Austria — reported that nationals had the highest employment rates. Lithuania was the exception, recording its highest employment rate for people living in cities among non-EU citizens.

A similar analysis for towns and suburbs reveals that there were 12 EU Member States where citizens of other EU Member States recorded the highest employment rates, while there were six 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 Greece and Hungary, the highest employment rates for people aged 20-64 years living in towns and suburbs were recorded by non-EU citizens.

In rural areas, the highest employment rates in eight EU Member States (among those for which data are available, reliable or with limited reliability) were recorded for citizens of other Member States, while there were also eight Member States where nationals recorded the highest employment rates. In Croatia (2018 data for non-EU citizens) and Portugal, the highest employment rates for people aged 20-64 years living in rural areas were recorded by non-EU citizens. In Austria, the employment rate among people living in rural areas in 2019 was joint highest for nationals and for citizens of other Member States.

Figure 9: Employment rates by citizenship and degree of urbanisation, 2019
(% 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 and who had a tertiary level of educational attainment.

In 2019, 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 2019, EU-27 employment rates for people living in cities and who had a tertiary level of educational attainment were notably higher among nationals (85.8 %) and citizens from other EU Member States (82.5 %) than they were for non-EU citizens (68.3 %). Figure 10 reveals that, subject to data availability, in all EU Member States except for Greece the employment rates for people with a tertiary level of educational attainment living in cities were lower among non-EU citizens than among nationals or citizens of other EU Member States. In Greece, the rate for non-EU citizens was slightly higher than that for citizens of other EU Member States.

In 2019, in a small majority of EU Members States the highest employment rates among people of working-age with a tertiary level of educational attainment living in cities were recorded for nationals, although in Croatia, Luxembourg, Malta, Ireland, Hungary, Slovenia, Estonia and Sweden 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, 2019
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_erednu)

An additional analysis by sex (see Figure 11) reveals that three fifths (59.8 %) of all working-age women in the EU-27 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 over three quarters (77.8 %). 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 87.2 %, some 9.0 percentage points higher than the corresponding figure for women (78.2 %). 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 88.4 %, some 5.0 percentage points higher than the corresponding rate for female nationals (83.4 %).

Among the 22 EU Member States for which data are available, reliable or with limited 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 (33.5 percentage points), while gaps close to 30.0 percentage points were also recorded in Slovenia and Cyprus. Lithuania and Latvia were the only Member States where the employment gender gap for this group of people was less than 10.0 percentage points, being as low as 3.2 percentage points in the former and 0.7 percentage points in the latter.

Figure 11: Employment rates for foreign citizens with a tertiary level of educational attainment living in cities, by sex, 2019
(% share of population aged 20-64 years)
Source: Eurostat (lfst_r_erednu)

Regional unemployment rates

The unemployment rate is defined as the share of the working-age labour force who are in unemployment: in this article working age is defined as 20-64 years. In 2019, the EU-27 unemployment rate for nationals was 6.1 %, which was 1.8 percentage points lower than the rate recorded for citizens from other EU Member States. By contrast, the EU-27 unemployment rate for working-age people who were non-EU citizens was 14.7 % (some 8.6 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 so they may be more easily compared). Note also that the information presented in this section relates to NUTS level 1 regions (and is hence 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, 2019
For full-size maps please see the Excel file attached.
Source: Eurostat (lfst_r_lfur2gan)

In 2019, the highest regional unemployment rates for nationals were in Spain, Greece, Italy, France and Belgium (see Map 7). In one region the unemployment rate for nationals reached one fifth, with a rate of 20.1 % recorded in the Spanish 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, nine regions had unemployment rates for working-age nationals that were below 2.5 %. Just over half of these were in Germany while the remainder were in its neighbours, with one region in each of Czechia, Hungary, the Netherlands and Austria. The lowest rate of all was 1.6 % in Bayern in southern Germany.

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

Map 8 reveals that, in 2019, across the EU the highest regional unemployment rates for citizens of other EU Member States were often recorded in Greek, Spanish, Italian or French regions. The three highest rates of all were recorded in the Greek regions of Voreia Ellada, Attiki and Kentriki Ellada, with rates of 37.3 % (low reliability), 29.9 % and 22.6 % (low reliability) respectively. Noreste in Spain (21.0 %) was the only other region where the unemployment rate for citizens of other EU Member States reached or surpassed 20.0 %. There were 16 more regions where the rate was at least 10.0 % (but less than 20.0 %), among which the remaining six Spanish regions, five Italian regions, four French regions (including 2017 data for Bretagne and Normandie as well as 2016 data for Corse) and the remaining Greek region.

Czechia (one region at this level of detail) was the only region with an unemployment rate for citizens of other EU Member States (2.2 %, low reliability) that was below 2.5 % in 2019. A total of 11 regions recorded rates of at least 2.5 % but less than 5.0 % and these were concentrated in Germany (five regions) and the Netherlands (two regions), with one region each in Ireland (one region at this level of detail), Austria, Sweden and Malta (also one region at this level of detail).

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

Regional unemployment rates for non-EU citizens are shown in Map 9. The highest unemployment rate for this part of the population was 44.2 %, recorded in the Régions ultrapériphériques in France. The next highest regional unemployment rate for non-EU citizens was 32.4 % in Norra Sverige (Sweden). Following on from these two regions were 23 more with rates of at least 20.0 % but less than 30.0 %, comprising eight more French regions (including 2017 data for Bretagne), six of the seven Spanish regions, three of the four Greek regions, the other two Swedish regions, two of the three Belgian regions, and one region each in Germany and the Netherlands.

As for the unemployment rate for citizens of other EU Member States, Czechia (one region at this level of detail) had the lowest unemployment rate for non-EU citizens, its rate of 2.6 % (low reliability) being the only one below 5.0 % in 2019. Rates below 10.0 % (but of at least 5.0 %) were observed in 16 other regions, including five German regions, two Dutch regions and one Austrian region, as well as Poland (national data) and Malta, Ireland, Slovenia, Estonia, Latvia and Denmark (each of which is one region at this level of detail).

Figure 12 summarises the information concerning the highest and lowest regional unemployment rates in 2019 for citizens of other EU Member States and non-EU citizens.

Figure 12: Unemployment rates by citizenship for selected NUTS 1 regions, 2019
(% 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 2019, the lowest EU-27 unemployment rates for non-EU citizens and for citizens of other EU Member States were recorded in towns and suburbs. The highest EU-27 unemployment rate for non-EU citizens was in rural areas slightly above that for cities, while for citizens of other EU Member States the situation was reversed, with a slightly higher rate for people living in cities than for people living in rural areas. For nationals, the EU-27 rates were more clearly separated, with the lowest unemployment rate for people living in rural areas and the highest rate for people living in cities. EU-27 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 2019, Cyprus was the only EU Member States (among the 16 for which data are available, reliable or with limited reliability) where the highest unemployment rates in cities were recorded for nationals. In Italy, Greece and Ireland, citizens of other EU Member States reported the highest unemployment rates in cities, while in the remaining 12 Member States the highest unemployment rates were for non-EU citizens.

A similar analysis for towns and suburbs reveals a similar situation, with Cyprus the only one among the 13 EU Member States for which data are available (reliable or with limited reliability) where nationals had the highest unemployment rate. Denmark (2018 data for citizens of other EU Member States) and Greece reported that citizens of other EU Member States had the highest unemployment rates in towns and suburbs, while elsewhere the highest unemployment rates for people living in towns and suburbs were recorded among non-EU citizens, with a particularly high rate observed in Sweden for this subpopulation.

Data are available (reliable or with limited reliability) for 11 EU Member States for unemployment rates in rural areas. In Greece and Cyprus (2018 data for citizens of other EU Member States and 2016 data for non-EU citizens), the highest unemployment rate was recorded for citizens of other Member States, while in the remaining nine the highest rate was for non-EU citizens. ln all 11 of the Member States for which data are available (reliable or with limited reliability), the lowest unemployment rates in rural areas were observed among nationals.

Figure 13: Unemployment rates by citizenship and degree of urbanisation, 2019
(% 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, the United Kingdom, 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 considering 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. This is also the age group used for one of the Europe 2020 targets, namely, that the employment rate for persons aged 20-64 years in the EU should be at least 75 %.

Most of the regional statistics presented 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. Where little regional data exist for a particular EU Member State, national data have been used to provide a more complete coverage; these exceptions are also documented in the 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 2019. However, due to the limited availability of regional data for foreign citizens, the following approaches have been applied:

  • when showing a single indicator in a map or figure, the gaps have been filled with the latest available data;
  • 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 been used.

The use of data older than 2019 is documented in the footnotes.

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 the 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 2019. However, due to the limited availability of regional data for foreign citizens, the following approaches have been applied:
    • when showing a single indicator in a map or figure, the gaps have been filled with the latest available data;
    • 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 been used.
    The use of data older than 2019 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.
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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)