1. Output Information

  • Statistical designation: accredited official statistic

  • Survey name: Wealth and Assets Survey (WAS)

  • Data collection: WAS is a dual mode survey (face to face and telephone interviewing) of around 32,300 people aged 16 or over and 15,100 households in Great Britain for Round 8 (April 2020-March 2022)

  • Frequency: biennial

  • How compiled: longitudinal survey

  • Geographic coverage: Great Britain, excluding addresses north of the Caledonian Canal, the Scottish Islands and the Isles of Scilly

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2. About this Quality and Methodology Information report

This Quality and Methodology Information (QMI) report contains information on the quality characteristics of the data (including the European Statistical System's five dimensions of quality) as well as the methods used to create it.

The information in this report will help you to:

  • understand the strengths and limitations of the data

  • learn about existing uses and users of the data

  • understand the methods used to create the data

  • help you to decide suitable uses for the data

  • reduce the risk of misusing data

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3. Important points

  • We adapted data collection of Round 8 of the Wealth and Assets Survey (WAS) because it took place during the coronavirus (COVID-19) pandemic; while this round offers valuable insight, data are more uncertain because of data-collection mode changes, sample coverage and additional non-response, so users should treat results with a degree of caution, particularly in relation to regional breakdowns and estimates of property wealth.

  • We have updated the weighting scheme for Round 8 of WAS to include tenure as a calibration control to account for an under-representation of renters and an over-representation of owner occupiers within the achieved sample; the weighting scheme is now using population totals derived from the latest census data in England, Wales, and Scotland.

  • For Round 8 of WAS, we reviewed the methodology used to estimate defined benefit pension wealth and have updated assumptions used to calculate this; this constitutes a break in the time series for pensions wealth and total wealth where pensions wealth is included, and estimates are not directly comparable with the previous rounds (we will annotate this discontinuity on charts and datasets from Round 8 onwards).

  • Our latest Household total wealth in Great Britain bulletin contains several estimates adjusted for inflation, in line with our previous release; however, before the release of Wealth in Great Britain April 2016 to March 2018, we included estimates presented as current values that had not been adjusted for inflation.

  • All data presented in Total Household Wealth in Great Britain datasets are presented as current values and consequently may not match the figures quoted within the latest (April 2020 to March 2022) and previous (April 2018 to March 2020) bulletins.

  • All reasonable attempts have been made to ensure that the data are as accurate as possible; however, there are two potential sources of error that may affect the reliability of estimates and for which no adequate adjustments can be made, known as sampling and non-sampling errors, see Section 5: Quality characteristics of the Wealth and Assets Survey data for more information.

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4. Quality summary

Overview

The Wealth and Assets Survey (WAS) launched in 2006 and is a biennial longitudinal survey conducted by the Office for National Statistics (ONS). This survey measures the well-being of households and individuals in terms of their assets, savings, debt and planning for retirement. Data from this longitudinal survey will also provide users with the ability to measure changes of wealth in Great Britain (GB) over time. A funding consortium has sponsored the WAS up to Round 8, including the ONS, His Majesty's Revenue and Customs (HMRC), Scottish Government (SG) and the Department for Work and Pensions (DWP).

Table 1 shows the achieved sample size for the WAS from Wave 1 to the latest Round 8. Wave 6 of the WAS was only in the field for 21 months, because of the move of WAS to financial years (rounds). The number of households sampled for Wave 6 was therefore approximately 16,000. This was combined with the final 3 months of the preceding Wave 5 to produce an 18,000 household Round 6 file.

The fieldwork for Round 8 of the WAS took place during the coronavirus (COVID-19) pandemic where, for much of the time, national lockdown conditions and social distancing restrictions were in place. As such, interviewing took place over the telephone for the whole of Round 8. Response rates for the study dropped from 68% in Round 7 to 54% in Round 8 for the old cohort, and from 41% to 26% for the new cohort. In total an achieved sample of approximately 15,100 households was delivered across the latest round. For further details, see our Impact of COVID-19 on ONS social survey data collection methodology.

As wealth is known to be unevenly distributed, addresses more likely to contain wealthier households are sampled at a higher rate to improve the efficiency of the sample. These addresses are identified utilising data from HMRC.

The datasets for waves 1 to 5 and rounds 5 to 8 have been released to consortium members as well as the UK Data Service (UKDS) under an End User Licence (EUL) and to the Approved Researcher Scheme managed by the ONS. Given the need to maintain respondents' anonymity, certain variables have not been released to consortium members and the UKDS. To encourage the widest possible use of the data, including internationally, the latest EUL datasets were created and deposited with the UKDS in January 2025.

Uses and users

The results of the WAS are used by a range of users. These include other government departments such as the Department for Work and Pensions (DWP), His Majesty's Revenue and Customs (HMRC) and the Department of Health and Social Care (DHSC); the devolved administrations of Scotland and Wales, as well as elected national and local representatives (such as Members of Parliament (MPs) and local councillors). There is also interest in the results of WAS from academics, researchers, students, Think Tanks and the general public. The data provide a greater understanding of the levels and distribution of wealth in terms of pensions, property, financial and physical assets, and indebtedness.

Strengths and limitations

The WAS is unique in that it provides a single data source on the wealth and asset profile of households and individuals within GB. This can be taken with information collected on socio-demographic and economic characteristics of respondents, to provide micro-level distributional analysis of wealth and assets.

Behaviour and circumstance may have shifted considerably from previous rounds because of the coronavirus (COVID-19) pandemic. Round 8 provides a valuable insight into this period, however users should be aware of this context when observing shifts in circumstance, which may not have happened during a standard round. Given this increased uncertainty, users should apply greater caution when using the data. We have removed a small number of tables from our published debt and property wealth datasets where it was agreed that the quality was insufficient.

An important point to note is that the self-valuation method WAS uses tends to yield higher estimates of worth than most other property indicators may suggest.

A strength of WAS is that the survey is designed to pick up the very wealthy, where wealth is highly skewed towards the top of the distribution. All such cases are thoroughly checked and, as a result, they are included in the survey results. Given the skewed nature of wealth data and the effect that outliers can have, our Household total wealth in Great Britain statistical bulletin and the accompanying datasets do not generally report mean values. Instead, they use the median values to report central tendency. This is not possible for physical wealth estimates because of how physical wealth data are collected.

Recent updates

Data collection mode

Fieldwork for Round 8 was conducted during the coronavirus (COVID-19) pandemic where national lockdown and social distancing restrictions were in place. To conduct fieldwork during this time, the survey mode was entirely moved from face to face to telephone-based interviewing. Further details on the move to the new data collection method are outlined in Section 6: Methods used to produce the Wealth and Assets Survey data, with details of the impact of moving ONS surveys to telephone covered in Impact of COVID-19 on ONS social survey data collection methodology

Pension methodology change

In Round 8 of WAS the pension wealth methodology used to estimate defined benefit and pensions in payment pension wealth was reviewed in response to the changing economic landscape and user feedback.

To maintain the quality and stability of estimates of pension wealth within a rapidly changing economy, the Superannuation Contributions Adjusted for Past Experience (SCAPE) discount rate is now used in the updated model to place a present-day value on future pensions promises, both before and after retirement. Previously the model used a mix of SCAPE and market-based financial assumptions. The change helps protect our Defined Benefit (DB) pension wealth estimates against undue volatility and reflects the stability of DB pension promises for those that hold them.

The change in pension methodology reflects a methods update, and there are no current plans to revise the back series. As such, it will introduce a break in the time series for Round 8 estimates for both pension wealth and total wealth. We have clearly communicated this break in time series to users in line with Government Statistical Service (GSS) guidelines through our Round 8 bulletin text and figures, and within the pensions and total wealth analysis datasets.

For more information, including details on the impact of the change on pension wealth measure, see our Estimating defined benefit pension wealth in Great Britain: December 2024 article.

Updates to weighting calibration

For Round 8 of WAS there have been two updates to the weighting scheme to ensure it is as representative as possible of the GB population. Firstly, in addition to age-sex groups and regions, tenure has been included as a further control to the calibration scheme to account for the increased selection bias in the achieved sample during the coronavirus (COVID-19) pandemic, which under-represented renters and over-represented households who own outright. More detail on how response by household characteristic has been affected during the coronavirus pandemic can be found in our Impact of COVID-19 on ONS social survey data collection methodology.

Secondly, calibration targets are now derived from population series based on Census 2021 for England and Wales and the 2022 Census for Scotland, respectively. Deflation factors have been applied to the census-based estimates of the whole population to account for the fact that the target population for the WAS are private households. All calibration totals have been adjusted to refer to March 2021, the midpoint of the Round 8 data collection period. More detail, including the impact on headline statistics, can be found in Section 6: Methods used to produce the Wealth and Assets Survey data.

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5. Quality characteristics of the Wealth and Assets Survey data

Relevance

Several government departments initially joined the Wealth and Assets Survey (WAS) consortium because this survey was identified as being able to supply data on topics that were not sufficiently covered elsewhere. This survey fills a major information gap on wealth and indebtedness at a household and personal level.

The pension wealth data in particular is unique owing to its detail. The longitudinal element provides a further dimension to this dataset, allowing users to analyse levels of change across all periods, from lower levels of wealth and indebtedness to households' or individuals' total wealth. It is important to note that diminishing response for new and existing sample members, as outlined in the response section, impacts the level of detail longitudinal analysis can be conducted at, and the period it can be conducted over. We will continue to review this for future rounds, and communicate with users as needed.

Although the achieved sample has reduced over time, it still provides a relatively large sample and almost complete coverage of Great Britain (GB).

Accuracy and reliability

Multiple quality assurance methods ensure that the WAS data are as reliable as possible. These methods are applied during the interview and after collection through:

  • consistency checks

  • outlier detection

  • comparisons of the data between waves and rounds

  • checks carried out on all calculations used to estimate wealth

All data that are identified as possible errors are investigated and, where appropriate, adjusted.

Revisiting respondents in subsequent waves/rounds provides the opportunity to confirm the current round's data against that which has been collected previously.

Coherence and comparability

Major government surveys now use harmonised questions on important topics to ensure comparability of results. Where appropriate, WAS questions are harmonised with other government surveys. Further information on the GSS Harmonisation Strategy can be found on the GSS website.

Separate datasets for each wave or round are issued after all checks have been completed. Although many of the variables are comparable between waves/rounds, some datasets have changed as have some of the categories of responses for particular variables. When this occurs, details are provided in the user guides and variable lists.

A glossary of the main terms used in the WAS is provided in Glossary: Wealth in Great Britain, 2006 to 2008.

There is limited comparable data from administrative sources or major surveys for some topics covered by the WAS. Nevertheless, using information that was available, the comparability of the results with results from other sources have been checked by the various contributors to the report as part of the validation process. This comparison will have included information from less extensive surveys and administrative data.

Accessibility and clarity

The UK Data Service (UKDS) funded by UK Research and Innovation (UKRI) through the Economic and Social Research Council (ESRC) provides access to researchers under an End User Licence (EUL).

Documentation has been provided to the consortium members and is available to UKDS researchers to help assist users with the datasets.

Our recommended format for accessible content is a combination of HTML web pages for narrative, charts and graphs, with data being provided in downloadable formats such as CSV and Excel. We also offer users the option to download the narrative in PDF format. In some instances, other software may be used or may be available on request. Available formats for content published on our website but not produced by us, or referenced on our website but stored elsewhere, may vary. For further information, please email us at wealth.and.assets.survey@ons.gov.uk.

Timeliness and punctuality

The survey has been in existence since 2006 and has a biennial interview wave pattern. The survey period moved to a two-year financial year-based periodicity (April to March) from April 2016, with this periodicity being referred to as a "round". See more information in Moving the Wealth and Assets Survey onto a financial years' basis.

These data are available in the following main releases:

For more details on related releases, the Release calendar provides 12 months' advance notice of release dates. If there are any changes to the pre-announced release schedule, public attention will be drawn to the change and the reasons for the change will be explained fully at the same time, as set out in the Code of Practice for Official Statistics.

For Round 8, there was a delay of around 34 months between the end of data collection and the availability of full results. This represents a drop in timeliness from the target of around 18 months. An extended period of data processing and additional quality assurance was required in response to process changes introduced by the coronavirus (COVID-19) pandemic and methods updates outlined in Section 6: Methods used to produce the Wealth and Assets Survey data.

Concepts and definitions (including list of changes to definitions)

The classifications used for the WAS are harmonised with other government surveys. These classifications are:

  • Household Outcome Code

  • UK Standard Industrial Classification (UK SIC)

  • UK Standard Occupational Classification (UK SOC)

  • Country of birth

  • Nationality

  • Religion

  • Ethnicity

Output quality

There is a trade-off between accuracy and timeliness of data dissemination. In theory, the WAS data could be disseminated immediately after fieldwork completion. However, the format of the data and level of item or unit non-response would significantly reduce the analytical value and usability of the data.

We have decided to undertake editing and imputation of the WAS data before its dissemination. This significantly improves the quality and usability of data available for analysis, but it delays the dissemination of data. For Round 8, prolonged data processing and quality assurance steps have affected the timeliness of the data more than is usual. We are actively working to reduce the amount of time that the edit and imputation stages take, to retain accuracy while ensuring the data are disseminated as soon after data collection as possible.

Sampling error

There are two potential sources of error that may affect the accuracy of estimates and for which no adequate adjustments can be made: sampling and non-sampling errors.

Sampling error refers to the difference between the results obtained from the sample and the results that would be obtained if the entire population was fully enumerated. The survey estimates are therefore likely to differ from the figures that would have been produced if information had been collected for all households or individuals in Great Britain. The extent to which survey estimates vary from their population values can be estimated, to a given level of confidence, through the calculation of confidence intervals via the standard error of the estimate.

The standard error is a measure of sampling variability, which shows the extent to which the estimates are expected to vary over repeated random sampling. To estimate standard errors correctly, the complexity of the survey design needs to be accounted for.

Some estimates of standard errors for main variables are available in the supporting tables, wealth in Great Britain Round 8: Quality indicators.

Additional inaccuracies, which are not related to sampling variability, may occur for reasons such as errors in response and reporting. Inaccuracies of this kind are collectively referred to as non-sampling errors and may occur in a sample survey or a census. The main sources of non-sampling error are:

  • response errors resulting from misleading questions, interviewer bias or respondent misreporting

  • bias resulting from non-response, as the characteristics of non-responding persons may differ from responding persons

  • data input errors or systematic mistakes in processing the data

Non-sampling errors are difficult to quantify in any collection. However, every effort is made to minimise their effect through careful design and testing of the questionnaire, training of interviewers, and extensive editing and quality control procedures at all stages of data processing. Statistical imputation is another method used to improve accuracy resulting from missing observations in the dataset, see Section 6: Methods used to produce the Wealth and Assets Survey data for more on imputation.

Response

Response rates are reported on a monthly basis and are based on the number of fully and partially co-operating households as a proportion of the numbers of eligible households in the sample. A response rate of 55% was achieved for Wave 1, and 68% of the eligible households sampled responded in Wave 2. For Wave 3 onwards, the overall response rates and the breakdown for new and old cohorts are included in Table 2.

Changes to collection methods in response to the coronavirus pandemic prompted larger issued sample sizes to compensate for lower expected contact and response rates to help maintain achieved sample sizes. For further information, see our Impact of COVID-19 on ONS social survey data collection methodology.

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6. Methods used to produce the Wealth and Assets Survey data

How the data are collected

The Wealth and Assets Survey (WAS) gathers information on the number and value of assets, debt and savings; as well as attitudes to savings and indebtedness of households and individuals using Computer Assisted Interviewing (CAI). Classificatory variables, including age, sex and employment status, are also gathered.

Fieldwork for Round 8 was conducted during the coronavirus (COVID-19) pandemic. Therefore, end-to-end data collection methodologies were revised to permit the WAS to continue, while seeking to safeguard the wellbeing of respondents and interviewers. 

In response to the coronavirus pandemic, all of the WAS mainstage interviews were conducted by telephone for the round and the length of the questionnaire was also reduced to increase accessibility. This involved the removal of numerous questions which did not feed into core WAS wealth estimates. Further detail on questionnaire cuts will be found in the WAS user guide scheduled to be deposited with the UK Data Service (UKDS) in January 2025.

Contact approaches were adapted to help facilitate telephone-based fieldwork during the coronavirus pandemic. This included pre-notification of the survey mode change, the extended use of telematching and collecting missing telephone details via an online portal.

Wave 1 collected data for the two years from July 2006 to June 2008. Wave 2, a follow up to Wave 1, was conducted between July 2008 and June 2010. To compensate for attrition across Waves 1 and 2, a new cohort of addresses was introduced for Wave 3 and each subsequent collection.

New cohorts help reduce some of the bias introduced by attrition. Participants are selected from the current population to help account for changes in the characteristics of population over time, while maintaining the size of the cross-sectional sample.

As response rates have declined and attrition has increased, as described in previous sections, the proportion of the achieved sample derived from households being re-interviewed has diminished.

Having collected data for "Waves" (July to June two years later) for 10 years the periodicity of the survey changed to "Rounds" (April to March two years later) to align with the financial year.

Following a two-stage approach to sampling, Primary Sample Units (PSUs), based upon the postcode sectors of the small user Postcode Address File (PAF), are selected from a list geographically sorted by NUTS Level 2 geographies, i.e. a sub-regional geography of the classification. Selected PSUs cover the whole of Great Britain (GB), except mainland Scotland north of the Caledonian Canal, the Scottish Islands and the Isles of Scilly.

Historically within each of these postcode sectors, 26 addresses were randomly selected with addresses listed by postcode and street number. Selected addresses were then split into two quotas of 13 addresses to ease the management of fieldwork.

In response to the coronavirus pandemic, quota sizes were adjusted across Round 8, first doubling to 26 addresses from June 2020, before being gradually reduced across the remainder of the round.

With the distribution of household wealth highly skewed, households likely to be in the top percentile of the GB wealth distribution are now oversampled by a factor of five, and households in the 2nd to 10th percentile by a factor of three.

Survey interviews are conducted evenly over the year, to help ensure estimates are not biased by seasonal variations.

"Keep-in-Touch Exercise" interviews are undertaken four months before follow-up mainstage interviews to help maintain the accuracy of contact details and encourage further participation.

Editing

An extensive range of validation checks and computer edits were applied to both the household and individual questionnaires during the computer-assisted interview (CAI) and to the consolidated monthly data.

Imputation

Imputation is an adjustment process that is used to determine and assign replacement values to resolve problems of missing, invalid or inconsistent data.

The problem of missing data in the WAS is approached in two stages: first, a deductive imputation method, followed by a statistical method. Deductive imputation is applied where a missing or inconsistent value could be deduced with certainty. Secondly, statistical imputation is carried out using a nearest-neighbour imputation method where information from a donor record that had no errors or missing values is used to replace the missing values for a recipient record. In this approach, a donor is selected from a pool of potential donors with similar characteristics based on conditional probabilities.

In total, for Round 8, 665 variables underwent nearest-neighbour imputation. The majority of these variables (414) had under 10% of responses requiring imputation. Of the remaining variables:

  • 84 had between 10% and 20% of responses requiring imputation

  • 79 had between 20% and 40% of responses requiring imputation

  • 88 required over 40% of the data to be imputed

Further information can be found in the Round 8 user guide which will be published on the UKDS website once the micro data are released.

For longitudinal households, where an observed value is present in one wave but the other wave is missing and therefore requires imputation, an imputed value is drawn from a donor with reference to the observed value or is calculated based on observed relationships or ratios between variables in the donor record. The imputation is conducted under edit constraints to ensure that outliers and implausible relationships are not introduced into the data through the imputation process.

Outliers

As part of the data cleaning process, cross-sectional outliers are identified on all monetary variables used to compile derived variables. Large changes between waves are also identified as longitudinal outliers. Outlier thresholds are determined through analysis of the distribution of the data. Each variable is analysed dependent upon the nature of that variable and the spread of its data. A percentage of the highest and lowest values are identified as outliers. Not all variables have their lowest values labelled as outliers as low values can be acceptable for some variables, for example, zero values in financial accounts.

Outliers are checked for credibility through examination of other variables, including the previous waves' responses, in an attempt to find evidence to support or inform an edit to the outlier. This evidence includes the inspection of wealth, through income, assets and debts, and verification from linked variables (for example, comparisons of mortgage value with monthly mortgage payment and remaining term). There can be reasons to justify substantial longitudinal changes. For example, alterations to working status or household structure, in particular a split in partnership or a house move, can significantly affect the longitudinal change of many variables.

Amendments are only made to data where sufficient evidence to support an amendment exists. In waves one and two, approximately 5% of the data were investigated as outliers, of which a minority of these were amended. A more systematic approach was established for the identification of cross-sectional and longitudinal outliers from wave three onwards.

Weighting

A three-stage weighting procedure is implemented in the WAS. First, a design weight, equal to the reciprocal of the address selection probability, is constructed. Secondly, a non-response weight is created to reduce potential non-response bias. The non-response model currently includes region (GOR), a socio-economic indicator (OAC) and the His Majesty's Revenue and Customs (HMRC)-provided wealth index used to identify the wealthiest households. This applies to a new cohort. In older panels, an attrition adjustment was applied, and joiners were incorporated, before calibration.

The final stage of the weighting procedure calibrates the adjusted weights from the first stages to known population totals present at the time of the fieldwork period. These estimates are now derived from Census 2021 for England and Wales and the 2022 Census for Scotland. Different sets of weights are created so that analysis can be performed both longitudinally (person-level) and cross-sectionally (household-level and person-level) on the data.

Notably, tenure has been introduced as an additional control variable in the final calibration step of the weighting pipeline for Round 8. This was introduced to counteract the increased selection bias in the achieved sample - where renters were under-represented and those who own outright were over-represented, likely because of changes in fieldwork. For further detail, see our Impact of COVID-19 on ONS social survey data collection methodology. With this adjustment, the estimate for median Household total wealth in GB is approximately 13% lower when compared with a weighting scheme without the tenure calibration control.

The adjustments to the weighting scheme help improve the overall representativity of Round 8 at the GB level. However, it remains unlikely that the weighting scheme will fully compensate for all imbalances in the sample introduced during the coronavirus (COVID-19) pandemic. For example, the inclusion of tenure to correct for under-representation of renters is likely to have a greater impact on London-based estimates where over 50% of households are renters (compared with the England average of 38% of households who rent).

Furthermore, the weighting scheme is also unlikely to account for unusual household circumstances resulting from the coronavirus pandemic, such as where people were more likely to relocate or change household composition temporarily.

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7. Other information

More information on the methods used to compile the output can be found in Chapter 10, Technical details, in the Wealth in Great Britain, Main Results from the Wealth and Assets Survey, 2006 to 2008 (PDF, 820KB)and Chapter 4 in the Wealth in Great Britain Wave 2, 2008 to 2010 (Part 1).

Statistical disclosure control methodology is applied to Wealth and Assets Survey (WAS) data. This ensures that information attributable to an individual or individual organisation is not identifiable in any published outputs. The Code of Practice for Official Statistics and specifically the Principle on Confidentiality set out practices for how we protect data from being disclosed. The principle includes the statement that Office for National Statistics (ONS) outputs should "ensure that official statistics do not reveal the identity of an individual or organisation, or any private information relating to them, taking into account other relevant sources of information".

More information can be found in the Privacy and data confidentiality methods: a Data and Analysis Method Review (DAMR) and on the disclosure control policy for social survey microdata page.

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8. Cite this methodology

Office for National Statistics (ONS), released 24 January 2025, ONS website, Quality and Methodology Information report, Wealth and Assets Survey QMI

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Manylion cyswllt ar gyfer y Methodoleg

Wealth and Assets Survey team
wealth.and.assets.survey@ons.gov.uk
Ffôn: +44 2071 120178