{"doc_desc":{"title":"zaf-statssa-qlfs-2021-q1-v1","idno":"DDI_ZAF_2021_QLFS-Q3_v01_M","producers":[{"name":"DataFirst","abbreviation":"","affiliation":"University of Cape Town","role":"Metadata producer"},{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Metadata adapted for Microdata Library"}],"prod_date":"2021-12-09","version_statement":{"version":"Version 01: This metadata was downloaded from DataFirst website(https:\/\/www.datafirst.uct.ac.za\/dataportal\/index.php\/catalog\/central). The following two metadata information has been edited - Document and Survey ID."}},"study_desc":{"title_statement":{"idno":"ZAF_2021_QLFS-Q3_v01_M","title":"Quarterly Labour Force Survey 2021","sub_title":"Quarter 3","alt_title":"QLFS-Q3 2021"},"authoring_entity":[{"name":"Statistics South Africa","affiliation":"Government of South Africa"}],"distribution_statement":{"contact":[{"name":"DataFirst Support","affiliation":"University of Cape Town","email":"support@data1st.org","uri":""}]},"series_statement":{"series_name":"Labor Force Survey [hh\/lfs]"},"version_statement":{"version":"Version 01: Edited, anonymised dataset for public distribution","version_date":"2021","version_notes":"This version was retrieved by DataFirst on the 9th December 2021."},"study_info":{"abstract":"The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.","coll_dates":[{"start":"2021-07","end":"2021-09","cycle":""}],"nation":[{"name":"South Africa","abbreviation":"ZAF"}],"geog_coverage":"National coverage","geog_unit":"Provincial and metropolitan level, as well as by geographic type.","analysis_unit":"Individuals","universe":"The QLFS sample covers the non-institutional population of South Africa with one exception. The only institutional subpopulation included in the QLFS sample are individuals in worker's hostels. Persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.","data_kind":"Sample survey data [ssd]","notes":"For Q3 2021 Statistics South Africa contiued to use Computer Assisted Telephone Interviewing (CATI), in an attempt to reduce the spread of COVID-19. This meant that households without telephones were out of scope. See the statistical release for more information.\n\nINDIVIDUALS: labour market activity, labour preferences, labour market history, demographic characteristics, marital status, employment status, education, grants, tax."},"method":{"data_collection":{"sampling_procedure":"The QLFS uses a master sampling frame that is used by several household surveys conducted by Statistics South Africa. This wave of the QLFS is based on the 2013 master frame, which was created based on the 2011 census. There are 3324 PSUs in the master frame and roughly 33 000 dwelling units.\n\nThe sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.\n\nFor each quarter of the QLFS, a quarter of the sampled dwellings are rotated out of the sample. These dwellings are replaced by new dwellings from the same PSU or the next PSU on the list. For more information see the statistical release.","coll_mode":"Computer Assisted Telephone Interview [cati]","coll_situation":"COVID 19 affected data collection for QLFS 2020 Q3. Please see the sampling section and the statistical release for more on this.","weight":"The sample weights were constructed in order to account for the following: the original selection probabilities (design weights); adjustments for PSUs that were sub-sampled or segmented; excluded population from the sampling frame (EAs with insufficient DUs); non-response; weight trimming; benchmarking to known population estimates from the Demographic Analysis Chief Directorate within Stats SA; and raking to bias-adjusted control estimates from a bias-adjustment procedure to compensate for the non-coverage bias in the sample due to only observing those households that can be contacted by telephone.","method_notes":"In general, imputation is used for item non-response (i.e., blanks within the questionnaire) and edit failures (i.e. invalid or inconsistent responses). The eligible households in the sampled dwellings can be divided into two response categories: respondents and non-respondents. Weight adjustment is applied to account for the non-respondent households (e.g. refusal, no contact, etc.). The adjustment for total non-response was computed at two levels of non-response: PSU non-response and household non-response."}},"data_access":{"dataset_use":{"contact":[{"name":"DataFirst","affiliation":"University of Cape Town","email":"support@data1st.org","uri":"support.data1st.org"}],"cit_req":"Statistics South Africa. Quarterly Labour Force Survey 2021: Q3 [dataset]. Version 1. Pretoria: Statistics South Africa [producer], 2021. Cape Town: DataFirst [distributor], 2021. DOI: https:\/\/doi.org\/10.25828\/beav-z377","conditions":"Public access data, available to all","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}},"schematype":"survey","tags":[{"tag":"noDOI"}]}