Table of contents
- Main points
- Total young people who were not in education, employment or training
- Unemployed young people who were not in education, employment or training
- Economically inactive young people who were not in education, employment or training
- Young people who are not in education, employment or training data
- Glossary
- Measuring the data
- Strengths and limitations
- Related links
1. Main points
- There were 800,000 young people (aged 16 to 24 years) in the UK who were not in education, employment or training (NEET) in July to September 2019; this number increased by 43,000 when compared with July to September 2018 and was up 8,000 from April to June 2019.
- The percentage of all young people in the UK who were NEET in July to September 2019 was 11.6%; the proportion was up 0.7 percentage points from July to September 2018 and up 0.1 percentage points from April to June 2019.
- Of all young people in the UK who were NEET in July to September 2019, 39.6% were looking for, and available for, work and therefore classified as unemployed; the remainder were either not looking for work and/or not available for work and therefore classified as economically inactive.
2. Total young people who were not in education, employment or training
There were 800,000 young people (aged 16 to 24 years) in the UK who were not in education, employment or training (NEET) in July to September 2019. This is the highest number since October to December 2016, but still well below the peak of 1.2 million in the latter half of 2011. The number was up 43,000 when compared with July to September 2018, the largest annual increase since January to March 2012, and increased by 8,000 from April to June 2019.
In July to September 2019, 11.6% of all people aged 16 to 24 years were NEET. This is the highest proportion seen since the same period in 2016. The proportion was up 0.7 percentage points from July to September 2018, the largest annual increase since January to March 2012, and increased by 0.1 percentage points from April to June 2019.
Figure 1 shows the percentage of people aged 16 to 24 years who were NEET over the last ten years. The percentage had been gradually decreasing since the latter half of 2011 but, as shown in Figure 1, has been relatively flat since the beginning of 2017.
Figure 1: The percentage of people who are not in education, employment or training (NEET) had been decreasing since 2011 but has been relatively flat since 2017
People aged 16 to 24 years NEET as a percentage of all people aged 16 to 24 years, seasonally adjusted, UK, July to September 2009 to July to September 2019
Source: Office for National Statistics – Labour Force Survey
Download this chart Figure 1: The percentage of people who are not in education, employment or training (NEET) had been decreasing since 2011 but has been relatively flat since 2017
Image .csv .xls3. Unemployed young people who were not in education, employment or training
Unemployment measures people without a job who have been actively seeking work within the last four weeks and are available to start work in the next two weeks. For July to September 2019, there were 317,000 unemployed young people (aged 16 to 24 years) who were not in education, employment or training (NEET), up 33,000 from July to September 2018 but down 13,000 from April to June 2019.
For July to September 2019, there were:
- 212,000 unemployed men aged 16 to 24 years who were NEET
- 105,000 unemployed women aged 16 to 24 years who were NEET; the lowest number since records began in October to December 2001.
4. Economically inactive young people who were not in education, employment or training
Economic inactivity measures people not in employment who have not been seeking work within the last four weeks and/or are unable to start work within the next two weeks. For July to September 2019, there were 484,000 economically inactive young people (aged 16 to 24 years) who were not in education, employment or training (NEET), up 10,000 from July to September 2018 and up 21,000 from April to June 2019.
For July to September 2019, there were:
- 211,000 economically inactive men aged 16 to 24 years who were NEET
- 272,000 economically inactive women aged 16 to 24 years who were NEET
5. Young people who are not in education, employment or training data
A06 SA: Educational status and labour market status for people aged from 16 to 24 (seasonally adjusted)
Dataset | Released 12 November 2019
Educational status and labour market status (employment, unemployment and economic inactivity) of people aged from 16 to 24 (seasonally adjusted).
Young people not in education, employment or training (NEET)
Dataset | Released 21 November 2019
Quarterly estimates for young people (aged 16 to 24 years) who are not in education, employment or training (NEET) in the UK.
Sampling variability for estimates of young people not in education, employment or training
Dataset | Released 21 November 2019
Labour Force Survey sampling quarterly variability estimates for young people (aged 16 to 24 years) who are not in education, employment or training (NEET) in the UK.
6. Glossary
Young people
For this release, young people are defined as those aged 16 to 24 years. Estimates are also produced for the age groups 16 to 17 years and 18 to 24 years and by sex.
Education and training
People are considered to be in education or training if any of the following apply:
- they are enrolled on an education course and are still attending or waiting for term to start or restart
- they are doing an apprenticeship
- they are on a government-supported employment or training programme
- they are working or studying towards a qualification
- they have had job-related training or education in the last four weeks
Young people not in education, employment or training (NEET)
Anybody who is not in any of the forms of education or training listed above and not in employment is considered to be NEET. Consequently, a person identified as NEET will always be either unemployed or economically inactive.
Economic inactivity
People not in the labour force (also known as economically inactive) are not in employment but do not meet the internationally accepted definition of unemployment because they have not been seeking work within the last four weeks and/or they are unable to start work in the next two weeks.
Employment
Employment measures the number of people in paid work, or had a job that they were temporarily away from (for example, because they were on holiday or off sick). This differs from the number of jobs because some people have more than one job.
Unemployment
Unemployment measures people without a job who have been actively seeking work within the last four weeks and are available to start work within the next two weeks.
A more detailed glossary is available.
Back to table of contents7. Measuring the data
This statistical bulletin contains estimates for young people not in education, employment or training (NEET) in the UK. The bulletin is published quarterly in February or March, May, August and November. All estimates discussed in this statistical bulletin are for the UK and are seasonally adjusted.
Statistics in this bulletin are used to help monitor progress towards the Sustainable Development Goals (SDGs). Explore the UK data on our SDGs reporting platform.
An article called Young people who are NEET providing background information is available. The article explains how missing information for identifying someone as NEET is apportioned based on individual characteristics.
Relationship to other labour market statistics for young people
Our monthly labour market statistical bulletin includes the dataset A06: Educational status and labour market status for people aged from 16 to 24. The NEET statistics and the dataset A06 statistics are both derived from the Labour Force Survey and use the same labour market statuses; however, the educational statuses are derived differently.
For dataset A06, the educational status is based on participation in full-time education only. For NEET statistics, the educational status is based on any form of education or training, as listed previously. Therefore, the dataset A06 category “not in full-time education” includes some people who are in part-time education and/or some form of training and who, consequently, should not be regarded as NEET.
The Labour Force Survey (LFS) Quality and Methodology Information report contains important information on:
- the strengths and limitations of the data and how they compare with related data
- uses and users of the data
- how the output was created
- the quality of the output, including the accuracy of the data
Further information about the LFS is available from:
Back to table of contents8. Strengths and limitations
Accuracy of the statistics: estimating and reporting uncertainty
The figures in this statistical bulletin come from the Labour Force Survey (LFS), a survey of UK households. Surveys gather information from a sample rather than from the whole population. The sample is designed carefully to allow for this and to be as accurate as possible given practical limitations such as time and cost constraints, but results from sample surveys are always estimates, not precise figures. This means that they are subject to some uncertainty. This can have an impact on how changes in the estimates should be interpreted, especially for short-term comparisons.
We can calculate the level of uncertainty (also called “sampling variability”) around a survey estimate by exploring how that estimate would change if we were to draw many survey samples for the same time period instead of just one. This allows us to define a range around the estimate (known as a “confidence interval”) and to state how likely it is in practice that the real value the survey is trying to measure lies within that range. Confidence intervals are typically set up so that we can be 95% sure that the true value lies within the range – in which case we refer to a “95% confidence interval”.
The total number of people not in education, employment or training (NEET) aged 16 to 24 years for July to September 2019 was estimated at 800,000. This figure had a stated 95% confidence interval of plus or minus 57,000. This means that we can be 95% confident that the true total number of people NEET aged 16 to 24 years for July to September 2019 was between 743,000 and 857,000. However, the best estimate from the survey was that the total number of people NEET aged 16 to 24 years was 800,000.
The percentage of people NEET aged 16 to 24 years for the same period was estimated at 11.6%, with a stated 95% confidence interval of plus or minus 0.8 percentage points. This means that we can be 95% confident that the percentage of people NEET was between 10.8% and 12.4%. Again, the best estimate from the survey was that the percentage of people NEET aged 16 to 24 years was 11.6%.
Working with uncertain estimates
In general, changes in the numbers (and especially the rates) reported in this statistical bulletin between three-month periods are small and are not usually greater than the level that is explainable by sampling variability. In practice, this means that small, short-term movements in reported rates (for example, within plus or minus 0.3 percentage points) should be treated as indicative and considered alongside medium- and long-term patterns in the series and corresponding movements in administrative sources, where available, to give a fuller picture.
Seasonal adjustment and uncertainty
Like many economic indicators, the labour market is affected by factors that tend to occur at around the same time every year; for example, school leavers entering the labour market in July and whether Easter falls in March or April. To compare movements other than annual changes in labour market statistics, such as since the previous quarter or since the previous month, the data are seasonally adjusted to remove the effects of seasonal factors and the arrangement of the calendar. Estimates discussed in this statistical bulletin are presented seasonally adjusted. While seasonal adjustment is essential to allow for robust comparisons through time, it is not possible to estimate uncertainty measures for the seasonally adjusted series.
Dataset table NEET 2 shows sampling variabilities for estimates of young people who are NEET derived from the LFS.
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