Manufacturing workshop

Home / publications / briefings /

Migrants in the UK Labour Market: An Overview

15 Jul 2019

This briefing provides data on migrants’ labour market integration and the jobs they do in the UK labour market. It also presents data on migrants’ employment and unemployment rates, occupational status, earnings and contract types.

  1. Key Points
    • About 17% of people employed in the UK in 2018 were born abroad
      More…
    • Among men, migrants are more likely to be employed than the UK born (83% vs 79% in 2018), but among women, migrants are less likely to be in work (66% vs 72%)
      More…
    • Unemployment rates for both migrants and the UK born fell steadily from 2012 to 2018, when they stood at 3.4% for EU workers and 5.7% for non-EU workers
      More…
    • Unemployed migrants were less likely to claim unemployment benefits (18%) than UK born unemployed workers (26%).
      More…
    • Migrant workers born in India, East and Southeast Asia and EU-14 countries are more likely to be in high skilled jobs than the UK born, while those born in new EU member states are more likely to be in low-skilled occupations
      More…
    • A third of workers born in new EU member states were in retail and manufacturing in 2018
      More…
    • Indian and EU-14 born workers were the broad migrant groups with the highest median earnings in 2018
      More…
    • More than half of highly-educated workers born in new EU member states (56%) were in low and medium-low skilled jobs in 2018, compared to 23% of UK born workers
      More…
    • The share of involuntary part-time workers is highest among migrants from the Middle East, North Africa and Central Asia (9%), compared to the UK born (3%)
      More…
    • Migrant workers were more likely to work during night shifts and in non-permanent jobs than the UK born, in 2018
      More…
  1. Understanding the Evidence

    This briefing examines the labour market situation of people who were born abroad and have migrated to the UK. The word ‘migrant’ is used differently in different contexts. In this briefing, we use the term ‘migrant’ to refer to the foreign born, regardless of whether they have become UK citizens. For a discussion of this terminology, see the Migration Observatory briefing Who Counts as a Migrant: Definitions and their Consequences.

    This briefing relies on the Labour Force Survey (LFS) quarterly data from 2018 and the Annual Population Survey (APS) from 2017. The LFS is the largest household study in the UK (39,000 households) and provides the official measures of employment and unemployment. It collects information about a wide range of topics on individuals above age 15 every quarter. The APS includes most of the same individuals as the LFS but also includes and additional boost to the sample. Some variables are not available in the APS, however, and in those cases this briefing uses the LFS instead. The LFS/APS have some important limitations. Some people are excluded, such as residents of communal establishments like hostels, and other groups may be under-counted due to survey non-response. Its response rate has declined over time, and is now below 50% (ONS, 2016); this means that people who are more likely not to respond to the survey may be under-counted. ONS analysis based on the Census suggests that non-response is a greater problem among people born outside of the UK (Weeks et al, n.d.).

    Labour market variables in the LFS

    The analysis focuses on the working age population, which includes all individuals aged 16 to 64. When referring to people in employment or the employed population, we include all individuals who are employees, self-employed, or under a government employment or training scheme. Both full-time and part-time workers are included unless otherwise specified.

    To indicate the skill level associated with a person’s job, this briefing uses a four-category classification based on the amount of training required, developed by the Office of National Statistics (ONS, 2010). This classification is based on the Standard Occupational Classification 2010 (SOC 2010) and distinguishes between low-skilled, medium-low skilled, medium-high skilled and high-skilled occupations. We use individuals’ current occupation or last occupation during 2018.

    This briefing uses an indicator of over-qualification which measures the share of workers among the highly-educated in low or medium-low skilled jobs. Highly-educated workers are those with undergraduate or postgraduate degrees, or with higher education qualifications below degree level (e.g. BTEC Higher Nationals, diploma in higher education, nursing). This indicator of over-qualification is similar to that used by the OECD and the European Commission in their report about immigrant integration (OECD/European Union, 2015).

    Salary information in the LFS is the self-reported gross weekly pay for the ‘reference week’ that interviewees are asked information about. To estimate yearly pay, this briefing calculates annualised figures, i.e. multiplies gross weekly pay by 52. LFS earnings figures calculated in this way are lower than other official figures on earnings that are taken from a different ONS data source, the Annual Survey on Hours and Earnings (ASHE). This is thought to be due to factors such as greater error in self-reporting of salaries in the LFS, and differences in the sample (in particular, ASHE only includes people who have been in their jobs for at least one year). The pay information in this briefing should thus be considered to be underestimated (ONS, 2019).

    Data breakdowns

     The briefing presents data for the UK-born and foreign-born populations either as a whole or for different country of birth groupings. The country categories are the following:

    • EU-14 countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden).
    • EU-8 (Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, Slovenia), EU-2 (Bulgaria and Romania) and EU Other (Croatia, Malta and Cyprus) countries. Sometimes we refer to this group as new EU countries or new EU member states.
    • Middle East and North African (MENA) countries and Central Asian countries; the largest groups in these categories were born in Afghanistan, Iran, Iraq and North Africa (Egypt, Libya, Algeria, Morocco, South Sudan and Tunisia).
    • East Asian & Southeast Asian countries; the largest groups within this category were born in the Philippines, China, Singapore, Malaysia, Japan and Taiwan.
    • India
    • Pakistan and other South Asian countries (Bangladesh, Sri Lanka, Nepal). Most of the respondents in this category were born in Pakistan and Bangladesh.
    • Sub-Saharan African countries; the largest groups within this category were born in Nigeria, South Africa, Kenya, Somalia, Zimbabwe, Ghana, Uganda and Tanzania.
    • All foreign born; this category includes all the non-UK born population. Migrants born in non-EU European countries, America and Oceania are included here along with those born in the above-mentioned country groupings.

    About 40% of migrants in the UK were born in the EU and around a quarter were born South, East or Southeast Asian countries. See the the Migration Observatory briefing Migrants in the UK: an overview for more information about the geographic origins of the foreign born population.

    Margins of error in the estimates

    Because the LFS and APS are sample surveys, the estimates come with margins of error. This means that small differences between numbers or percentages may not be statistically significant. However, all the differences between groups that are described in the text of the briefing are statistically significant. A difference between two groups is considered statistically significant when the probability that this difference is caused by chance is very small. In that case, we assume that the differences we observe in the data are likely to exist in the population. Note that small differences between estimates for different groups may not be statistically significant, if they are not described in the narrative of the briefing.

  1. Understanding the Policy

    This briefing provides data on the whole migrant population living and working in the UK in 2018, regardless of their reason for migration or their immigration status (asylum, work, family or study). The people this briefing examines will have migrated to the UK over the course of several decades under a number of different policy regimes, and for the majority, work will not have been the main reason for migration (see the Migration Observatory briefing Where do migrants live in the UK for information on the main reason for migration of the foreign born population). For more information on work visas and people who move specifically for work, see the Migration Observatory briefing Work visas and migrant workers in the UK.

    Across Europe, labour market integration policies tend to focus on recently arrived migrants and could include job search assistance, recognition of foreign qualifications or provision of specific skills, such as language courses or vocational and non-vocational training (Bilgili, 2015). For an overview of labour market integration policies in Europe, see the MIPEX report Evaluating Impact: Lessons  Learned from Robust Evaluations of Labour Market Integration Policies.

    The UK does not have an overarching policy on migrants’ labour market integration, though the 2019 Home Office Integration framework has emphasised that positive labour market outcomes are key for migrants’ wider integration process. Policies that could affect how well migrants fare in the labour market fall within several different areas, ranging from adult skills and welfare-to-work to employment regulations and occupational licensing. Some of these policy areas are managed at the UK level while others are devolved to Scotland, Wales and Northern Ireland. Some cities and local authorities have their own integration strategies, either focusing specifically on migrants or including migrants as one of several target groups. The recently published Integrated Communities Strategy – Action Plan (HM Government, 2019) summarises a series of initiatives lead by the DWP, the MHCLG or the DfE aimed at improving the economic integration of disadvantaged groups. However, this Action Plan only applies to England and does not exclusively focus on the migrant population, but mainly on ethnic minorities. For more information about policies on integration, see the Migration Observatory policy primer, Integration.

The foreign born made up 17% of the employed population in the UK in 2018

The share of workers in the UK who were born abroad has increased over the past 15 years. There have always been more non-EU born workers than EU-born workers, though this gap narrowed from 2004 to 2017 (Figure 1). In 2018, 10% of people working in the UK were born outside of the EU. The share of EU born workers in the labour market increased from 2% in 2004, but remained broadly stable from 2016 to 2018, when it stood at 7% in 2018 (Figure 1).

Figure 1

 

Return to top

Among men, migrants are more likely to be employed than the UK born (83% vs 79% in 2018), but among women, migrants are less likely to be in work (66% vs 72%)

There are many factors that shape the employment and unemployment rates of migrants in the UK, ranging from migrants’ varying levels of education and skills, how well they speak English, family and caring responsibilities, social networks, the extent to which UK employers recognise their qualifications, and discrimination. More information about English language use among migrants is available in the Migration Observatory briefing, Language Use and Proficiency of Adult Migrants in the UK. Migrants’ labour market activities also vary with their health; this is discussed in the Migration Observatory briefing, The Health of Adult Migrants in the UK.

On average, the employment rate of migrants (74%) was similar to the UK born (76%) in 2018. However, there were substantial differences between men and women.  The employment rate of foreign-born men (83%) was higher than for UK born men (79%). Most country-of-origin groups had higher employment rates than UK men, except for men born in East and Southeast Asia (71%), and in MENA and Central Asia (68%). Among women, all of the country-of-origin groups had lower employment rates than UK-born women (Figure 2) with the exception of women from EU countries.

Figure 2

The gender employment gap (the difference between the employment rates of men and women) is the smallest among the UK born (7%) and those born in East and Southeast Asia (8%), followed by the EU born (12%) and Sub-Saharan African born (12%) populations. The gender employment gap is the largest among migrants born in Pakistan and other South Asian countries, for which women’s employment rate was 46 percentage points lower than that of men (Figure 2). The gender unemployment gap is also the largest among this group (Figure 3).

The unemployment rate of foreign born men was the same as that of UK born men (4%) in 2018 (Figure 3). Men from India (2%), new EU accession countries (2%) and Pakistan and other South Asia (3%) have lower unemployment rates than UK born men, while Sub-Saharan African men and men born in MENA and Central Asia had higher unemployment rates (6% and 10%, respectively). Foreign born women had higher unemployment rates than UK born women (6% vs 4%), though this is mainly driven by the high unemployment rates of women born in Pakistan and other South Asian countries (15%).

Figure 3

Return to top

Unemployment rates for both migrants and the UK born fell steadily from 2012 to 2018

Unemployment rates have generally risen and fallen following similar trends for both migrants and the UK born over the past decade, with sharp increases in the aftermath of the 2008 financial crisis and steady declines from 2012 to 2018 (Figure 4). The EU born have had a lower unemployment rate than the UK born since 2008 and it stood at 3.4% in 2018. Non-EU migrants have always had higher unemployment rates than their UK-born counterparts (5.7% vs 4.1% in 2018), although the gap has narrowed since the mid-2000s.

Figure 4


Return to top

Unemployed migrants were less likely to claim unemployment benefits (18%) than UK born unemployed workers (26%)

The share of unemployed people claiming unemployment benefits (universal credit or job seekers allowance) is lower among EU born (16%) and non-EU born (19%) workers than among the UK born (26%) (Figure 5). There are several possible reasons for this. Migrant workers who are eligible to receive unemployment benefits may not understand their entitlements or may be unfamiliar with the process of claiming or visiting job centres. Some are not eligible: most non-EU citizens who are not yet permanently settled residents are ineligible for income-based jobseekers’ allowance and universal credit, as are EU citizens who have lived in the UK for less than 3 months. Migrants from EU countries in particularly are also on average unemployed for shorter periods (in 2018, 55% of unemployed EU migrants had been unemployed for less than 3 months, compared to 41% of those from non-EU countries and 44% of those born in the UK).

Figure 5

Workers born in India, East and Southeast Asia and in EU-14 countries are more likely to be in high skilled occupations than the UK born, while those born in new EU member states are more likely to be in low-skilled occupations

The occupational distribution of migrant workers taken as a whole was similar to that of the UK born in 2018 (Figure 6). A majority of both migrants and UK-born workers were in middle-skilled jobs, which includes occupations such as associate professionals, administrative jobs, sales assistants and some care work.

However, there were considerable differences across workers by country of birth. In 2018, 45% of workers born in India were in high-skilled jobs (especially as IT and communications specialists), as well as 40% of those born in East and Southeast Asia and in EU-14 countries. High-skilled jobs include positions such as corporate managers, health professionals and scientists or engineers. By contrast, workers born in new EU accession countries were over-represented in low-skilled occupations, such as entry-level services or trades positions (Figure 6).

Figure 6


Return to top

A third of workers born in new EU member states were in retail and manufacturing jobs in 2018

The retail (and wholesale) sector employed about 13% of both migrants and the UK born in 2018. However, this sector employed about 21% of workers born in Pakistan and other South Asian countries in 2018, and 17% of those born in new EU member states (Figure 7). Indian workers were particularly likely to work in the information and communication sector (16%), which includes computer programmers, while a quarter of EU-14 workers were in the education or professional and scientific sectors. A third of workers born in new EU member states were in either retail or manufacturing (which includes food manufacturing).

Figure 7


Figure 8 shows which occupations are most reliant on workers from EU and non-EU countries, respectively. Low-skilled factory and construction jobs have the largest share of EU born workers (21% of all workers were born in EU countries) (Figure 8). In contrast, health professional jobs (high-skilled) have the highest share of non-EU workers (17% of the total).

Figure 8


Return to top

Indian and EU-14 born workers had the highest annualised median earnings in 2018

Workers’ earnings are closely related to the occupations they hold, and data confirm that the migrant groups who were concentrated in high-skilled jobs also have higher earnings (Figure 9). In particular, Indian and EU-14 born full-time workers had the highest median earnings at £31,200 and £32,300 per year, respectively, compared to £27,000 of the UK born. By contrast, full-time workers born in new EU member states had the lowest median earnings (£21,000), followed by those born Pakistan and other South Asian countries (£23,700) (Figure 9). Workers born in post-2004 EU countries had the lowest variability in earnings of all the foreign born.

Figure 9


Return to top

More than half of highly-educated workers born in new EU member states (56%) were in low and medium-low skilled jobs in 2018

Compared to the UK born, migrants are more likely to work in jobs for which they are overqualified, especially if they have foreign qualifications (Chiswick and Miller, 2008). In general, workers are considered overqualified for their jobs if their educational level is above those required for their jobs.

Some of the factors explaining migrants’ high over-qualification rates could be the lack of UK specific skills, the lower quality of the education in their country of origin, employers’ mistrust of foreign qualifications, or migrants’ lack of information about the job searching process in the UK.

The indicator of over-qualification used here shows the share of highly educated workers in in low and medium-low skilled jobs (Figure 10). In 2018, the share of over-qualified workers was higher among people born in new EU member states (56%) and in Pakistan and other South Asian countries (44%), than among the UK born or the EU-14 born (23%) (Figure 10). Importantly, the migrant groups with the lowest earnings (see above) were also the ones most likely to be over-qualified for their jobs.

Figure 10


Return to top

The share of workers in part-time jobs because they could not find a full-time position was 9% for those born in the Middle East, North Africa and Central Asia and 3% for UK born workers

The share of workers who were in part-time jobs in 2018 because they could not find a full-time job is relatively low for both the UK born (3%) and the foreign born (4%) (Figure 11). However, the share of involuntary part-time workers was higher for those born in Pakistan and other South Asian countries (7%) and in MENA or Central Asia (9%).

Figure 11


Return to top

Foreign-born workers were more likely to work during night shifts and in non-permanent jobs than the UK born

Shift work is work that takes place outside typical working hours (9 to 5) from Monday to Friday. It could involve working on different time schedules each day of the week, on weekends, on split shifts (e.g. full shifts divided into two distinct parts with a gap of several hours in between) or during night time. Shift schedules are more common in sectors that require 24 hour service (e.g. nursing homes) or where service is concentrated at certain times of the day (e.g. restaurants, night clubs). About a quarter of EU-born workers have jobs involving some kind of shift work, compared to 17% of the UK born and 21% of the non-EU born.

Night shift work is thought to have a negative impact on physical and mental health and performance through its impact on sleep and circadian timing (The Parliamentary Office of Science and Technology, 2018). Foreign born workers were more likely to work during night shifts (7%) than the UK born (4%) (Figure 12).

In 2018, migrant workers were also more likely to be in non-permanent jobs (8%) than the UK born (5%) (Figure 12).

Figure 12


Return to top

Evidence gaps and limitations

The LFS does not collect data on earnings from self-employment, so cannot provide the full picture of migrants’ earnings in the UK. In addition, the estimation of annualised median earnings for each country grouping does not exactly match the official estimates, which are based on the Annual Survey of Hours and Earnings (see ‘Understanding the Evidence’ above).

The aggregate occupational categories used in this briefing (e.g. ‘high-skilled’ or ‘low-skilled’) are also imperfect as a measure of occupational skills. While using aggregated occupational groups is useful for providing an overview of the skills required to performed a certain job, in practice they can contain a wide range of occupations including workers with quite different levels of education, pay or working conditions.

This briefing presents data breakdowns by country groupings. However, there are characteristics other than the geographical origin that have an impact on labour market outcomes. For example, refugees tend to have worse employment outcomes than labour migrants (Zone et al., 2019; Ruiz & Vargas-Silva, 2017).

A limitation of using cross-sectional data such as the LFS/APS is that we cannot follow individuals over time and, therefore, we do not know whether migrants’ labour market position has improved or worsened since their arrival to the UK. In general, migrants’ integration in the labour market is likely to improve the longer they stay in the UK.

This report was produced with the support of the Paul Hamlyn Foundation.

The Paul Hamlyn Foundation is an independent funder working to help people overcome disadvantage and lack of opportunity, so that they can realise their potential and enjoy fulfilling and creative lives.

References

  • Bilgili, Ö. (2015). Evaluating Impact: Lessons Learned from Robust Evaluations of Labour Market Integration Policies. MIPEX Project. Available online
  • HM Government (2019). Integrated Communities Action Plan. Available online
  • Home Office Indicators of Integration framework 2019. Available online
  • Kone, Z., Ruiz, I. & Vargas-Silva, C. (2019). Refugees and the UK Labour market. Econref working paper 04-2019, Centre on Migration, Policy and Society. Available online
  • OECD/European Union (2015), Indicators of Immigrant Integration 2015: Settling In, OECD Publishing, Paris. Available online
  • ONS (2010). Standard Occupational Classification 2010: Volume 1 Structure and descriptions of unit groups.. Available online
  • ONS (2019). A guide to sources of data on earnings and income. Available online
  • Parliamentary Office of Science & Technology (2018). Shift work, sleep and health, number 586. Available online
  • Ruiz, I., & Vargas‐Silva, C. (2017). Are refugees’ labour market outcomes different from those of other migrants? Evidence from the United Kingdom in the 2005–2007 period. Population, Space and Place, 23(6). Available online
  • Week, A., Fallows, A., Broad, P., Merad, S., & Ashworth, K. Non-response Weights for the UK Labour Force Survey? Results from the Census Non-response Link Study. Survey Methodology and Statistical Computing, Office for National Statistics. Available online

Further readings

  • Anderson, B., & Ruhs, M. (2012). Reliance on migrant labour: inevitability or policy choice?. The Journal of Poverty and Social Justice, 20(1), 23
  • Chiswick, B. R., & Miller, P. W. (2008). Why is the payoff to schooling smaller for immigrants?. Labour Economics, 15(6), 1317-1340
  • Frattini, T. (2017). Evaluating the Labour Market Integration of New Immigrants in the UK. Social Policy and Society, 16(4), 645-658
  • Johnston, R., Khattab, N., & Manley, D. (2015). East versus West? Over-qualification and earnings among the UK’s European migrants. Journal of Ethnic and Migration Studies, 41(2), 196-218
  • McCollum, D., & Findlay, A. (2015). ‘Flexible’workers for ‘flexible’jobs? The labour market function of A8 migrant labour in the UK. Work, employment and society, 29(3), 427-443
  • Migration Advisory Committee. (2014). Migrants in low-skilled work: The growth of EU and non-EU labour in low-skilled jobs and its impact on the UK. Migration Advisory Committee Report
  1. Media Coverage

Next Update

July 16, 2020

Authors

Mariña Fernández-Reino
Dr Cinzia Rienzo

Download Briefing

Press Contact

If you would like to make a press enquiry, please contact:

Rob McNeil

+ 44 (0)7500 970081
robert.mcneil@compas.ox.ac.uk

 Contact Us 

 Connections 

This Migration Observatory is kindly supported by the following organisations.

  • University of Oxford logo
  • COMPAS logo
  • Esmee Fairbairn logo
  • Barrow Cadbury logo
  • Paul Hamlyn Foundation logo