Migrant workers and vulnerable employment: a review of existing data February 2008 – July 2008


The aim of this research, undertaken by COMPAS for the TUC Commission on Vulnerable Employment, was to investigate the extent of and conditions relating to vulnerable employment for migrant workers by comparing data from smaller‐scale regional/local datasets with data from the Labour Force Survey (LFS) and the Workers’ Registration Scheme (WRS).

While there are many media accounts of migrant vulnerability in the labour market, and some analyses accounting for it, there have been limited attempts to quantify this vulnerability. This research sought to fill this knowledge gap.

The indicators of vulnerable employment chosen for this study were: pay, hours, insecurity and accommodation. The geographical focus in the smaller‐scale datasets was two local areas: Birmingham and the West Midlands, and parts of the East of England and East Midlands. The project also analysed a database relating to domestic labour. This database includes many useful indicators both in terms of risk factors associated with individual characteristics (gender, immigration status, age) and vulnerable work. It also contains indicators of forced labour such as dependence on employer for accommodation, reports of threats and physical violence. The resulting analysis was used to deepen understanding of the structures that underpin vulnerable work.

Principal Investigator

Bridget Anderson, Hiranthi Jayaweera


TUC Commission on Vulnerable Employment




GenderLabour MarketsLow Skilled Migration




This project examined the LFS and WRS and compared them both with each other and with smaller datasets capturing recent migrant workers working in two regional areas of England: the West Midlands region and East of England/East Midlands. These were:

  • The West Midlands migrant worker survey (WMS)
  • The TUC Midlands survey (TUC)
  • Sub‐sample of Gangmasters in the West Midlands and East of England   in the Gangmasters Licensing Authority (GLA) register
  • Mobile Europeans Taking Action database (META)
  • Advice for Life database (AFL)
  • Eastern European Migrants Advice Committee  database (EMAC)

In addition, a detailed analysis was carried out of one database (the Kalayaan database) relating to an employment sector that is strongly associated with vulnerable employment: domestic labour. This database includes many useful indicators both in terms of risk factors associated with individual characteristics (gender, immigration status, age) and vulnerable work. It also contains indicators of forced labour. This analysis was used to deepen our understanding of the structures that underpin vulnerable work.


The main findings of the research were as follows:

  • The scale of under‐reporting of temporary work in the LFS for A8 nationals is significant, though an estimation of the scale would require a more sophisticated analysis. The WRS indicates that a substantial proportion of A8 nationals are in fact in temporary work, and there are indeed some indications that the WRS in turn is under‐estimating the numbers of A8 nationals in temporary employment.
  • There further seems to be under reporting of agency working. It seems that a combination of questionnaire design and data entry make it extremely difficult to extract firm figures about agency working from WRS data. There are high proportions of migrants working non‐standard hours, and this seems to be in part related to length of stay.
  • Pay below the minimum wage is a significant problem and is underestimated in the LFS. Young migrants are particularly poorly paid – even according to WRS.
  • Apart from age, particular factors influencing vulnerability include gender (and possibly life cycle stage), country of origin/nationality, sector, occupational level and the nature of the workplace.  Often these factors interact with each other to produce even greater vulnerability, and this is shown in a heightened way in the smaller scale datasets.
  • For some women migrants at particular life cycle stages working shorter hours may arise from choice rather than under‐employment.
  • Countries that migrant workers come from were seen to have a strong relationship with the extent of vulnerability in employment in both larger and small datasets. Workers from A8, A2 and Other European countries were generally worse off in terms of pay, hours and insecurity  than the other larger category of recent migrants, i.e. those from South Asian countries. However, part of the difference between these categories also relates to length of stay, as migrants from South Asian countries have generally arrived in the UK earlier.
  • Other mediating factors in relation to countries of origin include economic sectors, occupational levels, agency working, temporary work and English proficiency.
  • Finally, the Kalayaan data brings out the importance of the nature of the workplace in influencing vulnerability in employment for migrant workers. Given that domestic work in the UK is a sector where migrant workers more than workers generally are likely to be found, the lack of a clear distinction between work and non‐work, the close proximity and intimate nature of interaction between employers and workers, and the lesser likelihood than in other workplaces that employee and immigration rights are recognised, enables a context where employers could exert the maximum ‘imbalance of power in the employer‐worker relationship.’





The research played an important part in contributing to the TUC’s Commission on Vulnerable Employment.