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24.6.2019 | Von:
Parvati Raghuram
Gunjan Sondhi

Skilled Female Migrants in the EU

The share of women among tertiary level educated migrants in the EU is higher than that of men. However, many of these highly skilled women do not work in jobs that match their qualifications. A look at trends of skilled female migration in Europe.

Eine Wissenschaftlerin betrachtet eine ProbeFemale Scientist examines a sample. The share of women among tertiary level educated migrants in the EU is higher than that of men. (© picture-alliance, imageBROKER)

Between 2012 and 2017, the number of highly skilled persons immigrating to the 28 EU states grew by a third – from 204,403 to 321,597. [1] Tertiary-level educated women – referred to here as highly skilled migrant women – enter the host country through a variety of channels, as workers, family migrants, students and refugees. Since 2009, a number of changes have influenced the direction and nature of female skilled migration. This article explores what we know about skilled migrant women and their flows both into and within Europe in the last decade, a period which has seen the effects of recession and austerity in many countries, as well as new movements, particularly of refugees, which included skilled women.

Data Sources

Skills are variously defined in existing data: as qualification, according to sector of the labour market in which migrants are employed, wages and based on the route of entry, i.e. the migration category. Furthermore, "migrant" is also a variable category with some countries collecting ethnicity data but not on migration status, while others focus on country of qualification rather than that of birth or nationality.

Moreover, data is not always collected and published in a comparable manner. A decade earlier Kofman and Raghuram (2009) pointed to the dearth of gender disaggregated skilled migration data in most data collection systems. In the intervening years, there have been some attempts to collate such data on migrant stocks across different sources. In particular the Global Bilateral Migration Database and the Database on Immigrants in OECD countries have the potential to make significant contributions to our understanding of skilled female migration, but these have not yet been fully exploited. [2] These databases report the stock of migrants by education from each sending country to each country of destination. Highly skilled workers are defined as those with at least one year of tertiary level education. However, these databases are based on individual country statistics which are variable in quality, completeness, gender disaggregation and base year for which data is reported.

A second data source provides insights on migrant flows. Compiled from migrant entry data, this data set is more reliable, country specific, and current. Another source is the labour force surveys that are more or less routinely conducted within different countries. They may have bias because these are surveys of a sample and only of those who are in employment. These too may be collated such as in the European Labour Force Survey to provide some information on migration patterns.

While this data is useful, they provide an insufficient picture of gendered highly skilled migration as data is rarely collected, published or analysed by gender. Second, the data that is available, such as the OECD data, are limited in scope in what it can tell about this population. Because of their breadth and coverage, they do not offer the demographic details which can help us to understand this group. Despite these reservations it is possible to identify some broad patterns in female skilled migration in the EU.

Migrant Stock in the European Union

Within the 28 EU member states, 52 per cent of the foreign-born, first-generation, migrant population who are tertiary level educated, are women. A breakdown by countries shows that across the EU member states, nearly two-thirds of the countries have as many or more foreign-born women who are highly skilled than men. However, these qualifications often do not translate into skilled work, either due to poor participation rate or deskilling.

Figure 1: Gender composition of stock of first generation migrants with tertiary level educationFigure 1: Gender composition of stock of first generation migrants with tertiary level education in the EU-28, 2014 (bpb) Lizenz: cc by-nc-nd/3.0/de/

Even though there are more migrant women than migrant men in the stock population who are highly educated, this female bias is not reflected in the labour force participation rate, i.e. activity and employment rates. [3] The activity rates for migrant women are lower than those for men across all EU member states. This gap between activity rates is particularly high amongst migrants born outside the EU – 83 per cent for men and 63 per cent for women. However, this data is not disaggregated by education or any indicator that would identify the skill level of the migrant. The employment rate data give us a little more insight into highly educated women migrants. These figures show the gender gap in the employment rate by education level, as well as country of birth. While overall the employment rate is higher for tertiary level educated migrant women (66 per cent) as compared to migrant women with lower levels of education (40 per cent for primary educated, and 58 per cent for secondary educated), in comparison to migrant men’s employment rate, there is a large gap. More migrant men (82 per cent) with tertiary level education are employed than women (66 per cent).

This could be due to labour market problems or due to family pressures. First, across Europe, migrant women continue to dominate the socially reproductive sectors of the labour market: teaching, nursing, social care and domestic work. [4] Migrant women with skills in the former two often find jobs in the latter two, which are less regulated and where their skills are used but not valued or remunerated. Some of this work may be done informally. Thus, even if in work, they may not appear in formal employment statistics or if they do, they appear as less skilled. Moreover, their skills may end up being discounted because, for instance, in Germany, nursing and midwifery are not considered as skilled professions due to their local apprenticeship structures. This leads to devaluing of skills of migrant women who are tertiary level educated trained and experienced nurses. Secondly, migrant women are often removed from family support, especially with childcare, which enables them to enter the labour market so that the unequal division of socially reproductive labour within the family affects their labour market participation. The nature of deskilling however varies with ethnicity, language ability, level and type of qualification and the masculinity of the sector itself. Thus, even in vibrant economies such as Germany, women may find it difficult to be accepted into some sectors with labour market shortages because of a combination of these factors. [5]

Migrant Flows

Highly skilled migrants from outside the EU are usually required to obtain a visa/permit to enter an EU member state. These first permits – granted for a minimum of three months – show the annual flow of migrants entering the EU countries for work, education, family and other reasons. [6]

There was a steady increase from 2010 to 2015 followed by a sharp rise in 2016 as entries increased across all the above four categories of migration.

Figure 2: First permits issued to immigrants in EU-28, 2010-2016Figure 2: First permits issued to immigrants in EU-28, 2010-2016 Lizenz: cc by-nc-nd/3.0/de/ (bpb)

Women constitute approximately 46 per cent of migrant flows. Figure 3 provides a breakdown of the reasons for migration by gender.

Figure 3: First permits issued by EU-28 member states by reason for migrationFigure 3: First permits issued by EU-28 member states by reason for migration Lizenz: cc by-nc-nd/3.0/de/ (bpb)

Labour Migration

Between 2010 and 2016, there has been a decline in the number of first permits granted to women migrants for work. Figure 3 suggests that this might be due to the masculinisation of labour migration flows into the EU. However, this data is not skills sensitive. One approach to try and understand this is to draw on gender differentiated skilled labour market sector data from professional bodies such as nursing and engineering associations to identify the issues facing migrant women in EU member countries. Another is to look at more general schemes such as the EU Blue Card scheme and we do both below.


Calculations based on first permits issued for education, and EU Blue card permits issued.
Ghosh and Chanda (2015), Kerr et al. (2016).
Eurostat (2018).
Kofman and Raghuram (2015).
Grigoleit-Richter (2017).
Other reasons include: international protection, residence without the right to work (for example, pensioners), or people in the intermediate stages of a regularisation process.
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