United Kingdom
Not in education, employment or training
Key points
- One in eight 16- to 19-year-olds is not in education, employment or training. This is around 300-400,000 16- to 19-year-olds at any point in time. The proportion is somewhat higher than a decade ago.
- The reason for this slight rise is that, whilst the proportion of 16- to 18-year-olds who are in full-time education has increased in recent years, this has been more than offset by reductions in the proportions in other learning/training and in employment without training.
- The proportion of 16- to 19-year-olds who are not in education, employment or training is somewhat lower in Northern Ireland than elsewhere.
- Among 16- to 18-year-olds, more girls than boys are in full-time education: in 2009, 71% compared to 66%. This difference is then reflected in the lower proportion of girls than boys in some form of training: 13% compared with 16%. The proportions who are not in education, employment or training are similar.
- The proportion of White 16-year-olds who do not continue in full time education is much higher than that for any ethnic minority, but many are undertaking some form of training.
- See the Scotland, Wales and Northern Ireland indicators for an equivalent analysis for Scotland, Wales and Northern Ireland.
Graph 1: Over time
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Graph 2: By region
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Graph 3: By destination
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Graph 4: By gender
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Graph 5: By ethnic group
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Why this indicator was originally chosen
Many school leavers who are not in education or training are no longer developing their skills and thus are more likely to suffer from low pay at work both now and in the future (see the indicator on the impact of education on work).
Definitions and data sources
There are three possible sources for data about those not in education, employment or training (sometimes referred to as NEETs):
- The Labour Force Survey (LFS). This is the traditional source, provides data on a timely basis and covers the whole of the United Kingdom. However, sample sizes are small, the publicly available version of the data now only includes age by band (e.g. 16-19) rather than by individual year (thus preventing external analysis for the traditional 16-18 age group), and there are some worries about whether it completely captures participation in the wide variety of vocational education/training that now exists.
- Department for Children, Schools and Families (DCSF) publications. This is the source officially used by the Government to monitor progress towards its Public Service Agreement targets and is based on a large volume of administrative data that is considered to be very reliable. However, it only covers England (rather than the whole of the United Kingdom), the underlying data is not available (and therefore any analyses are restricted to whatever DCSF happens to publish), and it is less timely than LFS.
- Connexions. This is the source often used for more detailed analyses. However, it uses a somewhat different definition of what is a NEET, it only covers England (rather than the whole of the United Kingdom), the underlying data is not available (and therefore any analyses are restricted to whatever happens to be published), and it is not available over extended time periods.
For a discussion of these various data sources, and how their results compare, see the 2010 DCSF briefing paper. The results from LFS and the DCSF publications are actually very similar and, in this context, the following approach has been adopted in the analysis on this page:
- Because it is available for the United Kingdom as a whole, and because the underlying data is available, LFS is used as the main source for looking at both trends over time and variations by region.
- Because they provide a fuller analysis of different statuses, the DCSF publications are used to look at these various statuses, including by gender.
- The Connexions data is used to look at variations by ethnic group.
The first graph shows the proportion of 16- to 19-year-olds who are not in education, employment or training (sometimes referred to as NEETs).
The second graph shows how proportion of 16- to 19-year-olds who are not in education, employment or training varies by region. To improve its statistical reliability, the data is the average for the latest three years.
The data source for the first two graphs is the Labour Force Survey (LFS) and relates to the United Kingdom. The reason for the 16-19 age grouping, rather than the traditional 16-18 age grouping, is that the publicly available version of LFS now only includes age by band rather than by individual year. Analysis of past years suggests that the proportion not in education, employment or training is typically around one percentage point lower for the 16-18 age group compared with the 16-19 age group so, for example, a percentage of 11% for 16-19s in the first graph suggests that the percentage for 16-18s for that year would be around 10%. The figures for each year are the average for the four quarters of the relevant year. Note that the figures are not precisely the same as those in official government publications, partly because of the age group used and partly because government publications are typically based on analysis of the fourth quarter data for each year only.
The third graph shows, over time, the proportion of 16- to 18-year-olds by education/training/work status.
The fourth graph shows, for the latest year, the proportion of 16- to 18-year-olds by education/training/work status and gender.
The data source for the third and fourth graphs is the DCSF publication entitled Participation in education, training and employment by 16-18 year olds in England. The data relates to England only and is based on internal DCSF analysis of large volumes of administrative data, including records for individual young people. 'Learning/training' is an aggregation of 'Work-based learning but not in full-time education', 'Employer-funded training' and 'Other education and training'.
The fifth graph shows, for the latest year, how the proportion of pupils who have completed year 11 but are not in full-time education varies by ethnic group. Note that this is a different age group (basically 16-year-olds) than the other graphs.
The data source for the fifth graph is the Connexions Careers Service Activity Survey obtained via the annual publications entitled Moving on - pathways taken by young people beyond 16. The data relates to England only. The analysis omits any operational area which shows a proportion of 'ethnicity not known' of more than 11% plus those who either refused to answer the questions or with whom Connexions had lost contact.
Overall adequacy of the indicator: medium. The LFS is a large, well-established, quarterly government survey designed to be representative of the population as a whole but nevertheless the sample sizes for this age group are small. Furthermore, the number of NEETs is estimated by deducting those in education, employment or training from the total population and LFS may not always capture all types of education or training that a person is engaged with. Despite these theoretical shortcomings, however, the results from LFS - at least for England - are actually in very close agreement with equivalent results from administrative data on individual young people.
External links
- See the 2010 briefing note from the Department for Children, Schools and Families entitled NEET Statistics - Quarterly Brief.
- See the 2005 report for the Department for Children, Schools and Families entitled Young people not in education, employment or training: evidence from the Education Maintenance Allowance Database.
- See the Connexions site and the page on the results of their pupil destinations survey.
Relevant 2007 Public Service Agreements
Overall aim: Increase the number of children and young people on the path to success
Lead department
Department for Children, Schools and Families.
Official national targets
Reduce the proportion of young people not in education, employment or training by 2 percentage points by 2010.
Reduce the under-18 conception rate by 50% by 2010 as part of a broader strategy to improve sexual health.
Other indicators of progress
Young people participating in positive activities.
Young people frequently using drugs, alcohol or volatile substances.
First-time entrants to the Criminal Justice System aged 10-17.
Previous 2004 targets
Reduce the proportion of young people not in education, employment or training by 2 percentage points by 2010.
Relevant government policies
- Improving participation and attainment of 14- to 19-year-olds
- Education maintenance allowance
- Connexions
The numbers
Graph 1
| 1997 | 11% |
|---|---|
| 1998 | 10% |
| 1999 | 10% |
| 2000 | 10% |
| 2001 | 10% |
| 2002 | 11% |
| 2003 | 11% |
| 2004 | 11% |
| 2005 | 12% |
| 2006 | 12% |
| 2007 | 12% |
| 2008 | 12% |
| 2009 | 12% |
Graph 2
| East | 11% |
|---|---|
| East Midlands | 12% |
| London | 11% |
| North East | 15% |
| North West | 13% |
| Northern Ireland | 9% |
| Scotland | 12% |
| South East | 10% |
| South West | 10% |
| Wales | 11% |
| West Midlands | 13% |
| Yorkshire and The Humber | 13% |
Graph 3
| Year | Full-time education | Other learning/training | Employment without training | Not in education, employment or training |
|---|---|---|---|---|
| 1994 | 57% | 21% | 14% | 8% |
| 1995 | 58% | 20% | 13% | 8% |
| 1996 | 58% | 20% | 12% | 10% |
| 1997 | 56% | 20% | 14% | 9% |
| 1998 | 56% | 20% | 15% | 9% |
| 1999 | 57% | 20% | 15% | 8% |
| 2000 | 57% | 20% | 15% | 9% |
| 2001 | 56% | 19% | 15% | 10% |
| 2002 | 57% | 19% | 15% | 10% |
| 2003 | 57% | 19% | 15% | 10% |
| 2004 | 58% | 18% | 15% | 10% |
| 2005 | 60% | 17% | 13% | 11% |
| 2006 | 61% | 16% | 13% | 10% |
| 2007 | 63% | 16% | 12% | 10% |
| 2008 | 65% | 15% | 10% | 10% |
| 2009 | 68% | 15% | 8% | 9% |
Graph 4
| Destination | Boys | Girls |
|---|---|---|
| Full-time education | 66% | 71% |
| Other learning/training | 16% | 13% |
| Employment without training | 8% | 8% |
| Not in education, employment or training | 10% | 8% |
Graph 5
| Ethnic group | In neither full-time education nor training | Not in full-time education but in training |
|---|---|---|
| Bangladeshi | 7% | 4% |
| Black African | 6% | 1% |
| Black Caribbean | 7% | 4% |
| Indian | 4% | 2% |
| Pakistani | 6% | 4% |
| White | 7% | 7% |