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.
- About 16% of people employed in the UK in in the third quarter (July-September) of 2020 were born abroad
- Migrant men are more likely to be employed than UK-born men (84% vs 79% in 2019). However, among women, migrants are less likely to be in work (67% vs 73%)
- Unemployment rates for both migrants and the UK born fell steadily from 2012 to 2019, but the unemployment rate increased sharply among migrants during Q2 and Q3 of 2020
- Non-EU born migrants who moved to the UK seeking asylum are more likely to be unemployed than those who moved for employment, family or study reasons
- In 2019, unemployed migrants were less likely to claim unemployment benefits (17%) than UK born unemployed workers (29%)
- Workers born in India, East and Southeast Asia and EU-14 countries are more likely to be in high skilled occupations than the UK born, while those born in new EU member states (EU-8 and EU-2) are more likely to be in low-skilled occupations
- In 2019, migrants were over-represented in the hospitality sector (30%), transport and storage (28%), information, communication and IT (24%) and health and social work (20%)
- Employees born in EU-14 countries and India had the highest annualised median earnings in 2019 (£33,000)
- Around half of highly-educated workers born in new EU member states were in low and medium-low skilled jobs in 2019
- The share of workers in part-time jobs because they could not find a full-time position was 6% for those born Pakistan and other South Asian countries and 3% for UK born workers
- In 2019, foreign-born workers were more likely to work during night shifts and in non-permanent jobs than the UK born
- About 16% of people employed in the UK in in the third quarter (July-September) of 2020 were born abroad
Understanding the Evidence
This briefing examines the labour market situation of people who were born abroad and have migrated to the UK. ... Click to read more.
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 2019 and 2020 (only quarters 2 and 3) and the Annual Population Survey (APS) from 2019. 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 undercounted 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 undercounted. 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.).
Impact of COVID-19 pandemic on the LFS/APS
Due to the coronavirus pandemic, face-to-face interviewing was suspended on the 17 March 2020 and respondents have been interviewed by telephone ever since. This change in the mode of data collection impacted the survey response rate, which has been significantly lower, and the non-response bias (the profile of people who do not participate in the survey has changed). For more information on the impact of the pandemic on data collection and the reliability of the estimates derived from the LFS/APS 2020, see Athow (2020) and the ONS report Coronavirus and its impact on the Labour Force Survey.
Due to the higher degree of uncertainty of the estimates based on Q2 (April-June) and Q2 (July-September) of the LFS 2020, we highlight those data points in the charts with a different colour.
Labour market variables in the LFS/APS
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. In this context, job skills mainly indicate the educational credentials and training that are required to perform a job and do not consider other types of personal skills that are valued in the labour market.
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).
Earnings 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).
The briefing presents data for the UK-born and foreign-born populations either as a whole or for different country of birth 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 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.
Understanding the Policy
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. ... Click to read more.
For information on the main reason for migration of the foreign born population, see the Migration Observatory briefing Where do migrants live in the UK. 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 emphasises 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 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 16% of the employed population in the third quarter (July-September) of 2020
The share of workers in the UK who were born abroad has steadily increased since 2004 (9% of the workforce) to 2019, when they represented 18% of the workforce. There have always been more non-EU born than EU-born workers, though this gap narrowed from 2004 to 2017 (Figure 1).
Likely as a result of the coronavirus pandemic, the estimated share of migrant workers among the employed population decreased from 18% in Q3 of 2019 to 16% in Q3 of 2020. This decrease was more pronounced among the EU born than among the non-EU born (Figure 1). However, it is important to note that the estimated change over time may be unreliable because of challenges in data collection since March 2020.
There are several factors that could explain the decrease in the estimated share of foreign-born workers among the total employed population, including a larger increase in unemployment among migrant workers compared to the UK born; an increase in the number of migrant workers leaving the UK to their countries of origin; and problems in data collection since March 2020 mentioned above. At the time of writing, the available data are not sufficient to determine how much each of these factors is contributing.
Migrant men are more likely to be employed than UK-born men (84% vs 79% in 2019), but among women, migrants are less likely to be in work (67% vs 73%)
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 foreign qualifications, and discrimination. More information about English language use among migrants is available inathe Migration Observatory briefing, Language Use and Proficiency of Adult Migrants in the UK.
In 2019, the employment rate of migrant men aged 16 to 64 (84%) was higher to that of the UK born (79%) (Figure 2). Most country-of-origin groups had higher employment rates than UK-born men, except for men born in East and Southeast Asia (71%), and in MENA and Central Asia (71%). Among women, however, all of the country-of-origin groups had lower employment rates than UK-born women with the exception of EU-born women.
The gender employment gap (the difference between the employment rates of men and women) is the smallest among the working-age population born in the UK (6%), EU-8 countries (8%), and Sub-Saharan Africa (11%). 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 unemployment rate of foreign-born men was similar as that of UK born men (4%) in 2019 (Figure 3). Men from India (2%), Bulgaria and Romania (2%), EU-8 countries (3%) and Pakistan and other South Asia (3%) had lower unemployment rates than UK-born men, while Sub-Saharan African men had higher unemployment rate in 2019 (6%). Foreign-born women had higher unemployment rates than UK born women (3% vs 5%), though this is mainly driven by the high level of unemployment among women born in Pakistan and other South Asian countries, excluding India (11%). The gender unemployment gap is also the largest among this group (Figure 3).
Unemployment rates for both migrants and the UK born fell steadily from 2012 to 2019, but the unemployment rate increased sharply among migrants between April and September 2020
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 2019 (Figure 4). The EU born had a lower unemployment rate than the UK born since 2008 until 2019, while non-EU migrants have always had higher unemployment rates than their UK-born counterparts, although the gap has narrowed since the mid-2000s.
Due to economic downturn in 2020, the unemployment rates increased for both UK-born and foreign-born workers, especially for the latter (Figure 4). The unemployment rate for the UK born was 4% in Q3 2019 and increased up to 5% in Q3 2020. However, among the EU born, the unemployment rate during the same period increased from 3% to 6%, while for non-EU born increased from 5% to 7%. The greater increase in unemployment among migrant workers compared to the UK-born may be related to differences in the occupational profile (migrants are over-represented in the hospitality sector, which has been hit hardly by the pandemic) and type of job contracts (migrants are more likely to be on non-permanent contracts). People with temporary contracts or less secure work arrangements have been more likely to lose their jobs during the pandemic (see the Migration Observatory report Migrants’ labour market profile and the health and economic impacts of the COVID-19 pandemic).
Non-EU born migrants who moved to the UK seeking asylum are more likely to be unemployed than those who moved for employment, family or study reasons
Non-EU migrants moving to the UK seeking asylum have a higher unemployment rate and a lower employment rate than other non-EU migrants (Figure 5). For example, the unemployment rate in 2019 among non-EU born people who moved to the UK seeking asylum was 10% for men and 13% for women, while among those moving for employment reasons their unemployment rates were 7 and 11 percentage points lower, respectively. Differences in health status, especially mental health, might be one of the factors that partly explain these gaps, according to recent research (Ruiz and Vargas-Silva, 2018).
Both EU-born and non-EU born migrants moving to the UK for family reasons tend to have lower employment rates and higher unemployment rates than those moving for work.
In 2019, unemployed migrants were less likely to claim unemployment benefits (17%) than UK born unemployed workers (29%)
The share of unemployed people claiming unemployment benefits (universal credit or job seekers allowance) is lower among EU born (10%) and non-EU born (20%) workers than among the UK born (29%) (Figure 6). 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. In addition, 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 (note that the rules for accessing public services and benefits will be the same for most EU and non-EU citizens arriving after 31 December 2020). Migrants from EU countries in particular are also less likely to be unemployed for long periods of time; in 2019, 57% of unemployed EU migrants had been unemployed for less than 3 months, compared to 44% among non-EU migrants and UK-born workers.
Workers born in India, East and Southeast Asia and EU-14 countries are more likely to be in high skilled occupations than the UK born, while those born in new EU member states (EU-8 and EU-2) are more likely to be in low-skilled occupations
In 2019, the occupational distribution of migrant workers taken as a whole did not differ much to that of UK-born workers, although migrants were over-represented in low-skilled jobs compared to the UK born (15% vs 9%) (Figure 7). In this context, job skills mainly indicate the educational credentials and training that are required to perform a job and do not consider other types of personal skills that are valued in the labour market. 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 region of birth. In 2019, 45% of workers born in India were in high-skilled jobs (especially as IT and communications specialists), as well as 42% of those born in EU-14 countries. High-skilled jobs include positions such as corporate managers, doctors, nurses, and scientists or engineers. By contrast, workers born in new EU accession countries were over-represented in low-skilled occupations, such cleaners, waiters, or packers (Figure 7).
In 2019, migrants were over-represented in the hospitality sector (30%), transport and storage (28%), information, communication and IT (24%) and health and social work (20%)
Figure 8 shows the distribution of workers born in different regions across different sectors (by country of birth), and the presence of workers of different regions in each economic sector (by economic sector).
About a quarter of workers born in East and Southeast Asia and in Sub-Saharan Africa work in the health and care sector, mainly as care workers and nurses. Over a third of workers born in EU-8 countries were in retail and manufacturing jobs in 2019.
An estimated 18% of workers in 2019 were migrants. However, their presence varies considerably across economic sectors; for example, migrants were over-represented in the hospitality sector (30%), in transport and storage (28%), in information, communication and IT (24%) or in health and social work (20%) (Figure 8). By contrast, foreign-born workers were under-represented in public administration (10%). EU-8 workers made up 3% of the total working population, but they represented 7% of workers in the manufacturing sector. Indian workers are over-represented in the information and communication sector, which includes occupations such as computer programmers.
Figure 9 shows the top 10 occupations that 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 (19% of all workers were born in EU countries) (Figure 9). In contrast, health professional jobs, such as doctors and nurses (high-skilled), have the highest share of non-EU workers (18% of the total).
Employees born in EU-14 countries and India had the highest annualised median earnings in 2019 (£33,000)
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 10). In particular, Indian- and EU-14 born full-time employees had the highest median earnings at £33,200 per year compared to £28,000 of the UK born. By contrast, full-time employees born in new EU member states had the lowest median earnings (£23,000 and £22,000 among employees born in EU-2 and EU-8, respectively), followed by those born Pakistan and other South Asian countries (£26,000) (Figure 10). Workers born in post-2004 EU countries also had the lowest earnings dispersion of all the foreign born; that is, the difference in earnings between workers the 25th and 75th percentile of the earnings distribution is the smallest. The lower variability in earnings among EU-2 and EU-8 workers is likely to be related to their more homogenous occupational profile compared to other migrant groups.
Around half of highly-educated workers born in new EU member states were in low and medium-low skilled jobs in 2019
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 that required for their jobs.
Some of the factors explaining migrants’ high over-qualification rates include the lack of UK-specific skills, employers’ mistrust of or unfamiliarity with 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 (those with university degrees or with higher education qualifications below degree level, such as nursing) in low and medium-low skilled jobs (Figure 11). In 2019, the share of over-qualified workers was higher among people born in EU-8 countries (50%), Romania and Bulgaria (48%) and in Pakistan and other South Asian countries (36%), than among the UK born or the EU-14 born (20%) (Figure 11). Importantly, the migrant groups with the lowest earnings (see above) were also the ones most likely to be over-qualified for their jobs.
The share of workers in part-time jobs because they could not find a full-time position was 6% for those born in Pakistan and other South Asian countries and 3% for UK born workers
The share of workers who were in part-time jobs in 2019 because they could not find a full-time job is relatively low for both the UK born (3%) and the foreign born (4%) (Figure 12). However, the share of involuntary part-time workers was higher for those born in Pakistan and other South Asian countries (6%).
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 and care homes) or where service is concentrated at certain times of the day (e.g. restaurants, night clubs). In 2019, an estimated 24% of foreign-born workers have jobs involving some kind of shift work, compared to 17% of the UK 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 (8%) than the UK born (5%) (Figure 13).
In 2019, migrant workers were also more likely to be in non-permanent jobs (7%), especially those born in Sub-Saharan Africa (8%), compared to the UK born (5%) (Figure 13).
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.
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. This piece was also made possible by the University of Oxford Social Science Division’s Economic, Social, Cultural and Environmental Impacts of Covid-19 – Urgent Response Fund.
- Athow, J. (2020). Measuring the labour market during the pandemic. Office for National Statistics, National Statistical blog. Published on October 12, 2020. Available online
- 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
- 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
- Ruiz, I., & Vargas‐Silva, C. (2018) Differences in labour market outcomes between natives, refugees and other migrants in the UK, Journal of Economic Geography, volume 18, Issue 4, pp 855–885. Available online
- Crofts, S. (2020). What could the impact of COVID-19 be on UK demography? Office for National Statistics, National Statistical blog. Published on December 7 2020. Available online
- ONS (2020). Coronavirus and its impact on the Labour Force Survey. Published on 13 October 2020. 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
- 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
The Guardian online (20 Feb 2017)
Thousands of migrant workers to take part in UK's first day of action
- The Guardian online (20 Feb 2017)