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24.6.2019 | Von:
Parvati Raghuram
Gunjan Sondhi

Skilled Female Migrants in the EU

Sectoral: Female Dominated Labour Market Sectors

The Nursing and Midwifery Council (NMC) data on the UK highlights the changing nature of the relations between the UK, the EU and other overseas countries. In 2016, 85 per cent of all registered (male and female) nurses and midwives working in the UK were first registered as nurses or midwives (post-qualification) in the UK, ten per cent overseas, and five per cent in other EU member states. [7] Importantly, in some sectors such as health, data is collected and analysed according to country of qualification which is often used as proxy for country of birth or migration status.

Figure 4: Total initial registrations of nurses in the UK by sex, 2005-2016Figure 4: Total initial registrations of nurses in the UK by sex, 2005-2016 Lizenz: cc by-nc-nd/3.0/de/ (bpb)

Women from the Philippines, India and Australia – all English-speaking countries due to their US and UK colonial histories – make up the three largest sources of overseas trained nurses in the UK, as figure 5 shows.

Figure 5: Female nurses registered in UK, with initial registrations overseas, 2005-2016Figure 5: Female nurses registered in UK, with initial registrations overseas, 2005-2016 Lizenz: cc by-nc-nd/3.0/de/ (bpb)

The five per cent of the nurses who were initially registered in other EU states, make up the smallest group. The breakdown by the top five EU countries is shown in figure 6. Italian trained nurses are a relatively new addition to the register. However, Spain and Romania have been consistent sources of trained nurses currently registered in the UK.

Figure 6: Female nurses registered in UK, with initial registration within EU countries, 2005-2016Figure 6: Female nurses registered in UK, with initial registration within EU countries, 2005-2016 Lizenz: cc by-nc-nd/3.0/de/ (bpb)

Significantly, the introduction of the Code of Ethics, i.e. cap on recruitment of skilled migrants (brain drain migration) from overseas countries with small nursing workforce, the opening of the UK labour market to EEA applicants (A8 countries in 2004 and A2 countries in 2012), and the effects of recession, particularly in Southern European countries like Italy and Spain, have led to sharp increases in EU qualified migrants with a concomitant significant decline in the numbers of overseas qualified nurses (Figure 5). Thus from 2011 onwards there was a significant jump in nurses from Spain, Romania and Italy; only to then take a sudden drop since 2015. However, in July 2016 the NMC introduced language checks for EEA nurses which led to a rapid increase followed by a sharp drop in numbers. The reasons for this sharp increase are not clear but may be due to the registration of those who met the qualification criteria. The subsequent drop in EU qualified nurses has been further exacerbated by the Brexit vote which has led to a 96 per cent drop in EU applicants in less than a year after the Brexit vote. [8] In light of Brexit, it will be important to monitor how these patterns of EU origin countries shift, and how that impacts the mobility of highly skilled women from EU countries.

The overseas nurse market has acted as a reserve army of labour, declining and growing inversely to the EEA intakes. Thus, after low levels of registration for overseas trained nurses between 2008-2013, there appears to be growth, particularly sharply since 2015.

General Programs for Skilled Migration: EU Blue Card

Beyond the UK, EU policies have aimed to encourage intra-European mobility and attract highly skilled migration from non-EU countries. One such policy is the EU Blue Card, which, although adopted by 25 of the 28 countries, has primarily been deployed by Germany (see Table below). In 2016, nearly 50 per cent of the EU Blue Card holders in Germany came from just five countries: India (22.1 per cent), China (8.7 per cent), the Russian Federation (7.9 per cent), Ukraine (5.3 per cent) and Syria (4.7 per cent). [9]

EU Blue Cards granted

20122013201420152016
Germany2.58411.58012.10814.62017.360
France126371604657750
Luxembourg183236262336636
Poland21646369673
Other7697618491.1221.290
Total EU3.66412.96413.86917.10420.979

Source: Eurostat: EU Blue Cards by type of decision, occupation and citizenship (migr_resbc1), (accessed: 12-12-2018).

Concerns have been raised about the potential gender selectivity of the policy with salary thresholds, years of professional experience and an inflection towards male dominated sectors of the labour market influencing how many women receive these cards. [10] Systematic gender pay gaps between women and men in the same sector but also the preponderance of women in lower paying sectors, caring responsibilities and hence, career breaks and the gender selectivity of the sectors all shape the outcomes of such directives. [11] The scheme is currently being renegotiated to enable recruitment of highly skilled migrants in greater numbers.

Other Migration Streams

Women make up over two-thirds of the family migration stream with children and then men making up the rest of the flows. Skilled women often enter through the family route as "trailing spouses". They may move into and out of the labour market but deskilling amongst this group is noticeable globally. Women may be disadvantaged because of ethnicity, gender, language acquisition and due to their socially reproductive responsibilities. [12]

One of the streams with a visibly higher proportion of skilled women (55 per cent) than men is student migration. As figure 3 above shows, it is a rapidly growing flow within and across Europe. Many of these students will work while they study or may move in to work after study as part of a two-step migration system, potentially forming a part of current or future skilled migration stocks.

Finally, across Europe, the last decade has seen significant flows of asylum seekers and refugees. Germany, during 2015 and 2016 admitted more than one million people seeking protection. [13] Women made up a third of this population. [14] Although many of the women were not skilled and have struggled to integrate into the labour market more than men because of language barriers, unequal responsibility for childcare reducing their access to reskilling programmes and due to previous skill levels in ‘desirable’ parts of the labour market, others have upskilled and tried to find jobs. The impact of these flows on overall skilled migrant stocks is yet to be analysed.

Changing Migration Patterns

As suggested above, one of the key factors influencing skilled migration flows is the changing boundaries of Europe itself. The expansion of the EU has led to an increase in intra-European flows of skilled migrants, [15]particularly from Eastern Europe to Western Europe leading to fears of brain drain. However, these flows are gender-selective. For instance, although men outnumber women among overall Polish migration to Germany, this is reversed amongst highly skilled migrants. Moreover, highly skilled women are also less likely to want to return to Poland. [16] Although Poland represents a particularly extreme case, similar flows of highly skilled women can be seen across the EU.

Another key factor influencing migration in the last decade has been the global financial crisis and its differential impact across Europe. Countries have readjusted migration polices, shifting from an open-door policy welcoming skilled migrants, to closing off parts of the labour market to certain skilled professions by imposing work permit quotas, higher income threshold to acquire work permits, and stricter return programmes. [17] Mandatory return programmes have resulted in highly skilled women migrants being the first to be fired and therefore the first to forcefully return. [18] Gender segregation across sectors within the labour market puts women in more precarious positions during times of recession which means they bear a disproportionate share of job loss compared to men. [19] Moreover, the austerity programmes have led to cuts in the socially reproductive sectors which are often government funded, leading to a greater impact on skilled women.

Conclusions

The last decade has seen a number of economic and political changes. There have been continuities as well as new patterns to skilled female migration in Europe as a result. Linguistic alignment due to colonial histories continues to shape migration and female migration is still predominantly in the socially reproductive sectors of the labour market. However, political changes affected female skilled migration. First, the boundaries of the EU have altered as it has expanded and now threatens to shrink, following Brexit. The flows of some overseas migrants have also varied according to whether intra-European flows were able to fill the labour market needs or not. Secondly, political turmoil outside European boundaries has influenced flows to the EU. There has been a sharp growth in the number of female and male refugees some of whom are upskilling, thus leading to a potential increase in skilled migrant stock. Thirdly, economic challenges such as the recession have shaped female labour markets. Migrant women are more likely to lose their jobs than migrant men because women are more likely to be employed in the socially reproductive sectors, which are often government-funded and have seen job losses due to the effects of austerity. Through these political and economic changes, gender continues to be an important divider in how skilled migration is experienced. In the coming decade, as anti-immigration sentiment rises across some parts of Europe, and the contours of the EU are being redrawn due to Brexit, the shape of skilled female migration too is likely to change.

Fußnoten

7.
NMC (2017).
8.
Siddique (2017).
9.
BAMF (2016).
10.
BAMF (2016).
11.
Enriquez and Triandafyllidou (2016), Gropas and Bartolini (2016), Boucher (2018).
12.
Grigoleit-Richter (2017).
13.
UNHCR (2018).
14.
Weise (2017).
15.
Beaumont et al (2017).
16.
Fihel and Górny (2013).
17.
Fihel and Górny (2013).
18.
Issakayan and Triandafyllidou (2015), Arslan et al (2015).
19.
Rubery and Rafferty (2013).
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