DOI: 10.5255/ukda-sn-7674-11
title: Labour Force Survey Household Datasets, 2002-2021: Secure Access
title: Quarterly Labour Force Survey, 1992- : Secure Access
title: QLFS

description: &lt;p&gt;&lt;span style="font-weight: bold;"&gt;Background&lt;/span&gt;&lt;br&gt;The &lt;i&gt;Labour Force Survey&lt;/i&gt; (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the &lt;i&gt;Quarterly Labour Force Survey&lt;/i&gt; (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.&lt;br&gt;&lt;/p&gt;&lt;p&gt;&lt;span style="font-weight: bold;"&gt;New reweighting policy&lt;/span&gt;&lt;br&gt;Following the &lt;a href="http://doc.ukdataservice.ac.uk/doc/8343/mrdoc/pdf/biennial_lfs_aps_reweighting_policy.pdf" target="_blank" style="background-color: rgb(255, 255, 255);"&gt;new reweighting policy&lt;/a&gt; ONS has reviewed the latest population estimates made available during 2019 and have decided not to carry out a 2019 LFS and APS reweighting exercise. Therefore, the next reweighting exercise will take place in 2020. These will incorporate the 2019 Sub-National Population Projection data (published in May 2020) and 2019 Mid-Year Estimates (published in June 2020). It is expected that reweighted Labour Market aggregates and microdata will be published towards the end of 2020/early 2021.&lt;br&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;Secure Access QLFS household data&lt;/b&gt;&lt;br&gt;Up to 2015, the LFS household datasets were produced twice a year (April-June and October-December) from the corresponding quarter's individual-level data. From January 2015 onwards, they are now produced each quarter alongside the main QLFS. The household datasets include all the usual variables found in the individual-level datasets, with the exception of those relating to income, and are intended to facilitate the analysis of the economic activity patterns of whole households. It is recommended that the existing individual-level LFS datasets continue to be used for any analysis at individual level, and that the LFS household datasets be used for analysis involving household or family-level data. For some quarters, users should note that all missing values in the data are set to one '-10' category instead of the separate '-8' and '-9' categories. For that period, the ONS introduced a new imputation process for the LFS household datasets and it was necessary to code the missing values into one new combined category ('-10'), to avoid over-complication. From the 2013 household datasets, the standard -8 and -9 missing categories have been reinstated.&lt;br&gt;&lt;br&gt;Secure Access household datasets for the QLFS are available from 2002 onwards, and include additional, detailed variables not included in the standard 'End User Licence' (EUL) versions. Extra variables that typically can be found in the Secure Access versions but not in the EUL versions relate to: geography; date of birth, including day; education and training; household and family characteristics; employment; unemployment and job hunting; accidents at work and work-related health problems; nationality, national identity and country of birth; occurence of learning difficulty or disability; and benefits.&lt;br&gt;&lt;br&gt;Prospective users of a Secure Access version of the QLFS will need to fulfil additional requirements, commencing with the completion of an extra application form to demonstrate to the data owners exactly why they need access to the extra, more detailed variables, in order to obtain permission to use that version. Secure Access users must also complete face-to-face training and agree to Secure Access' User Agreement (see 'Access' section below). Therefore, users are encouraged to download and inspect the EUL version of the data prior to ordering the Secure Access version.&lt;br&gt;&lt;br&gt;&lt;b&gt;LFS Documentation&lt;/b&gt;&lt;br&gt;The documentation available from the Archive to accompany LFS datasets largely consists of each volume of the User Guide including the appropriate questionnaires for the years concerned. However, LFS volumes are updated periodically by ONS, so users are advised to check the ONS &lt;a href="http://www.ons.gov.uk/ons/guide-method/method-quality/specific/labour-market/labour-market-statistics/index.html" title="Labour Force Survey (LFS) User Guidance"&gt;LFS User Guidance&lt;/a&gt; pages before commencing analysis.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Review of imputation methods for LFS Household data - changes to missing values&lt;/b&gt;&lt;br&gt;A review of the imputation methods used in LFS Household and Family analysis resulted in a change from the January-March 2015 quarter onwards. It was no longer considered appropriate to impute any personal characteristic variables (e.g. religion, ethnicity, country of birth, nationality, national identity, etc.) using the LFS donor imputation method. This method is primarily focused to ensure the 'economic status' of all individuals within a household is known, allowing analysis of the combined economic status of households. This means that from 2015 larger amounts of missing values ('-8'/-9') will be present in the data for these personal characteristic variables than before. Therefore if users need to carry out any time series analysis of households/families which also includes personal characteristic variables covering this time period, then it is advised to filter off 'ioutcome=3' cases from all periods to remove this inconsistent treatment of non-responders.&lt;br&gt;&lt;br&gt;&lt;b&gt;Variables DISEA and LNGLST&lt;/b&gt;&lt;br&gt;Dataset A08 (Labour market status of disabled people) which ONS suspended due to an apparent discontinuity between April to June 2017 and July to September 2017 is now available. As a result of this apparent discontinuity and the inconclusive investigations at this stage, comparisons should be made with caution between April to June 2017 and subsequent time periods. However users should note that the estimates are not seasonally adjusted, so some of the change between quarters could be due to seasonality. Further recommendations on historical comparisons of the estimates will be given in November 2018 when ONS are due to publish estimates for July to September 2018. &lt;br&gt;&lt;br&gt;An article explaining the quality assurance investigations that have been conducted so far is available on the &lt;a href="https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/methodologies/analysisofthediscontinuityinthelabourforcesurveydisabilitydataapriltojune2017tojulytoseptember2017" target="_blank"&gt;ONS Methodology&lt;/a&gt; webpage. For any queries about Dataset A08 please email Labour.Market@ons.gov.uk.&lt;br&gt;&lt;br&gt;&lt;b&gt;Latest Edition Information&lt;/b&gt;&lt;br&gt;&lt;/p&gt;&lt;p class="MsoNormal"&gt;For the eleventh edition (May 2022), five quarterly data files covering the time period up April 2020 to June 2021 have been updated and two quarterly files covering the time period July to December 2021 have been added to the study. In addition the documentation has been updated to reflect this extended time period.&lt;o:p&gt;&lt;/o:p&gt;&lt;/p&gt;