Quarterly Labour Force Survey 2019, Quarter 3
South Africa, 2019
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Reference ID
zaf-statssa-qlfs-2019-q3-v1
Producer(s)
Statistics South Africa
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Created on
Apr 07, 2020
Last modified
Sep 10, 2020
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18584
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Identification
Survey ID Number
zaf-statssa-qlfs-2019-q3-v1
Title
Quarterly Labour Force Survey 2019, Quarter 3
Subtitle
Quarter 3
Country
| Name | Country code |
|---|---|
| South Africa | zaf |
Study type
Labour 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
Unit of Analysis
Individuals
Version
Version Description
v1.0: Edited, anonymised dataset for public distribution
Version Date
2020-04-03
Version Notes
This version was downloaded by DataFirst on the 2nd of March 2020.
Scope
Notes
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.
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
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.
For more see the statistical release.
For more see the statistical release.
Producers and sponsors
Primary investigators
| Name |
|---|
| Statistics South Africa |
Sampling
Sampling Procedure
The Quarterly Labour Force Survey (QLFS) uses the Master Sample frame that has been developed as a general-purpose household survey frame. The 2013 Master Sample is based on information collected during the 2011 Census. There are 3 324 primary sampling units in the Master Sample, with an expected sample of approximately 33 000 dwelling units. The sampling procedure 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.
The Master Sample is designed to be representative at the provincial level and within provinces at metro/non-metro levels. The sample is divided equally into four subgroups or panels called rotation groups. For each quarter of the QLFS, a quarter of the sampled dwellings are rotated out of the sample and replaced by new dwellings from the same PSU or the next PSU on the list.
The Master Sample is designed to be representative at the provincial level and within provinces at metro/non-metro levels. The sample is divided equally into four subgroups or panels called rotation groups. For each quarter of the QLFS, a quarter of the sampled dwellings are rotated out of the sample and replaced by new dwellings from the same PSU or the next PSU on the list.
Weighting
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.
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. In the final step of constructing the sample weights, all individuals within a household are assigned the same adjusted base weight. The base weights are calibrated such that the aggregate totals will match independently derived population estimates for various marginal totals.
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. In the final step of constructing the sample weights, all individuals within a household are assigned the same adjusted base weight. The base weights are calibrated such that the aggregate totals will match independently derived population estimates for various marginal totals.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2019-07 | 2019-09 |
Data Collection Mode
Face-to-face [f2f]
Data Processing
Data Editing
In general, imputation is used for item non-response (i.e. blanks within the questionnaire) and edit failures (i.e. invalid or inconsistent responses).
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst Helpdesk | University of Cape Town | support@data1st.org | Link |
Access conditions
Public use files, available to all
Citation requirements
Statistics South Africa. Quarterly Labour Force Survey 2019: Q3 [dataset]. Version 1.0. Pretoria: Statistics South Africa [producer], 2019. Cape Town: DataFirst [distributor], 2020. DOI: https://doi.org/10.25828/1F1A-F611
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst | University of Cape Town | support@data1st.org | Link |
Disclaimer and copyrights
Copyright
Copyright, Statistics South Africa
Metadata production
Producers
| Name | Affiliation | Role |
|---|---|---|
| DataFirst | University of Cape Town | DDI Producer |
Date of Metadata Production
2020-04-03
DDI Document version
Version 1.0