Official Statistics

Get Britain Working: Labour Market Insights – background information and methodology

Published 30 October 2025

Applies to England, Scotland and Wales

1. Introduction 

This background report accompanies the Get Britain Working: Labour Market Insights October 2025 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 are available alongside the publication. The statistics release and data tables can be found in the Get Britain Working: Labour Market Insights October 2025. 

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.  

HM 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 

You are welcome to contact us directly with any comments: labour.marketstatistics@dwp.gov.uk. 

Alternatively, you can contact 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 for DWP  benefits statistics.  

Analysis is quality assured (QA) by Department for Work and Pensions (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 is 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 have 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 tables, such as merged cells, has been avoided.

See the  Accessibility statement for 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 first in a new quarterly statistical publication series of labour market insights. The next edition is planned for 29 January 2026. The publication contains some core statistics which will be updated periodically, while other statistics will be published on a one-off basis or updated less frequently. Each 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 

People on Universal Credit in employment 

The analysis in 1a. People on Universal Credit in employment of the Get Britain Working: Labour market Insights October 2025 uses the Employment Characteristics Database (ECD), a DWP-derived dataset based on HM Revenue and Customs (HMRC) PAYE data, alongside other data sources described below. This is not a HMRC dataset. It reflects a combination of P14 and P45 employment records rather than the monthly Real Time Information (RTI) submissions used in operational systems. 

The ECD provides spell-based employment and pension histories from the 2004 to 2005 tax year onwards, including start and end dates, durations, and cumulative earnings. Employer characteristics information is sourced via linkage to the Inter-Departmental Business Register (IDBR), enabling sectoral classification using Standard Industrial Classification (SIC) codes.

It is created using HMRC P14 and P45 records. It is used within these statistics for identifying those who are employed and what sector they work within. Universal Credit (UC) administrative data is used only to identify UC status on the reference date. Someone is classed as being on UC if they have completed the UC claim process and accepted their Claimant Commitment. Methodology for UC data processing is covered in the next section. 

Flows between Universal Credit conditionality regimes and remaining in a conditionality regime 

The analysis in 3b. Flows between Universal Credit conditionality regimes and 3c. Remaining in a conditionality regime in Get Britain Working: Labour market Insights October 2025 uses UC administrative data which 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.  

Proportions in this publication are not comparable with the monthly statistics on the number of people on UC. This is because they are drawn from the underlying administrative databases rather than the extracts that comprise the monthly Official Statistics (which would not facilitate this analysis).

The metadata on Stat-Xplore for the People on UC Official Statistics  provides details of the methodology used for those statistics, which differs in various ways from the definitions in this publication. 

Into-work rates 

The analysis in 4a. The into-work rate, through to 4h. Into-work rates for customers on the Universal Credit Heath Journey in the Get Britain Working: Labour market Insights October 2025 explores into-work rates which are produced using a combination of UC administrative data and HMRC PAYE RTI data.

This additional data on a customer’s earnings, beyond that collected by DWP, 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. 

Local labour markets 

The analysis in 5a. Employment and inactivity by local labour market type and age, 5b. Into-work rate by local labour market type and 5c. Payrolled employment by local labour market type in Get Britain Working: Labour market Insights October 2025 explores the experiences of local labour markets using DWP developed local labour market types. To create the local labour market types, we used cluster analysis. For our analysis this was based on 6 local labour market variables. These variables and the data sources used to create them are detailed in table 1.  

Table 1: Variables used to classify local authorities

Variable	Data source
A. Number of UC Searching for Work and Jobseeker’s Allowance customers in the local authority	ONS Claimant Count – includes UC Searching for Work and Jobseeker’s Allowance claims - 2023[footnote 1]
B. Local authority employment rate	ONS Annual Population Survey - 2022 to 2023[footnote 2]
C. Local authority working-age work-limiting disability rate	ONS Annual Population Survey - 2022 to 2023 average
D. Proportion of local authority working-age population with at least level 4 qualifications[footnote 3]	ONS Annual Population Survey - 2022-23 average
E. Local authority musculoskeletal condition rate	Office for Health Improvement and Disparities (OHID) Local Authority Health Profiles - 2023[footnote 4]
F. Proportion of local authority population with a mental health condition	OHID Local Authority Health Profiles - 2017

The cluster analysis uses the Annual Population Survey (APS), micro-data provided to DWP by the ONS. The APS is a continuous household survey, covering the UK. The topics covered include employment and unemployment, as well as housing, ethnicity, religion, health and education. The purpose of the APS is to provide information on important social and socio-economic variables at local levels. The published statistics enable monitoring of estimates between censuses for a range of policy purposes and provide local area information for labour market estimates.

Employment and inactivity by local labour market type and age

The analysis in 5a. Employment and inactivity by local labour market type and age in Get Britain Working: Labour market Insights October 2025 uses the APS. The observed data periods are January 2019 to December 2019 and July 2024 to June 2025.

Into-work rate by local labour market type

The analysis in 5b. Into-work rate by local labour market type in Get Britain Working: Labour market Insights October 2025 explores into-work rates which are produced using a combination of UC administrative data and HMRC PAYE RTI data. This additional data on a customer’s earnings, beyond that collected by DWP, 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. The observed data period is July 2024 to June 2025.

Payrolled employment by local labour market type

The analysis 5c. Payrolled employment by local labour market type in Get Britain Working: Labour market Insights October 2025 is produced using HMRC PAYE RTI data taken from the monthly publication on payroll employment and earnings from ONS and HMRC.

7. Methodology

People on Universal Credit in employment

The analysis in 3a. People on UC in employment in Get Britain Working: Labour market Insights October 2025 explores the sectors of employment for people on Universal Credit (UC), on 13 March 2025. The focus is on employment status and sectoral distribution, using robust administrative data sources.

Someone is classed as employed if they have an active or multiple active employment spells in the Employment Characteristics Database (ECD), supported by earnings and employer data. Employment spells are derived from the ECD, which combines P14 (annual earnings and tax) and P45 (start/end dates) records. Where both sources are available, P45 dates are prioritised for accuracy. Start dates and end dates are supplied by employers and are dates of contractual employment. An individual can be contractually employed but not receiving pay.

Sector classification is based on SIC 2007 codes, assigned to PAYE schemes via IDBR linkage. Where employers operate in multiple sectors, the primary SIC code is used, with caution applied to potential misclassification. A person’s sector of employment is the primary industry of the employer, as determined by the SIC code associated with the PAYE scheme in the ECD.

The analysis uses a snapshot approach to identify individuals employed on 13 March 2025, that is having an employment spell with a start and end date covering this date, aligning with the data used for the People on Universal Credit statistics. For individuals with multiple concurrent employments, the most recently started spell is selected for sectoral analysis.

Flows between Universal Credit conditionality regimes and remaining in a conditionality regime

Alongside this publication a series of data tables has been included showing movements between different UC conditionality regimes each month from January 2019 to May 2025, including a breakdown by employment status. The analysis presented in 3b. Flows between UC conditionality regimes in Get Britain Working: Labour market Insights October 2025 uses these tables to explore flows between different conditionality regimes.

The analysis in 3c. Remaining in a conditionality regime, looks at the percentage of people remaining in a conditionality regime over time. This analysis is not derived from the flows data tables.

Both 3b. Flows between Universal Credit conditionality regimes, and 3c. Remaining in a conditionality regime, are derived from UC administrative data. This data is converted into an individual level dataset tracking people’s conditionality regime and earnings over time. Conditionality flows are then calculated looking at the month-on-month changes in an individual’s conditionality. Employment status is tracked by whether an individual has received PAYE earnings according to the UC system.

Conditionality journeys look at monthly conditionality changes, using the conditionality at the end of the assessment period as their conditionality for the calendar month in which the assessment period starts. It is possible for individuals to change conditionality multiple times in a calendar month, so this is a simplifying assumption that may hide individual volatility.

Alongside this publication, a series of data tables has been included showing movements to and from different UC conditionality regimes and employment statuses each month between January 2019 and May 2025. All values in 3b.Flows between UC conditionality regimes have been derived directly from these data tables. Figures for onflows in Figure 2 are calculated by summing all flows in a given month where the conditionality before flow is ‘Not on UC’ and the conditionality after flow is not equal to ‘Not on UC’. For off-flows the same calculation is done, but the conditionality conditions are flipped. Figures 3 and 4 take the values for Figure 2 but look at the specific conditionality regime someone flows into or flows out of. Table 1 takes the monthly flows for each conditionality combination (including flows on and off UC) from January 2024 to December 2024. The mean average of these months is then calculated and the top 5 mean average flows between difference conditionality regimes are shown in the table.

The analysis in 3c. Remaining in a conditionality regime is based on different analysis and cannot be derived from the flows data tables. These are generated from the administrative data by counting the number of individuals who stay in the same conditionality regime for 3, 6, 12 and 24 months in a row with no flows to other regimes. This is then divided by the total number of people who flowed into that regime in the first month (month 0) to get a percentage, which is presented, by month in the table.

These statistics may be revised at a later date based on the outcome of the Universal Credit Caseload Methodology review.

Into-work rates

Producing the into-work rate analysis in section 4. of Get Britain Working: Labour market Insights October 2025 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.

The caseload characteristics analysis is based on those customers in the base month, or into-work denominator.

Employment and inactivity by local labour market type and age

The statistics are calculated using Annual Population Survey (APS) micro-data of the economically inactive population, split by main reason for economic inactivity and age (between 16 to 64-year-olds). Some reasons for inactivity have been grouped to provide a more coherent narrative. Additionally, there are age group breakdowns for ages 16 to 24, 25 to 49, and 50 to 64. This has been matched to local labour types. A percentage point change is used to determine the change in inactivity for each local labour market type since the COVID-19 pandemic began.

Employment and inactivity by local labour market type and age

In 5a. Employment and inactivity by local labour market type and age of Get Britain Working: Labour market Insights October 2025, local labour market types have been matched and an arithmetic mean is used to produce a yearly average by local labour market type.

Payrolled employment by local labour market type

The analysis in 5c. Payrolled employment by local labour market type in Get Britain Working: Labour market Insights October 2025 calculates the percentage change in employees payrolled from February 2020 to May 2025. The number of payrolled employees is defined as the number of people receiving paid renumeration included in PAYE RTI within the reference period, including people who have not done work but are an employee - such as those on paid leave. The data is matched to local labour market types to determine the percentage change in employees payrolled for each local labour market type.

8. Limitations of the statistics

People on Universal Credit in employment

There are some limitations to the analysis in 3a. People on Universal Credit in employment in Get Britain Working: Labour market Insights October 2025. People who are self-employed are not included in this analysis – only people who work as employees. This means that the analysis undercounts the number of people on Universal Credit (UC) that are employed.

Additionally, sectoral classification may be affected by:

• reduced coverage of Standard Industrial Classification (SIC) information for newly created businesses in the Inter-Departmental Business Register (IDBR)
• large employers reporting under a single enterprise-level SIC despite operating in multiple sectors
• the SIC 2007 framework may not fully capture hybrid or emerging industries
• Employer’s PAYE schemes are sometimes restructured or reclassified, meaning their sectoral grouping may change year on year

Flows between UC conditionality regimes, remaining in a conditionality regime and into-work rates

For all the analysis 3b. Flows between UC conditionality regimes and 3c. Remaining in a conditionality regime a customer’s circumstances in Get Britain Working: Labour market Insights October 2025 are taken as at the start of their assessment period, and a month relates to the month where an assessment period starts.

For the into-work rate analysis in section 4. a customer’s circumstances are taken as at the end of their assessment period, and a month relates to the month where an assessment period ends.

It is possible for individuals to change conditionality multiple times in a calendar month, so this is a simplifying assumption that may hide individual volatility. 

For age level breakdowns across this analysis a small number of individuals have a missing age variable in the underlying UC data and are therefore removed from these figures.

Local labour markets

There are some limitations to the Annual Population Survey (APS) data used for the cluster analysis to determine the local labour market types used in 5a. Employment and inactivity by local labour market type and age, 5b. Into-work rate by local labour market type and 5c. Payrolled employment by local labour market type in Get Britain Working: Labour market Insights October 2025. While the Office for National Statistics (ONS) considers the quality of the APS to be robust for national and headline regional estimates, there are concerns with the quality of estimates for smaller segments of the population, such as local authority geographies. ONS outputs produced using the APS data, including those disseminated on the ONS’ NOMIS website, are now labelled as ‘official statistics in development’.^{[footnote 5]} There is greater uncertainty associated with estimates at a local authority level compared to estimates at a regional or national level. Areas with smaller populations will, other things being equal, have smaller samples and thus wider margins of error.

There are some limitations with the cluster analysis used to determine the local labour market types. The groupings are only based on the 6 variables listed above. The choice of variables to construct the groups is, to an extent, subjective. The variables are intended to provide a good description of labour market strengths and weaknesses. We did however experiment with a number of different labour market variables and used decision rules to narrow down our choice to the 6 listed above. Ideally in cluster analysis you want dimensionality – i.e. variables that relate to the central construct of interest (in this case the local labour market) but are not highly correlated with each other. In this way you get cluster groups forming out of combinations of high and low values of the variables. This explains why there are some variables (for example wages or vacancy rates) that might seem relevant labour market measures that are not included in the analysis.

The groupings will vary depending on the variables selected and the time period to which the data pertains, so they should not be taken as rigid groupings that define the characteristics of group members. Our analysis is a data driven exercise to generate groupings that will be practically useful rather than intended to identify fixed qualities of local areas.

The groupings are of local authorities – these are administrative groupings rather than areas that might be recognised as spatially distinct labour markets. The reason for this is that most sub-national data is readily available at the local authority level and hence it made sense to maximise the data available for this exercise. In addition, policy devolution is at the local authority or the combined authority level, so it makes sense to produce analysis that matches this.

Employment and inactivity by local labour market type and age

The analysis in 5a. Employment and inactivity by local labour market type and age in Get Britain Working: Labour market Insights October 2025 also uses the APS. Sample surveys like the 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 we have calculated use recent APS data which is subject to heightened volatility due to ongoing data quality challenges with the Annual Population Survey as explained above. The ongoing challenges with response rates and other aspects of the survey mean ONS labour market statistics based on the APS are currently considered ‘official statistics in development’ until further notice. Because of increased volatility of APS estimates, estimates of change should be treated with additional caution.

9. Glossary

This glossary gives a brief explanation for each of the key terms used in the publication. Further details on these definitions, are available on request from the DWP Labour Market Analysis team at: labour.marketstatistics@dwp.gov.uk.

Assessment Period

The amount of Universal Credit (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 and/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.

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 (JCP) 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 invites 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.

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, meaning employed added to 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 6]}

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

1. Number of UC Searching for Work and Jobseeker’s Allowance customers in the local authority. Available at: Office for National Statistics ↩

2. Nomis - Official Census and Labour Market Statistics. Local authority employment rate ↩

3. What qualification levels mean. ↩

4. Department for Health and Social Care, Fingertips Public Health Profiles, Musculoskeletal health profile ↩

5. Stephanie Howarth to Ed Humpherson: Request to suspend APS accreditation – ONS Regulation. Available at: Office for Statistics Regulation. ↩

6. 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. ↩