Accredited official statistics

Family Resources Survey: background information and methodology

Updated 12 May 2023

1. Introduction

This report accompanies the main Family Resources Survey 2020 to 2021 report.

The purpose of this report is to provide further contextual information to aid understanding of the statistics presented in the main report and detailed tables. It outlines points to note as well as strengths and limitations of the information presented in each section of the main report; alternative data sources; as well as changes to the survey this year compared to last year.

A detailed description of the Family Resources Survey (FRS) methodology, fieldwork operations, data processing and quality assurance are presented within the relevant sections in this report. These descriptions are intended to help users in the use and interpretation of FRS 2020 to 2021 data.

The FRS is a major study of income levels in the UK. Given its prominence in the landscape of income data resources, a decision was taken to continue with fieldwork throughout the 2020 to 2021 financial year, albeit recognising the need for several coronavirus (COVID-19) related adaptations. The aim was to maintain the output of FRS estimates and data for 2020 to 2021, the first twelve months of the pandemic, because of the depth of insight the FRS gives on household circumstances.

The coronavirus (COVID-19) pandemic impacted the FRS at several levels, all of which have some bearing on the survey results. Later sections discuss the changes to the survey questionnaire and fieldwork approaches, both of which were materially different to a typical FRS year. Later sections also set out the difference in response rate, and composition of responses, achieved this year. There have also been changes to the production process of the survey results, in particular around the grossing regime and suppression policy applied to estimates.

Editorial team

Alex Brandon-Bravo, Anna Britton, Claire Cameron, Annabel Connolly, Marwan Hassan, Harrison Jones, Sheridan Lomas, Charlotte McCaughey, Justyna Owen, Clive Warhurst.

Feedback

If you have any comments or questions about any aspect of the FRS, or are interested in receiving information on consultations, planned changes, and advance notice of future releases, please contact: Claire Cameron, Surveys Branch, Department for Work and Pensions. Email: team.frs@dwp.gov.uk

Acknowledgements

In this year of challenging circumstances, we wish to give special acknowledgement to:

• all the respondents in households across the United Kingdom who agreed to and made the time to be interviewed
• interviewers from the Office for National Statistics, NatCen Social Research and the Northern Ireland Statistics and Research Agency who adapted to the change, from face-to-face to telephone interviewing
• colleagues in those organisations who supported us in developing in-year questionnaire changes, to capture important information about the pandemic
• all those who have contributed towards the Family Resources Survey 2020 to 21 publication, through providing quality assurance and feedback
• our web support team
• the UK Data Service, who distribute our research data

2. Background

The Family Resources Survey (FRS) is a continuous survey which collects information on the income and circumstances of individuals living in a representative sample of private households in the United Kingdom. The survey has been running in Great Britain since October 1992 and was extended to cover Northern Ireland in the survey year 2002 to 2003.

The primary objective of the FRS is to provide the Department for Work and Pensions (DWP) with information to inform the development, monitoring and evaluation of social welfare policy. Detailed information is collected on: respondents’ incomes from all sources including benefits, tax credits and pensions; housing tenure; caring needs and responsibilities; disability; expenditure on housing; education; childcare; family circumstances; child maintenance; household food security.

Microsimulation is central to DWP’s use of the data. Therefore, careful attention is paid to the accurate collection of information followed by meticulous data processing, editing, and quality assurance.

The FRS data are designated by the Office for Statistics Regulation (OSR) as National Statistics. The FRS provides the data for a number of other DWP National Statistics publications:

• Households Below Average Income
• Pensioners’ Incomes Series
• Income-Related Benefits: Estimates of Take-up

The survey contains information of much interest to other government departments, particularly for tax and benefit policy analysis by Her Majesty’s Revenue and Customs and Her Majesty’s Treasury. The survey is also used extensively by academics and research institutes for social research purposes.

Status and Development

These statistics underwent a full assessment against the Code of Practice for Statistics in 2011 and were confirmed as National Statistics in November 2012 by the Office for Statistics Regulation.

The OSR published its Review of Income-based Poverty Statistics on 19 May 2021. As announced in our Statistical Work Programme, we have taken several recommendations on board. This release includes the following recommendations which were relevant to the Family Resources Survey data and publication:

• the Alternative Data Sources section of this Background Information and Methodology report has been expanded with additional links to sources to provide clearer and more detailed signposting to other income-based poverty statistics

• DWP and Office for National Statistics (ONS) have worked together to provide clear guidance about the strengths and limitations of the FRS household survey, this year taking particular account of the impacts of the coronavirus (COVID-19) pandemic on data collection methods and the quality of the achieved sample data

• particular regard has been given to how under-sampled groups could accurately be presented in the population-level statistics, clearly setting out the changes in the methodology to adjust for this and being transparent about any remaining areas for concern

• the use of an accessibility checklist has further improved the accessibility of both our main publication text, charts and images in HTML, and also the Excel and ODS versions of our accompanying tables. We have also reviewed our supporting guidance to ensure accessibility to lay users

• in both the technical advice provided alongside the publication, and in the supporting documentation provided to the UK Data Archive with the dataset, we have been clear on the appropriate uses and quality of the statistics and data, being transparent in how this may differ in this COVID-19 impacted year

In addition to further tables by ethnicity, to respond to Cabinet Office requirements and the inclusion of FRS based statistics in Ethnicity facts and figures ethnicity representation rates are now calculated from known declarations and exclude ‘choose not to declare’ and ‘unknown’.

Please see the DWP Statistical Work Programme for more details.

A summary of historical improvements since the latest review by the Office for Statistics Regulation includes:

• the timeliness of the publication has been improved so that, since the 2015 to 2016 survey year, reports have been released within 12 months of the completion of the survey
• audits of processing methodology have been made, and subsequent changes to imputation methodology have led to improvements in the quality of statistics
• the publication code has been revised allowing both a more streamlined process for publication and a clearer approach to update for annual changes, while retaining the core structure for consistency and harmonisation
• a review of the grossing regime was conducted to follow the move to use of 2011 Census results in the production of mid-year population estimates by ONS. The new grossing regime was implemented in the 2012 to 2013 publication
• value has been added in line with DWP statistics reporting practices. Publications have been made significantly shorter to enable a focus on commentary and analysis
• a publication consultation was held in Autumn 2020 to capture views of users of the publication
• the content of the FRS has evolved in response to user needs, with the addition of additional regular chapters for emerging areas of increased policy interest such as Self Employment and Household Food Security
• the previous, March 2021 publication included a section on Household Food Security for the first time. It included the proportion of households with low or very low household food security and:
  • (i) whether or not they receive state benefits
  • (ii) educational attainment
  • (iii) overall level of income
• new questions and variables are added each year, as necessary to reflect changes in policy, such as benefit changes specific to some areas of the UK, and in different policy fields. This enables related policy analysis to be conducted

3. Uses of FRS Data

The FRS is used extensively both within and outside DWP. The main uses are as follows.

Households Below Average Income (HBAI)

The HBAI publication uses household disposable incomes, adjusted for household size and composition, as a proxy for material living standards or, more precisely, for the level of consumption of goods and services that people could attain given the disposable income of the household in which they live.

Pensioners’ Incomes Series

The HBAI dataset is used in the Pensioners’ Incomes Series, the Department’s analysis of trends in components and levels of pensioners’ incomes.

Income-Related Benefits: Estimates of Take-Up

The Estimates of Take-Up figures are based on a combination of administrative and survey data. The FRS provides information about people’s circumstances, which is used to estimate numbers of people who are not claiming benefits to which they may be entitled.

DWP Policy Simulation Model and other policy analysis

DWP’s Policy Simulation Model (PSM) is used extensively for the development and costing of policy options. FRS responses are uprated to current prices, benefits and earnings levels and can be calibrated to the DWP Departmental Report forecasts of benefit caseload. Using FRS data has made it possible to model some aspects of the benefit system which could not be done previously, for example severe disability premiums or allowances for childcare costs.

In addition to their use in formal modelling, FRS data play a vital role in the analysis of patterns of benefit receipt for policy monitoring and evaluation, and benefit forecasting.

Other government departments and the wider research community

The survey is widely used by other government departments, including Her Majesty’s Treasury, Her Majesty’s Revenue and Customs, the Department for Environment, Food and Rural Affairs and the Children’s Commissioner’s Office (an executive non-departmental public body, sponsored by the Department for Education).

The Department for Communities Northern Ireland uses the FRS to produce similar reports to those from DWP, which are focused on Northern Ireland.

Researchers and analysts outside government can also access the data through the UK Data Service.

The Office for National Statistics produces small area model-based income estimates. These are the official estimates of annual household income at the middle layer super output area (MSOA) level in England and Wales. The estimates are produced using a combination of survey data from the Family Resources Survey and previously published data from the 2011 Census plus a number of administrative data sources.

The Race Disparity Unit published the first in a series of summaries of data on their ‘Ethnicity Facts and Figures’ website in June 2019. Ethnicity Facts and Figures provides information about the different experiences of people from a variety of ethnic backgrounds. It gathers data collected by Government in one place, making it available to the public, specialists and charities. The FRS contributes data on state support, that is, receipt by ethnicity and type of benefit.

4. Points to Note

Impact of Coronavirus (COVID-19)

FRS 2020 to 2021 is an important data resource, which gives several insights into British household incomes during the coronavirus (COVID-19) pandemic. Nevertheless, caution should be taken when interpreting some of the statistics reported in this release. Each of the sections below provides further insight into the challenges to the results which were presented by the pandemic. The first section outlines several overarching factors which affected every topic area in the survey. Subsequent sections then step through each chapter, to discuss the impacts specific to them. This is contextual detail, which aims to show the strengths and limitations of the survey. It is intended to aid users in their interpretation of FRS 2020 to 2021 data.

The data in this report are from interviews conducted between April 2020 and March 2021. The whole of the fieldwork year was affected by the coronavirus (COVID-19) pandemic, and there are several overarching ways in which the pandemic might have affected the survey results. Most of these stem from the achieved sample, including the data collection method, the response rate achieved and the distribution of characteristics among respondents. All of these represent ways in which the 2020 to 2021 survey is different to previous survey years. The key changes to consider are:

• changes in people’s behaviours and circumstances
• changes in the methods used to contact survey participants and response
• change in the mode, to telephone interviewing

Changes in people’s behaviours and circumstances

It is not possible to outline all issues that affected either participation in the FRS itself, or how differently circumstances were reported this year, in comparison to previous years. But from a social research perspective, it is clear that the pandemic not only changed the UK labour market and household circumstances, but also our ability to measure them. This is because our measurement relies on data collected from a survey of households.

Many societal changes took place during 2020 to 2021, including an increase in remote working, home-schooling and the introduction of social distancing, and all of these could have impacted survey participation. Other factors, such as personal restrictions, health, and attitudes to social interaction may also have influenced the amount and type of data that the survey has been able to collect.

This extends to family formation, which is the key building block of FRS results. Pandemic restrictions may have resulted in differences to previous surveys, as people chose to form support bubbles with friends and family. This implies a reduction in house sharing amongst unrelated adults and an increase in multi-generational households (as adult children moved in with their parents or parents moved in with their children).

FRS data for 2020 to 2021 supports this view. Compared to 2019 to 2020: the percentage of adults living with cohabiting adults has increased (13.6% to 14.7 %); the percentage of adults living with unrelated (not cohabiting) people has decreased (5.0% to 2.9%), and the number of households containing multiple generations has increased (15.3% to 16.2%).

It should be noted that many of these “additional adults” in the household may not have been captured by the FRS, if they were not considered to be usually resident at the address. Moreover, and later on in the survey year, it is possible that respondents ceased to view such living arrangements as temporary and would instead regard them as being permanent (for survey purposes). The FRS results are structured to minimise such in-year effect, as they relate to the survey year as a whole.

It is also the case that the government response to the pandemic had a significant effect in supporting incomes, and on the UK labour market: government interventions allowed for the furloughing of workers, which affects both reported incomes and also other variables such as working hours. This factor sits alongside wider labour market and business developments, whereby some businesses ceased operations, and many others altered their working practices. All of these factors may have impacted the type and number of respondents taking part in the FRS.

Changes in the methods used to contact survey participants and response

The approach to engage with respondents to encourage them to participate in the survey did evolve during the year, whereas in a normal survey year there is a consistent approach throughout. This was partly because of changing COVID-19 restrictions during the year, and partly the need to set up new fieldwork operations at pace early in the year.

Full details of how engagement with respondents evolved is given in the Methodology section.

Change in the mode, to telephone interviewing

In mid-March 2020, as a result of Government restrictions introduced in response to coronavirus (COVID-19), face-to-face interviewing was halted across the UK. For this survey year, starting in April 2020, FRS processes were changed to allow data collection by telephone. These changes remained in place for the whole of the 2020 to 2021 survey year. Full details of how the survey adapted to a telephone basis are given in the Methodology section.

Ordinarily such changes would not be made without thorough testing to examine the impact on the data collected. In the time available, this was not possible. It is therefore difficult to quantify precisely how far the 2020 to 2021 survey results have changed since previous surveys because the mode was by telephone, as distinct from real-world changes.

In broad terms, DWP’s assessment is that, where data has been collected, it is not materially different to what would have been collected from the same respondent face-to-face. This is because the FRS is almost wholly a survey of factual information rather than attitudinal information. Wherever possible, as part of the quality assurance process, results have been compared both with other data sources, and to previous FRS years.

However, the FRS achieved sample this year is significantly smaller than usual, with around 10,000 households interviewed in 2020 to 2021 (down from between 19,000 and 20,000 in a normal year). In terms of the effect of the smaller sample on confidence in the results, the later section on Reliability of estimates sets out how much more uncertain this year’s results are, when compared with a normal FRS year.

The change in fieldwork approach also affected the composition of the FRS achieved sample. For example, there were significantly more outright owners and fewer renters in the sample. There was also a skew toward older respondents (aged 65 or over), and fewer households with children than in 2019 to 2020. Later sections discuss the impacts and limitations this brings to results. It should be noted that the impact of several aspects of difference have been mitigated by an alteration to the survey grossing regime (and the later section on grossing outlines the steps taken to improve the representativeness of the sample).

Whilst some change from year to year can be expected as a result of real-world changes in household circumstances, the pandemic would likely have prevented some households from taking part in the survey who would otherwise have done so (for example, home schooling, caring responsibilities, and ill health meant that some households would be less inclined to respond).

Income and State Support

The FRS captured information about people on the Coronavirus Job Retention Scheme (CJRS) via a new set of interview questions. Employees who were out on furlough were classified as employed, but temporarily away from work. This will mean that workers on furlough will still count towards the number of people in employment (or the employment rate). The classification of Economic Status remains the same as in previous years, with anyone on furlough in the Benefit Unit being classified as an employee.

The calculation of ‘income from employment’ uses Wages which are treated as income from employment (as opposed to state support), irrespective of any support payments from CJRS that the respondent’s employer was receiving in respect of their employment.

The calculation of earnings uses actual pay (GRWAGE) over usual pay (UGROSS) for people on furlough. This aligns to the Annual Survey of Household Earnings (ASHE) employee earnings methodology, which uses actual payments made to the employee from company payrolls.

The calculation of self-employed income and then total individual income does not include grants received from the Self-Employment Income Support Scheme (SEISS).

The decision to treat both CJRS and SEISS in this way follows our discussions with experts.

All income figures are presented gross of tax, national insurance and before other deductions from wages except where noted.

It is thought that household surveys underestimate income from both self-employment and investment income. We rely on respondent recall of very detailed financial information across a comprehensive range of income sources. Some of these are hard for respondents to recall. The FRS interviewers ask respondents to check pay slips, tax returns and other financial paperwork at the time of the interview. This helps to improve the reliability of what respondents report they earn.

The FRS captures detailed information on benefit receipt. In most cases this is analysed at a benefit unit (family) level because income-related benefits are paid to families as a whole rather than being separately assessed for each individual.

Some respondents do not know or do not have the necessary information to answer specific questions about individual benefits which makes it difficult to collect accurate information. (State Benefits on the Family Resources Survey (WP115))

Relative to administrative records, the FRS under-reports numbers on benefit (caseload). See Methodology Tables M.6a and M.6b for a comparison of (i) numbers on benefit (caseload) and also (ii) the average £ per week received, showing any differences between DWP administrative data and the numbers implied by the survey results. However, one of the strengths of the FRS is that it collects many personal and family characteristics which are not available from administrative sources. This means that the FRS can be used to analyse income and benefit receipt in ways which are not possible from administrative sources alone.

Tenure

In 2020 to 2021, the achieved sample had a higher proportion of households in the higher Council Tax bands (band C and above) than in recent survey years. This was reflected in the accommodation mix of the achieved sample, which showed a higher proportion of owner-occupier properties (rather than rented), and also a higher proportion of detached houses (rather than flats or terraced or semi-detached houses).

However, the difference made to survey estimates has been minimised by the grossing regime applied. This uses both Council Tax band and also the numbers renting versus owning as control totals, which will weight publication results to the real-world numbers seen of each different type of property.

It should be noted that the grossing regime was more effective in enabling a representative dataset of English households, than in Scotland or Wales, where sample sizes were relatively smaller. See Methodology Table M3.

As presented in the FRS, the “social rented sector” is a combination of the categories “Rented from Council” and “Rented from a Housing Association”. These categories are combined because some housing association tenants may misreport that they are council tenants. For instance, where their home used to be owned by the council and although ownership has now transferred to a housing association, the tenant may still think that their landlord is the council (local authority).

FRS outcomes are similar in composition to the English Housing Survey (EHS), but it should be noted that the EHS also switched from face-to-face interviews to telephone, so the ability to contact interviewees would have been similar to that of FRS interviewers.

Disability

There were changes in the prevalence of disability reported in 2020 to 2021 FRS, with a two percentage-point increase in the proportion of working-age adults reporting a disability, and a four percentage-point decline in the proportion of those over State Pension age reporting a disability.

For those of working age, the change may be linked to restrictions limiting movement outside of the home. For those above State Pension age, the reduction may be a consequence of the change in mode, as fewer participants reported impairments in hearing, memory or vision.

Results show a substantial increase in the number of disabled people who classified their impairment as ‘Other’. In the early months of the pandemic, those asked by the NHS to shield in the home may have been more responsive to the telephone survey. Many of the conditions covered by the shielding guidance – for example, conditions causing a weakened immune system – may have been reported as ‘Other’ because they do not fit neatly into another category of impairment.

Our assessment is that while some of the change in disability may have been genuine, we believe a substantial portion of it was due to sample bias. This is because we are unable to explain some of the changes in the sample with reference to changes in the real world. Therefore, they are likely to be a consequence of the change in mode rather than a real-world reduction in prevalence. It was not possible to further adapt the FRS grossing regime to adjust for this observable bias.

It has been recognised that in this survey year the FRS may be reporting a wider disability employment gap when compared with other sources. The FRS should be looked at in conjunction with both the Annual Population Survey (APS) and the Labour Force Survey (LFS).

The APS aims to provide more detailed analysis of key labour market indicators (employment, unemployment, and economic inactivity) for sub-groups of the population including disability. The latest analysis considers long-term trends as well as the more recent impacts of the coronavirus (COVID-19) pandemic.

The APS is not a stand-alone survey: it uses data combined from two waves of the main Labour Force Survey (LFS), alongside a local sample boost. The APS is a recommended source for employment statistics for smaller groups of the population. The LFS is the source recommended for employment-related statistics, such as estimates of the number of people in employment and is the key source for trend data on different measures of disability employment. The latest releases can be found in the Alternative Data Sources section of this report.

The way in which disabled people have been identified in the FRS has changed over time. From 2002 to 2003 statistics were based on responses to questions about barriers across a number of areas of life; figures from 2004 to 2012 are based on those reporting barriers across nine areas of life.

From 2012 to 2013 a person is considered to have a disability if they regard themselves as having a long-standing illness, disability or impairment which causes substantial difficulty with day-to-day activities. This updated definition is consistent with the core definition of disability under the Equality Act 2010, and complies with harmonised standards for social surveys published in August 2011 and updated in June 2019

An impairment is different to a medical condition. It looks at the functions that a person either cannot perform or has difficulty performing because of their health condition. For example, glaucoma is a medical condition but being unable to see or being partially sighted is an impairment

Some people classified as disabled and having rights under the Equality Act 2010 are not captured by this definition, such as people with a long-standing illness or disability which is not currently affecting their day-to-day activities. More information is available from the GSS Policy Store.

Care

FRS respondents are asked if they receive care from anyone. This includes both professional help – paid-for care from the local authority, health professionals or domestic staff – but it also includes informal care. This is any care where their carer is not doing it as a paid job; it can be for many, or only a few hours a week, and can take several different forms. The survey is intentionally not prescriptive about what counts as care; it could, for example, include going shopping for someone, or helping them with paperwork.

Where respondents are receiving care at least once a week, they are further asked about the nature and frequency of that care. FRS respondents are also asked if they provide care to someone else, on an informal basis. That person could be living with them, in their household, or they could live somewhere else (outside the household).

Pension participation

The FRS pension participation reference tables present data for both ‘all adults’ and ‘working-age adults only’. Those over State Pension age are often excluded from analysis of pension participation in other publications, although they could continue to work and participate in pension schemes. The ‘all adults’ category allows data for this group to be represented and also provides continuity across all chapters within the FRS.

Employer-sponsored pensions comprise any company or occupational pension scheme run by an employer including group personal pensions and group stakeholder pensions.

Individual pensions include individual stakeholder pensions and retirement annuity contracts as well as personal pensions.

Although the numbers are relatively small, self-employed people can contribute to an employer-sponsored pension scheme, for a variety of reasons. Doctors and dentists in private practice can be members of an occupational scheme. People who have recently become self-employed can continue to contribute to their previous employer scheme and people whose main job is self-employed, may work part-time as an employee and contribute to an employer scheme. These circumstances are captured within the FRS tables under the ‘Self Employed – Other’ category.

Savings and investments

The FRS does not capture information on non-liquid assets. Physical wealth and pensions accruing are not included in FRS estimates. The survey also does not capture detailed information on expenditure (except for housing costs). Therefore, it is not possible to show how households are coping financially, in terms of income versus outgoings.

However, the FRS does capture information on liquid financial assets, referred to in the survey as ‘savings and investments’. Estimates for savings and investments should be treated with caution, as they are likely to be under-estimates, since respondents often inaccurately report their account details.

The process of gathering information on savings and investments was the same as in previous survey years, but with adjustments to the pound thresholds:

• respondents are asked, as a benefit unit, to say which of several £ bands their total level of savings and investments are in

• benefit units that report between £1,500 and less than £30,000 (£20,000 in 2019 to 2020) (42% of benefit units) are then asked, for each of their accounts and assets, how much each is worth and how much interest they accrue. The total level of savings and investments is then calculated using this set of reported values

• benefit units with reported savings and investments outside those limits – below £1,500 or above £30,000 (£20,000 in 2019 to 2020) (58% of benefit units) – are only asked how much interest each account and asset accrue. These respondents are also asked to estimate the value of all their current accounts and basic bank accounts combined

It should be noted that in April and May question changes that were approved prior to the coronavirus (COVID-19) pandemic were included within the questionnaire. For interviews in these two months respondents with estimated total assets of between the wider scope of £100 and £30,000 and benefit units where respondent (or partner) were of State Pension age with reported total assets between £100 and £200,000, answered the ‘Benefit Unit’s Assets block of questions with more detail about their savings and investments.

There was also an in-year change to the questionnaire, to reduce respondent burden for a telephone interview, which is outlined in the later section on Questionnaire Changes. From June onwards, this reversed the approach of April and May 2020, where routing was decided by virtue of the respondent being State Pension age or otherwise. The routing bracket for estimated savings should have returned to £1,500 to £30,000.

However, due to the complexities of the software routing, this was only partially successful as a mid-survey exercise, meaning that many households who should have been asked to report their “Estimated value of current accounts/investments” were not. The survey therefore collected no information on the value of a household’s current and basic bank accounts for these interviews.

As is standard for missing survey responses, this missing data was imputed to ensure that the amount of savings / investments held by each household has not been under-estimated. Levels of imputation are shown in Methodology Table M.4.

Self employment

It is difficult to calculate current-year income for the self-employed. In line with international standards, the FRS calculates self-employed income from the profit data for a previous tax year or regular self-employment income over the past twelve months. Whilst this provides less of an issue when incomes are broadly stable, this was more of a challenge in 2020 to 2021 given the sharp changes in self-employed incomes caused by the pandemic.

The survey has also had to adapt to several forms of government assistance for the self-employed:

• for those claiming Universal Credit (UC), the government announced that from 6 April 2020 the Minimum Income Floor would be temporarily relaxed. Self-employed people claiming UC would thereafter have their UC calculation based on their submitted earnings and not the Minimum Income Floor. It follows that where FRS incomes include UC, that UC payment will include the additional amount
• the government introduced the Self-Employment Income Support Scheme (SEISS) to help the self-employed who were affected by the coronavirus (COVID-19) pandemic. Although the FRS specifically asked about receipt of SEISS grants from June 2020, self-employed income amounts reported in the FRS do not include the grants received from SEISS. This means that household and individual income amounts do not directly include grants received from SEISS

The expected impact of SEISS in reporting levels and characteristics of self-employment is that people will remain as self-employed but may class themselves as temporarily away from work and record no hours of employment. However, as under the terms of the scheme, they can continue to work or take on other employment, their economic status and number of hours worked may change during the scheme’s lifespan. This may affect the reporting of self-employed income.

The FRS asks a detailed set of questions to capture earnings from self-employment, as described in the Glossary, at the end of this document.

The FRS does not fully capture information on all types of income in kind accurately – for example, benefits of vehicles, computers and mobile phones purchased by the business – that are also for personal use. And these benefits are likely to be more important for the self-employed than for employees. Therefore, the FRS earnings measures are likely to underestimate the true monetary and other benefits of self-employment. However, it is very difficult to quantify this.

Other benefits of self-employment compared to employment are not captured, such as flexibility in working patterns, independence and flexibility in the way money is drawn from the business. The complexity of self-employment circumstances, with irregular income and benefits-in-kind coming from a range of sources, could also contribute to inaccuracy of information capture.

One of the significant advantages of the FRS is that it has captured self-employment in a consistent way over time. Therefore, the trends in self-employment compared to employment are likely to be reasonably accurate.

The Labour Force Survey is considered the definitive source where numbers participating in the labour market are concerned. It has previously been recognised that the FRS does undercount the number of people reporting self-employment compared to the LFS. This is still the case, although where previously the trends and proportions by gender were consistent across the two surveys, in 2020 to 2021 both overall and for female respondents, the fall in the numbers of self-employed is larger for the FRS than in the LFS. Correspondingly, there is a large difference in the percentage decrease in both groups, and especially for female respondents only.

For self-employed individuals, net income figures are presented after any deductions which include, but are not limited to tax, National Insurance and pension contributions. Where gross income figures are presented these include all of these elements.

Household Food Security

Restrictions put in place due to the pandemic may have influenced the requirement for and the opportunity to buy food as easily as before the pandemic.

Since the introduction of questions on household food security in the 2019 to 2020 survey year the FRS continues to provide evidence on the standing of households in relation to their food security. Household Food Security is a measure of whether households have sufficient food to facilitate an active and healthy lifestyle. Questions are asked of the person in the household who knows the most about buying and preparing food. In common with the rest of the FRS, the focus is on the period immediately before the interview (30 days).

The questions are comparable to those used by other public bodies in the UK, and also internationally. The following points should be noted when interpreting these statistics:

• where a household is food insecure, information about the individual experiences of food insecurity within the household is not available. A young child’s experience in a food insecure household may be very different from their parent’s, for example

• these statistics do not directly measure hunger. They instead explore the financial situation of households and how that affects their access to food. Only households with very low food security would anticipate substantive disruption to their food intake

For further information see the Glossary section and the relevant publication tables.

Adjusting for inflation

Some figures in the main FRS report and the accompanying tables combine several years of income data. In these circumstances, uprating factors are used to adjust for inflation by bringing values from previous years into current price terms.

Since the 2014 to 2015 FRS, the Consumer Price Index (CPI) has been used to adjust for inflation. Read more information concerning this methodological change

5. Policy changes for the year 2020 to 2021

Council Tax

The Department for Levelling Up, Housing and Communities estimated that the average Band D tax set by local authorities in England for 2020 to 2021 represented an increase of 3.9% from 2019 to 2020 levels.

In Wales, the average Band D council tax for 2020-21 increased by 4.8% from 2019 to 2020 levels.

In Scotland, the average Band D council tax for 2020-21 represented an increase of 4.8% from 2019 to 2020 levels.

In Northern Ireland, the domestic Regional Rate was frozen for 2020 to 2021. Consequently, it was no higher for 2020 to 2021 than for 2019 to 2020.

Housing Support for private renters

In April 2020, Local Housing Allowance rates were made more generous, as they increased to the 30th percentile of market rents.

National Living Wage

In April 2020, the National Living Wage increased to £8.72 per hour for employees aged 25 years and over. Employees aged under 25 years continued to receive the National Minimum Wage. In April 2020, the National Minimum Wage increased to £8.20 per hour for those aged 21 to 24 years, £6.45 per hour for those aged 18 to 20 years, £4.55 per hour for those aged under 18 years and £4.15 per hour for apprentices.

State Pension

In October 2020, the State Pension age increased to 66 years for both men and women.

Pensioner TV licences

From 1 August 2020, anyone who was aged 75 years or over and received Pension Credit was entitled to a free TV licence.

Universal Credit £20 uplift

From April 2020, the government increased the standard allowance in Universal Credit by £1,040.04 per year and the basic element in Working Tax Credit by £1,045 per year. Both new and existing Universal Credit claimants and existing Working Tax Credit claimants received an additional £20 per week on top of annual uprating.

Universal Credit removal of Minimum Income Floor for self-employed people

Between April 2020 and July 2021, the government temporarily suspended the Minimum Income Floor (MIF) so that a drop in a claimant’s earnings was reflected in their monthly Universal Credit payment.

Severe Disability Premium transitional payments

From 27 January 2021, the Severe Disability Premium (SDP) Gateway was removed. SDP recipients would instead claim Universal Credit from this date onwards.

The SDP transitional payments were introduced for those who were entitled to the SDP and migrated to Universal Credit before the SDP Gateway commenced on 16 January 2019. These payments comprised of the following:

• £285 a month for single claimants who were not receiving the Universal Credit limited capability for work and work-related activity (LCWRA) addition
• £120 a month for single claimants who were receiving the LCWRA addition
• £405 a month for joint claimants who were receiving the higher couple rate SDP in their legacy benefit
• £285 a month for joint claimants who were receiving the lower couple rate SDP and were not receiving the LCWRA addition in UC
• £120 a month for joint claimants who were receiving the lower couple rate SDP and were receiving the LCWRA addition in UC
• an additional lump-sum payment to encompass the time period since the claimant moved onto Universal Credit

Up-rating

For 2020 to 2021, the uprating of inflation-linked benefit and tax credit rates resumed.

This resulted in an increase of 1.7% which was consistent with the Consumer Prices Index (CPI). This followed a four-year period from 2016 to 2020 where most working-age benefits including Jobseeker’s Allowance, Income Support, Universal Credit, Employment and Support Allowance and Housing Benefit; Child Benefit and some elements of Tax Credit were frozen at their 2015 to 2016 values.

Benefits for carers were excluded from the freeze and continued to be up-rated in line with prices during the period from 2016 to 2020.

In April 2020:

• the State Pension increased by average weekly earnings of 3.9% in line with the ‘triple lock’. The ‘triple lock’ ensured that in 2020-21 the State Pension increased by the highest of the increase in earnings, price inflation as measured by the CPI or 2.5%
• the Standard Minimum Guarantee in Pension Credit was up-rated by 3.9% in line with earnings. For those who were single, the Standard Minimum Guarantee in Pension Credit increased from £167.25 per week to £173.75 per week which was a cash increase of £6.50. For couples, this increased from £255.25 per week to £265.20 per week which was a cash increase of £9.95
• Universal Credit Work Allowances were up-rated in line with CPI

Rent and mortgage payments

On 17 March 2020, the Government announced that anyone struggling to pay their mortgage or rent as a result of the coronavirus (COVID-19) pandemic, as well as landlords with buy-to-let mortgages whose tenants were unable to pay the rent could apply for a payment holiday. Mortgage holidays were initially set to run until October 2020 but were then extended to 31 July 2021.

Payment holidays could either last up to three months or up to six months. For those continuing to struggle financially once their payment holiday had ended, lenders should have provided additional support through tailored forbearance options.

Landlords and lenders were prevented from evicting those occupying their properties by the Coronavirus Act 2020. From March 2020 to September 2020, housing possession action was suspended in courts and a ban on repossessions was in place from November 2020 until the end of May 2021.

Self-Employment Income Support Scheme

The Government introduced the Self-Employment Income Support Scheme (SEISS) to help self-employed individuals who were affected by coronavirus (COVID-19). SEISS is for people who are self-employed or a member of a partnership in the UK and have lost income because of coronavirus (COVID-19). The first round of the SEISS paid taxable grants worth 80% of the claimant’s average monthly trading profit, up to £7,500 in total, and covered a three-month period.

The government announced the second round of SEISS in May 2020 with taxable grants worth 70% of the claimant’s average monthly trading profit, up to £6,570 in total, and encompassing a three-month period.

In September 2020, the Government announced an extension to the SEISS which firstly covered from November 2020 to January 2021 and then from February 2021 to April 2021. The first of these two grants was worth 80% of the claimant’s average monthly trading profit, up to £7,500 in total, and the second was partly determined by the amount that claimant’s turnover had reduced from April 2020 to April 2021.

‘Furlough’: Coronavirus Job Retention Scheme

In March 2020, the government announced the Coronavirus Job Retention Scheme (CJRS). Employers who were unable to maintain their workforce because of the coronavirus (COVID-19) pandemic could put their employees on furlough and apply for a grant. Government and employer contributions varied during the scheme to ensure that an employee received at least 80% of their monthly wage, up to £2,500 a month, including National Insurance and any pension contributions. This scheme was in place from March 2020 to September 2021.

6. Alternative data sources

Income

A Guide to Sources of Data on Earnings and Income

The Income and Earnings Interactive Tool where you can filter by government department and country of interest to find relevant statistics

The Effects of Taxes and Benefits on Households

Living Costs and Food Survey

Wealth and Assets Survey

Income, spending and wealth: how do you compare? – joined-up data from the Wealth and Assets Survey (WAS) and the Living Costs and Food Survey (LCF) providing insight into the financial vulnerability of different households.

Annual Survey of Hours and Earnings

Labour Force Survey

Benefits statistics on Stat-Xplore

Households Below Average Income on Stat-Xplore

Pensioners’ Incomes Series on Stat-Xplore

Income Dynamics: Income movements and persistence of low incomes

ONS: explanation of incomes and earnings

Changing trends and recent shortages in the labour market, UK: 2016 to 2021

Tenure

English Housing Survey

Private Landlords Survey

English Private Landlords Survey 2018

Index of Private Housing Rental Prices

Housing affordability in England and Wales: 2021

Rent affordability: Literature and evidence review: 2019

More information about housing statistics Housing and planning statistics

Disability

Life Opportunities Survey

Outcomes for disabled people in the UK: 2021

The employment of disabled people 2021

Labour market data for protected groups in Wales and the UK, April 2004 to March 2021

Disabled people in the labour market in Scotland: 2019

Disability Employment Gap in Northern Ireland 2020

Care

Department of Health Personal Social Services survey of adult carers in England

Health and care statistics for England

Pension Participation

Occupational Pension Schemes Survey

Note that the collection and publication of the annual Occupational Pension Schemes Survey (OPSS) has ceased. A quarterly publication has superseded this Employers’ Pension Provision Survey

The Pensions Regulator – DC Trust: a presentation of scheme return data

The Pensions Regulator

HMRC Pensions Tables

English Longitudinal Study of Ageing Wave 9: 2002-2019

Annual Survey of Hours and Earnings (pension tables)

Self Employment

Trends in self-employment in the UK

Labour Market overview UK (including breakdown of the self-employed)

Household Food Security

The Food and You 2 Survey - Wave 3: Combined report for England, Wales and Northern Ireland

Household resources and finances - Coronavirus (COVID-19) support in low income households: evaluation (Scottish Government)

7. Population and sample selection methodology

The FRS sample is designed to be representative of private households in the United Kingdom.

The sampling frame and selection methods for the FRS did not change in response to the coronavirus (COVID-19) pandemic.

The sampling frame in Great Britain

The Great Britain FRS sample is drawn from the Royal Mail’s small users Postcode Address File (PAF). The small users PAF is limited to addresses which receive, on average, fewer than 50 items of post per day and which are not flagged with Royal Mail’s “organisation code”. An updated version of this list is obtained twice a year. By using only the small-user delivery points most large institutions and businesses are excluded from the sample. Small-user delivery points which are flagged as small business addresses are also excluded. However, some small businesses and other ineligible addresses remain on the sampling frame. If sampled, they are recorded as ineligible once the interviewer verifies that no private household lives there.

The sample design in Great Britain

The Great Britain FRS uses a stratified clustered probability sample design. The survey samples 1,417 postcode sectors, from around 9,200 in Great Britain, with a probability of selection that is proportional to size. Each postcode sector is known as a Primary Sampling Unit (PSU).

The PSUs are stratified by 27 regions and three other variables, described below, derived from the 2011 Census of Population. Stratifying ensures that the proportions of the sample falling into each group reflect those of the population.

Within each region the postcode sectors are ranked and grouped into eight equal bands using the proportion of households where the household reference person (HRP) is in National Statistics Socio-Economic Classification (NS-SEC) 1 to 3. Within each of these eight bands, the PSUs are ranked by the proportion of economically active adults aged 16-74 and formed into two further bands, resulting in sixteen bands for each region. These are then ranked according to the proportion of economically active men aged 16-74 who are unemployed. This set of stratifiers is chosen to have maximum effectiveness on the accuracy of two key variables: household income and housing costs. The table below summarises the stratification variables.

Within each PSU a sample of addresses is selected. In 2020 to 2021, 28 addresses were selected per PSU. The total Great Britain set sample size in 2020 to 2021 was 39,676 addresses. Each address had approximately a 1-in-713 chance of being included in the survey. For England and Wales each address had approximately a 1-in-780 chance of inclusion in the survey. In order to improve the quality of estimates for Scotland, PSUs there are over-sampled. Approximately twice the numbers of PSUs were sampled in Scotland than would be required under an equal-probability sample of the UK. Therefore, 6,832 addresses were selected in Scotland, with approximately a 1-in-389 chance of being included in the survey.

FRS sample stratification variables for Great Britain

Regions	19 in England (inc. Metropolitan vs non-Metropolitan split
Regions	4 in London
Regions	2 in Wales
Regions	6 in Scotland
The proportion of households where the HRP is in NS-SEC 1 to 3	8 equal bands
The proportion of economically active adults aged 16-74	2 equal bands
The proportion of economically active men aged 16-74 who are unemployed	Sorted within above bands

Each year, half of the PSUs are retained from the previous year’s sample, but with new addresses chosen; for the other half of the sample, a fresh selection of PSUs is made (which in turn will be retained for the following year). This is to improve comparability between years.

The sampling frame in Northern Ireland

The sampling frame employed on the Northern Ireland FRS is the NISRA Address Register (NAR). The NAR is developed within NISRA and is primarily based on the Land and Property Services (LPS) Pointer database, the most comprehensive and authoritative address database in Northern Ireland, with approximately 752,000 address records available for selection.

The sample design in Northern Ireland

A systematic random sample of 4,080 addresses was selected for the 2020 to 2021 Northern Ireland FRS from the NISRA Address Register. Addresses are sorted by district council and ward, so the sample is effectively stratified geographically. Each address had approximately a 1-in-184 chance of being selected for the survey.

8. Data collection

Fieldwork operations for the Family Resources Survey (FRS) were rapidly changed in response to the coronavirus (COVID-19) pandemic and the subsequent introduction of national lockdown restrictions. The established face-to-face interviewing approach employed on the FRS was suspended and replaced with telephone interviewing for the whole of the 2020 to 2021 survey year.

Data collection in Great Britain

A consortium consisting of the Office for National Statistics (ONS) and NatCen Social Research conducts fieldwork for the FRS in Great Britain on behalf of the Department for Work and Pensions (DWP).

Each month the PSUs are systematically divided between the two organisations and then assigned to the field staff.

Fieldwork operations for the 2020 to 2021 FRS were changed in response to the coronavirus (COVID-19) pandemic and the social distancing measures that were implemented in Spring 2020. The normal FRS approach of interviewing face-to-face was suspended and changed to a telephone interview from April 2020 to ensure that there was no face-to-face contact between interviewers and respondents. Interviewers who would ordinarily conduct the survey in the respondent’s home changed approach to interviewing by telephone, whilst working from their own homes.

A number of operational changes were introduced to the FRS in order to facilitate this switch to phone interviewing. Other measures were subsequently put in place with the aim of improving response.

Before interviewers contacted the selected addresses, a letter was sent to the occupier explaining that they had been chosen for the survey and that how they should provide their contact phone number in preparation for a telephone interview. The letter also explained that the survey relies on the voluntary co-operation of respondents and emphasised that information given in the interview would be treated in the strictest confidence and used only for research and statistical analysis purposes. As a token of appreciation and to encourage participation, a £10 Post Office voucher was included with the letter.

Respondents were offered various options to provide their telephone numbers, including an online portal, which was set up in May 2020. Telephone numbers for sampled addresses were also obtained where possible to supplement those provided directly by respondents. This included telematching sourced via ‘UKChanges’, which ONS adopted from April and NatCen introduced in June. In September, additional telephone numbers were sourced by matching the FRS sample with telephone numbers held on DWP’s internal databases and other administrative systems.

From November, and where local lockdown restrictions allowed, interviewers who had agreed to take part in “Knock to Nudge” visited addresses for which they had not received any contact details. The aim was to collect a phone number in person and make an appointment for a later phone interview. It should be noted that the success of this by geographical region may have been affected by local lockdown restrictions that existed between the specific lockdown in Leicester in July 2020, followed by the tier system that began in October 2020 and lasted until March 2021 (interspersed with National lockdown restrictions).

ONS interviewers remained available for work throughout 2020 to 2021 and therefore all cases (i.e. those with and without telephone numbers) were issued as sampled to interviewers at the start of data collection. When a telephone number became available for a case (either via the portal or through telematching), it was supplied to the interviewer who had been assigned the case for them to attempt to make contact. ONS interviewers also received some contact numbers directly from respondents in response to the “introductory” letter they sent out.

A proportion of NatCen interviewers were initially put on furlough and therefore unable to work. NatCen therefore took a different approach, whereby those cases which had “opted in” (i.e. got in touch via the central freephone number, central email address or online portal to provide a contact number) were prioritised and issued to a central pool of interviewers. Once the portal had been closed and all cases with contact details sourced in this way had been issued to interviewers, a review of the cases which had been successfully tele-matched was carried out. Any cases which had not already been successfully contacted were identified and issued in further batches to interviewers for them to attempt to contact.

Until November, those NatCen cases for which no contact telephone number was available from either source were not routinely issued to interviewers, since they would have no means of attempting contact. From November, all cases with no portal number available were issued to interviewers and included in the doorstep recruitment, subject to field capacity and local lockdown restrictions.

Data collection in Northern Ireland

In Northern Ireland the sampling and fieldwork for the survey are carried out by the Central Survey Unit at the Northern Ireland Statistics and Research Agency. The responsibilities for programming the survey questionnaire, making annual modifications, initial data processing and data delivery are retained within ONS and NatCen.

NISRA interviewers remained available for work throughout 2020 to 2021 and therefore all cases were issued as sampled to interviewers at the start of data collection. When a telephone number became available for a case via the portal it was supplied to the interviewer who had been assigned the case. NISRA interviewers also received some contact numbers directly from respondents in response to the “follow-up” letter issued to addresses in which they provided respondents with their own contact number. However, telematching was not used as a supplementary source of telephone numbers in Northern Ireland and “Knock to Nudge” was not rolled out to NISRA interviewers.

Success rates of different methods of contacting respondents

Composition of final sample, by mode of contact

In April, May and June the mode of contact was not collected in the data. Therefore these are represented here as “Not Classified”.

Length of interview

Due to the coronavirus (COVID-19) restrictions interviews were conducted by telephone for the whole of the 2020 to 2021 survey year and questions required for monitoring the impact of the pandemic (e.g. questions on the furlough scheme) were added to the questionnaire from May onwards.

The length of each fully co-operating interview is recorded by the questionnaire program. In 2020 to 2021 the median interview length for Great Britain was 52 minutes, but the time varied according to the size of household and its circumstances. The distribution of interview lengths in Great Britain is shown below, with full data in Methodology Table M.7. The timings exclude interviewer time spent preparing for and completing administration tasks after the interview. They are based on completed audit data from 9,299 fully productive ONS and NatCen interviews.

Distribution of FRS interview lengths, 2020 to 2021, Great Britain

Respondent Burden

The Code of Practice for Statistics states that producers of statistics should consider the burden on survey respondents. The FRS can measure the burden placed on respondents by using measured interview times for 9,299 full interviews, in Great Britain.

Great Britain Respondent burden is calculated as Number of responses x median interview time.

The median interview time for these 9,299 interviews was 51.9 minutes. Therefore, the respondent burden for the FRS in 2020 to 21 was 482,618 minutes [335 days].

Multi-household procedures

If more than one household receives mail at an address a single household is interviewed. Multi households are not selected in Northern Ireland.

9. The FRS questionnaire

Changes to the FRS questionnaire were made during the fieldwork year to collect information on new government support initiatives, and to manage respondent burden for a telephone survey. This was important to enable the statistics to reflect changes in the economy and society in response to the pandemic, and to inform policy. Due to the impact of coronavirus (COVID-19) FRS interviews were conducted using Computer Assisted Telephone Interviewing (CATI) during 2020 to 2021.

The questionnaire is divided into three parts.

• the first part is the household schedule which is addressed to one person in the household (usually the household reference person, although other members are encouraged to be present) and mainly asks household level information, such as relationships of individuals to each other, tenure and housing costs

• next is the individual schedule which is addressed to each adult in turn and asks questions about employment, benefits, pensions, investments, and other income. Information on children in the household is collected by proxy from a responsible adult

• a final section asks the value of investments (by type) for respondents with savings between a lower and an upper pound limit

Interviewers new to the FRS are briefed on the questionnaire and an annual re-briefing is given to all interviewers on changes to the questionnaire. For 2020 to 2021 additional training was provided to interviewers on key aspects of the questionnaire to be aware of with respect to telephone interviewing. This included how to ask questions which were designed to reference showcards, including:

• adapting the question wording to avoid mentioning the showcard

• for most questions simply reading aloud all responses as listed on the showcard

• some further specific guidance for certain questions with unusually long showcards

Recommended approaches for collecting information from two-person benefit units were also covered, ideally speaking to both respondents at once (for example, via speakerphone or two handsets).

Interviewers who have worked on the survey for some time also completed a written field report each year, describing their experiences with specific parts of the questionnaire and commenting on how changes were received in the field.

Prior to the start of fieldwork, DWP consults FRS users and draws up a list of possible questionnaire changes. Users are asked to identify individual questions or sections which were no longer of interest. The FRS questionnaire is lengthy and demanding and a key concern is, where possible, to reduce (or at least not increase) its length, so as not to overburden respondents or interviewers.

As part of the process of agreeing annual changes, suggestions from contractors are also considered, as well as those arising from an evaluation of feedback from interviewers. Any changes to the questionnaire are checked for consistency with the harmonised standards for social surveys across government.

Questionnaire changes

Whilst the questionnaire was largely unchanged from the previous 2019 to 2020 survey year, a number of changes were made in response to collecting data on the coronavirus (COVID-19) pandemic. This included the reversal, from June onwards, of some changes which had been introduced in April 2020, to reduce respondent burden on a telephone interview while maintaining core FRS questions.

Employment Status block – May

The most significant change was the introduction of questions around the CJRS ‘furlough’ scheme; and for those who were put on furlough in their main job, to clarify answers to the preceding question about whether they were working in the week they were interviewed.

Further changes to several Questionnaire blocks – June

Changes were introduced to capture several other COVID-19 related policy measures. These included questions within the Self-Employed Earnings block to capture Self-Employment Income Support Scheme (SEISS) grants, both applied for and received. There were additions to the Employee Pay Details block to capture furlough in second jobs if the respondent had more than one job as an employee.

There was an insertion to the Owned Accommodation and Mortgages block to ask whether the householder had taken a mortgage holiday.

In the State & Other Benefits and Pensions block, the question on receipt of Employment and Support Allowance was supplemented by asking whether receipt was due to coronavirus (COVID-19). A similar approach was taken to the Statutory Sick Pay question in the Employment Status block.

Total Assets block – April and May

All benefit units were asked the Reported Total Savings (TOTSAV) question. Depending on their answer, they might be routed to the more detailed asset-by-asset block of questions. This would be the case if they reported total assets of:

• between £100 and £30,000, where the respondent (and any partner) were (both) below State Pension age
• between £100 and £200,000, if the respondent (or their partner) were over State Pension age

This addition to the 2020-21 questionnaire was intended to yield more detailed information from working-age benefit units with assets, and for the first time from those with between £100 to £1,500 and £20,000 to £30,000. It also aimed to capture information on the high proportion of pensioner benefit units who report more than £30,000 in savings.

Total Assets block – from June

The routing of these questions was largely reverted to the setup of the previous survey year, such that the lower limit reverted from £100 to £1,500, and the age distinction was removed. However the upper limit was retained at £30,000 (previously £20,000). This allowed the new bands on the survey showcard to stay unaltered.

For all benefit units – regardless of age – who responded that they had between £1,500 and £30,000 in assets, the subsequent questions on asset-by-asset values were retained.

Debt block

Several new questions on personal debt, including personal loans and credit card debt, were introduced in April 2020. These were removed from June to reduce interview length.

Expenditure block

The Expenditure block of questions was suspended from June, for the remainder of the survey year. This was to save interview time, which was given to new questions relating to coronavirus (COVID-19).

Other changes

Numerous minor updates and changes to the questionnaire were made in response to feedback from interviewers on the operation of the questionnaire. Changes also stemmed from categories or definitions which were new for the 2020 to 2021 survey year. These included changes in relation to areas of policy overseen by the devolved administrations.

As in every survey year, a small number of removals were made, of questions which were either no longer relevant, or which were answered by too small a pool of respondents to yield useful information.

Consultation of documentation

Interviewers encourage respondents to consult documentation at all stages of the interview to ensure that the answers provided are as accurate as possible. For some items whether certain documents are consulted or not is recorded on the questionnaire. This assists FRS users in assessing the accuracy of the data.

It should be noted that due to the switch to telephone interviewing in 2020 to 2021 the consultation rates reported below may be less reliable than for face-to-face interviewing as the interviewer was not able to observe directly whether documents were being checked.

• employees have consulted their latest payslip for 32% of jobs they have reported. Of all employees, 96% reported having one job only and four per cent reported having more than one job
• employees did not have a payslip to consult for 9% of jobs they reported; 27% could not consult a payslip because their payslips were only received electronically
• 63% of all reported benefit and payable Tax Credit receipt involved consultation of documentation (that is, a letter from DWP or HM Revenue and Customs, or a bank statement)
• 55% of households in Great Britain consulted a Council Tax bill or statement in answering questions on their Council Tax payments

Response

In each eligible household, the aim is to interview all adults aged 16 and over, except those aged 16 to 19 who are classed as dependent children. A household is defined as fully co-operating when it meets this requirement and there are fewer than 13 ‘don’t know’ or ‘refusal’ answers to monetary amount questions in the benefit unit schedule (i.e. excluding the assets section of the questionnaire).

Proxy interviews are accepted when a household member is unavailable for interview. In 2020 to 2021, for those households classed as fully co-operating, proxy responses were obtained for 25% of adults. It should be noted that all data shown in the main body of this publication refer only to fully co-operating households.

Households that are not fully co-operating are further classified as partially co-operating, refusals, or unable to make contact. To be classified as partially co-operating a full interview has to be obtained from the Household Reference Person’s (HRP’s) benefit unit.

Methodology Table M.1 summarises the household response.

The UK-wide sample chosen for 2020-21 consisted of 43,756 households. In total 10,020 households UK-wide fully co-operated (23%), 244 partially co-operated (one per cent) and 7,855 refused to proceed with the interview (18%). The interviewer was unable to make contact with 25,637 households (59%).

Response rates are calculated as follows.

The number of fully co-operating households, multiplied by 100 / Divided by the number of eligible households after adjustment

The overall response rate for the FRS in 2020 to 2021 was 23%.

The response rate varied by month as different methods of contacting respondents were introduced.

When respondents refuse to participate in the FRS, interviewers record up to three reasons for refusal. The most common reasons for refusal in 2020 to 2021 are shown in the following table.

Reasons for refusal to participate in the FRS, Great Britain, 2020 to 21

Reason for refusal	Percentage of households
Couldn’t be bothered	17
Invasion of privacy	15
Concerns about confidentiality	15
Genuinely too busy	10
Don’t believe in surveys	10
Disliked survey of income	8
Personal problems	6
Anti-government	2
Temporarily too busy	2
Total number who gave a reason for refusal	3,663
Total number of refusals	6,591

Methodology Table M.2 shows response rates broken down by region. All regions have seen a fall in response in 2020-21, which reflects the impact of coronavirus (COVID-19) on data collection and similar trends have been seen across other social surveys such as the Labour Force Survey and the Living Costs and Food Survey. The North East had the highest response rate in England, where 28% of all households selected responded fully. London had the lowest response rate where 17% of the chosen households fully co-operated.

Non-response

The lower the response rate to a survey, the greater the likelihood that those who responded are significantly unlike those who did not, and so the greater the risk of systematic bias in the survey results.

For a United Kingdom survey of the size and complexity of the FRS, the total non-response rate typically seen of around 50% is not considered unreasonable. However, given the impact of coronavirus (COVID-19) on data collection, the non-response rate for the 2020 to 2021 survey year was 77%.

Any information that can be obtained about non-respondents is useful both in terms of future attempts to improve the overall response rate and potentially in improving the weighting of the sample results.

Non-response form analysis

Direct information about the non-responding households is valuable, although by definition difficult to obtain.

In a normal survey year, some non-responding households who are not willing to take part in the full survey are willing to provide basic information by completing a non-response form. A detailed analysis of these forms is usually conducted to monitor characteristics of non-respondents and trends in non-response. However, due to the switch to telephone interviewing and other changes to field procedures introduced because of the coronavirus (COVID-19) pandemic, it was not possible for interviewers to record full non-response information during 2020 to 2021.

As interviewers were not able to visit sampled properties for most of the year, they were not able to record features such as barriers to entry that are relevant to non-response. They were also not able to record any observable characteristics of non-responding households such as the age and sex of non-responders.

FRS non-response and Council Tax band

Comparisons were made between the achieved sample of FRS responses in Great Britain, and 2020 to 2021 administrative data on the number of households within each Council Tax band.

Methodology Table M.3 shows that the achieved (ungrossed) FRS sample has a smaller proportion of households in the lower Council Tax bands than the administrative data.

Conversely, the ungrossed sample has a higher proportion of households in higher Council Tax bands than administrative data shows. Table M.3 also shows the extent to which the FRS grossing regime controls for this bias in the achieved sample, effectively correcting it to be closer to the proportions seen on the administrative data.

10. Validation, editing, conversion and imputation

In addition to unit non-response, where a household does not participate, a problem inherent in all large surveys is item non-response. This occurs when a household agrees to give an interview, but either does not know the answer to certain questions or refuses to answer them. This does not prevent them being classified as fully co-operating households because there is enough known data to be of good use to the analyst (although see the first paragraph of the Response section above for information about non-response to monetary questions).

The fact that the FRS allows missing values in the data collection can create problems for users, so missing values are imputed where appropriate. The policy is that for variables that are components of key derived variables, such as total household income and housing costs, and areas key to the work of DWP, such as benefit receipt, there should be no missing information in the final data.

In addition to imputation, prior to publication FRS data are put through several stages of validation and editing. This ensures the final data presented to the public are as accurate as possible.

The stages in the validation, editing, conversion and imputation process are as follows.

Stage one – the interview

One of the benefits of interviewing using CATI is that in-built checks can be made at the interview stage. This helps to check respondents’ responses and also that interviewers do not make keying errors. There are checks to ensure that amounts are within a valid range and also cross-checks which make sure that an answer does not contradict a previous response. However, it is not possible to check all potential inconsistencies, as this would slow down the interview to an unacceptable degree, and there are also capacity constraints on interviewer notes. FRS interviewers can override most checks if the answers are confirmed as accurate with respondents.

Stage two – post-interview checks

Once an interview has taken place, data are returned to ONS, NatCen, or NISRA. At this stage, editing takes place, based on any notes made by interviewers. Notes are made by the interviewer when a warning has been overridden, for example, where an amount is outside the expected range, but the respondent has documentation to prove it is correct. Office-based staff make editing decisions based on these notes. Other edits taking place at this stage are checking amounts of fixed-rate benefits and, where possible, separating multiple benefit payments into their constituent parts, such as separating Disability Living Allowance into the Care and Mobility components.

Stage three – data conversion

Before further validation, FRS data are converted from CATI format into SAS readable tables. Using DWP specifications, SAS tables are created by ONS, with each table displaying information from different parts of the questionnaire. Both DWP and ONS then carry out validation checks on key input and output variables to ensure that the data have converted correctly to the new format. Checks include ensuring that the number of adults and children recorded is correct, and that records are internally consistent.

Stage four – state support validation

Information on benefit and tax credit receipt is one of the key areas of the FRS, and it is very important that this section is thoroughly validated and cleaned.

It is not appropriate to use the imputation methods outlined in stages five and six (below) for benefits data so instead a separate procedure of validation and editing is used. The following types of validation were carried out for 2020 to 2021 FRS data.

Missing values

For cases where a respondent had answered ‘yes’ to whether they are in receipt of a particular benefit, but did not give the amount received, an imputation decision has been made, depending on the benefit. For benefits such as Universal Credit, where the rate could vary greatly depending on the situation of the respondent, individual benefit assessments have been carried out. However, for benefits such as Personal Independence Payment, where fewer rates apply, a more general method has been used.

Near-zero amounts

Where benefit amounts are recorded as near-zero, the case is examined individually and an edit decision is made.

Multiple benefits

Any combined benefit amounts (for example where State Pension is paid with Attendance Allowance) are edited by carrying out benefit entitlement assessments on individual cases, while preserving the reported total wherever possible.

Validation reports

Computer programs are run to carry out a final check for benefit entitlement and to output any cases that look unreasonable. All cases detected as a result of this validation exercise are individually checked and edited where necessary.

Stage five – other pre-imputation cleaning

In preparation for imputing missing values, data are made as clean as possible. This involves edits and checks of the following nature.

Weekly amounts

In the FRS, most monetary amounts are converted to a weekly equivalent. To calculate this, respondents are usually asked the amount, then the length of time this amount covered. The latter is known as a “period code”. Period codes are used in conjunction with amounts to derive weekly figures for all receipts and payments. Some variables, such as interest on savings accounts, refer to the amount paid in the whole of the past year. These are also converted to a weekly amount.

Sometimes the period code relates to a lump sum or a one-off payment. In these cases, the corresponding value does not automatically convert to a weekly amount. In order for the data to be consistent across the survey, edits are applied to convert most lump sums and one-off payments to weekly amounts. In the same way, where period codes are recorded as ‘don’t know’ or ‘refused’, these are imputed so that the corresponding amount can be converted to a weekly value in the final dataset.

Near-zero amounts

It is not possible for interviewers to enter zero amounts where it is inappropriate to do so. For example, in response to a question on receipt of benefit, a zero amount will result in a warning message being displayed. Some interviewers try to avoid this message by recording near-zero amounts. As a result, all near-zero values are examined and a decision taken as to whether the value is genuine or whether the value should be treated as missing.

Outliers

Statistical reports of the data are produced to show those cases where an amount was greater than four standard deviations from the mean. For the seven largest values over this limit, the individual record is examined and where necessary (but only if a value looks unrealistic), the case is edited. The outliers remaining in the dataset are verified by examining other relevant data. Compared with earlier FRS years, only a small number of these edits are now carried out, because of the many range checks in the computerised questionnaire.

Credibility checks

Checks are carried out for the internal consistency of certain variables. For example, one check on mortgage payments ensures that payments to the mortgage from outside the household are not greater than the mortgage payment itself. Such cases are examined and edited where necessary.

Stage six – imputation

The responses to some questions are much more likely to have missing values than others. For example, it is very unlikely that a respondent will refuse to give or will not know their age or marital status; whereas it is much more likely that they will not be able to provide precise information on the amount of interest received from their investments.

Two areas where missing values are a problem are (1) income from self-employment and (2) income from investments. Results in the tables provided in this publication include imputed values. Elsewhere however, values are left to remain as missing in some variables (such as hours of care).

Methodology Table M.4

This table illustrates the extent of missing values. Of the 6.3 million set values in the 2020-21 FRS dataset, one per cent were originally recorded as either ‘don’t know’ or ‘refused’. Out of 86,594 missing values, approximately 99% were then imputed. The main imputation methods are summarised below, in the order in which they were applied.

Closing down routes

As with any questionnaire, a typical feature of the FRS is a gatekeeper question positioned at the top of a sequence of questions, at which a particular response will open up the rest of the sequence. If the gatekeeper question is answered as ‘don’t know’ or ‘refused’ then the whole sequence is skipped.

A missing gatekeeper variable could be imputed such that a further series of answers would be expected. However, these answers will not appear because a whole new route has been opened. For example, if the amount of rent is missing for a record and has since been imputed, any further questions about rent would not have been asked. From the post-imputed dataset, it will appear that these questions should have been asked because a value is present for rent.

For this reason, where the gatekeeper question has been skipped the onward routes should be closed down. In most cases, gatekeeper variables are of the ‘yes or no’ type. If missing, these would be imputed to ‘no’, assuming that if a respondent does not know whether an item is received or paid, then it is not.

Hot-decking

This process looks at characteristics within a record containing a missing value to be imputed, and matches it up to another record with similar characteristics for which the variable is not missing. It then takes the known variable and copies it to the missing case. For example, when imputing the Council Tax Band of a household, the number of bedrooms, type of accommodation and region are used to search for a case with a similar record. This method ensures that imputed solutions are realistic, and allows for a wide range of outcomes which maintain variability in the data.

Algorithms

These are used to impute missing values for certain variables, for example variables relating to mortgages. The algorithms range from very simple calculations to more sophisticated models, based on observed relationships within the data and individual characteristics, such as age and gender.

‘Mop-up’ imputation

This is achieved by running a general validation report of all variables and looking at those cases where missing values are still present. At this stage, variables are examined on a case-by-case basis to decide what to impute. Credibility checks are re-run to identify any inconsistencies in the data caused by imputation, and further edits are applied where necessary.

All imputations, by each of the methods above, are applied to the un-imputed dataset via a transaction database. This ensures auditability in that it is always possible to reproduce the original data.

Points to note with imputed data

• whilst several processes are used to impute missing values, it should be remembered that they represent only a very small proportion (typically 1 per cent) of the dataset as a whole
• imputation will have a greater effect on the distribution of original data for variables that have a higher proportion of non-response, as proportions of imputed data will be higher
• as mentioned above, in certain situations, imputed values will be followed by ‘skipped’ values. It was decided in some cases that it was better to impute the top of a route only, and not large amounts of onward data. For a small proportion of imputations it is not possible to close down a route. These cases are followed by ‘skipped’ responses (where a value might otherwise be expected)

Stage seven – derived variables

Derived variables (DVs) are those which are not created by the original interview, but instead are made by combining information, both within the survey and from other sources.

They are created at the FRS user’s request. Their main purpose is to make it easier for users to carry out analysis and to ensure consistent definitions are used in all FRS analyses. For example, INDINC is a DV which sums all components of income to find an individual’s total income. This is possible because of the various sources collected by the survey. As new information is collected in the survey, the relevant DVs are updated as necessary.

11. Grossing

The grossing regime this year has been adapted to try to control for the larger impacts of the coronavirus (COVID-19) pandemic upon the achieved sample. Whilst the existing FRS grossing regime brought estimates close to the age and tenure profile of the UK population, it retained a disproportionate number of respondents who had been educated to at least degree level. It was important to adjust for this bias because income levels are strongly correlated with the level of education achieved. Therefore, additional grossing controls were introduced to rebalance the educational levels of those in the sample.

The grossing regime has also been adapted to control for the differential level of response through the year. There were fewer responses in the early months of the survey year than in later months. This is not normally a feature of the FRS achieved sample, with response normally spread relatively equally over each twelve-month run of fieldwork.

There has, however, been no change to the overall population basis for the estimates. These remain the population in private households in 2020 to 2021, as estimated by ONS. ONS has not adjusted these figures in the light of coronavirus (COVID-19). More information on mid-year estimates of population can be found on the ONS website.

The FRS publication presents tabulations where the percentages refer to sample estimates grossed-up to apply to the whole population.

Grossing-up is the term given to the process of applying factors to sample data so that they yield estimates for the overall population. The simplest grossing system would be a single factor for example, the number of households in the population divided by the number in the achieved sample. However, surveys are normally grossed by a more complex set of grossing factors that attempt to correct for differential non-response, at the same time as they scale up sample estimates.

The system used to calculate grossing factors for the FRS divides the sample into different groups. The groups are designed to reflect differences in response rates among different types of household. The FRS stratified sample structure is designed to minimise differential non-response in the achieved sample. Grossing is then designed to account for residual differential non-response.

They have also been chosen with the aims of DWP analysis in mind. The population estimates for these groups, obtained from official data sources, provide control variables. The grossing factors are then calculated so that the FRS produces population estimates that are as close as possible to the control variables. As an example, a grossed FRS count of the number of men aged 35 to 39 would be consistent with the ONS population estimates of the same group.

In developing the grossing regime careful consideration has been given to the combination of control totals, and the way age ranges, Council Tax Bands and so on, are grouped together. The aim has been to strike a balance so that the grossing system will provide, where possible, accurate estimates in different dimensions without significantly increasing variances.

Some adjustments are made to the original control total sources so that definitions match those in the FRS, for example, an adjustment is made to the demographic data to exclude people whose residence is not a private household. It is also the case that some control totals have to be adjusted time-wise, to correspond to the FRS survey year which runs from April to March.

A software package called CALMAR, provided by the French National Statistics Institute, is used to reconcile control variables at different levels and estimate their joint population. This software makes the final weighted sample distributions match the population distributions through a process known as calibration weighting. It should be noted that if a few cases are associated with very small or very large grossing factors, grossed estimates will have relatively wide confidence intervals.

A review of the FRS grossing methodology was carried out by the ONS Methodological Advisory Service in 2013.

A number of relatively minor methodological improvements were made as a result, with the grossing calculations updated to use 2011 Census data at that point. Further details on the methodological changes have also been published.

Both Great Britain and Northern Ireland data use the same CALMAR software to reconcile control variables at different levels, and estimate their joint population. There are minor differences between the methods used to gross the Northern Ireland sample as compared with the Great Britain sample:

• local taxes in Northern Ireland are collected through the rates system, so Council Tax Band is not applicable as a control variable
• Northern Ireland housing data are based largely on small-sample surveys. It is not desirable to introduce the variance of one survey into another by using it to compute control totals; therefore tenure type is not used as a control variable

Details of the control variables used in the grossing regimes for Great Britain and Northern Ireland are shown on the following pages.

Grossing regime for Great Britain 2020 to 2021

Control variables used to generate grossing factors for private households

Variable	Groupings	Source of data
Individuals (Age, sex and Region)	Male children: 0-9, 10-19 Male adults: 16-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-59, 60-64, 65-74, 75-79, 80+ Female children: 0-9, 10-19 Female adults: 16-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-59, 60-69, 70-74, 75-79, 80+ Each grouping is further broken down by region: North East, North West, Yorkshire and the Humber, East Midlands, West Midlands, East, London, South East, South West, Scotland and Wales	Office for National Statistics (ONS) Mid-year population estimates
Dependants aged 16-19 years old	England, Wales, Scotland	DWP estimates using data derived from ONS and HMRC
Benefit units (with children)	England and Wales (combined), Scotland	HMRC Child Benefit data
Benefit units (with children)	Lone parents: Male, female	Labour Force Survey estimates
Households (Tenure type)	Local Authority or Housing Association renters, private renters, owner occupiers	Department for Levelling Up, Housing and Communities (DLUHC)
Households (Council Tax Band)	A and Not Valued Separately, B, C-D, E-H and I	Valuation Office, Scottish Government
Households (Region)	North East, North West, Yorkshire and the Humber, East Midlands, West Midlands, East, London, South East, South West, Scotland and Wales	ONS (England) Welsh Government (Wales) Scottish Government (Scotland)

Control variables used to generate grossing factors for private households

Variable	Groupings	Source of data
Households by month of interview (these have been added for 2020 to 2021 and will be reviewed for 2021 to 2022)	Each month April 2020 to March 2021	See Households by region/tenure/council tax band above
Working-age adults with degrees (these have been added for 2020 to 2021 and will be reviewed for 2021 to 2022)	Working-age adults aged 16 to 45 and working-age adults aged over 45	FRS 1994-95 to 2019-20

Grossing regime for Northern Ireland, 2020 to 2021

Control variables used to generate grossing factors for private households

Variable	Groupings	Source of data
Individuals (Age and sex)	Male children: 0-9, 10-19 Male adults: 16-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-59, 60-64, 65-74, 75-79, 80+ Female children: 0-9, 10-19 Female adults: 16-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-59, 60-69, 70-74, 75-79, 80+	Office for National Statistics (ONS)
Benefit units (with children)	Lone parents	Department for Communities Northern Ireland (DfCNI) estimates
Households		Northern Ireland Statistics and Research Agency (NISRA)

12. Reliability of estimates

The achieved sample this year is roughly half the usual number of households. Whilst this still represents a large sample, confidence intervals are wider than in a normal FRS year, and this needs to be borne in mind when interpreting the estimates in this publication. In broad terms, users should expect the standard errors around this year’s FRS estimates to be 40% larger than in a typical FRS year. The exact difference will vary from estimate to estimate.

All survey estimates have a sampling error attached to them, calculated from the variability of the observations in the sample. From this, a margin of error (confidence interval) is estimated. It is this confidence interval, rather than the estimate itself, that is used to make statements about the likely ‘true’ value in the population; specifically, to state the probability that the true value will be found between the upper and lower limits of the confidence interval. In general, a confidence interval of the estimate plus or minus two standard errors is used to state, with 95% confidence, that the true value falls within that interval. A small margin of error will result in a narrow interval, and hence a more precise estimate of where the true value lies.

The sample in Great Britain for the FRS, as described earlier, is selected using a stratified multi-stage design, based on addresses clustered within postcode sectors. As a result, FRS sampling error is not just dependent on the variability among units in the sample (whether households or individuals), but is also a function of variability within and between postcode sectors. For example, if a sample characteristic is distributed differently by postcode sector (i.e. is clustered) the sampling variability is greater overall than would occur in a simple random sample of the same size. Therefore, the complex (actual) sampling error is normally greater than the standard error calculated under the assumption of simple random sampling.

The size of the actual standard error relative to the standard error calculated under the assumption of simple random sampling is represented by the design factor, which is calculated as the ratio of the two. Where the standard errors are the same, the design factor equals one, implying that there is no loss of precision associated with the use of a clustered sample design. In most cases, the design factor will be greater than one, implying that the estimates based on the clustered sample are less precise than those of a simple random sample of the same size. Conversely a design factor of less than one implies the estimate is more precise than would be obtained from a simple random sample.

Standard Errors

Methodology Tables SE.1 to SE.9

These tables provide standard errors, design factors and confidence intervals for a selection of variables from the 2020 to 2021 FRS. An example of how to interpret figures in this table follows:

Example: Standard errors for household composition, table SE.1

Table SE.1 shows that 72% of households did not contain any children. The standard error is estimated as 0.7 per cent. This is the final estimate after rounding and taking into account the design factor.

The design factor for this variable is 1.5. That is, the effect of using a clustered sample rather than a simple random sample is a loss in precision of 50% on standard errors. In contrast, a design factor of 0.9 would have denoted a gain in precision of 10%.

The 95% confidence interval (of plus or minus two standard errors) is given as 70.9% to 73.6%. That is, if sampling error is the sole source of error, in 95 out of 100 samples the percentage of households without children will lie within this range.

The sampling errors shown are likely to be slightly larger than the true sampling errors because the software used for the calculation does not take into account the improvement in precision due to post-stratification.

See the linked paper for information on estimating variance and confidence intervals in special circumstances for example, where the occurrences of a response in the sample are very small.

In addition to sampling errors, consideration should also be given to non-sampling errors. Sampling errors arise through the process of random sampling and the influence of chance. Non-sampling errors arise from the introduction of some systematic bias in the sample compared with the population it is supposed to represent.

As well as response bias, such biases include inappropriate definition of the population; misleading questions; data input errors; data handling problems; or any other factor that might lead to the survey results systematically misrepresenting the population. There is no simple control or measurement for such non-sampling errors, although the risk can be minimised through careful application of the appropriate survey techniques from the questionnaire and sample design stages through to analysis of results.

13. Linking FRS data to administrative data

In line with the DWP Digital data strategy, the Department is committed to transforming its surveys by linking administrative data from the full range of available sources (for example, from other parts of government). Furthermore, as a national statistic, and in line with the Code of Practice for Statistics (Value V4.1) DWP looks to improve the FRS, year on year.

The FRS first started asking respondents for consent to link to administrative data in 2007. Consenting respondents were then matched by Name, Address, Postcode and Date of Birth to the department’s Central Information System, to obtain their National Insurance Numbers, which were used to link their administrative records.

This approach was used between 2007 and 2018. On average, around 66% of respondents consented, and with a successful match rate of around 80%, our effective match rate was just over 50% – which limited potential for enhancing the FRS with administrative data.

The introduction of GDPR in 2018, has provided us with an alternative to consent as the legal basis for linking. We can now link all respondents on the basis that the processing is necessary for the department to carry out its functions as a public body (GDPR Article 6(1)(e)).

This change, together with improvements in our linking methodology, means that we can now link at least 95% of FRS respondents to their admin records. This has opened the potential to realise a range of financial, data quality, respondent and user benefits through the integration of administrative data into the survey.

The FRS Administrative Data Transformation Project has been set up to investigate the potential of all administrative data sources and realise the benefits. This is in the wider context of DWP Digital’s Data Strategy for optimising use and re-use of administrative data, the UK Statistics Authority’s Strategy for data linking and the Office for National Statistics move by ONS towards an ‘admin data first’ approach to meeting government information needs.

It should also be noted that development has continued into 2021, in response to a number of OSR recommendations that relate to developments in the use of integrated survey and administrative data. These are:

• the strategic recommendation that innovation is needed for the statistics to deliver their full potential and serve the public good – opportunities for data linkage should be maximised and data gaps should be addressed, building on work already underway in the GSS to explore the use of administrative data and its integration with social surveys

• DWP and ONS, building on existing work to explore the feasibility and potential of social survey and administrative data integration, should explore whether integration can help improve the timeliness and robustness of income-based poverty statistics

• DWP and ONS should prioritise work to address under-reporting at the bottom end of the income distribution – they should consider a multifaceted approach to solving this problem, such as data linkage and making greater use of administrative data

Please see the DWP Statistical Work Programme for more details.

Our existing long-term work programme developing integrated survey-administrative datasets (see section 2.5) will meet the aims of these objectives in the future.

We make comparisons of FRS survey and administrative data in a number of ways. Please see Methodology tables M.6a and M.6b, for a summary of how FRS benefit caseloads and amounts compare with DWP administrative data. In particular, the benefit caseload undercounts for Carer’s Allowance, Employment and Support Allowance (ESA) and Personal Independence Payment (PIP) were smaller in 2020 to 2021 than in 2019 to 2020.

These are outlined in the following tables.

Methodology Table M.6a

M6a compares the grossed number of benefit recipients in the FRS 2020 to 2021 data, with the total caseload on benefit from administrative data sources. For all benefits, and as in most previous years, the FRS numbers in receipt are below those seen in administrative data. The difference varies by benefit, with State Pension and Disability Living Allowance (DLA) both showing a difference of less than five per cent.

Methodology Table M.6b

M6b compares the average weekly receipt of state support in the FRS 2020 to 2021 data, with average receipt from administrative data sources. For example, in 2020 to 2021 the FRS under-estimated the average weekly amount of Housing Benefit and Pension Credit, by 14% and 11% respectively. Some benefit types have not been included in this analysis because no directly comparable administrative data source is available.

Methodology Table M.8

M8 also compares FRS and administrative data, but linked at a record level, and shows receipt of DWP benefits for the 2020 to 2021 survey year across either or both of those sources. Percentages are on a post-grossing basis. It can be seen that some benefits are better represented on the FRS than others: For example, 99% of adults in receipt of State Pension are represented on the FRS, while only 69% of those in receipt of Attendance Allowance are.

Percentage of adults shown in receipt of DWP benefits, FRS and administrative data, 2020 to 2021, Great Britain

14. Glossary

This glossary provides a brief explanation for each of the key terms used in the Family Resources Survey (FRS). Further details on these definitions, including full derivations of variables, are available on request from the FRS team: team.frs@dwp.gov.uk.

Adult

All individuals who are aged 16 and over are classified as an adult, unless the individual is defined as a dependent child. All adults in the household are interviewed as part of the FRS.

Age

Respondent’s age at last birthday (at the time of the interview).

Automatic Enrolment

Automatic enrolment requires all employers to enrol their eligible workers into a workplace pension scheme if they are not already in one. This enrolment also commits the employer to make contributions into the employee’s pension. The staged timetable began in October 2012 for larger firms, with enrolment for all employers completed in 2018. In order to preserve individual responsibility for the decision to save, workers can opt out of the scheme. To be eligible for automatic enrolment, the jobholder must be at least 22 years old, under State Pension age, earn above the earnings threshold for automatic enrolment, and work or usually work in the UK.

However, those not eligible for automatic enrolment may be entitled to opt in. Those people now defined as self-employed could have been a member of an employer scheme, from auto-enrolment, but are entitled to remain in their auto-enrolled scheme and make their own contributions. Likewise, someone who is now an employee, who was previously self-employed can have employer contributions to their previous scheme. For more information see this pensions guide

Benefit Unit or Family

A benefit unit may consist of: a single adult, or a married or cohabiting couple, plus any dependent children. Same-sex partners (civil partners and cohabitees) have been included in the same benefit unit since January 2006. Where a total for a benefit unit is presented (such as total benefit unit income) this includes both income from adults plus any income from children.

There are various types of benefit unit:

• Pensioner couple: Benefit units headed by a couple where the head of the benefit unit is over State Pension age. Note that this differs from definitions used in the Households Below Average Income, Income Dynamics and Pensioners’ Incomes Series reports. These publications define a benefit unit as a pensioner couple if either the head of the benefit unit or their partner is over State Pension age
• Pensioner couple, married or civil partnered: Benefit units headed by a couple where the head of the benefit unit is over State Pension age and the couple are either married or in a civil partnership
• Pensioner couple, cohabiting: Benefit units headed by a couple where the head of the benefit unit is over State Pension age, and the couple are neither married nor in a civil partnership
• Single male pensioner: Benefit units headed by a single male adult over State Pension age
• Single female pensioner: Benefit units headed by a single female adult over State Pension age
• Couple with children: Benefit units containing two adults, headed by a non-pensioner, with dependent children
• Couple with children, married or civil partnered: Benefit units containing two adults, headed by a non-pensioner, with dependent children and the couple are either married or in a civil partnership
• Couple with children, cohabiting: Benefit units containing two adults, headed by a non-pensioner, with dependent children and the couple are neither married nor in a civil partnership
• Couple without children: Benefit units containing two adults, headed by a non-pensioner, with no dependent children
• Couple without children, married or civil partnered: Benefit units containing two adults, headed by a non-pensioner, with no dependent children and the couple are either married or in a civil partnership
• Couple without children, cohabiting: Benefit units containing two adults, headed by a non-pensioner, with no dependent children and the couple are neither married nor in a civil partnership
• Single with children: Benefit units containing a single adult (male or female), headed by a non-pensioner, with dependent children
• Single male without children: Benefit units containing a single male adult, headed by a non-pensioner, with no dependent children
• Single female without children: Benefit units containing a single female adult, headed by a non-pensioner, with no dependent children

Benefits

Financial support from the Government. Most of these benefits are administered by DWP. The major exceptions are Housing Benefit and Council Tax Reduction, which are administered by local authorities.

Child Benefit is administered by HM Revenue and Customs. HMRC also administer Tax Credits. These are not treated as benefits, but both Tax Credits and benefits are included in the term State Support. Tax Credits will ultimately be superseded by Universal Credit.

Benefits are often divided into income-related benefits and non-income-related benefits. In assessing entitlement to the former, the claimant’s income and savings will be checked against the rules of the benefit. In contrast, eligibility for non-income-related benefits is dependent on the claimant’s circumstances (a recent bereavement, for example), rather than their income and savings. A list of the main state benefits can be found in the table below.

United Kingdom benefits

Income-related benefits	Non-income-related benefits
Council Tax Reduction	Armed Forces Compensation Scheme
Employment and Support Allowance (income-related element)	Attendance Allowance
Extended Payments (Council Tax Reduction and Housing Benefit)	Bereavement or Widowed Parent’s Allowance
Housing Benefit	Bereavement Support Payment
Income Support	Carer’s Allowance
Jobseeker’s Allowance (income-based element)	Child Benefit
Pension Credit	Disability Living Allowance (both mobility and care components)
Social Fund – Funeral Grant	Employment and Support Allowance (contributory element)
Social Fund – Sure Start Maternity Grant	Guardian’s Allowance
Universal Credit	Jobseeker’s Allowance (contributory element)
	Incapacity Benefit
	Industrial Injuries Disablement Benefit
	Personal Independence Payment (Daily Living and Mobility components)
	Maternity Allowance
	Severe Disablement Allowance
	State Pension
	Statutory Maternity, Paternity or Adoption Pay
	Statutory Sick Pay
	Winter Fuel Payments

Northern Ireland benefits

Income related benefits	Non Income related benefits
Northern Ireland Other Rate Rebate	Northern Ireland Disability Rate Rebate
Northern Ireland Rate Rebate through energy efficient homes	Northern Ireland Lone Pensioner Rate Rebate
Northern Ireland Rate Relief
Rates Rebate

‘Disability-related benefits’ is the term used to describe all benefits paid on the grounds of disability. These are

• Personal Independence Payment
• Disability Living Allowance
• Severe Disablement Allowance
• Attendance Allowance
• Armed Forces Compensation Scheme
• Industrial Injuries Disablement Benefit
• Northern Ireland Disability Rate Rebate.

Before 2008 to 2009 Incapacity Benefit was also in this group.

The number of people on Incapacity Benefit (IB), and Severe Disablement Allowance (SDA) has been steadily decreasing over time, as both were replaced by Employment and Support Allowance from October 2008. Some benefits now have sample sizes which are too small to be presented separately in this publication.

Child

A dependent child is defined as an individual aged under 16. A person will also be defined as a child if they are 16 to 19 years old and they are:

• Not married nor in a civil partnership nor living with a partner; and
• Living with parents (or a responsible adult); and
• In full-time non-advanced education or in unwaged Government training

Child Benefit

This is a non-income related benefit in terms of eligibility, but remains taxable in households where one adult is earning more than £50,000 per year.

Council Tax

The tax is based on a set of bands that a property’s value falls into and is evaluated accordingly by each council. Its headline rate is based on two adults per household.

Disability

The definition of disability used in this publication is consistent with the core definition of disability under the Equality Act 2010. A person is considered to have a disability if they “have a physical or mental impairment that has a ‘substantial’ and ‘long-term’ negative effect on their ability to do normal daily activities”. Whereby ‘substantial’ means more than minor or trivial, and ‘long-term’ means 12 months or more. However, some individuals classified as disabled and having rights under the Equality Act 2010 are not captured by this definition:

• People with a long-standing illness or disability who would experience substantial difficulties without medication or treatment
• People who have been diagnosed with cancer, HIV infection or multiple sclerosis but who are not currently experiencing difficulties with their day-to-day activities
• People with progressive conditions, where the effect of the impairment does not yet impede their lives.
• People who were disabled in the past but are no longer limited in their daily lives are still covered by the Act

This definition of disability differs from that used for Economic status.

Economic status

This classification follows the harmonised output category for economic status, based on respondents’ answers to the survey questions. All definitions conform to those of the International Labour Organization (ILO):

• Employee: where respondents have an arrangement with an employer, whereby work is done in exchange for a wage or salary. This would include those doing unpaid work in a business that a relative owns
• Self-employed: where respondents report regular working activities, which over time are responsible only to themselves (and not an employer). Various groups are classified as self-employed, including farmers, doctors in private practice and some builders, as well as anyone whose job is habitually done on a freelance basis (e.g. journalists or musicians). The self-employed include anyone doing work for their own business, but which is currently unpaid

Several respondents have more than one job. The FRS identifies which of these is their ‘main job’. This is the job which the respondent says is the dominant activity. Where they cannot decide, the number of hours worked will determine which is the main job. This process of categorisation also applies to respondents who are employees in one job but self-employed in another; whilst the survey will capture information on both of these jobs, only one can be their main job.

• Unemployed: Adults who are under State Pension age and not working, but are available and have been actively seeking work in the last four weeks; includes those who were waiting to take up a job already obtained and were to start in the next two weeks

• Economically inactive: Individuals who are both out of work, and not seeking or not available to work. There are several sub-categories:

• Retired: individuals who are over State Pension age, or say they are now retired
• Student: individuals who have not completed their education
• Looking after family or home: working-age individuals who are looking after their family or their home
• Permanently sick or disabled: working-age individuals who have been sick, injured or disabled for longer than 28 weeks
• Temporarily sick or disabled: working-age individuals who have been sick, injured or disabled for less than 28 weeks. Note that the sick or disabled definitions are different to that used for Disability, as they are based on different questions that are only asked of working-age adults who are not working
• Other inactive: all respondents not already classified above

Employment status

This classification is equivalent to economic status but includes those in employment only.

Ethnic group

The ethnic group to which respondents consider that they belong. Ethnicity representation rates are now calculated from known declarations and exclude ‘choose not to declare’ and ‘unknown’.

Where respondents do volunteer their ethnicity, this is captured as one of 18 recognised groups. This is consistent with the harmonised principles for ethnicity, as set out by the Government Statistical Service, wherever social surveys are carried out.

• White
• Irish Traveller
• Mixed or Multiple ethnic groups
• Asian or Asian British
• Indian
• Pakistani
• Bangladeshi
• Chinese
• Any other Asian background
• Black or African or Caribbean or Black British
• Other ethnic group

Sample sizes for ‘Gypsy, Traveller or Irish Traveller’ are small. In Northern Ireland, ‘Irish Traveller’ is included in ‘Other ethnic group’ whereas elsewhere ‘Gypsy or Irish Traveller’ is included in ‘White’. The group ‘Arab’ is included in ‘Other ethnic group’.

Food Security. See Household Food Security.

Harmonised Principles

The harmonised principles contain harmonised definitions, survey questions, standards for administrative data and standards for presentation. They have been developed by topic groups, after wide consultation with producers and customers across the GSS and beyond. Further information is available via the Government Statistical Service pages

Full-time education

Individuals registered as full-time at an educational establishment. Students on sandwich courses are coded as working, or studying, depending on their position at the time of interview.

Head of benefit unit

If the household reference person does not belong to the benefit unit, then the head of benefit unit is simply the first person from that benefit unit, in the order they were named in the interview. If the household reference person does belong to the benefit unit, they are also the head of that benefit unit.

Household

A household consists of one person living alone or a group of people (not necessarily related) living at the same address, who share cooking facilities and share a living room or sitting room or dining area. A household will consist of one or more benefit units. Where a total value for a household is presented, such as total household income, this includes both income from adults plus any income from children.

Household food security

“Food security” as a concept is defined as “access by all people at all times to enough food for an active, healthy life”. Questions relate to the household’s experience in the 30 days immediately before the interview.

The questions are put to the person in each household who is best placed to answer about food shopping and preparation. These respondents are asked the first three questions, on whether they are concerned about:

• food running out before they had enough money to buy more
• the food they had bought not lasting, and not having money to buy more
• not being able to afford balanced meals

The possible answers are ‘often, ‘sometimes’ or ‘never’ true. If respondents say that all three statements are never true they will not be asked further questions on food security. If respondents answer that any of these statements are sometimes or often true they will be asked further questions on the extent of their food security.

Taking the responses together, a household ‘score’ for food security is then derived. This is a measure of whether households have sufficient food to facilitate active and healthy lifestyles. This measure has four classifications:

• High food security (score=0): The household has no problem, or anxiety about, consistently accessing adequate food
• Marginal food security (score= 1 or 2): The household had problems at times, or anxiety about, accessing adequate food, but the quality, variety, and quantity of their food intake were not substantially reduced
• Low food security (score = 3 to 5): The household reduced the quality, variety, and desirability of their diets, but the quantity of food intake and normal eating patterns were not substantially disrupted
• Very low food security (score = 6 to 10): At times during the last 30 days, eating patterns of one or more household members were disrupted and food intake reduced because the household lacked money and other resources for food

High and marginal food security households are considered to be “food secure”. Food secure households are considered to have sufficient, varied food to facilitate an active and healthy lifestyle. Conversely, low and very low food security households are considered to be “food insecure”. Food insecure households are where there is risk of, or lack of access to, sufficient, varied food.

The broad structure and sequence of the questions is the same as those used internationally. They are used within the UK (Food Standards Agency) and are also used by other countries, including the United States Department of Agriculture, enabling broad international comparability of the results.

Household Reference Person (HRP)

The highest income householder:

• In a single-adult household, the HRP is simply the sole householder (i.e. the person in whose name the accommodation is owned or rented)
• If there are two or more householders, the HRP is the householder with the highest personal income, taking all sources of income into account
• If there are two or more householders who have the same income, the HRP is the elder

Where we refer to ‘Head’ in tables relating to households, this is the HRP. The Head of benefit unit will not necessarily be the HRP.

Individual

An adult or child. Where ‘people’ are presented, this is all adults and children.

Informal carers

Individuals who provide any regular service or help to someone. That person can be within or outside of their household, and might be sick, disabled or elderly; this description excludes those who give this service or help as part of a formal job.

Marital status

This is the person’s de facto marital status:

• Married or Civil partnership: currently married or in a civil partnership, and not separated from spouse (excludes temporary absences)
• Cohabiting: not married nor in a civil partnership, but living as a couple
• Single: is not currently cohabiting and has never been married nor in a civil partnership
• Widowed: widowed and not currently cohabiting
• Separated: married or in a civil partnership, but separated from spouse and is not currently cohabiting
• Divorced or Civil partnership dissolved: marriage or civil partnership legally dissolved

Non-advanced education

Non-advanced education for benefits purposes includes:

• ‘A’ levels, or similar qualifications (eg. the International Baccalaureate and Pre-U)
• T levels (introduced in September 2020)
• Scottish national qualifications at higher or advanced higher level
• NVQ at Level 3
• study programme in England
• national diploma
• ordinary national diploma
• national certificate of edexcel

If the young person is studying for a course that is not classed as advanced education, the education is normally treated as non-advanced. Non-advanced education does not include university courses.

Pension

• Employer-sponsored pension: schemes that are set up and run by the employer
• Occupational pension: an occupational pension scheme is an arrangement an employer makes to give their employees a pension when they retire. They are often referred to as ‘company pensions’. As of 2017 the Occupational Pension Schemes regulations brought restrictions on the Early Exit charges for those aged 55 and older, and are eligible to access the pension freedoms

There are two main types of occupational pension:

• Defined-benefit (DB) schemes (also called salary-related pension or superannuation schemes). In a defined benefit scheme, the pension is based on the number of years you belong to the scheme and how much you earn. Your employer contributes to the scheme and trustees look after scheme members’ interests. Employees often have to pay contributions into the scheme on top of those made by the employer. Some schemes are ‘non-contributory’: The employee either makes no contributions, or makes a small contribution, typically 1%-2% of salary

• Defined-contribution (DC) schemes (also called Money purchase schemes). A defined contribution scheme can be a personal pension arranged by the individual or a workplace pension arranged by the employer (such as NEST). Money is paid in by the individual or the employer over time and is then invested by the pension provider. The size of the pension available to take out when the individual retires depends on how much was paid in and the level of growth from the investments. With a defined contribution pension the individual can also decide how to take their money out

• Group personal pension: some employers who do not offer an occupational pension scheme may arrange for a third-party pension provider to offer employees a pension instead. The employer may have negotiated special terms with the provider, which means that administration charges are lower than those for individual personal pensions. Although sometimes still referred to as ‘company pensions’, they are not run by employers and should not be confused with occupational pensions, which have different tax, benefit and contribution rules

• Group stakeholder pension: like Group Personal Pensions, an employer can make an arrangement with a pension provider and offer their employees a Group Stakeholder Pension (see Stakeholder Pension)

• Personal pension: a pension provided through a contract between an individual and the pension provider. The pension which is produced will be based upon the level of contributions, investment returns and annuity rates; a personal pension can be either employer provided (see Group Personal Pension) or privately purchased (see Private pension)

• Private pension: includes occupational pensions (also known as employer-sponsored pensions) and personal pensions (including stakeholder pensions). People can have several different private pensions at once

• Stakeholder pension: enables those without earnings, such as non-earning partners, carers, pensioners and students, to pay into a pension scheme. Almost anybody up to the age of 75 may take out a stakeholder pension and it is not necessary to make regular contributions

For more information, see the Gov.UK pension guide.

Pension Credit

The qualifying age for Pension Credit has been increasing gradually in line with the increase in the State Pension age.

Region

Regional classifications are based on the standard statistical geography of UK Regions: nine in England, and a single region for each of Wales, Scotland and Northern Ireland. Tables will also show statistics for the United Kingdom, Great Britain, and England as a whole.

Some split London into Inner and Outer where there is sufficient data to provide meaningful comparisons.

• Inner London boroughs: Camden, City of London, Greenwich, Hackney, Hammersmith and Fulham, Islington, Kensington and Chelsea, Lambeth, Lewisham, Southwark, Tower Hamlets, Wandsworth, Westminster

• Outer London boroughs: Barking and Dagenham, Barnet, Bexley, Brent, Bromley, Croydon, Ealing, Enfield, Haringey, Harrow, Havering, Hillingdon, Hounslow, Kingston upon Thames, Merton, Newham, Redbridge, Richmond upon Thames, Sutton, Waltham Forest

Savings

The total value of all liquid assets, including fixed-term investments. Pound amounts are informed by responses to questions on the value of assets or, in some cases, estimated from the interest on the savings. Note that banded savings do not include assets held by children in the benefit unit or household.
The FRS asks questions about all saving and investment products, including bank and building society accounts, and shares. These products go by many names. In this publication, the products are labelled as follows:

• Basic bank account: This type of account is similar to a current account. Payments can be received from other sources and it can pay bills by direct debit, but unlike a current account there are no overdraft facilities. Withdrawals can be made from cash machines and, in some cases, over the counter of the bank or building society itself

• Child Trust Funds (CTFs) have been replaced by Junior ISAs (JISAs) as the main tax-free savings account for children. See ISA

• Current account: This includes all accounts at both banks and building societies, which are used for day-to-day transactions; with a bank card. Overdraft facilities may be offered
• Company share schemes (profit sharing): Some companies provide extra rewards or bonuses to their employees depending on the profitability of the company. In publicly traded companies, this often takes the form of shares in the company. This label is given to any scheme which follows this general principle
• Credit union: A credit union is a financial co-operative similar in many respects to mainstream building societies. Its members both own and control the credit union, which is run solely for their benefit. All members of a specific credit union must share what is known as a “common bond” i.e. they must be connected in some way to the other members of that credit union. The members pool their savings into a single ‘pot’ from which loans can be made to members of the credit union. Members who have deposited money receive an annual dividend, while those to whom money is lent have to pay interest on the loan
• Endowment policy (not linked): An endowment policy taken out to repay a mortgage but no longer used to do so. This is where the mortgage has either been paid off or, more usually, converted to a different method of repayment. The respondent has decided to retain the endowment as an investment in its own right, even though it is no longer intended to repay the mortgage
• ISA: An Individual Savings Account (ISA) pays interest on a tax-free basis To be eligible for a Junior ISA, children must be under 18 and living in the UK. Junior ISAs are now included at the question ChSave. There are two types of Junior ISA. A child can have both types; a cash Junior ISA; a stocks & shares Junior ISA. There is a limit on annual payments into JISAs

As with Child Trust Funds, the Junior ISA is a long-term savings account which can only be accessed by the child on their 18th birthday. The Junior ISA is then transferred to an Adult ISA so that the child can access their money.

• Investment trust: See Unit trusts
• National savings bonds: All types of National Savings investments in this category are collected on the survey, except Easy Access and Investment accounts:
  • Fixed Rate Savings Bonds: replaced new issues of FIRST Option Bonds
  • National Savings Certificates: yield earnings in either a fixed or index-linked manner, for lump sum savings of £100 or more. Maximum earnings are obtained after five years and interest on investments is tax free
  • National Savings Income Bonds: minimum purchase is £2,000 and a maximum holding of £250,000; interest is paid monthly, and is gross of tax
  • Children’s Bonus Bonds: can be bought for any child aged under 16 as a five-year accumulating investment; interest is paid gross of tax
• NS&I savings accounts: The National Savings & Investments (NS&I) Investment Account and Direct Saver
• Other bank or building society account: Accounts belonging to adults recorded under categories “savings account, investment account or bond, any other account with bank building society, etc
• Post Office card account (POCA): This type of account can only be used to receive benefits and Tax Credit payments. Some other payments, such as Housing Benefit, occupational pensions, or wages cannot be paid into it. Payments can only be collected over the counter at a Post Office and will not incur any charges or accrue interest on money contained therein. Due to the limited capability to receive payments, these accounts are included or excluded in tables as noted
• Premium bonds: Investments which do not earn interest, but are entered in a monthly draw for tax-free cash prizes
• Stocks and shares: This includes all bonds, debentures and other securities which are usually traded on the financial markets. Bonds issued by the UK or foreign governments, or local authorities would also be recorded here. A share is a single unit of ownership in a company. ‘Stocks’ is the general term for various types of security issued by companies to raise financial support. If respondents are members of a shares club they will be included with those owning stocks and shares
• Unit trusts: A collectively managed investment in the financial markets, where investors buy ‘units’ of a fund, which invests in shares, stocks, Gilts, etc. Dividends are paid net of tax. The data presented for unit trusts also includes investment trusts, since these two assets are collected together in the FRS
• Any other type of asset: This is a catch-all category for the small numbers who own other types of financial asset. This includes Gilts (HM Government bonds) which raise money for the UK Government by offering a secure investment, usually over a fixed term, and usually with a set rate of interest although some are index-linked. Interest is paid half-yearly

The above products cover all types of savings. Some of them are grouped together in other ways in the tables:

• Direct payment account: A direct payment account is one that can accept electronic payment of benefits via BACS (the Banker’s Automated Clearing System). The types of accounts included in this grouping are:

• Current Account
• National Savings and Investments Savings Accounts
• Savings, investments etc.
• Basic Account

Where noted, Post Office Card Accounts are also included in this group.

Sources of income

• Wages and salaries: for a respondent currently working as an employee, income from wages and salaries is equal to: gross pay before any deductions, less any refunds of income tax, any motoring and mileage expenses, any refunds for items of household expenditure and any Statutory Sick Pay or Statutory Maternity Pay, plus bonuses received over the last 12 months (converted to a weekly amount) and any children’s earnings from part-time jobs

• Self-employed income: the total amount of income received from self-employment gross of tax and national insurance payments, based on profits (where the individual considers themselves as running a business) or on estimated drawings otherwise. Excludes any profits due to partners in the business. Any losses are recorded as such
• Self-employed respondents are asked questions on their most recent business accounts as submitted to HMRC: dates of the accounts, profit or loss figures, and amounts paid in tax and National Insurance
• They are then asked if they draw money from their business accounts for non-business purposes, such as for payments to themselves, personal spending, paying domestic bills etc. and how much this is per month on average. They are also asked if they receive other income from their business for personal use, e.g. cash in hand, and how much this is per month on average

• Those who do not keep annual business accounts and do not draw money for non-business purposes are asked for their income after paying for materials, equipment, goods etc. and whether they make tax and National Insurance payments on this amount

• Investments: Interest and dividends received on savings and investments. See Savings and investments for details of investments covered by the FRS
• Tax Credits: Income from Tax Credits
• State Pension plus any Pension Credit: for any adults who are over State Pension age, any State Pension plus any Pension Credit which is received; these benefits are shown together because of known problems with separating these amounts for pensioners
• Other pensions: payments received from pension schemes, including occupational, stakeholder or personal pension schemes; employee pensions for surviving spouses, annuity pensions, trusts and covenants
• Disability benefits: payments received from any of the benefits payable due to disability – see Benefits
• Other benefits: payments received from any of the other Benefits
• Other sources: payments from all other sources including, for example, baby-sitting, allowances from absent spouses including child maintenance, organisations, royalties, odd jobs, sub-tenants, educational grants, alimony and Healthy Start Vouchers

State Pension age

Since 6 April 2010, the State Pension age for women has been gradually increasing and since December 2018 has been increasing for both men and women. On 6 March 2020, the State Pension age for both men and women increased to over 65 years 8 months. The State Pension age for both men and women continued to increase at the same rate, reaching 66 by October 2020. Details of further planned changes to State Pension age

State support

An individual is in receipt of state support if they receive one or more benefits, or are being paid Tax Credits.

Tax Credits

Working Tax Credits and Child Tax Credits are paid by HM Revenue & Customs. Tax Credits are being phased out, as they are replaced by Universal Credit.

Tenure

This is the basis on which the head of household is resident in their dwelling. Types of renting or ownership as classified as follows:

• Social renting: includes all cases where the landlord is either the local authority, or a housing association
• Private renting: all cases where the property is rented from a private landlord, including those on a rent-free basis

Rent-free accommodation is any provided free by an employer or by an organisation to a self-employed respondent, provided that the normal activities of the tenant are to further the cause of the organisation (e.g. Church of England clergy). Accommodation is not classed as rent-free if anyone, apart from an employer or organisation, is paying a rent or mortgage on a property on behalf of the respondent.

• Buying with a mortgage: includes local authority and housing association part-own-and-part-rent, and shared ownership arrangements
• Owned outright: households who pay neither rent, nor any mortgage or loan used to purchase the property. These households may have other loans secured on their property for which information is collected on the FRS. However, these payments are excluded from the costs of housing

Prior to 2008-09, social renting was split into council and housing association groups. This division was removed because it was found to be unreliable. Comparison with administrative data showed that a significant number of housing association tenants wrongly reported that they were council tenants. Also, in 2008-09, a split between furnished and unfurnished private renting was removed.

Universal Credit

Universal Credit (UC) is now the primary working age benefit. Most claimants will be of working age, though claimants 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.

UC has now completed its nationwide roll-out for new claims, and is available throughout GB and Northern Ireland.

Universal Credit replaces all of 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. It replaces the numerous payments these benefits would have given with a single, usually monthly payment, administered by DWP.

The Universal Credit (Managed Migration Pilot and Miscellaneous Amendments) Regulations 2019 provided for the removal of the Severe Disability Premium (SDP) Gateway from 27 January 2021, meaning that from this date, SDP recipients will be able to make a new claim to Universal Credit.

The regulations also introduced the SDP transitional payments to those claimants who were previously entitled to the SDP as part of their legacy benefit and had moved to Universal Credit before the SDP Gateway came into effect on 16 January 2019.

Working

All respondents whose employment status was employed or self-employed, irrespective of full-time or part-time working patterns.

Working-age

Adults (see Adult and Child) under State Pension age.