Summary of achieved sample size
The achieved sample size for the UK Labour Force Survey (LFS) during January to March 2019 (JM19) was 87,417 individuals in 37,167 households. Please note that there were no NHS households in this period. Compared with the previous quarter, October to December 2018 (OD18), this represents a decrease of 1.4% in household interviews and a decrease of 1.5% in achieved person interviews.
Please note that historical reports can also be accessed.
In January to March 2019 (JM19), main response rates were as follows:
the total response rate for Great Britain excluding imputed cases (Table 2) was 40%; this is down 0.3 percentage points on the previous quarter
the response rate excluding imputed cases (Figure 3) was 54.6% in wave 1 and 33.8% in wave 5; this compares with 53.3% and 34.6% respectively in the previous quarter
the total response rate for Great Britain including imputed cases (Table 3) was 47.4%, down 0.1 percentage points on the previous quarter
of non-response in JM19 (Figure 4), non-contacts comprised 14.4% (down 2.5 percentage points on the previous quarter), circumstantial refusals were 9% (down 0.9 percentage points on the previous quarter), outright refusals comprised 56.4% (up 2.4 percentage points on the previous quarter) and other refusals comprised the remainder
the region with the highest accumulated response rate across the five waves (Table 6) was West Yorkshire (54.8%); the lowest was Inner London (39.6%)
the overall proxy response rate (Table 7) was 33.2%; the highest proxy response rates occur in the 16 to 17 years age group (89.3%), in males (38.4%) and in the non-white ethnicity group (42.3%)
the average income response rate (Table 8) was 85.2%
the data on attrition rates are shown in Table 9; these data reveal in percentage change terms that those who drop out of the survey between waves 1 and 5 are over-represented in the 20 to 29 years age bands, in employees, in households with six or more people, and amongst those living in Inner London
Methodological changes in January to March 2011 (JM11) have impacted response rates. From JM11, a proportion of initial interviews were conducted by the telephone unit rather than face-to-face as an efficiency measure. However, from JM18 onwards all initial interviews have been face-to-face, except for respondents north of the Caledonian Canal (NOC). Telephone interviews generally have higher levels of non-response. The removal of households with residents aged 75 years and over after their initial interview from JS10 also impacts response as these households generally have high response rates. See the Questionnaire changes section for more details.
Changes to State Pension age were introduced in 2010, which affected labour market and LFS publications, as well as other social surveys. Under the Pensions Act 2011, women's State Pension age will increase more quickly (than originally planned) to age 65 years between April 2016 and November 2018. From December 2018, the State Pension age for both men and women started to increase to reach age 66 years by October 2020.
From JS10, households that only contain respondents aged 75 years and over are removed from the sample after their wave 1 interview. This change was introduced to reduce the cost of the survey and reduce the burden on respondents. Households only containing individuals aged 75 years and over are largely economically inactive and therefore the value of interviewing these households is greatly reduced when considering the main aims of the LFS. The wave 1 interviews from aged 75 years and over households will receive a larger weight to make them representative of the UK population. This change results in around a 10% reduction in the household sample size and a 7% reduction in the individual sample size.
From JS10, the treatment of “concealed multi-households” on the LFS has also changed. Previously, if one sampled address turned out on inspection to be, for example, not one house but six flats, all six flats would be recorded as households and interviews would be attempted with each household. The number of households encountered could be in the hundreds. This was not a practical approach. We decided to harmonise the approach to multi-households across all our social surveys. From JS10, if a concealed multi-household is recorded only one household will be randomly selected to be interviewed.
Details of fieldwork issues and new, amended and deleted questions can be found in Section 7.Nôl i'r tabl cynnwys
The degree to which the statistical product meets user needs for both coverage and content.
The primary purpose of the Labour Force Survey (LFS) is "the prompt publication of key aggregate, whole economy, indicators, for the integrated assessment of labour market conditions" (Review of the Labour Force Survey, ONS, 2002). The “labour market” covers all aspects of people's work, including the education and training needed to equip them for work, the jobs themselves, job-search for those out of work and income from work and benefits.
Users and uses
Users of LFS data often combine them with related data from other sources to provide an overall view of the state of the labour market. One of the most important users of this sort of assessment is the Bank of England's Monetary Policy Committee, which sets interest rates to meet the government's inflation target.
Other important users of LFS data are HM Treasury and the Department for Work and Pensions, because they are responsible for UK economic and labour market policy. They are interested in a variety of indicators of the state of the labour market, including the number of people in employment, the number of hours worked and the number of unemployed people (defined according to the International Labour Organisation (ILO)). They often analyse these series by age groups, by regions and by sex. Other government users include the Department for Business, Energy and Industrial Strategy (BEIS), the Home Office, the Health and Safety Executive, the Scottish Government and the Welsh Government.
At the international level, LFS data are used by the European Parliament, Council and Commission, the European Central Bank and DG Employment (Directorate-General for Employment, Social Affairs and Equal Opportunities). They are also used by the Organisation for Economic Co-operation and Development (OECD) and the International Labour Organisation.
Other users include local authorities, the Trades Union Congress (TUC), the Employer's Association, the Confederation of British Industry, the Institute of Employment Studies, the Institute for Public Policy Research, the National Institute of Economic and Social Research, the Policy Studies Institute, the Institute for Fiscal Studies, academic researchers, the media and the general public.
Strengths and limitations
The strengths of the LFS are that it has the largest coverage of any household survey in the UK and can therefore generate statistics for small geographical areas. In addition, the sampling errors are relatively small, as a result of the wave structure and the size of the survey. The survey covers a large range of employment-related variables and non-employment-related variables, allowing cross-linking analyses to be undertaken (for example, earnings against educational attainment).
One of the limitations of the LFS is that the sample design provides no guarantee of adequate coverage of any industry, as the survey is not industrially stratified. The LFS coverage also omits communal establishments, except NHS housing, students in halls of residence and at boarding schools. Members of the armed forces are only included if they live in private accommodation. Also, workers under the age of 16 years are not covered.
The definitions of the three economic activity groups – employed, unemployed and economically inactive – that are used in the LFS are the standard International Labour Organisation (ILO) definitions. It should be noted that although the LFS uses ILO definitions, these definitions are not interpreted and applied in exactly the same way in different countries. For example, although “working age” is a common term, different countries have different statutory school leaving and retirement ages. However, Eurostat collects data from member states and adjusts them to produce comparable estimates.
The closeness between an estimated result and the (unknown) true value.
The main threats to accuracy are sources of error, namely sampling error and non-sampling error, where non- sampling error includes:
- coverage error
- non-response error
- measurement error
- processing error
- model assumption error
Many of the sources of non-sampling error are difficult to measure. However, the LFS publishes detailed response rates for all waves of the survey and an overall response rate, including time series (Tables 2 to 5 and Figures 3 and 4). Response rates are also published by government region for each wave during the particular quarter (Table 6). The LFS also publishes proxy response rates (Table 7), response rates for income questions by National Statistics (NS) Socio-Economic Classification (Table 8) and attrition rates (Table 9).
Surveys, such as the LFS, provide estimates of population characteristics rather than exact measures. In principle, many random samples could be drawn and each would give different results, due to the fact that each sample would be made up of different people, who would give different answers to the questions asked. The spread of these results is the sampling variability, which generally reduces with increasing sample size. A confidence interval is a range of values, defined by a lower and upper bound, which indicates the variability of an estimate. Statistical methods are used to calculate the sampling variability from which the confidence interval can be determined. For example, with a 95% confidence interval, it is expected that in 95% of the survey samples, the resulting confidence interval will contain the true value that would be obtained by surveying the whole population.
The LFS routinely publishes details of achieved sample sizes in terms of achieved number of household and person interviews (Table 1 and Figures 1 and 2) and sampling variability for estimates of main variables. Sampling variability (95% confidence intervals) can be found in the Sampling variability section (Table A11) of the Labour market statistical bulletin.Nôl i'r tabl cynnwys
|Includes imputed||Excludes imputed||Includes imputed||Excludes imputed|
|Individuals in private households||80,849||65,688||87,417||71,844|
|Individuals in NHS households||0||0||0||0|
Download this table Table 1: Great Britain and UK, achieved sample by type of household, January to March 2019.xls .csv
Nôl i'r tabl cynnwys
|Refusal to HQ||800||5.2||772||5.4||945||6.6||962||6.7||866||6.1||4345||6.0|
|Refusal to re-interview||n/a||n/a||561||3.9||797||5.6||975||6.8||1017||7.1||3350||4.6|
Download this table Table 2: Wave-specific response rates, Great Britain, January to March 2019, excluding imputed households.xls .csv
Download this table Table 3: Wave-specific response rates, Great Britain, January to March 2019, including imputed households.xls .csv
Download this table Table 4: Wave-specific response rates, UK, January to March 2019, excluding imputed households.xls .csv
|Refusal to HQ||833||5.1||782||5.1||951||6.2||966||6.2||869||5.7||4401||5.6|
|Addresses not |
Download this table Table 5: Wave-specific response rates, UK, January to March 2019, including imputed households.xls .csv
|Tyne & Wear||49.5||53.1||52.5||47.5||43.0||49.1|
|Rest of North East||59.7||62.9||56.6||49.3||41.5||54.1|
|Rest of North West||55.8||51.3||47.2||43.0||40.9||47.7|
|Rest of Yorkshire|
|West Midlands |
|Rest of West|
|East of England||55.2||52.6||46.3||44.0||42.1||48.2|
|Rest of Scotland||58.1||56.8||48.6||41.2||40.3||49.1|
Download this table Table 6: Wave-specific response rates, January to March 2019, including imputed households, by region.xls .csv
|Unpaid family workers||175||36||20.6|
Download this table Table 7: Proxy response, Great Britain, January to March 2019.xls .csv
|Wave 1 in JM19||Wave 5 in JM19||Total|
|Higher managerial and professional||87.5||89.1||88.1|
|Lower managerial and professional||85.9||88.3||86.8|
|Small employers and own account workers||81.8||87.5||84.2|
|Lower supervisory and technical||84.3||84.9||84.5|
Download this table Table 8: Income response rates by National Statistics Socio-economic Classification (NS-SEC), Great Britain, January to March 2019.xls .csv
|UPFW(Unpaid Family Workers)||0.2||0.2||0.2||0.2|
|Number of people in household||1||9.6||12.0||15.7||7.8|
|6 or more||4.8||3.3||1.9||6.0|
|Region||Tyne & Wear||2.2||2.3||2.3||2.2|
|(GOVTOR)||Rest of North East||2.4||2.3||1.7||2.5|
|Rest of North West||5.2||5.3||5.5||5.0|
|Rest of Yorkshire and Humberside||3.1||3.5||3.7||2.8|
|West Midlands Metropolitan Council||4.5||4.7||4.4||4.3|
|Rest of West Midlands||5.1||5.5||5.2||4.8|
|East of England||9.7||10.5||11.3||9.1|
|Rest of Scotland||5.1||4.8||5.3||5.4|
Download this table Table 9: Summary of attrition by main characteristics, Great Britain, January to March 2019.xls .csv
Timeliness refers to the lapse of time between publication and the period to which the data refer. Punctuality refers to the time lag between the actual and planned dates of publication.
To ONS Labour Market Division (LMD)
Scheduled delivery date for file: 18 April 2019.
Achieved delivery date for file: 18 April 2019.
Time lag between achieved delivery date and the end of the reference period: 18 days.
Data file for other users
Scheduled availability date for regional public and government normal release user files: 15 May 2019.
- Bank of England
- Department for Business, Energy and Industrial Strategy
- Ministry of Housing, Communities and Local Government
- Department for Education
- Department for Enterprise, Trade and Investment (Northern Ireland)
- Department for Digital, Culture, Media and Sport
- Department for Transport
- Department for Work and Pensions
- Department of Finance and Personnel (Northern Ireland)
- Economic and Social Research Council and Data Archive
- Health and Safety Executive
- HM Treasury
- Home Office
- Low Pay Commission
- Office for Standards in Education
- Office of Manpower Economics
- Scottish Government and Scottish Executive
- Small Business Service
- Welsh Government
Accessibility is the ease with which users are able to access the data, also reflecting the format(s) in which the data are available and the availability of supporting information. Clarity refers to the quality and sufficiency of the metadata, illustrations and accompanying advice.
The UK Data Archive at Essex University provides free access to the various Labour Force Survey (LFS) datasets.
A highly disaggregated dataset, which covers a wealth of data for local areas, is available free from NOMIS.
Labour market data, including data from the LFS, are published every month through statistical bulletins. These include text, tables and charts. Data contained within the bulletins are available to download, free of charge.
For questions relating to labour market statistics, please contact: email@example.com
For general queries about the LFS, please contact: firstname.lastname@example.orgNôl i'r tabl cynnwys
Comparability is the degree to which data can be compared over time and domain.
The Labour Force Survey (LFS) began in 1973 and was carried out every two years until 1983. Between 1984 and 1991, data were collected annually and the survey has been running in its present form, with quarterly sampling, since spring 1992. It is carried out under European Union regulations, which specify the way in which the survey should be conducted, the quality of the results that member states supply to Eurostat and the timetable for supplying results. Although the LFS began as a survey designed to meet international obligations, its primary purpose is now (as stated in Section 2, Relevance), "the prompt publication of key aggregate, whole economy, indicators, for the integrated assessment of labour market conditions" (Review of the Labour Force Survey, ONS, 2002).
The definitions of the three economic activity groups – employed, unemployed and economically inactive – which are used in the LFS are the standard International Labour Organisation (ILO) definitions.
Economically active – those aged 16 years or over, who are either employed or unemployed in the survey reference week.
Employed – those aged 16 years or over, who are regarded as in employment if they did at least one hour of work in the reference week (as an employee, self-employed, unpaid workers in a family business or participants in government-supported training schemes) and those who had a job that they were temporarily away from (for example, if they are on holiday).
Unemployed – those aged 16 years or over, who are without work, want a job, have actively sought work in the last four weeks and are available to start work in the next two weeks; or are out of work but have found a job and are waiting to start it within the next two weeks.
Economically inactive – those who are neither in employment nor unemployed. This group includes, for example, all those who are looking after a home or family, have a long-term illness or disability that prevents them working or are retired.
Unpaid family workers – those who are doing unpaid work in a family business.
New questions for January to March 2019 (JM19) were: Unpaid carers – UPCareA1; UPCareA2; National Statistics Socio-economic Classification (NS-SEC) – NSSECInt; PaySca; Notice; NotOth; Ladder; Includ; Ad-hoc module 2019 – Intro19; Intro19b; Variwt1a; Variwt1b; Freehou1; Freelea1; Flexwt1; Avaifre1; Avaifre2; Rechour1; Rechour2; Pressure1; Jobauto1; Jobauto2; Placewk1; Commutm1; Otherlo1; Otherlo2; AHM19ETQ.
Changes to existing questions for JM19
YLESS6 and YPAYL – “Other – please specify” option added; YerQal3 – levels added to GCSE option.
Changes to signals or checks
There were no changes to signals or checks for JM19.
Deleted questions for JM19 were: Veterans questions – variables include: VETSERV, VETCURR, VETYRLFT1, VTYRLFT2, VTYRLFT3 and VLFT2CHK. They were located after the INTUSE on Internet use. The reason for removing these is that customers have withdrawn their funding.
The quarterly specific questions for JM19 were: Accidents at work – ACCDNT; ROAD; WCHJB; GOBCK9; TIMEDAYS; TIMECODE; TYPINJ; SITEFR; SITEDI; ACCURH; ACCKIND; ILLWRK; NUMILL; TYPILL; AWARE; TMEOFF; ILCURR; WCHJB3; REASOFF9; NOBACK9; Training – EDIns11; TSTE10; TFEE10; TrnLen; Full time / part time and availability to start work – AXPB; AXFB; FWkWen; Internet use – INTUSE.
There were no amended questions for JM19.
Fieldwork and operational changes
There were no significant field work issues for this period. A timeline of recent incentive and operational changes that may have had an impact on response is outlined:
June 2017 – Introduction of £5 and £10 incentives randomly allocated across the sample
January 2018 – Around 10 to 15% of the wave 1 sample moved from telephone operations to face-to-face
April 2018 – Introduction of new administrative systems for recording field time and expenses
June 2018 – Changes to advance materials and procedures due to the introduction of the General Data Protection Regulation
July 2018 – Change of incentive type from a paper voucher to a card voucher
October 2018 – Launch of a new fieldwork management tool for use in face-to-face mode
March 2019 – Issues with the telephony system used for some cases in waves 2 to 5 resulted in poor connectivity, which may impact response rates
See Section 1 for full details of methodological changes; in January and March 2011 (JM11) a change was implemented to move some wave 1 interviews into the telephone unit, rather than being face-to-face interviews as would normally be the case. Wave 1 interviews are now taking place face-to-face (from JM18) and there are no longer wave 1 interviews in the Telephone Unit, except for respondents north of the Caledonian Canal (NOC).Nôl i'r tabl cynnwys
Coherence is the degree to which data that are derived from different sources or methods, but which refer to the same phenomenon, are similar.
The Labour Force Survey (LFS) is one of a number of sources of data about the labour market. Some sources provide data that overlap with LFS data on employment, unemployment and earnings. The Office for National Statistics (ONS) has published guidance about the strengths and limitations of each source in relation to these topics and has indicated which source is the most appropriate for different purposes. Details can be found in the Labour market guide.
Employment, unemployment and economic inactivity
The LFS is the source recommended by the ONS for certain employment-related statistics (for example, estimates of the number of people in employment or unemployed). The LFS is also a unique source of comprehensive, coherent information about economic inactivity, where it provides information separately about people who want a job and those who do not.
Number and industrial composition of jobs
The workforce jobs (WFJ) series provides estimates of the number of jobs in the UK economy and is the source recommended by the ONS for both the number of jobs and the industrial composition of jobs. Workforce jobs consist of the sum of employee jobs, self-employment jobs, jobs in the armed forces and government-supported trainees. Civilian workforce jobs are available by geographical region, sex and broad industry. Total workforce jobs are available by sex and broad industry.
For estimates of change in earnings (for example, pay growth in the economy), a non-LFS source, the Average Weekly Earnings (AWE) (formerly the Average Earnings Index (AEI)) is the most suitable source. It provides industry and whole-economy information, but excludes small employers, the self-employed and government- supported trainees. Pay, commission, bonuses, overtime and pay award arrears are included, but redundancy payments and benefits in kind are excluded.
The Annual Survey of Hours and Earnings (ASHE) includes information about the levels, distribution and make-up of earnings and hours worked for employees in different occupations, industries, ages and regions. It should be used when the information required is not available from the AWE (such as for occupational groups, or regional analyses) and is the preferred source of the earnings of full-time employees, and of the average hourly earnings of all employees. The LFS should be used when the information is not available from the AWE or from ASHE and is the preferred source of data about the earnings of part-time and low-paid employees. There is an ONS guide to sources of data on earnings and income.Nôl i'r tabl cynnwys
The Labour Force Survey (LFS) covers private households, including persons who are temporarily absent. The resident population comprises persons who regard the sample address as their main address and also those who have lived in the dwelling for more than six consecutive months, even if they do not regard this as their principal dwelling. Persons absent for more than six months are not regarded as members of the resident population.
A private household comprises of one or more persons (not necessarily related) living at the same address who share cooking facilities and share a living room or sitting room or dining area. Students living in halls of residence and pupils at boarding school are sampled through the private households of their parents. In Great Britain, an additional sample is drawn from persons living in National Health Service accommodation.
The year is divided into quarters of 13 weeks. Prior to January 2006, these were seasonal quarters: winter (December to February), spring (March to May), summer (June to August) and autumn (September to November). From January 2006, the LFS has been conducted on the basis of calendar quarters: Quarter 1 – January to March, Quarter 2 – April to June, Quarter 3 – July to September and Quarter 4 – October to December.
For most of Great Britain, the survey base is the Royal Mail's PAF (Postcode Address File), a database of all addresses receiving mail. The list is limited to addresses receiving fewer than 25 items of post per day, so as to exclude businesses. Because of the very low population density in the far north of Scotland (north of the Caledonian Canal), telephone directories are used as sampling frames and interviews are carried out by telephone because face-to-face interviews would be too expensive. In Northern Ireland POINTER, which is the government's central register of domestic properties, is used.
In Great Britain, a systematic sample is drawn each quarter from the three sampling bases, yielding 16,640 PAF addresses, 75 telephone numbers for the north of Scotland and 36 units of National Health Service housing. As the PAF is broken down geographically, the systematic sampling ensures that the sample is representative at regional level. In Northern Ireland, a simple random sample is drawn, each quarter, from each of three strata, giving 650 addresses in all.
A rotation system comprising five waves is used. Respondents are interviewed five times at 13-week intervals and one-fifth of the sample is replaced each quarter. Interviews are carried out on a face-to-face (CAPI) or telephone (CATI) basis with the help of portable computers for the interviews in the first wave. In the far north of Scotland (north of the Caledonian Canal) and for interviews in the second to fifth waves, wherever possible, interviews are carried out by telephone.Nôl i'r tabl cynnwys
If a household (or someone within a household) is unavailable for interview, but was interviewed in the previous wave, responses from the previous wave are rolled forward. This is referred to as “imputation”. Imputation is carried out to minimise non-response bias in estimates, while simultaneously improving precision by boosting the sample size. The rationale is that most Labour Force Survey (LFS) variables do not change from one quarter to another for most people. Responses are rolled forward for one wave only. Data are not rolled forward after a second consecutive non- response. Tables and charts (at person or household level) containing responses that have been rolled forward from the previous wave are denoted by the term “including imputed”. Tables and charts that do not contain responses that have been rolled forward from the previous wave are denoted by the term “excluding imputed”.
Method of calculating sampling variability
The sampling variability is the spread of results that would be obtained if different samples were drawn. A confidence interval is a range of values, defined by a lower and upper bound, which indicates the variability of an estimate. Statistical methods are used to calculate the sampling variability from which the confidence interval can be determined. For example, with a 95% confidence interval, it is expected that in 95% of the survey samples, the resulting confidence interval will contain the true value that would be obtained by surveying the whole population.
Method of calculating response rates
The response rate indicates how many interviews were achieved as a proportion of those eligible for the survey. The formula used is as follows:
RR equals (FR plus PR) divided by (FR plus PR plus OR plus CR plus RHQ plus NC plus RRI*)
where RR is response rate, FR is full response, PR is partial response, OR is outright refusal, CR is circumstantial refusal, RHQ is refusal to HQ, NC is non-contact, RRI is refusal to re-interview, and the asterisk (*) applies to waves 2 to 5 only.
Definitions of response outcome categories
A full response denotes a household in which each household member has answered all applicable questions.
A partial response denotes a household in which questions were not completed because someone refused to be interviewed, refused part way through the questionnaire or refused to let someone else answer on his or her behalf. However, at least one question block must have been completed. If only part of the information has been collected for a one-person household, it is coded as a refusal or non-contact.
An outright refusal is a household that refuses to respond to the survey and the interviewer feels that there is no chance of an interview at the current or in any future wave.
A circumstantial refusal is a household where the respondent refuses to respond because of a temporary circumstance (for example, going on holiday, too busy during the field period). A circumstantial refusal enables an interviewer to call back at the next wave.
A refusal to HQ is a household that contacts headquarters to refuse to participate in the survey in response to the advance letter.
A non-contact arises when an address is occupied, but where it has not been possible to contact any member of the household in the field period.
A refusal to re-interview is a household that takes part in the survey (at one or more of waves 1 to 4) but which, when asked to take part in the next wave (waves 2 to 5), refuses.
Method of calculating income response rates
The income question is asked at wave 1 and wave 5 only. Individuals aged 16 to 69 years who are in employment in the reference week, form the sub-set of respondents who are eligible for these questions. The percentage response rates for the income questions are based on all eligible, in-scope respondents at wave 1 and all eligible, in-scope respondents at wave 5. The total response rate is the aggregate response rate for income for the quarter (wave 1 and wave 5), based on all eligible, in-scope respondents.
NS-SEC is the National Statistics Socio-economic Classification, which replaces previous classifications that were based on social class and social and economic group.
The LFS has to complete fieldwork to a tight timetable and interview as many of the sampled households as possible, which leaves limited time for recalls. LFS interviewers try to interview every adult (aged 16 years and over) in each sampled household. However, when a household member is unavailable for interview, interviewers accept information by proxy from another responsible adult in the household. The proxy respondents are normally people living with a partner on behalf of their partner and parents on behalf of their adult offspring who live with them.
Attrition is the term applied to respondents who begin the survey but subsequently drop out. It has been known for some time that these respondents tend to have different characteristics to those who remain in all waves of the survey, which can, therefore, result in attrition bias. For example, if respondents in a particular age band have a higher tendency to drop out (attrition rate) than respondents in other age bands, then they will be under- represented in subsequent waves of the survey and in estimates.Nôl i'r tabl cynnwys