{"doc_desc":{"title":"Quarterly Labour Force Survey 2018 Q4","idno":"DDI_ZAF_2020_QLFS-Q1_v01_M","producers":[{"name":"DataFirst","abbreviation":"","affiliation":"University of Cape Town","role":"DDI Producer"}],"prod_date":"2020-03-31","version_statement":{"version":"Version 02: This metadata was downloaded from DataFirst microdata repository website. The following two metadata information have been edited \u2013 Document and Survey ID."}},"study_desc":{"title_statement":{"idno":"ZAF_2020_QLFS-Q1_v01_M","title":"Quarterly Labour Force Survey 2020","sub_title":"Quarter 1","alt_title":"QLFS-Q1 2020"},"authoring_entity":[{"name":"Statistics South Africa","affiliation":""}],"distribution_statement":{"contact":[{"name":"DataFirst Helpdesk","affiliation":"University of Cape Town","email":"support@data1st.org","uri":""}]},"series_statement":{"series_name":"Labor Force Survey [hh\/lfs]","series_info":"Statistics South Africa. Quarterly Labour Force Survey 2020: Q1 [dataset]. Version 1. Pretoria: Statistics South Africa [producer], 2020. Cape Town: DataFirst [distributor], 2020. DOI: https:\/\/doi.org\/10.25828\/vkhb-2j69"},"version_statement":{"version":"Verison 01: Edited, anonymised dataset for public distribution","version_date":"2020-07-22","version_notes":"This version was downloaded by DataFirst on the 15th of July 2020."},"study_info":{"keywords":[{"keyword":"Employment","vocab":"","uri":""},{"keyword":"in-job training","vocab":"","uri":""},{"keyword":"labour relations\/conflict","vocab":"","uri":""},{"keyword":"retirement","vocab":"","uri":""},{"keyword":"unemployment","vocab":"","uri":""},{"keyword":"working conditions","vocab":"","uri":""},{"keyword":"labour and employment","vocab":"","uri":""},{"keyword":"trade, industry and markets","vocab":"","uri":""},{"keyword":"demographics and population.","vocab":"","uri":""}],"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":"2020-01","end":"2020-03","cycle":""}],"nation":[{"name":"South Africa","abbreviation":"ZAF"}],"geog_coverage":"National coverage","geog_unit":"Provincial and metropolitan level","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":"INDIVIDUALS: labour market activity, labour preferences, labour market history, demographic characteristics, marital status, employment status, education, grants, tax."},"method":{"data_collection":{"data_collectors":[{"name":"Statistics South Africa","abbreviation":"","affiliation":""}],"sampling_procedure":"The Quarterly Labour Force Survey (QLFS) uses a master sample frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household surveys that have reasonably compatible design requirement as the QLFS. The 2013 master sample is based on information collected during the 2011 population Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the master sample since they covered the entire country and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the master sample with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current master sample (3 324) reflects an 8,0% increase in the size of the master sample compared to the previous (2007) master sample (which had 3 080 PSUs). The larger master sample of PSUs was selected to improve the precision (smaller CVs) of the QLFS estimates.\n\nFrom the master sample frame, the QLFS takes draws employing 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. The primary stratification occurred at provincial, metro\/non-metro, mining and geography type while the secondary strata were created within the primary strata based on the demographic and socio-economic characteristics of the population. For each quarter of the QLFS, a \u00bc of the sampled dwellings is rotated out of the sample. These dwellings are replaced by new dwellings from the same PSU or the next PSU on the list. \n\nFor more see the release document that is distributed with the data.","sampling_deviation":"It should be noted that the Quarterly Labour Force Survey (QLFS) for Quarter 1 (January to March) of 2020 data collection was disrupted when Stats SA suspended face-to-face data collection for all its surveys on 19 March 2020 as a result of the COVID-19 pandemic and restricted movement. This was to ensure that the field staff and respondents were not exposed to the risk of contracting coronavirus and to contain its spread. As a result, some dwellings (621 or 2,0% of the 30 608 sampled dwelling units) were not interviewed which otherwise would have been interviewed. To compensate for this, Stats SA made use of the fact that the design of the QLFS is such that sampled dwelling units are in the sample for four successive quarters. So, for persons in dwelling units that were not visited as a result of the lockdown, imputations were done where possible using data from the previous quarter. For respondents who were not visited in the first quarter of 2020 but had information from the fourth quarter of 2019, their responses were carried over to the first quarter of 2020. \n\nIf the person was shown as unemployed or not economically active in the last quarter of 2019, that was the status assigned to them for the first quarter of 2020. If the person was shown as employed in the fourth quarter of 2019, the imputation was somewhat more complex. This was necessitated by the fact that that there are usually temporary jobs created in the fourth quarter of each year that do not continue into the following year. Accordingly, if the person started the job that he\/she held in Q4: 2019 in some previous quarter, it was assumed that the job continued into Q1: 2020. On the other hand, if the job held in Q4: 2019 had only started in that quarter, that person was treated as non-respondent in Q1: 2020.","coll_mode":"Face-to-face [f2f]","research_instrument":"The survey questionnaire consists of five section:\nSection 1: Biographical information (marital status, language, migration, education, training, literacy, etc.) \nSection 2: Economic activities for persons aged 15 years and older \nSection 3: Unemployment and economic inactivity for persons aged 15 years and older \nSection 4: Main work activities in the last week for persons aged 15 years and older \nSection 5: Earnings in the main job for employees, employers and own-account workers aged 15 years and older","weight":"The sample weights were constructed in order to account for the following: the original selection probabilities (design weights), adjustments for PSUs that were subsampled or segmented, excluded population from the sampling frame, non-response, weight trimming, and benchmarking to known population estimates from the Demographic Analysis division within Stats SA. Weights were then  adjusted for non-response. In the final step of constructing the sample weights, all individuals within a household are assigned the same adjusted base weight. The adjusted base weights are calibrated such that the aggregate totals will match with independently derived population estimates (from the Stats SA Demographic Analysis division) for various age, race and gender groups at national level and individual metropolitan and non-metropolitan area levels within the provinces. The calibrated weights are constructed using the constraint that each person within the same household should have the same calibrated weight, with a lower bound on the calibrated weights set at 50."},"analysis_info":{"data_appraisal":"COVID 19 Affected data collection for QLFS 2020 Q1. Please see the sampling section for more on this."}},"data_access":{"dataset_use":{"contact":[{"name":"DataFirst","affiliation":"University of Cape Town","email":"support@data1st.org","uri":"http:\/\/www.datafirst.uct.ac.za"}],"cit_req":"Statistics South Africa. Quarterly Labour Force Survey 2020: Q1 [dataset]. Version 1. Pretoria: Statistics South Africa [producer], 2020. Cape Town: DataFirst [distributor], 2020. DOI: https:\/\/doi.org\/10.25828\/vkhb-2j69","conditions":"Public use files, available to all"}}},"schematype":"survey","tags":[{"tag":"noDOI"}]}