Households below average income series: quality and methodology information report FYE 2022

Question 1

Introduction

Accepted Answer

The Households Below Average Income (HBAI) report presents information on living standards in the United Kingdom and is the foremost source for data and information about household income, and inequality in the UK. It provides annual estimates on the number and percentage of people living in low-income households.

HBAI statistics incorporate widely-used, international standard measures of low income and inequality. They provide a range of measures of low income, income inequality, and material deprivation to capture different aspects of changes to living standards. The current series started in Financial Year Ending (FYE) 1995 and so allows for comparisons over time, as well as between different groups of the population.

The statistics are based on the Family Resources Survey (FRS), whose focus is capturing information on incomes, and as such captures more detail on different income sources compared to other household surveys. The FRS captures a lot of contextual information on the household and individual circumstances, such as employment, education level and disability. This is therefore a very comprehensive data source allowing for a lot of different analysis.

This report provides detailed information on key quality and methodological issues relating to HBAI data. Information on the FRS methodology is available in the FRS Background Information and Methodology.

Impact of the coronavirus (COVID-19) pandemic on the statistics for FYE 2021 and FYE 2022

Fieldwork operations for the Family Resources Survey (FRS) were changed in response to the coronavirus (COVID-19) pandemic and the introduction of national lockdown restrictions in March 2020. The established face-to-face interviewing approach employed on the FRS was suspended and replaced with telephone interviewing from April 2020 for the whole of the 2020 to 2021 and 2021 to 2022 survey year. This change impacted on both the size and composition of the achieved samples for those years. The data published for FYE 2021 is limited to headline measures and not available in our supplementary tables or on our Stat-Xplore tool. It is, however, still deposited for download by users in the UK Data Service.

We recommend that users exercise caution when interpreting any data published for these survey years, particularly when making comparisons with years prior to the coronavirus (COVID-19) pandemic.

This report will not detail the effect the coronavirus (COVID-19) pandemic had on the sample data and estimates. For this information, users are advised to consult the technical reports which accompanied the FYE 2021 and FYE 2022 publications. The report will, however, provide detail on the methodological changes made during the pandemic to take account of new income sources and the changes made to the HBAI grossing regime.

Comparing official statistics across the UK

All official statistics from the HBAI for the UK and constituent countries in this publication are considered by the Department for Work and Pensions (DWP) as “Fully Comparable at level A*” of the UK Countries Comparability Scale (with the exception of measures estimated on a before housing cost (BHC) basis for Northern Ireland, due to differing treatment of water rates).

National Statistics

The regulatory arm of the UK Statistics Authority, the Office for Statistics Regulation, has designated the Family Resources Survey as National Statistics, in accordance with the Statistics and Registration Service Act 2007 and signifying compliance with the Code of Practice for Statistics (the Code).

National Statistics status means that official statistics meet the highest standards of trustworthiness, quality and public value and comply with all aspects of the Code. The Office for Statistics Regulation has undertaken this assessment to consider whether the statistics meet the required standard.

It is DWP’s responsibility to maintain compliance with the standards expected of National Statistics. If DWP becomes concerned about whether these statistics are still meeting the appropriate standards, we will discuss any concerns with the Office for Statistics Regulation. National Statistics status can be removed at any point when the highest standards are not maintained, and reinstated when standards are restored.

Further information about National Statistics can be found here.

Acknowledgements

As in previous years, the DWP would like to thank the Institute for Fiscal Studies (IFS) for the substantial assistance that they have provided in checking and verifying the income data and grossing factors underlying the main results in this edition.

We are also grateful to HM Revenue and Customs (HMRC) for the provision of aggregated data from the Survey of Personal Incomes.

Users and uses

HBAI is a key source for data and information about household income and inequality and is used for the analysis of low income by researchers and the Government. Users include: policy and analytical teams within the DWP, the Devolved Administrations, other Government departments, local authorities, Parliament, academics, journalists, and the voluntary sector.

The Department for Work and Pensions’ responsibilities include understanding and dealing with the causes of poverty rather than its symptoms, encouraging people to work and making work pay, encouraging disabled people and those with ill health to work and be independent, and providing a decent income for people of pension age and promoting saving for retirement. Progress towards these responsibilities will affect these results.

The key uses of the published statistics and datasets are:

to provide detail on the overall household income distribution and low-income indicators for different groups in the population
for international comparisons
for parliamentary, academic, voluntary sector and lobby group analysis. Examples include using the HBAI data to examine income inequality, the distributional impacts of fiscal policies and understanding the income profile of vulnerable groups.

The first 3 of the 4 income-related measures included in the Welfare Reform and Work Act 2016 are reported in HBAI.

The 4 measures cover the percentage of children in the United Kingdom:

a) who live in households whose equivalised net income for the relevant financial year is less than 60% of median equivalised net household income for that financial year

b) who live in households whose equivalised net income for the relevant financial year is less than 70% of median equivalised net household income for that financial year, and who experience material deprivation

c) who live in households whose equivalised net income for the relevant financial year is less than 60% of median equivalised net household income for the financial year beginning 1 April 2010, adjusted to take account of changes in the value of money since that financial year

d) who live in households whose equivalised net income has been less than 60% of median equivalised net household income in at least 3 of the last 4 survey periods.

Definitions for relevant key terms in the Act are consistent with those given in the Glossary, Income Definition, Equivalisation, and Combined Low income and Child Material Deprivation sections of this report.

Data for reporting against the fourth measure will be released via the Income Dynamics publication.

Further details of the uses of HBAI statistics are given in Annex 3.

What do you think?

We are constantly aiming to improve this report and its associated commentary. We would welcome any feedback you might have and would also be particularly interested in knowing how you make use of these data to inform your work. Please contact us via email: team.hbai@dwp.gov.uk.

Question 2

New for this publication

Accepted Answer

Impact of the coronavirus (COVID-19) pandemic on the sample data and estimates

In FYE 2021 and FYE 2022, several factors impacted on FRS response rates and the distribution of characteristics among FRS survey respondents, including:

change in the mode of interviewing from face to face to telephone
changes in the methods used to elicit responses from survey participants
changes in people’s behaviours and circumstances during the coronavirus (COVID-19) pandemic which may have made them more or less likely to respond to a household survey

While it is not possible to quantify the impact each of these factors had on the HBAI statistics for FYE 2022, we have undertaken extensive analysis of our low-income measures across several dimensions and are content that levels of bias in the data resulting from the mode change are lower than FYE 2021 and are having less influence on the statistics. We have therefore returned to publishing the full suite of our statistics both in our supplementary tables and via the Stat Xplore tool.

More information on our extensive quality assurance is provided in detail in our technical report. This report also provides details on methodological changes made in response to the coronavirus (COVID-19) pandemic, and impact on the HBAI publication.

New statistics on food bank usage for individuals living in low-income households

A new series of questions was added to the FRS in FYE 2022 on the topic of food bank usage. Our household food security tables have been broadened to include statistics on food bank usage among individuals living in low-income households for the first time. The statistics report the number and percentage of individuals living in low-income households who have used a food bank i) within the last 12 months of, and ii) within 30 days of, their Family Resources Survey interview.

Food bank usage measures are reported separately for children, working-age adults, and pensioners, and cover different thresholds of both relative and absolute low income (below 50/60/70% of the appropriate median income). The measures are also available on a ‘before’ and ‘after’ housing costs basis.

Food bank usage questions are asked of the person in the household who knows the most about food purchasing and preparation. This means that the questions do not directly ask about the food bank usage needs of children, and it cannot be determined which individual or individuals the food parcels are for. Food bank usage in the FRS refers only to visits to a food bank when emergency food supplies (food parcels) were obtained. This excludes visits to the food bank made only for other support (e.g. financial advice or mental health support).

More information on these new questions can be found in the FRS report.

Combined low income and working-age adult material deprivation statistics

In March 2022, experimental statistics were published on the number and percentage of working-age adults living in households with combined absolute low income (below 50, 60 and 70% thresholds of the median) and working-age adult material deprivation. This year, the statistics are now included in the HBAI report, and have become National Statistics.

The statistics have also been extended to include relative low income measures. Several tables provide more detail on the composition of working-age adults who are in combined low income and working-age adult material deprivation. This ensures the suite of available statistics and outputs are consistent with those published for children.

There is more information on the methodology underpinning these measures later in this report.

Three-year rolling averages

The HBAI publication usually estimates of the number and proportion of people in low-income households for each UK region and ethnic group using a 3-year rolling average. This is an established method used to smooth out observed variation in single year estimates for these groups, which are subject to smaller sample sizes.

Following our decision to not publish breakdowns of the FYE 2021 estimates, all 3-year averages calculated and published for any period including FYE 2021 are based on 2 data points only.

Grossing changes

To address additional biases in the raw sample, we retained the inclusion of a new grossing control introduced in FYE 2021 to weight the sample by level of educational attainment. This boosted numbers of working-age adults with education levels below degree level and brought it more in line with expectations.

The grossing regime in FYE 2022 has also been adapted to control for the differential level of response seen through the year. We applied a biannual grossing control for Great Britain to balance the number of households across the 2 halves of the survey year. This was necessary due to the pre-planned introduction of FRS sample boost in England and Wales in October 2021.

In Northern Ireland, changes to the approach of contacting respondents in July 2021 meant that the achieved sample increased markedly partway through the year. This is not normally a feature of the FRS achieved sample, with response normally spread relatively equally over each twelve-month run of fieldwork. We introduced a quarterly household grossing control to balance their sample across the year.

For more information on the methodology, please see the grossing section of this report.

Treatment of income sources introduced during the coronavirus (COVID-19) pandemic

Two major new sources of income were introduced in FYE 2021 to support jobs and businesses affected by the coronavirus (COVID-19) pandemic – the Coronavirus Job Retention Scheme (CJRS) for employees, and Self-Employment Income Support Scheme (SEISS) grants. Levels of support from the Government decreased during the second quarter of the survey year, and both schemes ended on 30 September 2021.

Both income sources are taken into account in the FYE 2022 estimates, although for SEISS this is included in self-employed income based on reported profit data from previous tax years, rather than directly using amounts of SEISS grants received.

Inclusion of income from dividends

In FYE 2022, a question on the value of director’s dividends received within 12 months of interview was added to the Family Resources Survey. For the first time this income is included in our published estimates and is treated as income from either employment or self-employment.

More information on the treatment of specific income sources can be found in FRS Background Information and Methodology.

Guide to published tables

A wide range of ODS supported tables are available alongside this release, breaking down the results presented in this report for different demographic characteristics. This includes breakdowns of the statistics by region, ethnic group, family type, and economic status. All tables can be downloaded via the HBAI homepage (see Directory of Tables link on this webpage to locate tables referenced in the following pages and to generally find the desired tables). Results are available for most series back to FYE 1995.

UK-level HBAI data is also available between FYE 1995 and FYE 2022 on the Stat-Xplore online tool. You can use Stat-Xplore to recreate measures in our static tables and also create your own bespoke HBAI analysis.

The source data behind these statistics is available for download and further analysis via the UK Data Service.

Following consideration, we have maintained our decision to not release the unpublished FYE 2021 data, and it is excluded from both our tables and Stat-Xplore. The HBAI dataset underpinning the headline estimates for FYE 2021 remains available for expert users and researchers in the UK Data Service, and we recommend consulting the FYE 2021 technical report for more guidance on use and interpretation of sub-national estimates.

Question 3

Using and Interpreting HBAI Results

Accepted Answer

In the summary tables, estimates of the percentage and number in low income that are statistically significant from the previous year are shown with an asterisk. Changes marked by an asterisk are unlikely to have occurred as a result of chance.

The series started in FYE 1995 and so allows for comparisons over time, as well as between different groups of the population.

What do we mean by average?

In HBAI, the term ‘average’ is used to describe the median. This divides the population of individuals, when ranked by income, into 2 equal-sized groups, and unlike the mean is not affected by extreme values.

HBAI measures

There are a range of measures of low income, income inequality, and material deprivation to capture different aspects of changes to living standards:

Relative low income measures the number and proportion of individuals who have household incomes below a certain proportion of the average in that year - and is used to look at how changes in income for the lowest income households compare to changes in incomes near the ‘average’. In the HBAI report we concentrate on those with household incomes below 60 per cent of the average. Information on those with household incomes below 50 and 70 per cent of the average is available in the detailed tables published on the HBAI web pages.
Absolute low income measures the proportion of individuals who have household incomes a certain proportion below the average in FYE 2011, adjusted for inflation. It is used to look at how changes in income for the lowest income households compare to changes in the cost of living. In the HBAI report we concentrate on those with household incomes below 60 per cent of the average FYE 2011 income. Information on those with household incomes below 50 and 70 per cent of the average is available in the detailed tables published on the HBAI web pages.

Rounding

Due to rounding, the estimates of change in percentages or numbers of individuals in low income or material deprivation may not equal the difference between the total percentage or number of individuals for any pair of years.

The publication and tables follow the following conventions:

[low] the estimate is less than 50,000 or the percentage is less than 0.5 per cent

[u] the estimate is not available due to small sample sizes (fewer than 100)

[x] the estimate is not available. In FYE 2021 this was due to sample quality concerns across different household sizes and compositions.

Population estimates are rounded to the nearest 100,000.

Percentages are rounded to the nearest 1 per cent.

Key terminology

Income

This is measured as total weekly household income from all sources after tax (including child income), national insurance and other deductions. An adjustment called ‘equivalisation’ is made to income to make it comparable across households of different size and composition.

Median

Median household income divides the population, when ranked by equivalised household income, into 2 equal-sized groups. The median is the value at the very middle of the distribution.

Deciles and Quintiles

These are income values which divide the whole population, when ranked by household income, into equal-sized groups. This helps to compare different groups of the population.

Decile and quintile are often used as a standard shorthand term for decile/quintile group.

Decile groups are ten equal-sized groups - the lowest decile describes individuals with incomes in the bottom 10 per cent of the income distribution.

Quintile groups are 5 equal-sized groups - the lowest quintile describes individuals with incomes in the bottom 20 per cent of the income distribution.

Income distribution

The spread of incomes across the population.

Equivalisation

Equivalisation adjusts incomes for household size and composition, taking an adult couple with no children as the reference point. For example, the process of equivalisation would adjust the income of a single person upwards, so their income can be compared directly to the standard of living for a couple.

Housing costs

Housing costs include rent, water rates, mortgage interest payments, buildings insurance payments and ground rent and service charges. A full list can be found in the glossary at the end of this report.

Benefit unit and households

HBAI presents information on an individual’s household income by various household and benefit unit (family) characteristics. There are important differences between households and benefit units.

Household: The definition of a household used in the FRS is ‘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, sitting room, or dining area’. So, for example, a group of students with a shared living room would be counted as a single household even if they did not eat together, but a group of bed-sits at the same address would not be counted as a single household. A household may consist of 1 or more benefit units, which in turn will consist of 1 or more people (adults and children).

Family or Benefit Unit: A family in the FRS is defined as ‘a single adult or couple living as married and any dependent children’. A dependent child is aged 16 or under, or is 16 to 19 years old, unmarried and in full-time non-advanced education. This is consistent with the DWP term “benefit unit”, which is a standard grouping used for assessing benefit entitlement.

So, for example, a husband and wife living with their young children and an elderly parent would be 1 household but 2 families or benefit units. The husband, wife and children would constitute 1 benefit unit and the elderly parent would constitute another.

Other terms

For more information on these and other terms used throughout the report, see the glossary at the end of this report, and the infographics explaining key terms.

Issues to consider

The following issues need to be considered when using the HBAI:

Lowest incomes: Comparisons of household income and expenditure suggest that those households reporting the lowest incomes may not have the lowest living standards. The bottom 10 per cent of the income distribution should not, therefore, be interpreted as having the bottom 10 per cent of living standards. Results for the bottom 10 per cent are also particularly vulnerable to sampling errors and income measurement problems. For HBAI tables, this will have a relatively greater effect on results where incomes are compared against low thresholds of median income. For this reason, compositional and percentage tables using the 50 per cent of median thresholds have been italicised to highlight the greater uncertainty. We have also presented money value quintile medians in Table 2.3ts on 3-year averages to reflect this uncertainty (any period including FYE 2021 is based on 2 data points).
Adjustment for inflation: As advised in a Statistical Notice published in May 2016, from FYE 2015 HBAI has made a methodological change to use variants of CPI when adjusting for inflation. Prior to the FYE 2015 HBAI publication variants of RPI were used to adjust for inflation.

This change follows advice from the UK National Statistician that use of RPI should be discontinued in statistical publications.

Full details on the likely impact on this methodological change, together with estimates for trends in income and absolute low income under both the old and new methodologies, are presented in Annex 4 of the FYE 2015 HBAI Quality and Methodology Report.

Please note that following the decision to not publish breakdowns of the FYE 2021 estimates, all 3-year averages calculated and published for any period including FYE 2021 are be based on 2 data points only.

Household food security and food bank usage: The individual level statistics presented in our tables relate to the household’s food bank usage or household food security. The circumstances of the household are applied to all individuals within that household. The questions do not ask, for example, about the food bank usage of the individual or food bank usage needs of children. It should also be noted that the statistics presented exclude shared households, such as a house shared by a group of professionals.
Changes to deflators: Since the HBAI FYE 2018 publication, the Office for National Statistics (ONS) have made some very minor revisions to the bespoke Consumer Price Index (CPI) series we use to make real-terms income comparisons within and between survey years. However, because the effect of these revisions on low-income measures is negligible no revisions have been made to the deflators used in HBAI. See the following ONS update for more details.
Revision to FYE 1995 to FYE 2019 due to treatment of income from child maintenance: In HBAI FYE 2020 a minor methodological change was made to capture all income from child maintenance. This resulted in more income from child maintenance being included, in turn slightly increasing some household incomes and so tending to slightly reduce low-income rates for families with children. The full back series back to FYE 1995 was revised so that comparisons over time are on a consistent basis across the full time series.

This means that figures for FYE 1995 to FYE 2019 may be slightly different to the equivalent figures in publications issued prior to FYE 2019. Please refer to HBAI Quality & Methodology Information Report for FYE 2020 for more information.

Question 4

Survey Data

Accepted Answer

Most of the figures in the HBAI report come from the Family Resources Survey (FRS), a representative survey of over 16 thousand households in the United Kingdom in FYE 2022. The focus of the FRS is on capturing information on incomes and, as such, is the foremost source of income data and provides more detail on different income sources than other household surveys. It also captures a lot of contextual information on the household and individual circumstances, such as employment, education level and disability. This is therefore a very comprehensive data source allowing for a lot of different analysis.

Surveys gather information from a sample rather than from the whole population. The sample is designed carefully to allow for this, and to be as accurate as possible given practical limitations such as time and cost constraints. Results from sample surveys are always estimates, not precise figures. This means that they are subject to a margin of error which can affect how changes in the numbers should be interpreted, especially in the short-term. The latest estimates should be considered alongside medium and long-term patterns.

In addition to sampling errors, consideration should also be given to non-sampling errors. Non-sampling errors arise from the introduction of some systematic errors in the sample as compared to the population it is supposed to represent. As well as response bias, such errors include inappropriate definition of the population, misleading questions, data input errors or data handling problems – in fact any 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.

HBAI is based on data from a household survey and so subject to the nuances of using a survey, including:

Sampling error: Results from surveys are estimates and not precise figures. Confidence intervals help to interpret the certainty of these estimates, by showing the range of values around the estimate that the true result is likely to be within. In general terms the smaller the sample size, the larger the uncertainty. Statistical significance is an attempt to indicate whether a reported change within the population of interest is due to chance. It is important to bear in mind that confidence intervals are only a guide for the size of sampling error.
Non-response error : The FRS response rate each year is around 50 per cent. Due to the change in mode as a result of the coronavirus (COVID-19) pandemic, the FYE 2021 the response rate was only 23% and in FYE 2022 it improved slightly to 26%. In an attempt to correct for differential non-response, estimates are weighted using population totals.
Survey coverage: The FRS covers private households in the United Kingdom. Therefore, individuals in nursing or retirement homes, for example, will not be included. This means that figures relating to the most elderly individuals may not be representative of the United Kingdom population, as many of those at this age will have moved into homes where they can receive more frequent help.
Survey design: The FRS uses a clustered sample designed to produce robust estimates at former government office region (GOR) level. The FRS is therefore not suitable for analysis below this level.
Sample size: Although the FRS has a relatively large sample size for a household survey, small sample sizes for some more detailed analyses may require several years of data to be combined in order to generate reliable estimates. From April 2011, the target achieved GB sample size for the FRS was reduced by 5,000 households, resulting in an overall achieved sample size for the UK of around 20,000 households from FYE 2012 onwards. We previously published an assessment concluding that this still allows core outputs from the FRS to be produced, though with slightly wider confidence intervals or ranges.

The circumstances surrounding the coronavirus (COVID-19) pandemic resulted in a smaller achieved FRS sample size than pre-pandemic, with over 16,000 households in the FYE 2022 sample (down from around 20,000 in a usual year). This was an improvement on FYE 2021 where the achieved sample size was around 10,000 households.

The grossing regime in FYE 2022 has also been adapted to control for the differential level of response seen through the year. Due to the pre-planned introduction of FRS sample boost in England and Wales in October 2021, the FYE 2022 sample was unbalanced across the 2 halves of the survey year, with an achieved sample of 6,000 households for the period from April to September, and a 10,000 achieved sample for the period from October to March. We applied a biannual grossing control for Great Britain to balance the number of households across the 2 halves of the survey year.

In Northern Ireland, changes to the approach of contacting respondents in July 2021 meant that the achieved sample increased markedly partway through the year. This is not normally a feature of the FRS achieved sample, with response normally spread relatively equally over each twelve-month run of fieldwork. We introduced a quarterly household grossing control to balance their sample across the year.

Measurement error: The FRS is known to under-report certain income streams, especially benefit receipt. More detail can be found in Table M.6a and M.6b of the FRS report.

Further methodological details relating to the FRS are given in the FRS Background Information and Methodology.

Question 5

Reporting Uncertainty

Accepted Answer

As above, survey results are always estimates, not precise figures and so subject to a level of uncertainty. Two different random samples from 1 population, for example the UK, are unlikely to give exactly the same survey results, which are likely to differ again from the results that would be obtained if the whole population was surveyed. The level of uncertainty around a survey estimate can be calculated and is commonly referred to as sampling error.

We can calculate the level of uncertainty around a survey estimate by exploring how that estimate would change if we were to draw many survey samples for the same time period instead of just one. This allows us to define a range around the estimate (known as a “confidence interval”) and to state how likely it is that the real value that the survey is trying to measure lies within that range. Confidence intervals are typically set up so that we can be 95% sure that the true value lies within the range – in which case this range is referred to as a “95% confidence interval”. Annex 4 of this report provides further details on the Bootstrapping methodology used to estimate confidence intervals in HBAI, alongside estimates of the sampling error.

To reflect the greater level of uncertainty due to the coronavirus (COVID-19) pandemic, confidence intervals have been highlighted on charts and added to data tables. Users are encouraged to make use of them when interpreting and reporting changes in the data.

Question 6

Population

Accepted Answer

The analyses in the HBAI report are primarily based on the FRS. Households in Northern Ireland (NI) were surveyed for the first time in the FYE 2003 survey year. A detailed analysis of observed trends, together with results for NI and the UK for the first 3 years of NI data can be found in Appendix 3 of the FYE 2005 publication.

The FRS time series in this publication are presented with discontinuities in the years where there is a change from GB to UK. Prior to FYE 2015, for some tables, estimates for NI were imputed for the years FYE 1999 to FYE 2002. This allowed for changes since FYE 1999 to be measured at the UK level. For further details, see Appendix 4 of the FYE 2005 publication. This imputation is no longer carried out from the FYE 2015 publication.

The survey covers the private household sector. All the results therefore exclude people living in institutions, e.g. nursing homes, halls of residence, barracks or prisons, and homeless people living rough or in bed and breakfast accommodation. The area of Scotland north of the Caledonian Canal was included in the FRS for the first time in the FYE 2002 survey year and, from the FYE 2003 survey year, the FRS was extended to include a 100 per cent boost of the Scottish sample. This has increased the sample size available for analysis at the Scottish level.

A further adjustment is that households containing a married adult whose spouse is temporarily absent, whilst within the scope of the FRS, are excluded from HBAI. Similarly, prior to the FYE 1997 data, households containing a self-employed adult who had been full-time self-employed for less than 2 months were excluded. This exclusion is no longer made because of the improvements in the self-employment questions in the FRS.

Question 7

Grossing

Accepted Answer

The published HBAI analysis presents tabulations where the percentages refer to sample estimates grossed-up to apply to the whole population.

Grossing-up is the term usually 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, e.g. 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 HBAI mirrors that of FRS grossing with 2 differences described below.

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 households. 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 analyses in mind. The population estimates for these groups, obtained from official data sources, provide control variables. The grossing factors are then calculated by a process which ensures the FRS produces population estimates that are the same as the control variables.

As an example, the grossed number of men aged 35 to 39 would be consistent with the Office for National Statistics (ONS) estimate (see Table 1). Some adjustments are made to the original control total data sources so that definitions match those in the FRS, e.g. an adjustment is made to the demographic data to exclude people not resident in private households. It is also the case that some totals have to be adjusted to correspond to the FRS survey year.

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.

As stated above, the system used to calculate grossing factors for HBAI mirrors that of FRS grossing with 2 differences. The first difference with FRS grossing is that the sample of households is smaller for HBAI purposes because households with spouses living away from home are excluded (see Population section above). The second difference is that separate control totals are introduced for ‘very rich’ households, so that the top end of the income distribution is more accurately reflected, which is particularly important for estimates of mean income or inequality as measured by the Gini coefficient.

As with the FRS, the grossing regime for HBAI currently uses population and household estimates based on the results of the 2011 Census. Prior to FYE 2013, 2001 census-based estimates were used. In addition, a review of FRS grossing was carried out on behalf of DWP by the ONS Methodological Advisory Service. In implementing the review recommendations, a number of relatively minor methodological improvements were implemented from FYE 2013.

The main changes implemented were as follows:

improvements to the categorisation of tenure control totals
a full breakdown of the total number of households into each of the English regions (in addition breakdowns for Scotland, Wales and Northern Ireland)
a new adjustment to account for the different rates of sampling in England and Wales, Scotland, and Northern Ireland

A back-series of grossing factors calculated using the new methodology was created for each year back to FYE 2003 and are used in the HBAI publication tables from FYE 2013 onwards. Further details and analysis of the impact of these methodological changes are published in the grossing methodology review.

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, have been 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.

There are some 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 as a control variable is not applicable.
Northern Ireland housing data are based largely on small sample surveys. It is not desirable to introduce the variance of 1 survey into another by using it to compute control totals, therefore, tenure type has not been used as a control variable.

Details of the grossing regime for Northern Ireland are shown in Table 2.

Changes to the grossing regimes in FYE 2021 and FYE 2022

Due to the impact of the coronavirus (COVID-19) pandemic, there was a need to add in extra grossing controls for:

Month of interview (FYE 2021): the number of households sampled varied between months. There was no need to make changes to the back-series - adding month of interview in previous years has minimal impact as each month had approximately the same number of sample cases and there was less in-year variation in incomes.
Working-age adults with degrees (FYE 2021 and FYE 2022): there was a clear bias in the samples toward better-educated adults, specifically those with degrees. This bias was confirmed when comparing to an external data source – the Annual Population Survey (APS). It was important to address this as households with at least 1 working-age adult with a degree have statistically significantly higher incomes than households with adults that have lower levels of education. After adding in a control total for working-age adults with degree level education, there was still a bias towards younger adults with degrees so the grossing control was split into 2: working-age adults aged 16 to 45 with a degree and working-aged adults over 45 with a degree. The grossing control totals were based on education level splits reported in the FRS prior to the pandemic, projected forward using growth in the APS.
Biannual grossing control for number of households (FYE 2022): this was introduced to balance the number of households in Great Britain across the 2 halves of the survey year. This was necessary due to the introduction of the pre-planned boost to the FRS issued sample in England and Wales in October 2021. In Northern Ireland, changes to the approach of contacting respondents in July 2021 meant that the achieved sample increased markedly partway through the year. This is not normally a feature of the FRS achieved sample, with response normally spread relatively equally over each twelve-month run of fieldwork. We introduced a quarterly household grossing control to balance their sample across the year.

Table 1: HBAI grossing regime for Great Britain, FYE 2022

Control totals for Great Britain	Groupings	Original Source	Adjustments made by DWP
Private household population by region, age, and sex	Regions: North East, North West, Yorkshire and the Humber, East Midland, West Midlands, East, London, South East, South West, Wales, Scotland. Sex and Age: Males aged 0-9, 10-19 dependents, 16-24 non-dependents, 25-29, 30-34, 35-39, 40-44, 45-49, 50-59, 60-64, 65-74, 75-79, 80+; Females aged 0-9, 10-19 dependents, 16-24 non-dependents, 25-29, 30-34, 35-39, 40-44, 45-49, 50-59, 60-69, 70-74, 75-79, 80+	Mid-year population estimates, Office of National Statistics	ONS total population figures are adjusted for private household estimates using data supplied by ONS directly to DWP. 16-19-year-old dependents and non-dependents are split using data supplied by HMRC directly to DWP.
Benefit Units with children	Region: England and Wales, Scotland	Families in receipt of child benefit, HM Revenue and Customs
Lone parents	Sex: Males, Females	Lone parent estimates, Labour Force Survey	Adjusted for FRS survey year (April-March)
Households by region	Region: North East, North West, Yorkshire and the Humber, East Midlands, West Midlands, East of England, London, South East, South West, Wales, Scotland. Split from 11 into 22 controls for interview date in first or second 6 months of survey year.	Households by region, Office for National Statistics (England) / Welsh Government (Wales) / Scottish Government (Scotland)	Adjusted for FRS survey year (April-March). The 22 controls were calculated by taking the total number of households in each region, divided by 2 and rounded.
Households by tenure type	Tenure (Social Renters, Private Renters, Owner Occupied)	Dwellings by tenure type, Department for Levelling Up, Housing and Communities	Household control totals are calculated using dwellings data published by DLUHC, Welsh Government, Scottish Government. Adjusted for FRS survey year (April-March)
Households by council tax band	Council Tax Band (NVS and A, B, C and D, E to I)	Dwellings by council tax band, Valuations Office Agency. Dwellings by council tax band, Scottish Government	Household control totals are calculated using dwellings data published by VOA / Scottish Government, adjusted for FRS survey year (April-March). Estimates for properties not-valued-separately (NVS) based on FRS sample proportions.
Households containing ‘Very Rich’ people	Pensioners, Non-pensioners	HMRC Survey of Personal Incomes (SPI)
Working-age adults with degrees	Working-age adults aged 16 to 45/working-age adults aged over 45	FRS and Annual Population Survey (APS)	Growth numbers of working-age adults (16 to 45 and over 45) with a degree in the FRS between FYE 2021 and FYE 2022 was calibrated to growth in the UK populations as reported in the Annual Population Survey (APS)

Table 2: HBAI grossing regime for Northern Ireland

Control totals for Great Britain	Groupings	Original Source	Adjustments made by DWP
Private household population by age and sex	Sex and age: Males 0-19 dependants, 16-24 independents, 25-29, 30-34, 40-44, 45-49, 50-59, 60-64, 65-74, 75-79, 80+; Females 0-19 dependants, 16-24 independents, 25-29, 30-34, 40-44, 45-49, 50-59, 60-69, 70-74, 75-79, 80+	Private household estimates, Department for Social Development in Northern Ireland
Households		Household estimates, Department for Social Development in Northern Ireland
Lone Parents		Lone parent estimates, Department for Social Development in Northern Ireland
Households containing ‘Very Rich’ people	Pensioners, Non-pensioners	HMRC Survey of Personal Incomes (SPI)
Household totals for each quarter of the survey year	April 2021 – June 2021; July 2021 to September 2021; October 2021 – December 2021; January 2022 - March 2022; (each containing a quarter of all households in FYE 2022)	See Households above.	The total number of households divided by 4 and rounded.
Working-age adults with degrees	Working-age adults aged 16 to 45/working-age adults aged over 45	FRS and Annual Population Survey (APS)	Growth numbers of working-age adults (16 to 45 and over 45) with a degree in the FRS between FYE 2021 and FYE 2022 was calibrated to growth in the UK populations as reported in the Annual Population Survey (APS)

Question 8

Adjustment for individuals with very high incomes

Accepted Answer

An adjustment is made to sample cases at the top of the income distribution to correct for volatility in the highest incomes captured in the survey. This adjustment uses data kindly supplied by HM Revenue and Customs’ statisticians from HM Revenue and Customs’ Survey of Personal Incomes (SPI) to control the numbers and income levels of the ‘very rich’ while retaining the FRS data on the characteristics of their households. The methodology defines a household as ‘very rich’ if it contains a ‘very rich’ individual and it adjusts pensioners and non-pensioners separately. Thresholds have been set at the level above which, for each group, the FRS data is considered to be volatile due to small numbers of cases.

From the FYE 2010 publication, the SPI adjustment methodology was changed to be based on adjusting a fixed fraction of the population rather than on adjusting the incomes of all those individuals with incomes above a fixed cash terms level. This is intended to prevent an increasing fraction of the dataset being adjusted. The adjustment fraction was set at the same level as the fraction adjusted in FYE 2009. There was also a movement to basing all SPI adjustment decisions on gross rather than a mixture of gross and net incomes. These changes only have a very small effect on the results as presented.

The numbers of ‘very rich’ pensioners and non-pensioners in survey estimates are matched to SPI estimates by the introduction of 2 extra control totals into the grossing regime. One is for the total number of pensioners above the pensioner threshold and the other for the number of non-pensioners above the non-pensioner threshold. The grossing factors for individual cases are only marginally changed as a result of this adjustment. In addition, each ‘very rich’ individual in the FRS is assigned an income level derived from the SPI, as the latter gives a more accurate indication of the level of high incomes than the FRS. Again this adjustment is carried out separately for pensioners and non-pensioners.

The latest SPI data available when we carried out our analysis was the FYE 2020, which was projected forward to cover the FYE 2022. For FYE 2022, pensioners in Great Britain are subject to the SPI adjustment if their gross income exceeded £90,400 per year (£73,000 in Northern Ireland). Working-age adults (including the working-age partners of pensioners) are subject to the SPI adjustment if their gross income exceeded £343,700 per year (£180,600 per year in Northern Ireland).

Question 9

Equivalisation

Accepted Answer

HBAI uses net disposable weekly household income, after adjusting for the household size and composition, as an assessment for material living standards - the level of consumption of goods and services that people could attain given the net income of the household in which they live. In order to allow comparisons of the living standards of different types of households, income is adjusted to take into account variations in the size and composition of the households in a process known as equivalisation. HBAI assumes that all individuals in the household benefit equally from the combined income of the household. Thus, all members of any 1 household will appear at the same point in the income distribution.

The unit of analysis is the individual, so the populations and percentages in the tables are numbers and percentages of individuals – both adults and children.

Equivalence scales conventionally take an adult couple without children as the reference point, with an equivalence value of one. The process then increases relatively the income of single person households (since their incomes are divided by a value of less than one) and reduces relatively the incomes of households with 3 or more persons, which have an equivalence value of greater than one. The infographic below illustrates the process of equivalisation, Before Housing Costs.

Figure 1

Consider a single person, a couple with no children, and a couple with 2 children aged twelve and ten, all having unadjusted weekly household incomes of £300 (BHC). The process of equivalisation, as conducted in HBAI, gives an equivalised income of £448 to the single person, £300 to the couple with no children, but only £214 to the couple with children.

The main equivalence scales now used in HBAI are the modified OECD scales, which take the values shown in Table 3. The equivalent values used by the McClements equivalence scales are also shown for comparison alongside modified OECD values. The McClements scales were used by HBAI to adjust income up to the FYE 2005 publication.

In the modified OECD and McClements versions, 2 separate scales are used, 1 for income BHC and 1 for income AHC. The construction of household equivalence values from these scales is quite straightforward. For example, the BHC equivalence value for a household containing a couple with a fourteen-year-old and a ten-year-old child together with 1 other adult would be 1.86 from the sum of the scale values:

0.67 + 0.33 + 0.33 + 0.33 + 0.20 = 1.86

This is made up of 0.67 for the first adult, 0.33 for their spouse, the other adult and the fourteen-year-old child and 0.20 for the ten-year-old child. The total income for the household would then be divided by 1.86 in order to arrive at the measure of equivalised household income used in HBAI analysis.

Table 3: Comparison of modified OECD and McClements equivalence scales

	OECD rescaled to couple without Children=1	OECD ‘Companion’ Scale to equivalise AHC results	McClements BHC	McClements AHC
First Adult	0.67	0.58	0.61	0.55
Spouse	0.33	0.42	0.39	0.45
Other Second Adult	0.33	0.42	0.46	0.45
Third Adult	0.33	0.42	0.42	0.45
Subsequent Adults	0.33	0.42	0.36	0.40
Children aged under 14 years	0.20	0.20	0.20	0.20
Children aged 14 years and over	0.33	0.42	0.32	0.34

Notes:

All scales are presented to 2 decimal places
For the McClements scale, the weight for ‘Other second adult’ is used in place of the weight for ‘Spouse’ when 2 adults living in a household are sharing accommodation, but are not living as a couple. ‘Third adult and ‘Subsequent adult’ weights are used for the remaining adults in the household as appropriate. In contrast to the McClements scales, apart from for the first adult, the OECD scales do not differentiate for subsequent adults
The McClements scale varies by age for children, appropriate averages are shown in the table

Question 10

Income Definition

Accepted Answer

The income measure used in HBAI is weekly net (disposable) equivalised household income. This comprises total income from all sources of all household members including dependants.

Income is adjusted for household size and composition by means of equivalence scales, which reflect the extent to which households of different size and composition require a different level of income to achieve the same standard of living. This adjusted income is referred to as equivalised income.

In detail, income includes:

usual net earnings from employment
profit or loss from self-employment (losses are treated as a negative income)
income received from dividends (from FYE 2022)
state support - all benefits and tax credits
income from occupational and private pensions
investment income
maintenance payments
income from educational grants and scholarships (including, for students, student loans and parental contributions)
the cash value of certain forms of income in kind (free school meals, free school breakfast, free school milk, free school fruit and vegetables, Healthy Start vouchers and free TV licences for those aged 75 and over who receive Pension Credit.

Income is net of the following items:

income tax payments
National Insurance contributions
domestic rates/council tax
contributions to occupational pension schemes (including all additional voluntary contributions (AVCs) to occupational pension schemes, and any contributions to stakeholder and personal pensions)
all maintenance and child support payments, which are deducted from the income of the person making the payment
parental contributions to students living away from home
student loan repayments

Income After Housing Costs (AHC) is derived by deducting a measure of housing costs from the above income measure.

Housing costs

These include the following:

rent (gross of housing benefit)
water rates, community water charges and council water charges
mortgage interest payments
structural insurance premiums (for owner occupiers)
ground rent and service charges

For Northern Ireland households, water provision is funded from taxation and there are no direct water charges. Therefore, it is already taken into account in the Before Housing Costs measure.

In the FYE 1996 and subsequent datasets, a refinement was made to the calculation of mortgage interest payments to disregard additional loans which had been taken out for purposes other than house purchase.

Negative incomes

Negative incomes BHC are reset to zero, but negative AHC incomes calculated from the adjusted BHC incomes are possible. Where incomes have been adjusted to zero BHC, income AHC is derived from the adjusted BHC income.

State support

The Government pays money to individuals in order to support them financially under various circumstances. Most of these benefits are administered by DWP. The exceptions are Housing Benefit and Council Tax Reduction, which are administered by local authorities. Tax Credits are not treated as benefits, but both Tax Credits and benefits are included in the term State Support. Further information on UK state support and specific benefits for devolved administrations is available under ‘Benefits’ in the Glossary section of the FRS Background Information and Methodology.

Earnings from employment

During FYE 2021 and FYE 2022 many households experienced variation in their earnings within the survey year due to changes in employment and hours worked and/or receipt of support grants through schemes such as the Coronavirus Job Retention Scheme (CJRS) or the Self-Employment Income Support Scheme (SEISS). From May 2020, the FRS questionnaire incorporated questions to specifically ask about receipt of CJRS and from June 2020, this was extended to SEISS. The CJRS and SEISS schemes were closed in September 2021 and questions about income from the schemes were removed from the FRS questionnaire in January 2022.

For employees, receipt of CJRS (‘furlough’) and any resulting effect on levels of pay is fully reflected in the HBAI estimates. Employees who are furloughed have been classified as employed, but temporarily away from work. This will mean that, all things being equal, furloughed workers will not reduce the number of people in employment (or the employment rate). The calculation of ‘income from employment’ uses wages which are treated as income rather than state support, irrespective of any support payments from CJRS that the respondent’s employer was receiving in respect of their employment.

Earnings from self-employment

For the self-employed, it is difficult to calculate current-year income, and in line with international standards, the FRS questionnaire asks for profit data for a previous tax year and/or regular self-employment income over the past twelve months. While this is less of an issue when incomes are broadly stable, it became more of a challenge in FYE 2021 given the sharp changes in self-employed incomes over the course of the pandemic. Although from June 2020 the FRS specifically asked about receipt of SEISS grants and amounts, questions were not asked about receipt of income from continued trading which was permissible under the terms of the scheme. It is therefore not possible to adapt our methodology to estimate in-year income more accurately, taking account of both SEISS and non-SEISS sources.

This means that the HBAI estimates indirectly, rather than explicitly, include information on the amount of SEISS received. This is because we pull through information on previous trading profits, upon which the SEISS grants are based. In FYE 2021, while there was an option to ‘add in’ the SEISS amounts received for this group, there was a risk of double counting, as there was evidence that some respondents had already included income from SEISS in their responses. In FYE 2022, receipt of the first 3 SEISS grants was treated as taxable income when calculating profits in FYE 2021 tax returns. Therefore, money received from the scheme will have been automatically included in income estimates for self-employed people who reported their FYE 2021 profit data.

Sensitivity analysis completed internally showed that, as in other years, changes to self-employed incomes had only a marginal effect on the overall estimated proportions of the population in low income.

Further information is available in the FRS Background Information and Methodology.

Question 11

Interpreting low-income measures

Accepted Answer

Relative low income sets the threshold as a proportion of the average income and moves each year as average income moves. It is used to measure the number and proportion of individuals who have incomes a certain proportion below the average.

The percentage of individuals in relative low income will increase if:

the average income stays the same, or rises, and individuals with the lowest incomes see their income fall, or rise less, than average income
the average income falls and individuals with the lowest incomes see their income fall more than the average income.

The percentage of individuals in relative low income will decrease if:

the average income stays the same, or rises, and individuals with the lowest incomes see their income rise more than average income
the average income falls and individuals with the lowest incomes see their income rise, or fall less, than average income, or see no change in their income

Absolute low income sets the low income line in a given year, then adjusts it each year with inflation as measured by variants of the CPI. This measures the proportion of individuals who are below a certain standard of living in the UK (as measured by income).

The percentage of individuals in absolute low income will increase if individuals with the lowest incomes see their income fall or rise less than inflation.
The percentage of individuals in absolute low income will decrease if individuals with the lowest incomes see their incomes rise more than inflation.

Income inequality, measured by the Gini Coefficient, shows how incomes are distributed across all individuals, and provides an indicator of how high and low-income individuals compare to one another. It ranges from zero (when everybody has identical incomes) to 100 per cent (when all income goes to only 1 person). The 90:10 ratio is the average (median) income of the top 20 per cent (quintile 5) divided by the average income of the bottom 20 per cent (quintile 1). The higher the number, the greater the gap between those with the highest incomes and those with the lowest incomes.

Figure 2

Before Housing Costs (BHC) measures allow an assessment of the relative standard of living of those individuals who were actually benefiting from a better quality of housing by paying more for better accommodation, and income growth over time incorporates improvements in living standards where higher costs reflected improvements in the quality of housing.

After Housing Costs (AHC) measures allow an assessment of living standards of individuals whose housing costs are high relative to the quality of their accommodation. Income growth over time may also overstate improvements in living standards for low-income groups, as a rise in Housing Benefit to offset higher rents (for a given quality of accommodation) would be counted as an income rise.

Therefore, HBAI presents analyses of disposable income on both a BHC and AHC basis. This is principally to take into account variations in housing costs that themselves do not correspond to comparable variations in the quality of housing.

Question 12

Combined low income and child material deprivation

Accepted Answer

Material deprivation is an additional way of measuring living standards and refers to the self-reported inability of individuals or households to afford particular goods and activities that are typical in society at a given point in time, irrespective of whether they would choose to have these items, even if they could afford them.

A suite of questions designed to capture the material deprivation experienced by families with children has been included in the FRS since FYE 2005. Respondents are asked whether they have 21 goods and services, including child, adult and household items. Together, these questions form the best discriminator between those families that are deprived and those that are not. If they do not have a good or service, they are asked whether this is because they do not want them or because they cannot afford them.

The original list of items was identified by independent academic analysis. See McKay, S. and Collard, S. (2004). Developing deprivation questions for the Family Resources Survey, Department for Work and Pensions Working Paper Number 13. The questions are kept under review and for the FYE 2011 Family Resources Survey, information on 4 additional material deprivation goods and services was collected and from FYE 2012 4 questions from the original suite were removed.

The trends table 4.5tr available in the Data Tables on the HBAI homepage shows figures using the original suite of questions up to and including FYE 2011, and the new suite of questions from FYE 2011 onwards. FYE 2011 data is presented on both bases as figures from the old and new suite of questions are not comparable.

See Appendix 3 of the FYE 2011 HBAI publication for a discussion of the implications of changing the items.

A prevalence weighted approach has been used, in combination with a relative low-income or severe relative low-income threshold. Prevalence weighting is a technique of scoring deprivation in which more weight in the deprivation measure is given to families lacking those items that most families already have. This means a greater importance, when an item is lacked, is assigned to those items that are more commonly owned in the population.

For each question a score of 1 indicates where an item is lacked because it cannot be afforded. If the family has the item, the item is not needed or wanted, or the question does not apply then a score of 0 is given. This score is multiplied by the relevant prevalence weight. The scores on each item are summed and then divided by the total maximum score, this results in a continuous distribution of scores ranging from 0 to 1. The scores are multiplied by 100 to make them easier to interpret. The final scores, therefore, range from 0 to 100, with any families lacking all items which other families had access to scoring 100.

A child is considered to be in combined low income and child material deprivation if they live in a family that has a final material deprivation score of 25 or more and an equivalised household income below 50/60/70 per cent of relative/absolute median income BHC.

From the FYE 2009 edition of the HBAI publication, we moved to using the prevalence weights relative to the survey year in question, rather than fixed FYE 2005 weights, which were used in previous publications. The prevalence weights are shown in Table 4 below.

Table 4: Material deprivation scores used for children in FYE 2022

Material deprivation questions	Weights	Final Scores
For children
Outdoor space or facilities nearby to play safely	0.953	5.81
Enough bedrooms for every child of 10 or over of a different sex to have their own bedroom	0.844	5.15
Celebrations on special occasions such as birthdays, Christmas or other religious festivals	0.963	5.87
Leisure equipment such as sports equipment or a bicycle	0.872	5.32
A family holiday away from home for at least 1 week a year	0.647	3.94
A hobby or leisure activity	0.736	4.49
Friends around for tea or a snack once a fortnight	0.611	3.72
Go on school trips	0.792	4.83
Toddler group/nursery/playgroup at least once a week	0.666	4.06
Attends organised activity outside school each week	0.662	4.04
Fresh fruit and vegetables eaten by children every day	0.938	5.72
Warm winter coat for each child	0.983	6.00
For adults
Enough money to keep home in a decent state of decoration	0.825	5.03
A holiday away from home for at least 1 week a year, whilst not staying with relatives at their home	0.584	3.56
Household contents insurance	0.674	4.11
Regular savings of £10 a month or more for rainy days or retirement	0.688	4.20
Replace any worn out furniture	0.658	4.01
Replace or repair major electrical goods such as a refrigerator or a washing machine, when broken	0.707	4.31
A small amount of money to spend each week on yourself, not on your family	0.723	4.41
In winter, able to keep accommodation warm enough	0.945	5.76
Keep up with bills and regular debt payments	0.928	5.66
Sum of all weights	16.401	100

Question 13

Combined low income and working-age adult material deprivation

Accepted Answer

From FYE 2022, the HBAI publication includes statistics on combined low income and working-age adult material deprivation, with a back series of the data available to FYE 2011. The measures follow a similar methodology as that for children, with the 9 questions for adults detailed in table 4 forming the basis of the material deprivation measure for all working-age adults. Working-age adults without children are also asked these questions.

For each question a score of 1 indicates where an item is lacked because it cannot be afforded. If the working-age adult has the item, the item is not needed or wanted, or the question does not apply then a score of 0 is given. This score is multiplied by the relevant prevalence weight. The scores on each item are summed and then divided by the total maximum score, this results in a continuous distribution of scores ranging from 0 to 1. The scores are multiplied by 100 to make them easier to interpret. The final scores, therefore, range from 0 to 100, with any working-age adults lacking all items which other working-age adults had access to scoring 100.

However, every year the FRS does not gather data on a small proportion of working-age adults (this proportion varies year-on-year but is typically between 5-10%). Missing data appears to be non-random and predominantly is missing from those living in multiple benefit unit households or working-age adults in a couple where the other member of that couple is of pension age.

Missing values are therefore imputed using a method called hot-decking. Hot-decking 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. The specific variables used for the hot-decking procedure are:

benefit unit income
economic status
number of dependent children
savings held by the benefit unit
age that the head of benefit unit left education
ethnic group of the head of the benefit unit
family type (couple / single)
disability in the benefit unit
government region

This method ensures that imputed solutions are realistic and allows a wide range of outcomes which maintain variability in the data. This approach is also used for missing data in the child material deprivation measure.

More information on the methodology for the working-age adults measures accompanied the initial release of the data as experimental statistics in March 2022.

Below are the material deprivation prevalence weights for working-age adults in FYE 2022. Please note these are different to the weights given for the same questions in table 4, as these relate to the children measure.

Table 5: Material deprivation scores used for adults in FYE 2022

Material deprivation questions	Weights	Final Scores
For working-age adults
Enough money to keep home in a decent state of decoration	0.798	11.62
A holiday away from home for at least 1 week a year, whilst not staying with relatives at their home	0.638	9.29
Household contents insurance	0.672	9.78
Regular savings of £10 a month or more for rainy days or retirement	0.732	10.66
Replace any worn out furniture	0.651	9.47
Replace or repair major electrical goods such as a refrigerator or a washing machine, when broken	0.696	10.13
A small amount of money to spend each week on yourself, not on your family	0.824	12.00
In winter, able to keep accommodation warm enough	0.915	13.32
Keep up with bills and regular debt payments	0.943	13.73
Sum of all weights	6.868	100

2022 review of the material deprivation questions in the FRS

The DWP, in partnership with independent researchers at the London School of Economics and Political Science (LSE), has recently conducted a review of the HBAI material deprivation measures and the questions in the Family Resources Survey (FRS). This review aimed to ensure that the material deprivation measures continued to make high standards of:

public value
quality
trustworthiness

and explored:

which material deprivation items for families with children, families with working–age adults and families with pensioners should be included in the FRS
what are the advantages and disadvantages of different approaches for determining who is materially deprived
what are the advantages and disadvantages of developing a “core” set of questions for the whole population alongside measures aimed at specific family types
whether the advantages of changing the material deprivation items and methodology/methodologies outweigh the disadvantages, for example a break in the time series

Following the pilot of a suite of potential new questions the Steering Group for the project agreed to new questions being introduced to the FRS in 2023 to 2024. To support the presentation of analysis in the transition from one suite of measures to a new one, it has been agreed that for 2023 to 2024, 75% of the FRS sample will be asked the new questions and the remaining 25% the old questions.

The work of the review continues, and we will provide an update on publication plans for material deprivation measures in HBAI as they develop. The first results based on the new questions are expected to be published in HBAI in March 2025.

Question 14

Material deprivation for pensioners

Accepted Answer

A suite of questions designed to capture the material deprivation experienced by pensioner families has been included in the Family Resources Survey since May 2008. Respondents are asked whether they have access to 15 goods and services. The list of items was identified by independent academic analysis. See Legard, R., Gray, M. and Blake, M. (2008), Cognitive testing: older people and the FRS material deprivation questions, Department for Work and Pensions Working Paper Number 55 and McKay, S. (2008), Measuring material deprivation among older people: Methodological study to revise the Family Resources Survey questions, Department for Work and Pensions Working Paper Number 54. Together, these questions form the best discriminator between those pensioner families that are deprived and those that are not. Note that this measure is only available for pensioners aged 65 or over.

Where they do not have a good or service, they are asked whether this is because:

they do not have the money for this
it is not a priority on their current income
their health / disability prevents them
it is too much trouble or tiring
they have no one to do this with or help them
it is not something they want, it is not relevant to them
other

A pensioner is counted as being deprived of an item where they lack it for one of the following reasons:

they do not have the money for this
it is not a priority on their current income
their health / disability prevents them
it is too much trouble or tiring
they have no one to do this with or help them
other

The exception to this is for the unexpected expense question, where the follow up question was asked to explore how those who responded ‘yes’ would pay. Options were:

use own income but cut back on essentials
use own income but not need to cut back on essentials
use savings
use a form of credit
get money from friends or family
other

Pensioners are counted as materially deprived for this item if and only if they responded ‘no’ to the initial question.

The same prevalence weighted approach has been used to that for children, in determining a deprivation score. Prevalence weighting is a technique of scoring deprivation in which more weight in the deprivation measure is given to families lacking those items that most pensioner families already have. This means a greater importance, when an item is lacked, is assigned to those items that are more commonly owned in the pensioner population.

For each question a score of 1 indicates where an item is lacked because of the reasons outlined on the previous page. If the pensioner family has the item, the item is not needed or wanted, or the question does not apply then a score of 0 is given. This score is then multiplied by the relevant prevalence weight. The scores on each item are summed and divided by the total maximum score, this results in a continuous distribution of scores ranging from 0 to 1. The scores are multiplied by 100 to make them easier to interpret. The final scores, therefore, range from 0 to 100, with any families lacking all items which other families had access to scoring 100. The prevalence weights are shown in Table 6 below.

Table 6: Material deprivation scores used for pensioners in FYE 2022

Material deprivation questions	Weights	Final Scores
For pensioners aged 65 and over
At least 1 filling meal a day	0.989	7.20
Go out socially at least once a month	0.742	5.39
See friends or family at least once a month	0.917	6.67
Take a holiday away from home	0.614	4.46
Able to replace cooker if it broke down	0.929	6.76
Home kept in a good state of repair	0.977	7.11
Heating, electrics, plumbing and drains working	0.989	7.20
Have a damp-free home	0.945	6.87
Home kept adequately warm	0.969	7.05
Able to pay regular bills	0.984	7.16
Have a telephone to use, whenever needed	0.948	6.89
Have access to a car or taxi, whenever needed	0.928	6.75
Have hair done or cut regularly	0.900	6.55
Have a warm waterproof coat	0.988	7.19
Able to pay an unexpected expense of £200	0.929	6.75
Sum of all weights	13.749	100

A pensioner is considered to be in material deprivation if they live in a family that has a final score of 20 or more. For children and working-age adults, material deprivation is presented as an indicator in combination with a low-income threshold. However, for pensioners, the concept of material deprivation is broad and very different from low income, therefore it is appropriate to present it as a separate measure.

A technical note giving a full explanation of the pensioner material deprivation measure is available.

Question 15

Material deprivation weighting methodology

Accepted Answer

We currently recalculate the prevalence weights each year based on the question responses from that year. The maximum possible material deprivation score for each year is then rescaled to 100 for ease of interpretation, and children in a family with a score of at least 25, working-age adults with a score of at least 25 or pensioners with a score of 20 or more, are classed as being materially deprived. If over time more families can afford a certain item, then a family lacking such a good will see an increasing overall deprivation score and will be considered as becoming more materially deprived.

A concern which has been raised with the current method is that if there is a general increase in access to items, this should imply that a family lacking a particular number of items is now suffering from greater relative deprivation than before. However, because of the rescaling of scores to 100, each item lacked still counts the same amount towards the overall material deprivation score and a family is still required to lack the same number of items to reach a score of 25 and be declared materially deprived.

The HBAI Technical Advisory Group considered this issue. The Group agreed that this is a complex issue and recommended that any changes made should be implemented following a considered and evidence-based exploration of options. As a result, the Group agreed that the recommendation should be to continue to use the current methodology for material deprivation until such time as a thorough exploration of this issue can be conducted.

Question 16

Impact of the coronavirus (COVID-19) pandemic on the material deprivation measures

Accepted Answer

In FYE 2021, several of the questions asked as part of the measure were affected by government restrictions introduced in response to the coronavirus (COVID-19) pandemic. This meant that it was not possible for those sampled to access several social opportunities or services during periods of lockdown, regardless of deprivation or financial constraint. These included opportunities such as school trips, socialising with friends or family, attending organised activities or pursuing hobbies, going on holiday, and getting a haircut. Some of those in the sample may have responded to these questions with their ordinary circumstances in mind. Others may have responded according to their actual (lockdown affected) circumstances.

For FYE 2022, although the impact on survey responses was less marked than the previous year, restrictions remained in place throughout the first quarter of the survey year and the effect the coronavirus (COVID-19) pandemic had on social interactions continued to unwind during the remainder of the survey year as restrictions were removed and society began returning to normal. Therefore, for both FYE 2021 and FYE 2022, all estimates of material deprivation, including those combined with low-income measures, are not strictly comparable with the pre-pandemic period. Changes in recorded material deprivation for FYE 2022 may not fully reflect the real change in household circumstances compared to FYE 2021 or the pre-pandemic period.

Question 17

Household food security

Accepted Answer

In FYE 2020 measures of combined low income and household food security was added to the publication. To measure household food security, 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 of 30 days leading up to interview. The questions are comparable to those used by other public bodies in the UK, and also internationally. From the questions, a ten-point household score is generated, and the household is given a food security status:

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 1 or more household members were disrupted and food intake reduced because the household lacked money and other resources for food.

Households with high or marginal food security are “food secure”. Food secure households are considered to have sufficient, varied food to facilitate an active and healthy lifestyle. Households with low or very low food security are “food insecure”. Food insecure households have a risk of, or lack of access to, sufficient, varied food.

Question 18

Food bank usage

Accepted Answer

A new series of questions was added to the FRS for FYE 2022 on the topic of food bank usage. Food bank usage questions are asked of the person in the household who knows the most about food purchasing and preparation. This means that the questions do not directly ask about the food bank usage needs of children, and it cannot be determined which individual or individuals the food parcels are for. Food bank usage in the FRS refers only to visits to a food bank when emergency food supplies (food parcels) were obtained. This excludes visits to the food bank made only for other support (e.g. financial advice or mental health support).

The FRS asks food bank usage questions relating to 2 time periods: 12 months prior to interview, and in the 30 days prior to interview. This means that caution may be needed when making direct comparisons between the FRS results and other studies on this subject.

For details on household food security measurement and food bank questions please see the FRS Background Information and Methodology.

Question 19

Ethnicity categories

Accepted Answer

The ethnicity questions used in the FRS adopt the UK harmonised standards for use in major government social surveys, that is, they adopt the standard way of collecting information on the ways in which people describe their ethnic identity. The latest harmonised standards were published in August 2011 and cover the ethnic group question in England, Wales, Scotland and Northern Ireland. They also cover harmonised data presentation for ethnic group outputs. The standards were updated in February 2013 detailing how Gypsy, Traveller and Irish Traveller should be recorded in the outputs, due to differences across the UK.

The FRS adopted these latest harmonised standards for England, Wales and Northern Ireland for the FYE 2012 survey questionnaire, and the standards for Scotland were adopted for the FYE 2013 survey questionnaire. The FYE 2012 publication therefore adopted the latest harmonised output standards for ethnic groups for the UK. The most significant changes to previous publications are that the ‘Chinese’ category has moved from the ‘Chinese or other ethnic group’ section to the ‘Asian/Asian British’ section, and ‘Irish Traveller’ is included under ‘Other ethnic group’ for respondents in Northern Ireland and ‘Gypsy or Irish Traveller’ is included under the ‘White’ section for respondents in Great Britain, therefore UK figures have been allocated accordingly.

Question 20

Disability definition

Accepted Answer

The means of identifying people with a disability has changed over time. Data are not available for FYE 1995. Up until FYE 2002 all those who reported having a long-standing limiting illness were identified as having a disability. From FYE 2003, statistics are based on responses to questions about difficulties across a number of areas of life. Figures for FYE 2003 and FYE 2004 are based on those reporting substantial difficulties across 8 areas of life and figures from FYE 2005 to FYE 2012 are based on those reporting substantial difficulties across 9 areas of life. From FYE 2013 the FRS disability questions were revised to reflect new harmonised standards.

Disabled people are identified as those who report any physical or mental health condition(s) or illness(es) that last or are expected to last 12 months or more, and which limit their ability to carry out day-to-day activities a little, or a lot.

FRS questions FYE 2005 to FYE 2012

The FRS/HBAI definition for an adult with a disability is if they answered yes to the ‘Health’ question and yes to any of the difficulties listed in ‘DisDif’.

Health:

Do you have any long-standing illness, disability or infirmity? By ‘long-standing’ I mean anything that has troubled you over a period of at least 12 months or that is likely to affect you over a period of at least 12 months.

If ‘yes’ to Health.

Health Problem Limit Activities (HProb):

Does this physical or mental illness or disability (Do any of these physical or mental illnesses or disabilities) limit your activities in any way?

If ‘yes’ to Health.

Health Problems cause Difficulties (DisDif):

SHOW CARD E1

Does this/Do these health problem(s) or disability(ies) mean that you have substantial difficulties with any of these areas of your life? Please read out the numbers from the card next to the ones which apply to you.

PROBE: Which others?

Mobility (moving about)
Lifting, carrying or moving objects
Manual dexterity (using your hands to carry out everyday tasks)
Continence (bladder and bowel control)
Communication (speech, hearing or eyesight)
Memory or ability to concentrate, learn or understand
Recognising when you are in physical danger
Your physical co-ordination (e.g.: balance)
Other health problem or disability
None of these

FRS questions FYE 2013 onwards

The FRS/HBAI definition for an adult with a disability is if they answered yes to the ‘Health1’ and yes, a lot or yes, a little to the ‘Condition’ question.

Longstanding illness or disability (Health1):

Do you have any physical or mental health conditions or illnesses lasting or expected to last for 12 months or more?

Yes
No
Don’t know (spontaneous)
Refusal (spontaneous)

If ‘yes’ to Health1

Health Problems cause Difficulties (Dis1)

SHOW CARD E1

Do any of these conditions or illnesses affect you in any of the following areas?

Vision (for example blindness or partial sight)
Hearing (for example deafness or partial hearing)
Mobility (for example walking short distances or climbing stairs)
Dexterity (for example lifting and carrying objects, using a keyboard)
Learning or understanding or concentrating
Memory
Mental Health
Stamina or breathing or fatigue
Socially or behaviourally (for example associated with autism, attention deficit disorder or Asperger’s syndrome)
Other
Refusal (spontaneous)

If Health1=Yes

Limiting longstanding illness (Condition)

Does your condition or illness/do any of your conditions or illnesses reduce your ability to carry-out day-to-day activities?

Yes, a lot
Yes, a little
Not at all

INTERVIEWER: Day to day activities include washing and dressing, household cleaning, cooking, shopping for essentials, using public or private transport, remembering to pay bills, lifting objects from the ground or lifting objects from a work surface in the kitchen.

Comparisons over time

Compared to FYE 2012 the number of individuals in disabled families went up by 0.2m in FYE 2013 (similar to those in non-disabled families).

However, while the number of pensioners in non-disabled families increased by 0.4m, the number in disabled families decreased by 0.3m.

The reverse was true for the number of children in disabled families, which increased by 0.3m, while those in non-disabled families fell by 0.2m.

These figures could be affected by the change in the disability questions. Individuals might have different interpretations of particular health conditions or question wording meaning that changes to the disability question may have had a different effect on certain groups. Therefore, comparisons over time should be made with caution, as they may be affected by the change in the definition of disability.

Question 21

Comparison with EU low-income statistics

Accepted Answer

The UK’s cross-Europe-comparable low-income statistics have previously been derived from the ONS Survey of Living Conditions, a different survey source than the HBAI, meaning that there will be some differences due to the different data source. In addition to this, the figures will differ for several further reasons:

Time period: The figures are presented on different timescales. The HBAI figures are presented for the financial year, while the EU comparable figures are presented for the calendar year.
Population groups: The European low-income statistics are presented in different age groups than the HBAI figures:
Children: the EU figures relate to those under 18 – HBAI figures are based on individuals aged under 16, in addition 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, are living with parents, and are in full-time non-advanced education or in unwaged government training
Pensioners: EU figures relate to the 65+ population. The data in this report were collected throughout FYE 2022, during which the State Pension age for both men and women was 66 years.
Preferred measures: The European low-income estimates are usually presented on a Before Housing Costs basis, while this is consistent with the most commonly used measure for working-age adults and children, we choose to look at pensioners’ incomes after deducting housing costs as this better reflects pensioner living standards compared to others and over time.
Income derivation: The definition of income in the European figures differs from the official UK figures:
Pension contributions are not deducted from income in the European comparable methodology.
The European definition of income includes the value of non-cash employee income from company cars as employee income, which will raise the average income of people in work.
High income adjustment: For the HBAI figures an adjustment is made to sample cases at the top of the income distribution to correct for volatility in the highest incomes captured in the survey. This adjustment is not applied to the European figures.
In year deflation: The HBAI estimates make an in year adjustment to individuals’ incomes to ensure that respondents income collected across the financial year are comparable. This adjustment is not applied to the European figures.
Sample cases: The HBAI figures exclude cases containing a married adult whose spouse is temporarily absent whereas these are included in the European figures, however this has a minimal effect on the figures.
Income tax and national insurance: The European income tax and national insurance figures are calculated using a model of taxation, whilst the HBAI estimates are mostly calculated on the amount of tax and national insurance reported as being paid.

After the UK’s exit from the EU in 2020, some EU-SILC outputs were still delivered by ONS to Eurostat during the transition period in 2020, but all planned deliveries from 2021 onwards ceased. Data for the UK up to and including the 2018 calendar year remain available on Eurostat’s EU-SILC database.

Question 22

Glossary

Accepted Answer

Adult

All those individuals who are aged 16 and over, unless defined as a dependent child (see Child) all adults in the household are interviewed as part of the Family Resources Survey (FRS).

Benefit units or Family

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

Bills in arrears

The number of bills in arrears is presented at a benefit unit level. Bills considered are: electricity, gas, other fuel, Council Tax, insurance, telephone, television / video rental, hire purchase, water rates, rent, mortgage payments and other loans. From FYE 2013 onwards, the analysis of income by whether people are behind with household bills has been extended to include rent, mortgage payments and other loans, so the figures are not comparable with those presented in previous reports.

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
living with parents/a responsible adult
in full-time non-advanced education or in unwaged government training

Confidence interval

A measure of sampling error. A confidence interval is a range around an estimate which states how likely it is that the real value that the survey is trying to measure lies within that range. A wider confidence interval indicates a greater uncertainty around the estimate. Generally, a smaller sample size will lead to estimates that have a wider confidence interval than estimates from larger sample sizes. This is because a smaller sample is less likely than a larger sample to reflect the characteristics of the total population and therefore there will be more uncertainty around the estimate derived from the sample. Note that a confidence interval ignores any systematic errors which may be present in the survey and analysis processes.

Contemporary median income

The average income for the period covered by the survey. Household incomes are adjusted from the date of interview to an average of survey-year prices.

Deciles and Quintiles

These are income values which divide the whole population, when ranked by household income, into equal-sized groups. This helps to compare different groups of the population.

Decile and quintile are often used as a standard shorthand term for decile/quintile group.

Deciles groups are ten equal-sized groups - the lowest decile describes individuals with incomes in the bottom 10 per cent of the income distribution.

Quintiles groups are 5 equal-sized groups - the lowest quintile describes individuals with incomes in the bottom 20 per cent of the income distribution.

Disability

From FYE 2013 onwards, the definition of disability used 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’ is meant by more than minor or trivial, and long-term is meant by 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 and 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 and are no longer limited in their daily lives are still covered by the Act.

Economic status of the family

The economic status of the family classification is in line with the International Labour Organisation economic status classification. This means that no economic status data is available for FYE 1995 and FYE 1996 as the relevant information was not collected in the Family Resources Survey for these years. This also means the economic status of the family and economic status of the household classifications are aligned.

The ‘Workless, other inactive’ group consists of families in which all adults are economically inactive (i.e. where no adult is in work or unemployed). This includes working-age adults in receipt of sickness and disability benefits, who may have living standards lower than those implied by the results presented because of additional costs associated with their disability (for which no adjustment has been made here).

Families are allocated to the first applicable category:

One or more full-time self-employed - Benefit units where at least 1 adult usually works as self-employed in their main job where the respondent regards themselves as working full-time. Those respondents not working in the last 7 days but doing unpaid work in their own business are considered as full-time self-employed.
Single or couple, all in full-time work - Benefit units where all adults regard themselves as working full-time. Those respondents not working in the last 7 days doing unpaid work in a business that a relative owns are considered as in full-time work, as are those in training.
Couple, one in full-time work, one in part-time work - Benefit units headed by a couple where 1 partner considers themselves to be working full-time and the other partner considers themselves to be working part-time. Those respondents not working in the last 7 days but doing an odd job are considered as working part-time.
Couple, one in full-time work, one not working - Benefit units headed by a couple, where one partner considers themselves to be working full-time and the other partner does not work.
No-one in full-time work, one or more in part-time work - Benefit units where at least one adult works but considers themselves to be working part-time.
Workless, one or more aged 60 or over - Benefit units where at least 1 adult is aged 60 or over.
Workless, one or more unemployed - Benefit units where at least 1 adult is unemployed.
Workless, other inactive - Benefit units not classified above (this group includes the long-term sick, disabled people and non-working single parents).

Economic status groups for children

Estimates for dependent children use an amended economic status classification closely related to the definitions used above. Children are grouped according to family type and the economic status of their parent(s) as defined in the previous section. As with the main economic status groups, individuals are allocated to the first category that applies in the following order:

Lone parent - In full-time work (includes full-time self-employed)
Lone parent - In part-time work
Lone parent - Not working (unemployed or inactive)
Couple with children - One or more full-time self-employed
Couple with children - Both in full-time work
Couple with children - One in full-time work, one in part-time work
Couple with children - One in full-time work, one not working
Couple with children - Neither in full-time work, one or more in part-time work
Couple with children - Both workless (unemployed or inactive)

Economic status of household

For the analysis of working and workless households, households are classified according to whether they contain a working-age adult or pensioner who works, but the status of non-working pensioners is not considered, except in the case of those households where children live only with pensioners, in which case the status of all adults is included.

Individuals are assigned to one of 3 categories:

All adults in work - A household where all working-age adults are in employment or are self-employed, or if there are no working-age adults in the household, at least 1 working pensioner.
At least one, but not all adults in work - A household where at least 1 working-age adult is in employment or is self-employed, or where a pensioner is in work if none of the working-age adults in the household are in work.
Workless household - A household where no adult members are in employment or are self-employed. Within households, pensioners are excluded from the classifications if they are not working and are included if they are working. So for example, a household with a pensioner in work, but a working-age person not in work, would be in the ‘At least 1 adult in work, but not all’ category. A household with all working-age adults in work and a pensioner not in work would be categorised as ‘All adults in work’.

Educational attainment

This looks at the highest level of educational attainment for each working-age adult. Information for students should be treated with some caution because they are often dependent on irregular flows of income. Only student loans are counted as income in HBAI, any other loans taken out are not. The figures are also not necessarily representative of all students because HBAI only covers private households and this excludes halls of residence.

Comparisons between the numbers with no qualifications in the FRS, LFS and the Census indicate that the FRS figures have historically overstated the numbers of working-age adults with no qualifications. As a result of the FRS mode change in FYE 2021 and FYE 2022, the raw FRS sample contained a much higher proportion of working age adults than in the years prior to the COVID-19 pandemic, and much lower numbers with no qualifications. We therefore introduced additional grossing controls in FYE 2021 and FYE 2022 to weight the sample by level of educational attainment. This boosted numbers with education levels below degree level in younger age groups. We did this using historical proportions from the FRS and calibrated growth over the 2 years to growth in levels recorded in the Annual Population Survey (APS), derived from the LFS. This maintained the previous relationship between the 2 sources while ensuring that grossed FRS proportions were more in line with expectations.

Equivalisation

Income measures used in HBAI take into account variations in the size and composition of the households in which people live. This process is called equivalisation.

Equivalisation reflects the fact that a family of several people needs a higher income than a single individual in order for them to enjoy a comparable standard of living.

Equivalence scales conventionally take a couple with no children as the reference point. Consider a single person, a couple with no children, and a couple with 2 children aged twelve and ten, all having unadjusted weekly household incomes of £300 (BHC). The process of equivalisation, as conducted in HBAI, gives an equivalised income of £448 to the single person, £300 to the couple with no children, but only £214 to the couple with children.

Ethnicity

Ethnicity in HBAI reflect the harmonised standards included from the FYE 2012 publication onwards. The harmonised standards for Scotland were adopted in the FYE 2013 FRS questionnaire, however, there has been no change to the HBAI outputs as the harmonised output standards were previously adopted.

Individuals have been classified according to the ethnic group of the household reference person (see Household reference person) which means that information about households of multiple ethnicities is lost.

Smaller ethnic minority groups exhibit year-on-year variation which limits comparisons over time. For this reason, analysis by ethnicity is usually presented as 3-year averages. Please note that following the decision to not publish breakdowns of the FYE 2021 estimates, all 3-year averages calculated and published for any period including FYE 2021 are be based on 2 data points only.

Families/family unit

The terms ‘families’ and ‘family units’ are used interchangeably with benefit units. See Benefit unit definition.

Family type

For some analyses, individuals are classified into family type or economic status groups. Individuals are classified according to the status of the benefit unit in which they live. All individuals in a benefit unit (adults and children) will therefore be given the same classification. The classifications are defined below:

Pensioner couple - a couple where 1 or more of the adults are State Pension age or over. However, in the HBAI tables relating specifically to pensioners results for individuals who are in pensioner couples do not count anyone who is not a pensioner.
Single male pensioner - single male adult of State Pension age or over.
Single female pensioner - single female adult of State Pension age or over.
Couple with children - a non-pensioner couple with dependent children.
Single with children - a non-pensioner single adult with dependent children.
Couple without children - a non-pensioner couple with no dependent children.
Single male without children - a non-pensioner single adult male with no dependent children.
Single female without children - a non-pensioner single adult female with no dependent children.

Full-time work

The respondent regards themselves as working full-time, either as an employee or self-employed.

Gender

In any analysis of gender, it must be remembered that HBAI attempts to measure the living standards of an individual as determined by household income. This assumes that both partners in a couple benefit equally from the household’s income and will therefore appear at the same position in the income distribution. Any difference in figures can only be driven by gender differences for single adults, which will themselves be diluted by the figures for couples. The lower level gender disaggregation in the family type classification is therefore likely to be more informative.

Research has suggested that, particularly in low-income households, the above assumption with regard to income sharing is not always valid as men sometimes benefit at the expense of women from shared household income. This means that it is possible that HBAI results broken down by gender could understate differences between the 2 groups. See, for instance, Goode, J., Callender, C. and Lister, R. (1998) Purse or Wallet? Gender Inequalities and the Distribution of Income in Families on Benefits. JRF/Policy Studies Institute.

Gini coefficient

A widely-used, international standard summary measure of inequality. It can take values from zero to 100, where a value of zero would indicate total equality, with each household having an equal share of income, while higher values indicate greater inequality.

Head of benefit unit

The head of the first benefit unit will be the same as the household reference person. For second and subsequent benefit units, the head will be the first adult to be interviewed.

High Income

Results for the top 10 per cent are particularly susceptible to sampling errors and income measurement problems.

Household

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 1 or more benefit units. Where a total value for a household is presented, such as total household income, this includes both income from adults and income from children.

Household food bank usage

Household food bank usage in the FRS refers only to visits to a food bank when emergency food supplies (food parcels) were obtained. This excludes visits to the food bank made only for other support (e.g. financial advice or mental health support).

The FRS asks food bank usage questions relating to 2 time periods:

usage within the 12 months prior to interview
usage within the 30 days prior to interview

Only households that report using a food bank in the last 12 month are asked about 30-day usage.

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 3 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 3 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 4 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 1 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 (used from FYE 2002 onwards)

The household reference person (HRP) is usually the highest Income householder. Note:

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 2 or more householders, the HRP is the householder with the highest personal income, taking all sources of income into account.
If there are 2 or more householders who have the same income, the HRP is the elder.

The Head of benefit unit will not necessarily be the HRP.

Housing costs

Housing costs are made up of:

rent (gross of housing benefit)
water rates
community water charges and council water charges
mortgage interest payments (net of tax relief)
structural insurance premiums (for owner occupiers)
ground rent and service charges

Income

The income measure used in HBAI is weekly net (disposable) equivalised household income. This comprises total income from all sources of all household members including dependants. For BHC, housing costs are not deducted from income, while for AHC they are.

Households receive income from a variety of sources. The main ones are earnings, self-employment, state support (i.e. benefits and tax credits), interest on investments and occupational pensions.

In detail, income includes:

usual net earnings from employment
profit or loss from self-employment (losses are treated as a negative income)
income received from dividends (from FYE 2022)
state support - all benefits and tax credits
income from occupational and private pensions
investment income
maintenance payments
income from educational grants and scholarships (including, for students, student loans and parental contributions)
the cash value of certain forms of income in kind (free school meals, free school breakfast, free school milk, free school fruit and vegetables, Healthy Start vouchers and free TV licence for people 75 and over who receive Pension Credit)

Income is net of the following items:

income tax payments
National Insurance contributions
domestic rates / council tax
contributions to occupational pension schemes (including all additional voluntary contributions (AVCs) to occupational pension schemes, and any contributions to stakeholder and personal pensions)
all maintenance and child support payments, which are deducted from the income of the person making the payment
parental contributions to students living away from home
student loan repayments

Income distribution

The spread of incomes across the population.

Income growth in real terms

For some years, income growth in the HBAI-based series appears slightly lower than the National Accounts estimates. The implication of this is that absolute real income growth could be understated in the HBAI series. Comparisons over a longer time period are believed to be more robust.

Income inequality

The extent of disparity between high income and low-income households, commonly measured using either the Gini coefficient or 90:10 ratio. The Gini coefficient is a widely-used, international standard summary measure of inequality. It can take values from zero to 100, where a value of zero would indicate total equality, with each household having an equal share of income, while higher values indicate greater inequality. The 90:10 ratio is the average (median) income of the top 20 per cent (quintile 5), divided by the average income of the bottom 20 per cent (quintile 1). The higher the number, the greater the gap between those with the highest incomes and those with the lowest incomes.

Low income

‘Low income’ is defined using thresholds derived from percentages of median income for the whole population. Households reporting the lowest incomes may not have the lowest living standards. The bottom 10 per cent of the income distribution should not, therefore, be interpreted as having the bottom 10 per cent of living standards. Results for the bottom 10 per cent are also particularly vulnerable to sampling errors and income measurement problems.

Individuals are said to be in relative low income if they live in a household with an equivalised income below a percentage of contemporary median income BHC or AHC. Relative low-income statistics fall if income growth at the lower end of the income distribution is greater than overall income growth.
Individuals are said to be in absolute low income if they live in a household with an equivalised income below a threshold of median income (for example 60 per cent of median income) in a specific year adjusted for inflation BHC or AHC. The FYE 2011 median is used in this report, in order to measure absolute low income as referenced in the Welfare Reform and Work Act 2016, and to keep the absolute measure more in line with contemporary living standards. Absolute low-income statistics fall if low-income households are seeing their incomes rise faster than inflation.

Material deprivation for children

A suite of questions designed to capture the material deprivation experienced by families with children has been included in the FRS since FYE 2005. Respondents are asked whether they have 21 goods and services, including child, adult and household items. If they do not have them, they are asked whether this is because they do not want them or because they cannot afford them. These questions are used as an additional way of measuring living standards for children and their families. A prevalence weighted approach has been used in combination with relative or absolute low-income thresholds.

Combined low income and child material deprivation

A child is considered to be in combined low income and child material deprivation if they live in a family that has a final child material deprivation score of 25 or more and an equivalised household income below 50/60/70 per cent of relative/absolute median income BHC.

Material deprivation for working-age adults

Measures of combined low income and working-age adult material deprivation are available since FYE 2011 and were first published in HBAI in FYE 2022. Working-age adults are asked whether they have access to 9 goods and services. If they do not have them, they are asked whether this is because they do not want them or because they cannot afford them. A prevalence weighted approach has been used in combination with relative or absolute low-income thresholds.

Combined low income and working-age adult material deprivation

A working-age adult is in combined low income and working-age adult material deprivation if they have a final working-age adult material deprivation score of 25 or more and a household income below the relevant threshold of median income, before housing costs.

Material deprivation for pensioners

A suite of questions designed to capture the material deprivation experienced by pensioners aged 65 or over has been included in the Family Resources Survey since May 2008. These questions are used as an additional way of measuring living standards for pensioners. Respondents are asked whether they have access to 15 goods, services and experiences. Where a pensioner lacks one of the material deprivation items for 1 of the following reasons they are counted as being deprived for that item:

they do not have the money for this
it is not a priority on their current income
their health / disability prevents them
it is too much trouble or tiring
they have no one to do this with or help them
other

The exception to this is for the unexpected expense question, where pensioners are counted as materially deprived for this item if and only if they responded ‘no’ to the initial question.

A prevalence weighted approach has been used.

Mean

Mean equivalised household income of individuals is found by adding up equivalised household incomes for each individual in a population and dividing the result by the number of people.

Median

Median household income divides the population, when ranked by equivalised household income, into 2 equal-sized groups. Contemporary median income refers to the median income in the survey year being considered.

Part-time work

The respondent regards themselves as working part-time, either as an employee or self-employed.

Pensioner

Pensioners are defined as all those adults at or above State Pension age (SPa).

For women born on or before 5th April 1950, SPa is 60. Since 6 April 2010, the State Pension age for women increased until it matched men’s SPa of 65 in November 2018. The State Pension age for men and women then increased together, reaching 66 by October 2020.

State pension age timetables can be seen here.

Pensioner classifications

In HBAI tables relating to ‘all individuals’, the classification pensioner couple includes individuals in a family unit where one member is above State Pension age, and one is below. This differs from results in HBAI tables relating specifically to ‘pensioners’, where only individuals above State Pension age are included. Thus, if a pensioner above State Pension age has a working-age partner, they will both be included under results for pensioner couple in ‘all individuals’ tables, but in ‘pensioner’ tables the working-age partner will be excluded as they will appear in the ‘working-age population’ tables.

Prevalence weighting

Prevalence weighting is a technique of scoring deprivation, in which more weight in the deprivation measure is given to families lacking those items that most families already have. This means a greater importance, when an item is lacked, is assigned to those items that are more commonly owned in the population.

Region and country

Regional classifications are based on the standard statistical geography of the former Government Office Regions: 9 in England, and a single region for each of Scotland, Wales and Northern Ireland. These regions are built up of complete counties or unitary authorities. Tables also include statistics for England as a whole, and detailed breakdown tables split London into Inner and Outer London to aid comparison with other Family Resources Survey-based publications. For more information on National Statistics geography see ONS’s webpage on UK Geographies.

Disaggregation by geographical regions is usually presented as 3-year averages. This presentation has been used as single-year regional estimates are considered too volatile. Please note that following the decision to not publish breakdowns of the FYE 2021 estimates, all 3-year averages calculated and published for any period including FYE 2021 are based on 2 data points only.

Estimates for the UK are shown as single-year estimates for the latest available year.

Although the FRS sample is large enough to allow some analysis to be performed at a regional level, it should be noted that no adjustment has been made for regional cost of living differences, as the necessary data are not available. In the analysis here it is therefore assumed that there is no difference in the cost of living between regions, although the AHC measure will partly take into account differences in housing costs.

Sampling error

The uncertainty in the estimates which arises from taking a random sample of the household population. The likely size of this error for a particular statistic can be identified and expressed as a confidence interval.

Savings and investments

The total value of all liquid assets, including fixed term investments. Figures are taken from responses to questions on the value of assets or estimated from the interest on the savings when these questions are not asked. Note that banded savings do not include assets held by children in the benefit unit/household. The derivation of total savings used in the tables means that “no savings” specifically relates to cases where the respondent said that they had no accounts/investments, refused to answer, didn’t know, or some accounts/investments were recorded but none of them yielded any interest/dividends.

The data relating to investments and savings should be treated with caution. Questions relating to investments are a sensitive section of the questionnaire and have a low response rate. A high proportion of respondents do not know the interest received on their investments. It is likely that there is some under-reporting of capital by respondents, in terms of both the actual values of the savings and the investment income.

The level of savings and investments, for some families (benefit units) and households was estimated using a slightly different methodology from FYE 2020 than in previous years. The new method more accurately estimates savings in current accounts and basic bank accounts. It should be noted that savings and investments breakdowns from FYE 2020 are not directly comparable with those for previous years.

Skewness

Skewness measures the degree to which a statistical distribution is asymmetrical or lopsided. A perfectly symmetrical distribution is not skewed. A distribution with a long tail to the right, such as the UK income distribution, is positively skewed.

Sources of income

Households receive income from a variety of sources. The main ones are earnings, self-employment, state support (i.e. benefits and tax credits), interest on investments and occupational pensions.

It should be noted that comparisons with National Accounts data would suggest that surveys such as the FRS understate investment income. It is also the case that the FRS underestimates receipt of most types of State Support.

State support

The Government pays money to individuals in order to support them financially under various circumstances. Most of these benefits are administered by DWP. The exceptions are Housing Benefit and Council Tax Reduction, which are administered by local authorities. Tax Credits are not treated as benefits, but both Tax Credits and benefits are included in the term State Support. Further information on UK state support and specific benefits for devolved administrations is available under ‘Benefits’ in the Glossary section of the FRS Background Information and Methodology.

Threshold

An equivalised income value used for comparing sections of an income distribution over time or for comparing proportions of groups over time, for example: fractions of FYE 2011 median income or fractions of contemporary medians. A relative threshold is relative to the contemporary median for each year’s survey. A fixed threshold uses the median from an ‘anchor’ year which is then uprated for inflation as appropriate. For example, the absolute threshold ‘60 per cent of the FYE 2011 median income’ in FYE 2011 is the same as the relative threshold, but the corresponding value in the latest survey year has been up-rated by inflation from the FYE 2011 level over the intervening period.

Working-age

Working-age adults are defined as all adults below State Pension age.

Question 23

Annex 1: Benefit and tax reform in FYE 2022

Accepted Answer

This Annex summarises some of the major benefit and tax reforms which came into effect in FYE 2022. It is not intended to represent an exhaustive list.

Council Tax

The Department for Levelling Up, Housing and Communities estimated that the average Band D council tax set by local authorities in England for 2021 to 2022 increased by 4.4% from 2020 to 2021 levels.

In Wales, the average Band D council tax for 2021 to 2022 represented an increase of 3.8% from 2020 to 2021 levels.

In Scotland, the average Band D council tax for 2021 to 2022 has not increased from 2020 to 2021 levels.

In Northern Ireland, there were increases in rates (poundage) of no more than 1 per cent in some council areas, but in others the rates (poundage) remained as it was in 2020 to 2021.

National Living Wage

On 1 April 2021, the National Living Wage increased to £8.91 per hour for employees aged 23 years and above.

Employees aged under 23 years continued to receive the National Minimum Wage. On 1 April 2021, the National Minimum Wage increased to £8.36 per hour for those aged 21 to 22 years inclusive, £6.56 per hour for those aged 18 to 20 years inclusive and £4.62 per hour for those aged below 18 years (but over compulsory school leaving age). Additionally, the National Minimum Wage rose to £4.30 per hour for apprentices, both those aged below 19 years and those aged 19 years and above who were in the first year of their apprenticeship.

Universal Credit and Tax Credit uplift

From April 2021, the temporary £20 per week Universal Credit uplift continued until 6 October 2021 when it ended. For working households receiving Tax Credits, a one-off payment of £500 was announced by the government and made in April 2021.

Universal Credit removal of minimum income floor for self-employed people

Between 6 April 2020 and 31 July 2021, the government suspended the Minimum Income Floor (MIF) so that self-employed Universal Credit claimants with earned incomes below the MIF would not be treated as earning more than they actually had.

Reducing the Universal Credit taper rate

At the Autumn 2021 Budget, it was announced that the Universal Credit taper rate would be reduced from 63% to 55%. The taper is a reduction to a claimant’s Universal Credit based on their earned income. This change was implemented from 1 December 2021.

Up-rating

In April 2021:

Inflation-linked benefits and tax credits rose by 0.5% in line with the Consumer Prices Index (CPI).
The Basic and New State Pension increased by 2.5% in line with the ‘triple lock’. The ‘triple lock’ ensured that in 2021 to 2022 both the Basic and New State Pension increased by the highest of the increase in earnings, price inflation as measured by the CPI or 2.5%. The Basic State Pension increased from £134.25 per week to £137.60 per week, a cash increase of £3.35 per week. The New State Pension increased from £175.20 per week to £179.60 per week, a cash increase of £4.40 per week.
The Standard Minimum Guarantee in Pension Credit increased by 1.9%. For those who were single, the Standard Minimum Guarantee in Pension Credit increased from £173.75 per week to £177.10 per week, a cash increase of £3.35 per week. For couples, this increased from £265.20 per week to £270.30 per week, a cash increase of £5.10 per week.
Both the lower and higher Universal Credit Work Allowances rose broadly in line with the CPI.

Rent and mortgage payments

The government announced, on 17 March 2020, that those struggling to pay their mortgage or rent because of the coronavirus (COVID-19) pandemic and landlords with buy-to-let mortgages whose tenants were unable to pay the rent were able to apply for a payment holiday. Payment holidays were extended until 31 July 2021.

Payment holidays could either last up to 3 months or up to 6 months. Extra support should have been given by lenders through tailored forbearance options for those who continued to face financial struggles once their payment holiday ended.

The introduction of the Coronavirus Act 2020 stopped both landlords and lenders from evicting those who occupied their properties. Additionally, there was a ban on repossessions from November 2020 until the end of May 2021.

Self-Employment Income Support Scheme

The Self-Employment Income Support Scheme (SEISS) was introduced by the government to help those who were self-employed or a member of a partnership in the United Kingdom and lost income because of the coronavirus (COVID-19) pandemic.

The fourth round of the SEISS paid 80% of 3 months’ average trading profits of the claimant, up to £7,500 in total, and covered from February 2021 up to and including April 2021.

The fifth and final round of the SEISS was partly determined by the amount a claimant’s turnover had reduced in the year April 2020 to April 2021. The grant was worth either 80% of 3 months’ average trading profits, up to £7,500 in total, for claimants with a turnover reduction of 30% or above or 30% of 3 months’ average trading profits, up to £2,850 in total, for claimants with a turnover reduction below 30%. This round of the SEISS covered from May 2021 up to the end of September 2021.

‘Furlough’: Coronavirus Job Retention Scheme

The Coronavirus Job Retention Scheme (CJRS), announced by the government in March 2020, was extended until 30 September 2021. Employers who were unable to keep their workforce due to the coronavirus (COVID-19) pandemic were able to put their employees on furlough and apply for a grant. During this scheme, government and employer contributions varied to ensure that employees received 80% of their monthly wage, up to £2,500 per month. At the employer’s own expense, they could top up their employees’ wages above this threshold.

“IR35” private sector changes

Reforms to worker classification, from self-employed to employee, were implemented from April 2021.

ONS (Labour Force Survey) statistics on self-employment show that in January to March 2021, prior to the implementation of the reforms, 155,000 workers (72.8%) who moved from self-employment to employee status reclassified. In April to June 2021, this fell to 88,000 workers (62.2%) who reclassified. This fell again in January to March 2022, with 75,000 workers (53.5%) who reclassified.

Household Support Fund

The government announced, on 30 September 2021, that vulnerable households in England would be able to access a £500 million support fund with the aim of helping them with necessities over winter. This was in place from 6 October 2021 up to and including 31 March 2022. On 23 March 2022, an extension to 30 September 2022 to the Household Support Fund was announced with an additional £500 million of funding.

To help directly the most vulnerable households, the Household Support Fund was distributed by councils in England through small payments. The aim was to ensure that daily needs such as food, clothing, and utilities of those in such households were met.

Question 24

Annex 2: Other relevant statistics

Accepted Answer

The HBAI report and statistics are released alongside a number of other statistics focused on income and low-income statistics across Government.

In February 2015 the United Kingdom Statistics Authority (UKSA) published a report on the outcome of a monitoring review into the Coherence and Accessibility of Official Statistics on Income and Earnings. A progress report was published in January 2016, with a further update in December 2018.

This review considered the way in which official statistics about income and earnings across Government are presented and includes summary details of the official statistics within the Review’s scope, discussion of the conceptual issues faced by users and advice needed when attempting to analyse official statistics and makes recommendations around potential solutions to concerns identified and for the longer-term development of income and earnings statistics.

The Office for Statistics Regulation (OSR) published a further review of income-based poverty statistics on 19 May 2021. This included background information on why the review was commissioned as well as the findings and recommendations for statistics producers. Recommendations focussed on key areas including accessibility and guidance, understanding poverty, data gaps, data quality, and trustworthiness. Several of the recommendations were taken into account in the FYE 2021 HBAI publication. Please refer to the DWP Statistical Work Programme for further information on DWP’s response to the OSR review.

Work was taken forward by the Government Statistical Service (GSS) Coherence Team at the Office for National Statistics (ONS), who carried out a review of signposting across income and earnings statistics and made several recommendations for improvement. The ONS also developed a new interactive tool which can be used to identify sources of statistics on income and earnings, and their key features.

The statistics highlighted below represent several statistical releases which might be considered alongside results from HBAI in order to give a more complete picture. This is not intended to be an exhaustive list and should be considered alongside details from the UKSA review highlighted, as well as ONS guidance on sources of data on earnings and income, with additional details at on important questions also available.

Poverty and income inequality in Scotland

In-depth analysis of HBAI data for Scotland.

Poverty statistics for Wales

In-depth analysis of relative income poverty in Wales can be found on the relative income poverty page of the Welsh Government website, which has links to material deprivation and persistent poverty analysis.

Households Below Average Income Report for Northern Ireland

In-depth analysis of HBAI data for Northern Ireland.

EU comparisons

After the UK’s exit from the EU in 2020, some EU-SILC outputs were still delivered by ONS to Eurostat during the transition period in 2020, but all planned deliveries from 2021 onwards ceased. Data for the UK up to and including the 2018 calendar year remain available on Eurostat’s EU-SILC database.

Details of the differences between the EU and HBAI methodology are given in the main body of this report.

OECD international comparisons

The OECD income distribution database provides international comparisons on trends and levels in Gini coefficients before and after taxes and transfers, average household disposable incomes, relative poverty rates and poverty gaps, before and after taxes and transfers.

The effects of taxes and benefits on household income

The UK has 2 main, official data sources of household income statistics: the Family Resources Survey (FRS) run by the Department for Work and Pensions (DWP) and the Household Finances Survey (HFS) run by the Office for National Statistics (ONS).

The FRS estimates underpin DWP’s Households Below Average Income (HBAI) series, which is the UK’s official source of poverty estimates. With a larger sample size, it is also the main source on household and individual incomes. HFS data are used to produce ONS’s Household Disposable Income Inequality (HDII) and Effects of Taxes and Benefits (ETB) series, these outputs are the main source for considering the overall financial well-being of households.

There are some key methodological differences between the 2 series which means that their income estimates are different. For example, the FRS focuses on respondents’ weekly incomes at the time of interview, whereas HFS focuses more on annual income. The treatment of pension contributions also differs, with ONS’ estimate of Gross Household Income being calculated before pension contributions. Further details are available in the income and earnings statistics guide.

Pensioners’ Incomes series

The Pensioners’ Incomes series (PI) publication gives more a more detailed analysis of pensioners’ incomes.

Family Resources Survey

The Family Resources Survey (FRS) publication gives some further results of FRS data analysis.

Income Dynamics

Income Dynamics (ID) is a publication based on longitudinal data, containing analysis of income movements and the persistence of low income for various population groups.

It supersedes Low-Income Dynamics, which was last published in September 2010.

Personal Incomes Statistics

The Personal Incomes statistics publication gives summary information about UK taxpayers, their income and the Income Tax to which they are liable.

Wealth in Great Britain

The Wealth and Assets Survey (WAS) is a large-scale longitudinal survey with 7 rounds currently published. Round 7 (2018 to 2020) had a sample of around 18,000 private households or 39,000 individuals in Great Britain. It is conducted by the Office for National Statistics (ONS). The WAS dataset holds information about the economic status of households and individuals including their physical and financial assets, debts, and pension provision. WAS data are also used to understand how wealth is distributed and the factors which may affect financial planning, as well as a respondents’ attitudes and behaviours towards saving. The Pension Wealth tables in WAS provides estimates of the types of private (non-state) pension wealth, split by a wide range of socio-demographic and economic breakdowns

Measuring National Well-being

The Measures of National Well-being Dashboard: Quality of Life in the UK brings together the latest national well-being data from the Office for National Statistics (ONS) and other sources to give an overview of how the UK is doing across the 10 areas of life that the UK public told us matter most.

Estimates of income and low-income levels for small areas

HBAI data cannot be broken down below the level of region, due to sample size and coverage issues. However, there are some data sources that present information at smaller geographies.

Children in Low-Income Families Local Area Statistics

Children in Low Income Families(CiLIF) provides estimates of the number and proportion of children living in low-income families, Before Housing Costs (BHC), across the United Kingdom by local area.

Small area model-based income estimates for England and Wales

ONS produce model-based estimates of income at Middle Layer Super Output Area (MSOA) level for FYE 2018.

Admin-based income statistics, England and Wales

ONS also produce experimental estimates of gross and net income based on data from the Pay As You Earn and benefits systems.

English Indices of Deprivation

The English Indices of Deprivation, produced by the Ministry of Housing, Communities and Local Government is a measure of relative levels of deprivation in small areas of England called Lower Layer Super Output Areas.

Welsh Index of Multiple Deprivation

The Welsh Index of Multiple Deprivation (WIMD) is the official measure of deprivation in small areas in Wales. It is a relative measure of concentrations of deprivation at the small area level.

Scottish Index of Multiple Deprivation

The Scottish Index of Multiple Deprivation (SIMD) is the Scottish Government’s official tool for identifying those places in Scotland suffering from deprivation.

Northern Ireland Multiple Deprivation Measure

The Northern Ireland Multiple Deprivation Measure (NIMDM) is the official measure of spatial deprivation in Northern Ireland.

Question 25

Annex 3: Uses and users of HBAI statistics

Accepted Answer

HBAI is a key source for data and information about household income. Users include: policy and analytical teams within the DWP, the Devolved Administrations and other government departments, local authorities, parliament, academics, journalists, and the voluntary sector.

Researchers and analysts outside government use the statistics and data to examine topics such as income inequality, the distributional impacts of fiscal policies and understanding the income profile of vulnerable groups. Examples of published reports using HBAI data include:

Within government the statistics and data are used:

The Scottish Government uses the HBAI data:

The Welsh Government uses the HBAI data:

to support users to understand issues relating to poverty in Wales, and to help inform policy in this area
to measure progress on the National Indicators for Wales
to monitor progress of the Welsh Government’s Child Poverty Strategy (2015)

The Department for Communities in Northern Ireland uses HBAI data to:

monitor progress of the Northern Ireland Child Poverty Strategy
monitor progress against proposed indicators in the Northern Ireland Executive’s Programme for Government 2016-21. The Programme for Government is currently in draft form.

Question 26

Annex 4: Communicating uncertainty

Accepted Answer

Introduction

The figures in this publication come from the Family Resources Survey. This is a survey of over 16 thousand households across the UK. Like all surveys, it gathers information from a sample rather than from the whole population. The size of the sample and the way in which the sample is selected are both carefully designed to ensure that it is representative of the UK as whole, whilst bearing in mind practical considerations such as time and cost constraints. Survey results are always estimates, not precise figures. This means that they are subject to a level of uncertainty which can affect how changes, especially over the short term, should be interpreted.

Estimating and reporting uncertainty

Two different random samples from 1 population, for example the UK, are unlikely to give exactly the same survey results and are likely to differ again from the results that would be obtained if the whole population was surveyed. The level of uncertainty around a survey estimate can be calculated and is commonly referred to as sampling error. In addition to sampling error the HBAI estimates can also be affected by non-sampling error such as non-response and a tendency to under-report benefit receipt.

We can calculate the level of uncertainty around a survey estimate by exploring how that estimate would change if we were to draw many survey samples for the same time period instead of just one. This allows us to define a range around the estimate (known as a “confidence interval”) and to state how likely it is that the real value that the survey is trying to measure lies within that range. Confidence intervals are typically set up so that we can be 95% sure that the true value lies within the range – in which case this range is referred to as a “95% confidence interval”.

Measuring the size of sampling error

Accuracy of the statistics: Confidence intervals are used as a guide to the size of sampling error. A confidence interval is a range around an estimate which states how likely it is that the real value the survey is trying to measure lies within that range. A wider confidence interval indicates a greater uncertainty around the estimate. Generally, a smaller sample size will lead to estimates that have a wider confidence interval than estimates from larger sample sizes. This is because a smaller sample is less likely than a larger sample to reflect the characteristics of the total population and therefore there will be more uncertainty around the estimate derived from the sample.

Statistical significance: Some changes in estimates from 1 year to the next will be the result of different samples being chosen, whilst other changes will reflect underlying changes in income across the population. Confidence intervals can be used to identify changes in the data that are statistically significant, that is, they are unlikely to have occurred by chance due to a particular sample being chosen.

Confidence intervals can give a range around the difference in a result from 1 year to the next. If the range does not include zero it indicates this change is unlikely to be the result of chance. The examples below give more detail on how confidence intervals can be interpreted.

In the commentary report, results that are statistically significant are shown with an asterisk. Any results not marked by an asterisk are likely to have occurred as a result of chance. The HBAI estimates that are presented are the best estimate of the real value that the survey is trying to measure.

In the summary tables presented in this report, estimates of the percentage in low income that are statistically significant from the previous year are shown with an asterisk, with further information in the Uncertainty and Commentary Tables pages. Estimates of the number in low income that are statistically significant from the previous year are also shown with an asterisk. Changes marked by an asterisk are unlikely to have occurred as a result of chance. The HBAI estimates that are presented are the best estimate of the real value that the survey is trying to measure.

Non-sampling error: In addition to sampling error, non-sampling error is another area of uncertainty and is present in all surveys as well as in censuses. Non-sampling error encompasses all error other than sampling error. Types of non-sampling error include: coverage error, non-response error, measurement error and processing error. These errors are minimised in this survey by rigorous procedures, however, it is not possible to eliminate it completely and it cannot be quantified. It is important to bear in mind that confidence intervals are only a guide for the size of sampling error and cannot tell us anything about non-sampling error.

Working with uncertain estimates: Some changes between years will be small in relation to sampling variation and other sources of error and may not be statistically significant. This is relevant for particular sub-groups, as these will have smaller sample sizes than the overall survey sample size. For these sub-groups it is important to look at long-term trends.

Calculating uncertainty in the HBAI report

As the FRS is a sample from the UK population, any statistics derived from it are only estimates of the true numbers for the overall population. Prior to the FYE 2013 publication, confidence intervals for HBAI estimates were calculated using an estimating function approach. Since then, DWP has used bootstrapping techniques to measure how different a HBAI estimate might have looked if different FRS samples had been drawn.

The bootstrapping methodology used for the FYE 2013, FYE 2014 and FYE 2015 publications applied the original HBAI grossing factors to simple random resamples of the HBAI dataset to calculate confidence intervals for HBAI estimates.

The Institute for Fiscal Studies (IFS) were commissioned to develop the DWP methodology further to account as fully as possible for the specific features of the FRS sampling design for Great Britain (GB) and Northern Ireland (NI) and HBAI grossing process.

The new methodology, introduced from the FYE 2016 publication onwards, produces:

GB resamples simulating the FRS stratified, cluster sampling of GB households
NI resamples simulating the FRS stratified sampling of NI households
a unique set of grossing factors for each GB and NI resample, replicating the original HBAI grossing process, to produce lower and upper confidence intervals

accounting for:

cluster sampling – this widens confidence intervals for most estimates, reflecting that this feature makes survey estimates less precise
post-sample grossing to population totals – this narrows confidence intervals for estimates sensitive to incomes towards the very top of the income distribution, as specific control totals are set for high income individuals

Further details on methodological work undertaken by IFS, together with illustrative details of the impact of different aspects of the new methodology on key HBAI estimates for FYE 2014, are available in the published IFS report.

The following diagrams present:

Figure A4a: Summary of the New Bootstrapping Methodology
Figure A4b: GB FRS Sampling and Bootstrapping Resampling Process
Figure A4c: NI FRS Sampling and Bootstrapping Resampling Process
Figure A4d: HBAI Grossing and Bootstrapping Grossing Process

Further development work has been carried out on the derivation of the confidence intervals for HBAI estimates in the FYE 2017 publication, meaning results published in reports before this date may have changed slightly. The resample grossing factor datasets from FYE 1995 to the latest published year have been deposited at the UK Data Archive, along with user guidance on creating confidence intervals.

Figure A.4a: Summary of the New Bootstrapping Methodology

Figure A.4b: Great Britain FRS Sampling and Bootstrapping Resampling Process

Figure A.4c: Northern Ireland FRS Sampling and Bootstrapping Resampling Process

Figure A.4d: HBAI Grossing and Bootstrapping Grossing Process

95 per cent confidence intervals

Confidence intervals are typically set up so that we can be 95 per cent sure that the true value lies within a certain range – in which case this range is referred to as a “95 per cent confidence interval”.

Example 1: Interpreting confidence intervals

17 per cent of individuals are estimated to be living in relative low income BHC. This figure has a stated confidence interval of 15 to 18 per cent (Table 8b). This means that we can be 95 per cent sure that between 15 and 18 per cent of individuals are in relative low income. Our best estimate is 17 per cent of individuals.

As well as calculating confidence intervals around the results obtained from 1 year of the survey, confidence intervals can also be calculated for the changes in results across survey years.

Example 2: Statistical significance

The estimated change in the percentage of individuals living in relative low income BHC from FYE 2021 to FYE 2022 is an increase of 1 percentage points (Table 8b). The confidence interval around this figure is -2 to 3 percentage points. This means that we can be 95 per cent sure that the actual change in the percentage of people living in relative low income is between a decrease of -2 percentage points and an increase of 3 percentage points, with the best estimate being an increase of 1 percentage points. As the confidence interval includes zero this change is not statistically significant, which indicates that there is at least a 5 per cent probability that the change in the percentage of individuals in relative low income is the result of chance.

If the confidence interval did not include zero, we would conclude that the change is statistically significant i.e. the change is unlikely to be the result of chance.

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Introduction

Impact of the coronavirus (COVID-19) pandemic on the statistics for FYE 2021 and FYE 2022

Comparing official statistics across the UK

National Statistics

Acknowledgements

Users and uses

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Impact of the coronavirus (COVID-19) pandemic on the sample data and estimates

New statistics on food bank usage for individuals living in low-income households

Combined low income and working-age adult material deprivation statistics

Three-year rolling averages

Grossing changes

Treatment of income sources introduced during the coronavirus (COVID-19) pandemic

Inclusion of income from dividends

Guide to published tables

Using and Interpreting HBAI Results

What do we mean by average?

HBAI measures

Rounding

Key terminology

Income

Median

Deciles and Quintiles

Income distribution

Equivalisation

Housing costs

Benefit unit and households

Other terms

Issues to consider

Survey Data

Reporting Uncertainty

Population

Grossing

Changes to the grossing regimes in FYE 2021 and FYE 2022

Table 1: HBAI grossing regime for Great Britain, FYE 2022

Table 2: HBAI grossing regime for Northern Ireland

Adjustment for individuals with very high incomes

Equivalisation

Figure 1

Table 3: Comparison of modified OECD and McClements equivalence scales

Income Definition

Housing costs

Negative incomes

State support

Treatment of coronavirus (COVID-19) pandemic related support schemes in the HBAI income estimates for FYE 2021 and FYE 2022

Earnings from employment

Earnings from self-employment

Interpreting low-income measures

Figure 2

Combined low income and child material deprivation

Table 4: Material deprivation scores used for children in FYE 2022

Combined low income and working-age adult material deprivation

Table 5: Material deprivation scores used for adults in FYE 2022

2022 review of the material deprivation questions in the FRS

Material deprivation for pensioners

Table 6: Material deprivation scores used for pensioners in FYE 2022

Material deprivation weighting methodology

Impact of the coronavirus (COVID-19) pandemic on the material deprivation measures

Household food security

Food bank usage

Ethnicity categories

Disability definition

FRS questions FYE 2005 to FYE 2012

FRS questions FYE 2013 onwards

Comparisons over time

Comparison with EU low-income statistics

Glossary

Adult

Benefit units or Family

Bills in arrears

Child

Confidence interval

Contemporary median income

Deciles and Quintiles

Disability

Economic status of the family

Economic status groups for children

Economic status of household