1. Executive summary October to December 2020

Summary of achieved sample size

The achieved sample size for the UK Labour Force Survey (LFS) during October to December 2020 (OD20) was 74,832 individuals in 33,685 households. Please note that there were no NHS households in this period. Compared with the previous quarter, Quarter 3 (July to Sept 2020), this represents an increase of 8.9% in household interviews and an increase of 7.8% in achieved person interviews.

Summary of response rates

Please note that historical reports can also be accessed.

In October to December 2020 (OD20), main response rates were as follows:

  • response rates presented in this report cover the October to December 2020 survey period; Coronavirus (COVID-19) social distancing measures were implemented towards the end of the January to March 2020 quarter and information has been added to this report to inform user understanding

  • the total response rate for Great Britain excluding imputed cases (Table 4) was 26.1%; this is down 1.4 percentage points on the previous quarter

  • the response rate excluding imputed cases (Figure 3) was 28.6% in wave 1 and 27.7% in wave 5; this compares with 26.9% and 28.3% respectively in the previous quarter

  • the total response rate for Great Britain including imputed cases (Table 5) was 29.4%, down 2.3 percentage points on the previous quarter

  • of non-response in OD20 (Figure 5), non-contacts made up 74.3% (up 9.5 percentage points on the previous quarter), circumstantial refusals were 2% (0.7 percentage points down from the previous quarter), outright refusals were 17.8% (down 6.2 percentage points on the previous quarter) and other refusals made up the remainder

  • the region with the highest accumulated response rate across the five waves (Table 8) was "Tyne and Wear" (33.8%); the lowest was Inner London (18.3%)

  • the overall proxy response rate (Table 9) was 35.2%; the highest proxy response rates occur in the 16 to 17 years age group (93.6%), in males (40.6%) and in the non-white ethnicity group (43.9%)

  • the average income response rate (Table 10) was 84.8%

  • the data on attrition rates are shown in Table 11; 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, unemployed, in households with 6 or more people, and among those living in West Midlands Metropolitan Council

  • A breakdown of key characteristic changes have been included in the "Impact of Coronavirus (COVID-19) on the LFS" section

There have been a number of methodological and operational changes that may have affected response rates. More details on these changes are outlined in the Comparability section of the report.

Impact of Coronavirus (COVID-19) on the LFS

Response rates presented in this report cover the October to December survey period. Coronavirus (COVID-19) social distancing measures were implemented towards the end of the January to March quarter. See below for a timeline of events for the Labour Force Survey (LFS):

9 March

  • The public's heightened awareness of coronavirus (COVID19) started to affect participation in LFS.

17 March

  • Wave 1 face-to-face data collection temporarily suspended while systems developed to allow interviewers to conduct telephone interviewing from their homes.

  • Telematching used for north of the Caledonian Canal cases extended to Great Britain to obtain additional telephone numbers for wave 1 cases.

  • LFS waves two to five continued to be conducted via telephone where possible.

23 March

  • Commencement of official UK lockdown measures.

  • Face-to-face interviewers restarted interviewing intermittently using telephone mode. Additional advance materials prepared to allow respondents to contact the interviewers.

30 March

  • Telephone interviewing rolled out fully to face-to-face interviewers.

20 April

  • New online portal put in place to allow improved collection of respondent details.

1 May

  • Unconditional incentive increased to £10 for all wave 1 households.

1 July

  • Wave 1 LFS sample size doubled to account for lower response rates.

Phone contact details for respondents are obtained through different sources. The two main methods in which phone numbers are obtained are through tele-matching and an online portal. Tele-matching phone contact details is achieved by taking sampled addresses and matching details through a database provided by REaD to obtain both landline and mobile phone numbers, which are subsequently provided to interviewers.

Phone contact details obtained through the online portal are achieved by respondents receiving a letter in advance with materials containing information about the study, which have been adapted since the start of the pandemic to reflect the pausing of face-to-face interviews. The advanced letter asks for sampled addresses to enter their name and phone number into the portal, which is then used to contact them. An additional reminder letter has also been developed specifically due to pandemic, to allow interviewers to follow-up on addresses where no phone contact information was obtained via telematching or through the online portal.

Table A shows the percentage of wave 1 respondents with phone numbers by different sources.

Table B shows the split between landline and mobile phone numbers for tele-matched cases from April 2020 to March 2021.

Table C shows the split between landline and mobile phone numbers for portal cases from August 2020 to February 2021.

A text message reminder service was introduced in October 2019. The reminder message is sent to respondents from wave 2 onwards the week before they are due to be interviewed.

From wave 2 onwards, sampled addresses are contacted by telephone interviewers. If a respondent has moved address during the time of the study, the interviewer records that the original respondent no longer lives at the address. This address is then reassigned to a field interviewer for them to make contact with any new occupants at the original address.

Figure 4 demonstrates the impact of these changes on the weekly response rate profile. Response for wave 1 in the first week of July was 17.5%. This increased to 28.4% in the last week in September. It has remained stable since this point.

Respondent characteristics

To identify any potential impact on the estimates, a range of characteristics have been investigated, including age, sex and tenure. The key changes to respondent characteristics are outlined:

  • age - there are a greater proportion of wave 1 respondents aged 65 years and over; 29% in wave 1 in OD20 which has increased throughout the previous quarters (see Table 1)

  • tenure - there are a greater proportion of responding household reference person (HRPs) who own their property outright (48% in wave 1 in OD20, 49% in JS20, and 48% in AJ20) compared to around 37% in the earlier periods looked at and there are fewer responding HRPs who are renting (22% in OD20, 22% in JS20, and 21% in AJ20 compared to around 32% in the other periods) (see Table 2)

  • country of birth - non-UK born respondents comprised, on average, 12.6% of all interviews at wave 1 through 2019. By AJ20 this had fallen to 9%. The average through 2020 was 10.2% (see Figure A)

  • disability - there are a smaller proportion of wave 1 respondents who identified themselves as disabled; 26.5% in OD20 compared to 27.8% in JS20. This has fluctuated through 2020 as 26.4% of respondents in AJ20 and 27.6% in JM20 identified themselves as disabled (see Figure B)

These percentages relate to wave 1 cases. Looking at waves 2 to 5 there is a similar pattern. For waves 2 to 5, 23.4% of respondents aged 65 years and over have continued to increase (23.4% in OD20 and 21.5% in JS20), compared with 19% in the earlier periods (OD19 to AJ20). For waves 2 to 5, 44% of responding HRPs owned their property outright in OD20 and 41% in JS20 compared with around 37% previously (OD19 to AJ20), while 22% rented in OD20 compared with 28% previously (OD19 to AJ20).

For waves 2 to 5, the proportion of non-UK born respondents has continued to decrease (10.3% in OD20 and 10.6% in JS20). The prevelance of disability in waves 2 to 5 is also similar, though with less difference between periods as the first and third quarters (24.7% in JM20, 24.8% in JS20) and second and fourth quarters (23.8% in AJ20, 24.3% in OD20) contain similar prevalence levels.

While some changes in the demographic coverage of the survey would be dealt within the weighting processes, this only covers age, sex and location. In order to mitigate the impact of the non-response bias in the LFS caused by changes to the way people were contacted for initial interviews since March, we have introduced housing tenure into the LFS weighting methodology. While not providing a perfect solution, this has redressed some of the issues that had previously been noted in the survey results. As a result we have moved to using the new tenure weighting from January to March 2020 onwards for all LFS and APS microdata, to help ensure they are produced on a consistent basis. There may also be further refinements to the methodology, such as constraining the tenure weighting within region, that lead to further improvements and revisions in the future. We will continue investigating these options and implement them if they are of sufficiently significant benefit.

More information is available in the Coronavirus and its impact on the Labour Force Survey indicating the work being carried out.

An outline of changes to other ONS surveys during the coronavirus (COVID-19) pandemic is indicated in the Ensuring the best possible information during COVID-19 through safe data collection article.

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2. Summary of quality

Relevance

(The degree to which the statistical product meets user needs for both coverage and content.)

Primary purpose

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, the Office for National Statistics (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 Organization (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 Organisation for Economic Co-operation and Development (OECD) and the International Labour Organisation (ILO).

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 main strengths of the LFS include:

  • it has the largest coverage of any household survey in the UK and can therefore generate statistics for small geographical areas

  • 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)

The main limitations of the LFS include:

  • the sample design provides no guarantee of adequate coverage of any industry, as the survey is not industrially stratified

  • the LFS coverage omits communal establishments, except NHS housing and students in halls of residence and at boarding schools; members of the armed forces are only included if they live in private accommodation and workers aged 16 years and under, are not covered

  • whilst the LFS data are used alongside other sources to feed into the estimates of population change, the main focus of the survey is to collect labour market information and as such is not designed to measure migration flows

Main definitions

The definitions of the three economic activity groups - employed, unemployed and economically inactive - that are used in the LFS are the standard 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.

Accuracy

(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 4 to 7 and Figures 3 and 5). Response rates are also published by government region for each wave during the particular quarter (Table 8). The LFS also publishes proxy response rates (Table 9), response rates for income questions by National Statistics  Socio-economic Classification (NS-SEC) (Table 10), and attrition rates (Table 11).

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, owing 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, that 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 3 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 (Dataset A11) of the Labour market statistical bulletin.

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3. Achieved sample

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4. Response rates

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5. Timeliness and punctuality

(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 the Office for National Statistics (ONS) Labour Market Division (LMD)

Scheduled delivery date for file: 22 January 2021.

Achieved delivery date for file: 22 January 2021.

Time lag between achieved delivery date and the end of the reference period: 22 days.

Data file for other users

Scheduled availability date for regional public and government normal release user files: 23 February 2021.

Recipients

  • Bank of England
  • Department for Business, Energy and Industrial Strategy
  • Ministry for 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
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6. Accessibility and clarity

(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 the University of Essex provides free access to the various Labour Force Survey (LFS) datasets.

NOMIS provide a free but highly disaggregated dataset, which covers a wealth of data for local areas.

The Social Surveys Team provide LFS data for a fee and can be contacted by phone on +441633 455678 or email at socialsurveys@ons.gov.uk.

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 labour.market@ons.gov.uk.

For general queries about the LFS, please contact lfs@ons.gov.uk.

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7. Comparability

(Comparability is the degree to which data can be compared over time and domain.)

Background

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 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 "the prompt publication of key aggregate, whole economy, indicators, for the integrated assessment of labour market conditions" (Review of the Labour Force Survey, Office for National Statistics, 2002).

Definitions

The definitions of the three economic activity groups - employed, unemployed and economically inactive - that are used in the LFS are the standard International Labour Organization (ILO) definitions.

Economically active - those aged 16 years and over, who are either employed or unemployed in the survey reference week.

Employed - those aged 16 years and 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 were on holiday).

Unemployed - those aged 16 years and 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.

October to December 2020 Questionnaire changes

New questions: None

Deleted questions: None

Amended questions: None

Fieldwork and operational changes

A timeline of significant operational changes that may have had an impact on response include:

  • July 2010 -  households with residents aged 75 years and over after are removed after their initial interview from October to December 2010 (JS10). This affects response rates, as these households generally have high response rates. See the Questionnaire changes section for more details.

  • January 2011 - a proportion of initial interviews were conducted by the telephone unit rather than face-to-face as an efficiency measure.

  • June 2017 - Introduction of £5 and £10 incentives randomly allocated across the sample.

  • January 2018 - from January to March 2018 (JM18) onwards all initial interviews have been face-to-face, except for respondents north of the Caledonian Canal (NOCC).

  • 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 telephone system used for some cases in waves 2 to 5 resulted in poor connectivity, which may affect response rates.

  • March 2020 - Social distancing measures were implemented in the UK. Face-to-face data collection paused and all interviewing moved to telephone mode. See Impact of Coronavirus (COVID-19) on LFS Data for more information.

  • May 2020 - Unconditional incentive increased to £10 for all wave 1 households in GB.

  • July 2020 - Wave 1 LFS sample size doubled to account for lower response rates.

  • July 2020 - Northern Ireland moved from unconditional to conditional incentives for waves 1, 2 and 5 and increased the amount from £10 to £20 in wave 1.

Survey Methodology Changes

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, the State Pension age of women was expected to increase more quickly (than originally planned) to aged 65 years between April 2016 and November 2018. From December 2018, the State Pension age for both men and women started to increase, expected 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. 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 would not be 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.

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8. Coherence

(Coherence is the degree to which data that are derived from different sources or methods, but that refer to the same phenomenon, are similar.)

Data sources

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 statistics 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.

Earnings

For estimates of change in earnings (for example, pay growth in the economy), a non-LFS source, the Average Weekly Earnings (AWE) measure (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 the 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.

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9. Summary of methods

The Labour Force Survey (LFS) covers private households, including persons who are temporarily absent. The resident population is made up of persons who regard the sample address as their main address and 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, sitting room or dining area. Students living in halls of residence and pupils at boarding schools are sampled through the private households of their parents. In Great Britain, an additional sample is drawn from persons living in NHS 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)

  • autumn (September to November)

From January 2006, the LFS has been conducted based on calendar quarters:

  • Quarter 1 - January to March

  • Quarter 2 - April to June

  • Quarter 3 - July to September

  • Quarter 4 - October to December

For most of Great Britain, the survey base is the Royal Mail's Postcode Address File (PAF), a database of all addresses receiving mail. The list is limited to addresses receiving fewer than 25 items of post per day, 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. Interviews in the far north of Scotland are also 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 NHS 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 made up of 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.

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10. Technical definitions

Imputation

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

See Summary of quality for information on the method of calculating sampling variability.

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

Full response - a household in which each household member has answered all applicable questions.

Partial response - 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.

Outright refusal - 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.

Circumstantial refusal - a household where the respondent refuses to respond because of a temporary circumstance (for example, going on holiday or being too busy during the field period). A circumstantial refusal enables an interviewer to call back at the next wave.

Refusal to HQ - a household that contacts headquarters to refuse to participate in the survey in response to the advance letter.

Non-contact - when an address is occupied, but where it has not been possible to contact any member of the household in the field period.

Refusal to re-interview - a household that takes part in the survey (at one or more of waves 1 to 4) but that, 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 waves 1 and 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

NS-SEC is the National Statistics Socio-economic Classification, which replaces previous classifications that were based on social class and social and economic group.

Proxy response

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

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 group have a higher tendency to drop out (attrition rate) than respondents in other age groups, then they will be under-represented in subsequent waves of the survey and in estimates.

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