Quarterly Labour Force Survey 2019, Quarter 1

South Africa, 2019

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Reference ID

zaf-statssa-qlfs-2019-q1-v1

Producer(s)

Statistics South Africa

Collections

South African Labour Force Survey Data

Metadata

DDI/XML JSON

Created on

Jun 24, 2019

Last modified

Sep 10, 2020

Page views

76261

Downloads

5272

Identification

Survey ID number

zaf-statssa-qlfs-2019-q1-v1

Title

Quarterly Labour Force Survey 2019

Subtitle

Quarter 1

Country

Name	Country code
South Africa	zaf

Study type

Labour Force Survey [hh/lfs]

Series Information

Statistics South Africa. Quarterly Labour Force Survey 2019: Q1 [dataset]. Version 1. Pretoria: Statistics South Africa [producer], 2019. Cape Town: DataFirst [distributor], 2019. DOI: https://doi.org/10.25828/5sny-n338

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

v1.0: Edited, anonymised dataset for public distribution

Version Date

2019-05-14

Version Notes

v1.0: This version was downloaded by DataFirst on the 7th of June 2018

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.

Topics

Topic	Vocabulary	URI
employment [3.1]	CESSDA
in-job training [3.2]	CESSDA
labour relations/conflict [3.3]	CESSDA
retirement [3.4]	CESSDA
unemployment [3.5]	CESSDA
working conditions [3.6]	CESSDA
LABOUR AND EMPLOYMENT [3]	CESSDA
TRADE, INDUSTRY AND MARKETS [2]	CESSDA
DEMOGRAPHY AND POPULATION [14]	CESSDA

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.

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.

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.

Data collection

Dates of Data Collection

Start	End
2019-01	2019-03

access_policy

Access authority

Name	Affiliation	URL	Email
DataFirst	University of Cape Town		support@data1st.org

Access conditions

Public use data, available to all

Citation requirements

Disclaimer and copyrights

Contacts

Name	Affiliation	Email	URL
DataFirst Helpdesk	University of Cape Town	support@data1st.org

Metadata production

DDI Document ID

ddi-zaf-datafirst-qlfs-2019-q1-v1.0

Producers

Name	Affiliation	Role
DataFirst	University of Cape Town	DDI Producer

Date of Metadata Production

2020-03-31

Metadata version

DDI Document version

Version 2

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