Young people not in education, employment or training (NEET), UK: March 2021

Estimates of young people (aged 16 to 24 years) who are not in education, employment or training, by age and sex.

This is not the latest release. View latest release

This is an accredited National Statistic. Click for information about types of official statistics.

Cyswllt:
Email Bob Watson

Dyddiad y datganiad:
4 March 2021

Cyhoeddiad nesaf:
27 May 2021

1. Main points

  • The percentage of all young people (aged 16 to 24 years) in the UK who were not in education, employment or training (NEET) in October to December 2020 was estimated at 11.6%; the proportion was up by 0.6 percentage points compared with July to September 2020 and up by 0.6 percentage points compared with October to December 2019.
  • Of all young people in the UK who were NEET in October to December 2020, an estimated 44.3% 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 were classified as economically inactive.
  • There were an estimated 797,000 young people in the UK who were NEET in October to December 2020; this increased by 39,000 compared with July to September 2020 and was up by 34,000 compared with October to December 2019.
  • The quarterly increase of 39,000 was the largest since July to September 2011 and was almost entirely driven by economically inactive men.

!

Labour Force Survey (LFS) responses are weighted to official population estimates and projections that do not currently reflect the impact of the coronavirus pandemic. The LFS is not designed to measure changes in the levels of population or long-term international migration. We are analysing the population totals used in the weighting process and may make adjustments if appropriate. Rates published from the LFS remain robust and reliable, however levels and changes in levels should be used with caution.

Nôl i'r tabl cynnwys

2. Coronavirus and measuring the labour market

For more information on how labour market data sources are affected by the coronavirus (COVID-19) pandemic, see the article published on 6 May 2020, which details some of the challenges that we have faced in producing estimates at this time.

An article published 11 December 2020 compares our labour market data sources and discusses some of the main differences.

Our latest data and analysis on the impact of the coronavirus on the UK economy and population are available on our dedicated coronavirus web page. This is the hub for all special coronavirus-related publications, drawing on all available data. In response to the developing coronavirus pandemic, we are working to ensure that we continue to publish economic statistics. For more information, please see COVID-19 and the production of statistics.

Because of COVID-19 and the suspension of face-to-face interviewing on 17 March 2020, we had to make operational changes to the Labour Force Survey (LFS), particularly in the way that we contact households for initial interview, which moved to a "by telephone" approach. These changes resulted in a response where certain characteristics have not been as well represented as previously. This is evidenced in a change in the balance of type of household that we are reaching. In particular, the proportion of households where people own their homes in the sample has increased and rented accommodation households has decreased.

To mitigate the impact of this non-response bias, in October 2020, we introduced housing tenure into the LFS weighting methodology for periods from January to March 2020 onwards. While not providing a perfect solution, this redressed some of the issues that had previously been noted in the survey results. More information can be found in Coronavirus and its impact on the Labour Force Survey and in this blog.

The change in weighting methodology resulted in revisions to all LFS estimates published on 13 October 2020 for the periods January to March 2020 through to May to July 2020. It consequently had an impact on recent movements for a number of the published series. More information about the impact of the change in weighting on main LFS indicators published in October 2020 can be found in Dataset X08.

Nôl i'r tabl cynnwys

3. Total young people who were not in education, employment or training

In October to December 2020, an estimated 11.6% of all people aged 16 to 24 years were not in education, employment or training (NEET). The proportion was up by 0.6 percentage points from October to December 2019 and increased on the quarter by 0.6 percentage points. An estimated 13.2% of men aged 16 to 24 years were NEET, which was the highest since October to December 2013, and for women the proportion was at 10.0%.

The percentage of those aged 18 to 24 years who were NEET was 13.8%.

Figure 1 shows the percentage of people aged 16 to 24 years who were NEET over the last 10 years. The percentage had been gradually decreasing since the peak of 16.9% in July to September 2011 but has been relatively flat since the beginning of 2017, averaging 11.2%.

There were an estimated 797,000 young people (aged 16 to 24 years) in the UK who were NEET in October to December 2020. This was up on the previous quarter by 39,000, the largest quarterly increase since July to September 2011. The total number who were NEET was up by 34,000 when compared with October to December 2019.

The total number of people aged 18 to 24 years who were NEET was 744,000.

Of the 797,000 people aged 16 to 24 years who were NEET in October to December 2020, 460,000 were men and 336,000 were women.

Nôl i'r tabl cynnwys

4. 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. In October to December 2020, there were an estimated 353,000 unemployed young people (aged 16 to 24 years) who were not in education, employment or training (NEET), up by 51,000 from October to December 2019 and up by 9,000 from July to September 2020.

In October to December 2020, there were an estimated 230,000 unemployed men aged 16 to 24 years who were NEET, down by 2,000 on the quarter, and 123,000 unemployed women aged 16 to 24 years who were NEET, up by 11,000 on the quarter.

Nôl i'r tabl cynnwys

5. 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. In October to December 2020, there were an estimated 444,000 economically inactive young people (aged 16 to 24 years) who were not in education, employment or training (NEET). This was down by 17,000 from October to December 2019 but up 31,000 from July to September 2020.

In October to December 2020, there were an estimated 230,000 economically inactive men aged 16 to 24 years who were NEET, up by 38,000 on the quarter, and 213,000 economically inactive women aged 16 to 24 years who were NEET, a record low, down by 8,000 on the quarter.

Nôl i'r tabl cynnwys

6. Young people not in education, employment or training data

Young people not in education, employment or training (NEET)
Dataset | Released 4 March 2021
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 4 March 2021
Labour Force Survey sampling quarterly variability estimates for young people (aged 16 to 24 years) who are NEET in the UK.

A06 SA: Educational status and labour market status for people aged from 16 to 24 (seasonally adjusted)
Dataset | Released 23 February 2021
Educational status and labour market status (employment, unemployment and economic inactivity) of people aged from 16 to 24 years (seasonally adjusted). This table shows estimates for people in full-time education and people not in full-time education. These estimates are sourced from the Labour Force Survey, a survey of households.

Nôl i'r tabl cynnwys

7. 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 by sex, and separately for the age groups 18 to 20 years, 21 to 22 years and 23 to 24 years.

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 before 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 who 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.

Nôl i'r tabl cynnwys

8. 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 (PDF, 88.6KB) providing background information is available. The article explains how missing information for identifying someone as NEET is appropriated based on individual characteristics.

Labour Force Survey (LFS) responses are weighted to official population estimates and projections that do not currently reflect the impact of the coronavirus pandemic. The LFS is not designed to measure changes in the levels of population or long-term international migration. We are analysing the population totals used in the weighting process and may make adjustments if appropriate. Rates published from the LFS remain robust and reliable, however levels and changes in levels should be used with caution.

The Office for National Statistics (ONS) is responsible for NEET statistics for the UK, published within this release. Estimates of the number of young people who are NEET within the countries of the UK and for subnational areas are the responsibility of the Department for Education, for England, and the devolved administrations for each of the other countries. There is further information on the availability of subnational estimates of young people who are NEET in Section 10: Related links.

Coronavirus

For more information on how labour market data sources are affected by the coronavirus (COVID) pandemic, see the article published on 6 May 2020 which details some of the challenges that we have faced in producing estimates.

Our latest data and analysis on the impact of the coronavirus on the UK economy and population are available on our dedicated coronavirus web page. This is the hub for all special coronavirus-related publications, drawing on all available data. In response to the developing coronavirus pandemic, we are working to ensure that we continue to publish economic statistics. For more information, please see COVID-19 and the production of statistics.

Impact of the coronavirus on data collection

The Labour Force Survey (LFS) design is based on interviewing households over five consecutive quarters. Generally, the first of these interviews, called Wave 1, takes place face-to-face, with most subsequent interviews, for Waves 2 to 5, conducted by telephone.

Because of the coronavirus and the suspension of face-to-face interviewing on 17 March 2020, we had to make operational changes to the LFS, particularly in the way that we contact households for initial interview, which moved to a "by telephone" approach.

These changes resulted in a response where certain characteristics have not been as well represented as previously and is evidenced in a change in the balance of type of household that we are reaching. In particular, the proportion of households where people own their homes in the sample has increased and rented accommodation households has decreased.

Impact of the coronavirus on survey weighting methodology

Because of the impact on data collection, different weeks throughout the quarter have different achieved sample sizes. To mitigate this impact on estimates the weighting methodology was enhanced to include weekly calibration to ensure that samples from each week had roughly equal representation within the overall three-month estimate. This meant that any impacts seen from changes in the labour market in those weeks would be fully represented within the estimates. For more information, see Section 2: Coronavirus and measuring the labour market.

Impact of government measures to protect businesses on the Labour Force Survey estimates

During late March, the government announced a number of measures to protect UK businesses. This included the Coronavirus Job Retention Scheme (CJRS), also referred to as furloughing, and the Self-Employment Income Support Scheme (SEISS).

The ONS classifies people within the labour market in line with International Labour Organization (ILO) definitions. Under the ILO definition employment includes employed persons "at work", that is, who worked in a job for at least one hour; and employed persons "not in work" because of temporary absence from a job, or to working time arrangements.

Under the current schemes it is likely that workers would expect to return to that job and would consider the absence from work as temporary. Therefore, those people absent from work under the current schemes would generally be classified as employed under ILO definitions.

Relationship to other labour market statistics for young people

Our monthly Labour market overview statistical bulletin includes the dataset A06: Educational status and labour market status for people aged from 16 to 24 (not seasonally adjusted). The NEET statistics and the dataset A06 statistics are both derived from the LFS 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.

More quality and methodology information on strengths, limitations, appropriate uses, and how the data were created is available in the Labour Force Survey (LFS) QMI.

Further information about the LFS is available from:

End of EU exit transition period

As the UK enters into a new Trade and Co-operation Agreement with the EU, the UK statistical system will continue to produce and publish our wide range of economic and social statistics and analysis. We are committed to continued alignment with the highest international statistical standards, enabling comparability both over time and internationally, and ensuring the general public, statistical users and decision makers have the data they need to be informed.

As the shape of the UK's future statistical relationship with the EU becomes clearer over the coming period, the Office for National Statistics (ONS) is making preparations to assume responsibilities that as part of our membership of the EU, and during the transition period, were delegated to the statistical office of the EU, Eurostat. This includes responsibilities relating to international comparability of economic statistics, deciding what international statistical guidance to apply in the UK context and to provide further scrutiny of our statistics and sector classification decisions.

In applying international statistical standards and best practice to UK economic statistics, we will draw on the technical advice of experts in the UK and internationally, and our work will be underpinned by the UK's well established and robust framework for independent official statistics, set out in the Statistics and Registration Service Act 2007. Further information on our proposals will be made available later this year.

We will continue to produce our labour market statistics in line with the UK Statistics Authority's Code of Practice for Statistics and in accordance with International Labour Organization (ILO) definitions and agreed international statistical guidance.

Nôl i'r tabl cynnwys

9. 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 October to December 2020 was estimated at 797,000. This figure had a stated 95% confidence interval of plus or minus 63,000. This means that we can be 95% confident that the true total number of people NEET aged 16 to 24 years for October to December 2020 was between 734,000 and 860,000. However, the best estimate from the survey was that the total number of people NEET aged 16 to 24 years was 797,000.

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 0.9 percentage points. This means that we can be 95% confident that the percentage of people NEET was between 10.7% and 12.5%. 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.

Nôl i'r tabl cynnwys

Manylion cyswllt ar gyfer y Bwletin ystadegol

Bob Watson
labour.supply@ons.gov.uk
Ffôn: +44 (0)1633 455070