|What it measures||Estimates of the structure and distribution of earnings and paid hours for employee jobs|
|Sample size||180,000 employee jobs|
|Periods available||2004 to 2018 (Annual Survey of Hours and Earnings including supplementary surveys) |
1997 to 2004 (Annual Survey of Hours and Earnings excluding supplementary surveys)
1970 to 2003 (New Earnings Survey unweighted estimates)
|Sample frame||HM Revenue and Customs Pay As You Earn system|
|Sample design||1% simple random sample with a longitudinal element|
|Weighting||Employee jobs are weighted to population totals taken from the Labour Force Survey based on classes defined by occupation, region, age and sex|
|Imputation||Donor imputation carried out for missing data items on partial returns; no non-responder imputation carried out|
|Outliers||No outlier treatment; all validated values are used in estimates|
|Last revised||25 October 2018|
This quality and methodology report contains information on the quality characteristics of the data (including the five European Statistical System 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 user of the data
reduce the risk of misusing data
help you to decide suitable uses for the data
understand the methods used to create the data
The Annual Survey of Hours and Earnings (ASHE) provides information about the levels, distribution and make-up of earnings and hours paid for employees by sex, and full-time and part-time working.
Estimates are available for various breakdowns including industries, occupations, geographies and age groups within the UK.
ASHE is used to produce hours and earnings statistics for a range of weekly, annual and hourly measures.
ASHE is the official source of estimates for the number of jobs paid below the national minimum wage and is also used to produce estimates of the proportions of jobs within workplace pension categories.
This quality and methodology information report relates to the Annual Survey of Hours and Earnings (ASHE), conducted by Office for National Statistics (ONS). ASHE is the most comprehensive source of earnings information in the UK.
ASHE replaced the New Earnings Survey (NES) as ONS’s main source of information on earnings in 2004 and brought improvements to the coverage of employees, imputation for item non-response and the weighting of earnings estimates.
ASHE is based on a 1% sample of employee jobs taken from HM Revenue and Customs (HMRC) Pay As You Earn (PAYE) records. Information on earnings and hours is obtained from employers and treated confidentially. ASHE does not cover the self-employed nor does it cover employees not paid during the reference period. Results are published annually via the ONS website.
Information relating to ASHE outputs, methodology and uses can be found on the guidance and methodology page.
There have been changes to the ASHE methodology over the years, which have resulted in breaks in the series in 2004, 2006 and 2011. These changes are described in section 5 of the ASHE and AWE comparison article.Back to table of contents
This report provides a range of information that describes the quality of the output and details any points that should be noted when using the output.
We have developed Guidelines for Measuring Statistical Quality; these are based upon the five European Statistical System (ESS) Quality Dimensions. This report addresses these quality dimensions and other important quality characteristics, which are:
- timeliness and punctuality
- coherence and comparability
- output quality trade-offs
- assessment of user needs and perceptions
- accessibility and clarity
More information is provided about these quality dimensions in the following sections.Back to table of contents
(The degree to which the statistical outputs meet users’ needs.)
Through consultation with the Annual Survey of Hours and Earnings (ASHE) user base, it has been established that ASHE data meet a vast and diverse range of user needs throughout government, professional organisations and the wider public.
Some examples of government uses, for which the department has confirmed that ASHE data are fit for purpose are:
Labour Market Division, Office for National Statistics (ONS) – statistics used in various analyses of conditions in the labour market, feeding into publications
HM Revenue and Customs (HMRC) – various routine uses including investigation of changes to rates of taxation
Department for Work and Pensions (DWP) – analysis of pension scheme membership, contributions and persistency of saving for policy development, monitoring and evaluation
Department for Business, Energy and Industrial Strategy (BEIS) and the Low Pay Commission (LPC) – data used in review body remits to analyse pay comparability; data used for low pay and National Minimum Wage (NMW) and National Living Wage (NLW) briefing, policy analyses and analyses of annual leave, agency workers and pay generally; data used to analyse the structure of earnings, monitor the impact of NMW and NLW, and recommend future rates
Office of Manpower Economics (OME) – data used in the provision of services to public sector pay review bodies and the Police Negotiating Board, which make recommendations to government on pay for public sector workers, with an estimated pay bill in excess of £100 billion (figure correct at 2018)
Department of Health (DH) – data used to estimate wage differentials at primary care trust level and feed into NHS funding; ASHE data are used in the process by which £115 billion is allocated to local health authorities (figure correct at 2018)
Some examples of non-government uses, for which users have confirmed that ASHE data are fit for purpose are:
- trade unions – statistics used to support pay negotiations
- media – statistics covered widely in various media organisations on television, radio, in newspapers and online
- legal – figures used to inform judgements about payments for loss of earnings or where home care is required
- academia – data used in a range of economic and labour market research
Users have said that the primary strengths of the ASHE dataset and the associated suite of outputs are:
- size and coverage – the ASHE dataset contains information on approximately 180,000 jobs in all industries, occupations and regions, making it the most comprehensive source of earnings information in the UK and enabling a vast range of analyses
- quality – alternative sources of earnings information such as the Labour Force Survey (LFS) rely on self-report or proxy data, which are known to be less reliable than information from employers’ administrative systems
- uniqueness – for many uses, ASHE is the main data source and for some uses it is the only data source
Users have said that the primary weaknesses of the ASHE dataset and the associated suite of outputs are:
- lack of personal demographic information such as ethnicity, religion, education, disability and pregnancy
- timing and periodicity – for some users, more regular and timely results would be beneficial
- ASHE does not cover the self-employed
- the quality of estimates at low levels of disaggregation can be poor
A summary of consultations about the relevance of the ASHE data and outputs is included in the Other information section.
Timeliness and punctuality
(Timeliness refers to the lapse of time between publication and the period to which the data refer. Punctuality refers to the gap between planned and actual publication dates.)
The survey reference date for ASHE is in April of each year. Provisional results for ASHE and low pay, which contains estimates for the number of jobs paid below the national minimum wage, are published in November of the same year and revised results are published in November of the following year. (The ASHE workplace pensions statistics are published in February in the following year. ASHE releases usually meet target publication deadlines, though there have been some exceptions to this where it has been necessary to delay publication by a few weeks in order for ONS to undertake additional quality assurance.)
For more details on related releases, the GOV.UK 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 Statistics.Back to table of contents
Sampling and data collection
The survey uses a random sample of 1% of all employee jobs from HM Revenue and Customs’s (HMRC’s) Pay As You Earn (PAYE) system, taken in January of the reference year. The sample is drawn in such a way that many of the same individuals are included from year to year, thereby allowing longitudinal analysis of the data.
The sample is matched against the Office for National Statistics’s (ONS’s) Inter-Departmental Business Register (IDBR) in order to obtain contact and address details for the employers. Information on the hours paid and earnings of employees is obtained from employers and treated confidentially.
The survey has a reference date in April and asks about individuals who were employees at that time. The reference date changes each year depending on when Easter falls. A second extract is taken from the PAYE system in April in order to identify people who have either joined the labour market or changed jobs since the January sample was taken.
ONS has a special arrangement with some very large employers for them to provide electronic returns extracted from their employee records in April. These employees are selected on the same basis as the regular Annual Survey of Hours and Earnings (ASHE) sample.
Since ASHE is a survey of employee jobs, it does not cover the self-employed or any jobs within the armed forces. Given the survey reference date in April, the survey does not fully cover certain types of seasonal work, for example, employees taken on for only summer or winter work.
Validation is carried out on returned data that is regarded as incomplete or potentially inaccurate, based on automatic comparisons with data for similar jobs or against data for the same job in previous years. In these cases, respondents may be re-contacted by ONS in order to verify the information that has been provided.
Returned data are weighted to UK population totals from the Labour Force Survey (LFS) based on classes defined by occupation, region, age and sex. There are two processes involved in the weighting of responses for ASHE.
The first allocates individual cases a design weight to adjust for non-response. For this purpose, responses are treated as being in one of four strata, depending on whether they were part of the original questionnaire despatch, one of the later supplementary surveys or have a special arrangement in place with ONS to return their data electronically.
For the second part of the weighting, the final file of responses is post-stratified to population estimates taken from the LFS in 108 post-strata. These post-strata are defined as a cross- classification of:
- occupation (nine groups) – major groups from Standard Occupational Classification 2010
- age-band (three groups) – 16 to 21 years, 22 to 49 years and 50 years and over
- sex (two groups) – male and female
- region (two groups) – London and South East, and the rest of the UK
In order to produce estimates for the number of jobs falling below the National Minimum Wage, the dataset is re-weighted to exclude employees whose earnings were affected by absence during the reference pay period.
Since the introduction of weighting for ASHE data, the problem of item non-response (that is, where a questionnaire is returned by a respondent, but in an incomplete form) has become a significant issue when processing ASHE data. A method of imputation, “donor imputation”, has been adopted. In this process, records with similar characteristics are sought to act as “donors” for missing variables.
Further information relating to ASHE methodology may be found on the Annual Survey of Hours and Earnings methodology and guidance page.
ASHE analyses for weekly and hourly earnings relate to employees on adult rates whose earnings for the survey pay period were not affected by absence. They do not include the earnings of those who did not work a full week, and whose earnings were reduced because of, for example, sickness. ASHE analyses for annual earnings relate to employees on adult rates of pay who have been in the same job for more than one year.
Estimates on the structure and distribution of earnings by a range of different breakdowns covering sex, occupation, industry, age and geography are produced from the survey. ASHE data are also used to produce estimates on the number of jobs paid below the National Minimum Wage and a range of statistics on membership of workplace pension schemes.
Statistical disclosure control
Statistical disclosure control methodology is applied to all outputs produced from ASHE. This ensures that information attributable to an individual or individual organisation is not identifiable in any published outputs. The Code of Practice for Statistics and, specifically, the pillar on trustworthiness, sets out principles for how we protect data from being disclosed. The pillar includes as part of principle T6.4: “Organisations should be transparent and accountable about the procedures used to protect personal data when preparing the statistics and data…appropriate disclosure control methods should be applied before releasing statistics and data...”
Firstly, to protect individual earnings data, a frequency count is taken and all cells that are based on a count of fewer than three individuals are suppressed. Secondly, to protect employers’ pay information, a dominance rule is applied within each cell, which uses the contribution from the largest employer and the overall standard error of the estimate to deduce whether information about the employer can be derived to any accuracy.
Given the nature and complexity of ASHE outputs it is not possible to use a practical method to check for issues of secondary suppression. Instead, ASHE applies a policy where no sample counts are released, only weighted sample counts rounded to the nearest 1,000. This gives users enough information about the sample size for a cell for them to make quality inferences, without giving sufficient information to derive data by difference with any degree of certainty. Although in some circumstances a figure can be derived by difference, it would be impossible to tell how many individuals contributed to the figure.Back to table of contents
(The degree of closeness between an estimate and the true value.)
Estimates from this survey are subject to various sources of error. Total error consists of two elements, the sampling error and the non-sampling error.
This occurs because estimates are based on a sample rather than a census. ASHE estimates this error through coefficients of variation (cv) which are published alongside all ASHE outputs. The cv is the ratio of the standard error (se) of an estimate to the estimate itself, expressed as a percentage. Generally, if all other factors are constant, the smaller the cv the higher the quality of the estimate.
In published tables the Annual Survey of Hours and Earnings (ASHE) uses colour coding as a quick reference guide to the cv of the estimates; estimates with cvs less than or equal to 5% are published with no colour fill; estimates with cvs between 5% and 10% are published with a light green background; estimates with cvs between 10% and 20% are published with a dark green background; cells for which estimates have been suppressed on quality or disclosure grounds are also filled in dark green.
High-level coefficients of variation for the 2017 ASHE estimates are shown in Table 1.
|Median gross weekly earnings||Men||0.3||0.3||1.1|
|Median gross hourly earnings (excluding overtime)||Men||0.2||0.3||0.6|
Download this table Table 1: Coefficients of variation for estimates of median gross weekly earnings and hourly earnings (excluding overtime), UK, April 2017.xls .csv
It should be noted that at low levels of disaggregation, high coefficients of variation imply estimates of low quality. For example, for an estimate of £400 with a cv of 10%, the true value is likely to lie between £321.60 and £478.40. This range is given by the estimate plus or minus 1.96 multiplied by the se. Where these ranges for different estimates overlap, interpretation of differences between the relevant domains becomes more difficult.
ASHE statistics are also subject to non-sampling errors. For example, there are known differences between the coverage of the ASHE sample and the target population (that is, all employee jobs). Jobs that are not registered on Pay As You Earn (PAYE) schemes are not surveyed. These jobs are known to be different from the PAYE population in the sense that they typically have low levels of pay.
Consequently, ASHE estimates of average pay are likely to be biased upwards with respect to the actual average pay of the employee population. Non-response bias may also affect ASHE estimates. This may happen if the jobs for which respondents do not provide information are different from the jobs for which respondents do provide information. For ASHE, this is likely to be a downward bias on earnings estimates since non-response is known to affect high-paying occupations more than low-paying occupations.
Finally, ASHE results tables do not account for differences in the composition of different “slices” of the employee workforce. For example, figures for the public and private sectors include all jobs in those sectors and are not adjusted to account for differences in the age, qualifications or seniority of the employees or the nature of their jobs, all factors that may affect how much employees earn.
Various procedures are in place to minimise errors in returned data. Returns undergo a range of checks that include validation against previous returns and expected values, selective editing (a technique for prioritising suspicious values for follow-up based on their impact on published results) and re-contacting businesses for verification. Similar checks are also made at the aggregate level for main results.
Provisional results are published during the October following the survey reference date. Revised results are then published one year later alongside the following year’s provisional results. The revised results take account of late returns to the survey and amendments to data resulting from validating returns to the current year’s survey.
Revisions are usually quite small, with revision at the UK level typically around 0.1%. However, estimates for domains with smaller sample sizes are susceptible to larger revisions.
Coherence and comparability
(Coherence is the degree to which data that are derived from different sources or methods, but refer to the same topic, are similar. Comparability is the degree to which data can be compared over time and domain, for example, geographic level.)
The AWE statistics, based on the Monthly Wages and Salaries Survey (MWSS) of about 9,000 employers, is the lead measure of short-term changes in average earnings in Great Britain. Figures are available with industrial breakdowns, and public and private sector splits. No information is available on occupation, hours worked and other characteristics of the workforce.
The AWE and ASHE are not directly comparable on all measures of earnings. The closest measure that can be derived and compared for these surveys is for mean gross weekly pay in Great Britain. In the year to April 2017, the ASHE estimate of mean gross weekly pay for all employees (regardless of whether they worked full-time or part-time) was £539, up 2.6% on the previous year. The corresponding estimate from the AWE was £503, up 1.3% from April 2016.
The Labour Force Survey (LFS) collects information on the earnings, and normal and actual hours worked of about 15,000 people aged 16 years and over each quarter. In addition it collects data on a wide range of personal characteristics, including education level and ethnic origin.
This information is collected from the employees by means of a household survey. Consequently, there are a number of important differences between LFS and ASHE since ASHE data usually come directly from company records. This means that ASHE collects the actual amounts paid and the number of hours that the employee has been paid for. It classifies the employee’s industry from the business perspective, which in the case of ASHE is the main business of the enterprise. In addition, descriptions of individuals’ occupations are provided by the business.
In contrast, LFS data are collected from the employee, or a member of the employee’s household. This can lead to proxy and estimated responses, for example, if someone responds on behalf of a partner who is not available at the time. This enables the production of statistics on levels and distribution of earnings similar to those from ASHE but with lower precision because of the much smaller sample size and less reliable data collection methods (since self-report and proxy data are not as reliable as data from employers’ administrative systems).Back to table of contents
(Concepts and definitions describe the legislation governing the output and a description of the classifications used in the output.)
Respondents are required by law to provide information for the Annual Survey of Hours and Earnings (ASHE) in accordance with the Statistics of Trade Act 1947.
As well as their use in a range of National Statistics on earnings, low pay and workplace pensions membership, the data are also the primary source for the UK results for the European Labour Costs Survey (LCS) and the European Structure of Earnings Survey (SES), which are required under regulation to Eurostat, the European statistical agency.
ASHE uses the principal UK coding schemes for classifying occupation and industry. Occupations are coded using the Standard Occupational Classification: SOC 2010 and industry using the Standard Industrial Classification 2007: SIC 2007.Back to table of contents
Assessment of user needs and perceptions
(The processes for finding out about uses and users, and their views on the statistical products.)
Office for National Statistics (ONS) has established a survey user group, which meets annually and includes representatives from 23 teams in 17 government departments. This group discusses changes to the questionnaire, methodology and survey outputs. ONS also meets with some of these users as and when necessary.
We conducted a triennial review of the Annual Survey of Hours and Earnings (ASHE) in 2011, which included a user questionnaire. With few exceptions, users said that they regarded the ASHE data and outputs as “good” or better in respect of their accuracy, relevance, timeliness, coherence, comparability and accessibility.
We conducted four strands of research into the uses made of ASHE by non-government users between 2012 and 2013. The outcome of this work is discussed in an article, Non-government uses of ASHE, which was published in March 2013. Feedback from these users indicated that the majority were satisfied or very satisfied with the extent to which ASHE outputs met their needs.Back to table of contents
Accessibility and clarity
(Accessibility is the ease with which users are able to access the data, also reflecting the format in which the data are available and the availability of supporting information. Clarity refers to the quality and sufficiency of the release details, illustrations and accompanying advice.)
Our recommended format for accessible content is a combination of HTML web pages for narrative, charts and graphs, with data being provided in usable formats such as CSV and Excel. Our website also offers 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 refer to the contact details at the beginning of this report.
For information regarding conditions of access to data, please refer to the following links:
In addition to this Quality and Methodology Information, basic quality information relevant to each release is available in the quality and methodology section of the ASHE statistical bulletins and the ASHE pensions statistical bulletin.