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.
Kind of Data
Sample survey data
Unit of Analysis
v2: Edited, anonymised dataset for public distribution
Verison 1: Version 1 of QLFS Q3 2020 was downloaded by DataFirst on the 17th November 2020. It did not include covid-related or earnings-related variables as per the questionnaire.
Version 2: Version 2 was received from Stats SA by email on the 19th of January 2021. The data included covid and earnings variables; DataFirst has removed the earnings data until we get permission to share.
For Q3 2020 Statistics South Africa contiued to use Computer Assisted Telephone Interviewing, 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.
INDIVIDUALS: labour market activity, labour preferences, labour market history, demographic characteristics, marital status, employment status, education, grants, tax.
From 2010 the income data collected by South Africa's Quarterly Labour Force Survey is no longer provided in the QLFS dataset (except for a brief return in QLFS 2010 Q3 which may be an error). Possibly because the data is unreliable at the level of the quarter, Statistics South Africa now provides the income data from the QLFS in an annualised dataset called Labour Market Dynamics in South Africa (LMDSA). The datasets for LMDSA are available from DataFirst's website.
Provincial and metropolitan level
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.
Producers and sponsors
Statistics South Africa
The samping procedure for this quarter of the QLFS had to be changed from the norm due to covid-19. In this 2020 Q3 the sample used was the same sample as from Q2 and Q1 from 2020. Because the interviews were done telephonically, any sampling units that did not have telephones dropped out of the sample. This was adjusted for in the weighting procedure.
Because the survey was done telehponically, households without telephones were essentially out of scope. To account for this problem, data from Q1 were used as the benchmark to which the Q3 weights were "bias-adjusted", in terms of labour market variables (status, sector, industry and occupation) and demographic (age, race and gender) characteristics, at three geographic levels. Note that Q1 2020 was itself imputed based on Q4 2019, so those imputations from Q4 would carry forward to 2020 Q1 and in turn to 2020 Q2 and Q3.
For more details see section 4 of the stastical release and the metadata document.
Dates of Data Collection
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Data Collection Notes
This QLFS used Computer Assisted Telephone Interviewing (CATI) instead of face-to-face interviews because of the covid-19 pandemic.
Data has been value-labelled and 9 possibly disclosive varibles were removed from the public version.
COVID 19 Affected data collection for QLFS 2020 Q3. Please see the data collection and sampling sections for more on this, and consult the statistical release for further information.
Note that Q1 2020 was itself imputed based on Q4 2019, so those imputations from Q4 would carry forward to 2020 Q1 and in turn to 2020 Q2 and Q3.
This wave of QLFS data has earnings data included, which is normally separated out into the LMDSA.
Statistics South Africa. Quarterly Labour Force Survey 2020: Q3 [dataset]. Version 2. Pretoria: Statistics South Africa [producer], 2020. Cape Town: DataFirst [distributor], 2020.DOI: https://doi.org/10.25828/e4wk-9c69