Official Statistics

Get Britain Working: Labour Market Insights July 2026 – Background Information and Methodology

Published 30 July 2026

1. Introduction

This background report accompanies the Get Britain Working: Labour Market Insights July 2026 publication. The purpose of this report is to provide further contextual information to aid understanding of how the statistics presented in the main report and data tables were developed and quality assured.

A comprehensive set of data tables complementing the results presented is available alongside the publication. This document, the statistics release and data tables can be found via the collections page.

2. Status of the statistics

Official statistics in development

These statistics are official statistics in development. Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality, and value in the Code of Practice for Statistics that all producers of official statistics should adhere to.

The Code of Practice for Statistics is built around 3 main concepts, or pillars: 

• trustworthiness – is about having confidence in the people and organisations that publish statistics

• quality – is about using data and methods that produce statistics

• value – is about publishing statistics that support society’s needs

The following explains how we have applied the pillars of the Code in a proportionate way. 

UK government analysts work to a professional competency framework and Civil Service core values of integrity, honesty, objectivity, and impartiality. The data and analysis in this release have been scrutinised and quality assured in line with the AQuA Book and received sign off by the subject expert lead senior civil service analyst.

3. Contact

Press enquiries should be directed to Department for Work and Pensions (DWP) Press Office via newsdesk@dwp.gov.uk.

Alternatively, you can contact the OSR by emailing: regulation@statistics.gov.uk or via the Office for Statistics Regulation website.

4. Quality of the statistics

The analysis presented in this publication is based on a range of administrative and survey data sources.

More information on the quality assurance checks that take place on Universal Credit (UC) administrative data can be found in the Quality statement DWP benefits.

Analysis is quality assured (QA) by DWP analysts before it is released to ensure the findings are robust. This includes peer review of the approach and implementation of the analysis as well as spot checks and comparisons to other data sources where available. Although extensive QA of the underlying data takes place, it is possible that errors still exist that may impact these statistics. If identified these will be rectified and the analysis will be updated in a future publication.

Some data are also subject to retrospection, where additional data becomes available later that affects historic figures. Retrospection usually has the largest impact on the most recent figures, with a negligible impact on figures at least 6 months old.

5. Background

Accessibility

DWP has published an accessibility statement regarding dissemination of statistics. We have reviewed our publication tables and supporting guidance to ensure accessibility to users. For compliance with The Public Sector Bodies (Websites and Mobile Applications) Accessibility Regulations 2018, some formatting in the accompanying ODS data tables, such as merged cells, has been avoided. Please see Accessibility statement for www.gov.uk for information on what to do if you need the information in this publication provided in a different format.

For ease of understanding, figures in the data tables have been rounded to an appropriate degree. When a figure rounds to 0 but is not equal to 0 it is labelled as [low]. In the case of geographies, these areas are shown as blank in the maps due to the small value.

Frequency

This publication is the fourth in a quarterly statistical publication series of labour market insights. The next edition is planned for October 2026. The publication contains some core statistics which will be updated periodically, while other statistics will be published as a one-off or updated less frequently. Every other edition will include a contextual chapter offering deeper analysis on a specific topic, helping readers build understanding without requiring full updates to all content.

6. Source of the statistics

Into-work, sustained employment and worklessness rates

The analysis in 3a. The into-work rate, 3b. Into-work rate by local authority and Jobcentre Plus district, 3c. Into-work rate by duration on Universal Credit,  3d. Into-work rate by age of Universal Credit customer, 4. Sustained employment of Universal Credit Customers and 5. Measure of worklessness of Universal Credit ‘Searching for work’ customers in Get Britain Working: Labour Market Insights July 2026 explores into-work, sustained employment and worklessness rates which are produced using a combination of UC administrative data and HM Revenue and Customs’ (HMRC), PAYE and Real Time Information (RTI) data.

The UC administrative data is collected from the UC data systems. The data is processed and released internally, often with a lag time of some months. To protect the confidentiality of customers, National Insurance numbers and other claim identifiers required for statistical processing are encrypted to prevent identification. A wide range of information is collected including information relating to the characteristics of UC customers and information about their claim and earnings, and how these change over time.

These HMRC PAYE data provides information on a customer’s earnings, beyond that collected by DWP, which enables more accurate identification of a movement into work, and the level of earnings received. It also provides functionality to observe earnings data, and by proxy ‘employment status’, of a previous customer following the closure of their UC claim.

Additional information is matched on from the DWP Customer Information System (CIS). CIS holds basic identifying information about all our customers, including their date of birth. Postcodes are taken from the CIS data and combined with geographical details obtained from the Office for National Statistics Postcode Look-up (NSPL). This process aggregates postcodes into local authorities. Jobcentre Plus geography is based on the Jobcentre Plus office which administers the UC claim. Jobcentre Plus offices build up to Jobcentre Plus districts. It is possible for the UC customer to reside in a different area (for example, local authority) to the area administering their benefit claim.

Young people aged 16 to 24 years who are not in education, employment or training across England’s regions

The analysis in 6. Young people aged 16 to 24 years who are not in education, employment or training (NEET) across England’s regions in Get Britain Working: Labour Market Insights July 2026 publication uses Labour Force Survey (LFS) micro-data. The LFS – conducted by the Office for National Statistics (ONS) - is a large, representative household study and provides detailed information related to the UK population’s activity in the labour market. The LFS is the basis of the headline labour market statistics produced by ONS; and a valuable data source to conduct analysis into more detailed aspects of the labour market.

7. Methodology

Into-work rate

Producing the into-work rate analysis in 3a. The into-work rate and 3b. Into-work rate by local authority and Jobcentre Plus district, 3c. Into-work rate by duration on Universal Credit and 3d. Into-work rate by age of Universal Credit customer in Get Britain Working: Labour Market Insights July 2026 involves the identification of whether a customer has moved into work. To calculate the into-work rate for a specific month we identify customers who are in the ‘Searching for work’ regime without earnings, where their assessment period end date falls in the preceding month. This is the base month, or the into-work denominator. The same customers are looked at in the following assessment period and any customers with earnings are included in the reporting month, or into-work numerator. The into-work rate is calculated by dividing the counts of these 2 groups. As the rate is based purely on the presence of earnings within assessment periods, the rate could miss some movements out of, and back into, work which happen within the time of 2 assessment periods if earnings are present in both.

Sustained employment rate

The focus of the sustainment rate of employment is on those who have started to earn and who have managed to immediately sustain earnings.

Producing the sustained employment rate analysis in 4. Sustained employment of Universal Credit Customers in Get Britain Working: Labour Market Insights July 2026 involves the identification of whether a customer has moved into work, as per above. To calculate the sustained employment rate for a specific month we identify customers without earnings who are in the ‘Searching for work’, ‘Working - with requirements’ and ‘Working - no requirements’ regimes, where their assessment period end date falls in the preceding month. The same customers are looked at in the following assessment period and any customers with earnings are included in the sustained employment denominator, as this identifies that they have moved into work. The same customers from the denominator are then looked at in the following 2 (or 5) assessment periods and any customers with earnings in all of these assessment periods are included in the 3-month (or 6-month) sustained employment rate numerator. The sustained employment rate is calculated by dividing the counts of the numerator by the denominator.

Measurement of worklessness

The analysis in 5. Measure of worklessness of Universal Credit ‘Searching for work’ customers in Get Britain Working: Labour Market Insights July 2026 looks at customers in the ‘Searching for work’ conditionality regime who have at least 6 consecutive months of no earnings.

Producing the worklessness rate involves the identification of whether a customer has been in the ‘Searching for work’ regime and out of work for at least 6 consecutive months. To calculate the worklessness rate for a specific month we identify customers without earnings who are in the ‘Searching for work’ conditionality regime. This is the worklessness rate denominator. The same customers from the denominator are then looked at to see if they have been in the ‘Searching for work’ conditionality regime for at least 6 consecutive months and received no earnings for at least 6 consecutive months. This is the worklessness rate numerator. The worklessness rate is calculated by dividing the counts of the numerator by the denominator. Individuals can count towards the indicator in multiple assessment periods, if worklessness continues or reappears. Each assessment period without earnings is a base month that the individual can be included in the indicator, if they are in the ‘Searching for work’ conditionality regime.

Young people aged 16 to 24 years who are not in education, employment or training across England’s regions

The analysis in 6. Young people aged 16 to 24 years who are NEET across England’s regions in Get Britain Working: Labour Market Insights July 2026 publication uses ONS LFS micro-data to make an estimate of those young people who are not in education, employment or training. The methodology behind constructing these estimates was altered in Get Britain Working: Labour Market Insights April 2026 meaning that, although the change is minor and the figures are similar, the figures published in this publication cannot be compared with similar figures in Get Britain Working: Labour Market Insights January 2026  and the Get Britain Working analytical annex . This methodology change was made to increase alignment with the ONS methodology which is explained below.

Estimates of young people who are NEET are calculated by first deriving a variable to distinguish those in education or training from those not in education or training. Then, by cross tabulating these variables by labour market status (in employment, unemployed or economically inactive as defined by the ILO framework), a NEET estimate for each region can be calculated. The data is initially disaggregated by single-age and gender and then combined to the 16 to 24 years age category for each region after the figures have been adjusted for missing responses.

For the regional NEET estimates, we use the same apportioning method for missing responses that the ONS use. Missing data is a particular problem with respondents who turn 16 years old during their household’s inclusion in the LFS sample, and who are then not interviewed as a 16-year-old. Their data is imputed from the previous wave due to non-response in the current wave of the survey and these cases are then treated as economically inactive. To account for the fact that the majority of these cases are likely still in education, the “missings” are split between being in education or training or not being in education or training, based on the proportions of cases without missing data. This is done regionally within each category defined by age, sex and economic activity because educational and employment characteristics are related to age and gender. If this apportioning method was carried out in aggregate (for all people aged 16 to 24 years in the region), different numbers would be produced than if carried out for females ages 16, males aged 17 and so on. These NEET numbers are then combined to create the overall NEET figure for people aged 16 to 24 years in each region.

The NEET rates are calculated by dividing the total number of NEET individuals in each region by the overall 16 to 24 population in each region and multiplying by 100. The England figures are calculated by summing the total number of young people and young people who are NEET in all of England’s regions. Because this age group represents a relatively small population subgroup, estimated from sample survey data, NEET estimates are particularly volatile. Our data is not seasonally adjusted, which may add to variability over time. To mitigate this inherent variability, NEET levels (available in the accompanying data tables) and rates were calculated using a rolling four-quarter average (January to March 2026), providing a more stable estimate over time.

In this edition, the methodology for the confidence intervals has been updated and cannot be compared with previous editions. Confidence intervals have been updated to better reflect the wave structure of the Labour Force Survey and the use of four quarter averages.

8. Limitations of the statistics

Limitations of all statistics derived from the Labour Force Survey and Annual Population Survey

The LFS – conducted by ONS – is a large, representative household study and provides detailed information related to the UK population’s activity in the labour market. The LFS is the basis of the headline labour market statistics produced by ONS.

The Annual Population Survey (APS) is a continuous household survey covering the UK, with the aim of providing estimates of main social and labour market variables between censuses, down to a local-area level. The APS is not a standalone survey; it uses combined data collected from two waves of the main LFS and data collected on local sample boost.

Sample surveys like the LFS and APS provide estimates of population characteristics, rather than exact measures. In principle, many random samples could be drawn, and each would give different results, because each sample is made up of different people who give different answers to the questions asked. The spread of these results is the sampling variability, which generally reduces with increasing sample size, but is present in all iterations of the survey data.

The micro-data estimates calculated use recent LFS and APS data which is subject to heightened volatility due to ongoing data quality challenges which the ONS are working on. The ongoing challenges with response rates, weighting approach and other aspects of the survey mean the LFS and APS-based labour market statistics are currently considered ‘official statistics in development’ until further review. Estimates of change should be treated with additional caution because of increased sample volatility of LFS and APS estimates and potential for elevated bias. This volatility is heightened when analysing smaller groups – for example, the 16 to 24 age group is a smaller population group and therefore estimates tend to be more volatile.

The LFS microdata used is also not seasonally adjusted, meaning changes from quarter to quarter may reflect typical changes in the labour market over the course of a year (for example, due to term times) as well as changes in the underlying strength of the labour market.

Young people aged 16 to 24 years who are not in education, employment or training across England’s regions

The analysis in 6. Young people aged 16 to 24 years who are not in education, employment or training across England’s regions Get Britain Working: Labour Market Insights July 2026 publication and the corresponding NEET levels in table 14 of the accompanying data tables is calculated using LFS micro-data of young people aged 16 to 24 years who are NEET across England’s regions. The limitations of this are explained above. To counteract these issues the data is calculated as a 4-quarter average (for the year ending January to March 2026). The NEET rates and levels are only given for England’s regions and not the other UK Nations (Scotland, Wales and Northern Ireland).

As the ONS’s method for missing response apportioning has been implemented into these statistics, assumptions are made surrounding how these “missings” are allocated. Although these assumptions are based on actual responses for the same age and gender category in each region, these cannot be measured directly. Additionally, the overall figures for England have been derived by totalling the number of young people and young people who are NEET in all of England’s regions. This means that, had the apportioning been carried out at country level and not per region, a slightly different result would have been produced.

The confidence intervals are based on pooled observations across four quarters, whereas the central estimates use a simple four quarter average. Consequently, there is some minor inconsistency between the estimation of central estimates and sampling variability. However, comparison of the results shows that the NEET rates and levels obtained from the pooled sample are very similar to those derived from the four-quarter average approach. The confidence intervals that have been calculated do not account for the complex survey design of the LFS.

9. Glossary

This glossary gives a brief explanation for each of the key terms used in the publication.

Assessment Period

The amount of UC someone is eligible for is calculated based on their circumstances each month. These are called ‘assessment periods’. A customer’s UC payment is based on their circumstances in the previous assessment period, and their first assessment period starts on the day they make a claim. Assessment periods are monthly and begin on the same day each month.

Customer (also claimant)

A person making a claim for a benefit.

Economically Inactive

Economically inactive people are not in employment but do not meet the internationally accepted definition of unemployment. This is because they have not been seeking work within the last 4 weeks or they are unable to start work in the next 2 weeks. The economic inactivity rate is the proportion of people aged between 16 and 64 years who are not in the labour force.

Education and Training

People are considered to be in education or training if they are enrolled on an education course and are still attending or waiting for term to start or restart; are doing an apprenticeship; are on a government-supported employment or training programme; are working or studying towards a qualification; have had job-related training or education in the last 4 weeks.

Young people not in education, employment or training (NEET)

Any 16 to 24-year-old who is not in any of the forms of education or training listed above and not in employment is considered to be NEET. As a result, a person identified as NEET will always be either unemployed or economically inactive.^{[footnote 1]}

Into-work Rate

The into-work rate is defined as the proportion of customers in ‘Searching for work’ who have earnings in one assessment period who did not have earnings in the preceding assessment period.

Jobcentre Plus (including Jobcentre Plus district)

Jobcentre Plus is a core part of support provided by the DWP for jobseekers in receipt of unemployment benefits and UC. It provides employment advice and uses knowledge of local labour markets to match unemployed customers to suitable job vacancies. It is also responsible for applying conditionality to the receipt of benefits.

Legacy Benefits

Universal Credit is replacing 6 benefits, commonly referred to as the legacy benefits:

• Income-based Jobseeker’s Allowance
• Income-related Employment and Support Allowance
• Income Support
• Working Tax Credit
• Child Tax Credit
• Housing Benefit

Limited capability for work and limited capability for work-related activity

Customers can report a health condition that restricts their ability to work either when they first claim UC or later as a change of circumstances. A customer can self-certify for up to 7 days, after which medical evidence is required. Once medical evidence, usually a fit note, is accepted by DWP, the customer joins the UC Health Journey and is referred for a Work Capability Assessment (WCA) if the health condition continues for more than 4 weeks. Prior to a WCA outcome, the customer remains in the ‘Searching for work’ regime but with tailored conditionality. Following a WCA, if not capable of work, a customer is found to have either limited capability for work (LCW) (and placed in ‘Preparing for work’) or limited capability for work and work-related activity (LCWRA) (and placed in ‘No work requirements’).

Move to Universal Credit

The Move to UC programme invited customers on legacy benefits to make a claim to UC to continue to receive financial support. 

Out of work

When someone is out of work they can be classified as unemployed or economically inactive.

Pre-COVID-19

The pre-COVID-19 reference period differs by data set and the methodology used. Throughout sections 3, 4 and 5c references to pre-COVID-19 are comparing to February 2020.

Section 5a uses January 2019 to January 2020 as the pre-COVID-19 reference period.

State Pension age

The current State Pension age is 66 years old for both men and women and is currently set to rise to age 67 between 2026 and 2028, and to age 68 between 2044 and 2046.

Sustained Employment Rate

The sustained employment rate is defined as the proportion of customers in ‘Searching for work’, ‘Working - with requirements’ and ‘Working - no requirements’ regimes who moved into-work and sustained earnings for 3 (or 6) months.

Unemployed

Unemployed people are without a job and have been actively seeking work within the last 4 weeks and are available to start work within the next 2 weeks. The unemployment rate is not the proportion of the total population who are unemployed. Rather, it is the proportion of the economically active population (people in work and those seeking and available to work, such as, employed and unemployed) who are unemployed. The ONS measure the unemployment level and rate for people aged 16 and over. The ONS unemployment rate follows internationally agreed guidelines set out by the International Labour Organisation.

Universal Credit

A single, usually monthly payment, administered by DWP. UC is now the primary working-age benefit. UC replaces all the following state support: income-based Jobseeker’s Allowance, income-related Employment and Support Allowance, Income Support, Working Tax Credit, Child Tax Credit and Housing Benefit.

Most customers will be of working-age, though customers can be over State Pension age if their partner is still of working-age. UC supports those on low incomes with their housing and living costs, as well as child and childcare support where appropriate. It is not just for those who are out of work; it is also for those who are working, but whose earnings are low enough to qualify. Customers must have capital of less than a set limit to be eligible.

UC completed its roll-out for new claims in Great Britain at the end of 2018 and is available for new claims throughout the UK. Legacy benefit customers will continue to transfer to UC over several years.

People on UC are assigned to one of 6 conditionality regimes^{[footnote 2]}:

1. Searching for work: not working, or with very low earnings. A customer is required to take action to secure work - or more or better paid work. The Work Coach supports them to plan their work search and preparation activity. Typical examples of people in this regime include jobseekers and self-employed in start-up period. Customers are only in this regime if they do not fit into one of the other regimes.

2. Working – with requirements: in work, but could earn more, or not working but has a partner with low earnings.

3. No work requirements: not expected to work at present. Health or caring responsibility prevents the customer from working or preparing for work. Examples of people on this include those in full time education, over state pension age, has a child under one and those with no prospect for work.

4. Working – no requirements: individual or household earnings over the level at which conditionality applies. Required to inform DWP of changes or circumstances, particularly at risk of earnings decreasing or job loss.

5. Planning for work: expected to work in the future/ lead parent or lead carer of child aged 1 (aged 1 to 2, prior to April 2017). The customer is required to attend periodic interviews to plan for their return to work.

6. Preparing for work: expected to start work in the future even with limited capability to work at the present time or a child aged 2 (aged 3 to 4, prior to April 2017). The customer is expected to take reasonable steps to prepare for working including Work Focused Interview.

Universal Credit Health Journey

Customers can report a health condition that restricts their ability to work either when they first claim UC or later as a change of circumstances. A customer can self-certify for up to 7 days, after which medical evidence is required. Once medical evidence, usually a fit note, is accepted by DWP, the customer joins the UC Health Journey and is referred for a WCA if the health condition continues for more than 4 weeks. Prior to a WCA outcome, the customer remains in the ‘Searching for work’ regime but with tailored conditionality. Following a WCA, if not capable to work, a customer is found to have either LCW (and placed in ‘Preparing for work’) or LCWRA (and placed in ‘No work requirements’).

Worklessness Rate

The worklessness rate is defined as the proportion of customers in the ‘Searching for work’ regime with no earnings and who continue to have no earnings for 6 consecutive months.

1. Young people not in education, employment or training (NEET), UK: May 2026 - Office for National Statistics (www.ons.gov.uk), published 28th May 2026. Available at: Young people not in education, employment or training (NEET), UK - Office for National Statistics ↩

2. Users should note that Universal Credit statistics uses the term ‘conditionality regime’ in place of conditionality groups and labour market regime. Available at: Universal Credit statistics: background information and methodology ↩