Quarterly Labour Force Survey 2022
Quarter 3
South Africa, 2022
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Reference ID
ZAF_2022_QLFS-Q3_v01_M
Producer(s)
Statistics South Africa
Collection(s)
Metadata
Created on
Mar 02, 2023
Last modified
Mar 02, 2023
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Identification
Survey ID Number
ZAF_2022_QLFS-Q3_v01_M
Title
Quarterly Labour Force Survey 2022
Subtitle
Quarter 3
Country/Economy
| Name | Country code |
|---|---|
| South Africa | ZAF |
Study type
Labor Force Survey [hh/lfs]
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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Individuals
Version
Version Description
Version 01: Edited, anonymised dataset for public distribution.
Version Date
2022
Version Notes
This version was retrieved by DataFirst on the 29 November 2022.
Scope
Notes
For Q3 2022 Statistics South Africa reverted back to using Computer Assisted Personal Interviewing (CAPI) after previously using Computer Assisted Telephone Interviewing (CATI), in an attempt to reduce the spread of COVID-19. 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.
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.
Coverage
Geographic Coverage
National coverage
Geographic Unit
Provincial and metropolitan level, as well as by geographic type.
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.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Statistics South Africa | Government of South Africa |
Sampling
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.
The 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.
For 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.
The 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.
For 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.
Weighting
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.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2022-07 | 2022-09 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collection Notes
COVID 19 affected data collection for QLFS for Q2: 2020 to Q4: 2021 where data was collected using Computer-assisted Telephone Interviewing (CATI). Since 2022, StatsSA took a decision to revert to face-to-face data collection using Computer-assisted Personal Interviewing (CAPI). In that regard for Q1: 2022 and Q2: 2022, data collections were mainly conducted using face-to-face interviewing with CAPI.
Questionnaires
Questionnaires
The survey questionnaire consists of the following sections:
- Biographical information (marital status, education, etc.)
- Economic activities for persons aged 15 years and older
- Biographical information (marital status, education, etc.)
- Economic activities for persons aged 15 years and older
Data Processing
Other Processing
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.
Access policy
Access conditions
Public access data for use under a Creative Commons CC-BY (Attribution-only) License
Citation requirements
Statistics South Africa. Quarterly Labour Force Survey 2022: Q3 [dataset]. Version 1. Pretoria: Statistics South Africa [producer], 2022. Cape Town: DataFirst [distributor], 2022. DOI: https://doi.org/10.25828/hc5q-aq58
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst | University of Cape Town | support@data1st.org | support.data1st.org |
Metadata production
DDI Document ID
DDI_ZAF_2022_QLFS-Q3_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| DataFirst | University of Cape Town | Metadata producer | |
| Development Economics Data Group | DECDG | The World Bank | Metadata adapted for Microdata Library |
Date of Metadata Production
2023-03-02
DDI Document version
Version 01 (March 2023): This metadata was downloaded from the DataFirst website (https://www.datafirst.uct.ac.za/dataportal/index.php/catalog/central) and it is identical to DataFirst DDI version (zaf-statssa-qlfs-2022-q3-v1). The following two metadata fields were edited - Document ID and Survey ID.