Labour Market Dynamics in South Africa 2015
South Africa, 2015
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Reference ID
zaf-statssa-lmdsa-2015-v1
Producer(s)
Statistics South Africa
Metadata
Created on
Feb 07, 2017
Last modified
Jul 03, 2020
Page views
27634
Downloads
3653
Identification
Survey ID Number
zaf-statssa-lmdsa-2015-v1
Title
Labour Market Dynamics in South Africa 2015
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 (StatsSA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa. Since 2008, StatsSA have produced an annual dataset based on the QLFS data, "Labour Market Dynamics in South Africa". The dataset is constructed using data from all all four QLFS datasets in the year. The dataset also includes a number of variables (including income) that are not available in any of the QLFS datasets from 2010.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Individuals
Version
Version Description
v1: Edited, anonymised dataset for public distribution
Version Date
2016
Version Notes
Version 1 of the Labour Market Dynamics in South Africa 2015 was downloaded from the Statistics South Africa website on the 7th of February 2017
Scope
Notes
Individuals: labour market activity, labour preferences, labour market history, demographic characteristics, marital status, employment status, education, grants, tax, income.
Keywords
| Keyword |
|---|
| Individual income |
| health systems and financing |
| education |
| social protection (includes pensions, safety nets, social funds) |
| labor markets |
| primary education |
| secondary education |
| tertiary education. |
Coverage
Geographic Coverage
The survey had national coverage.
The lowest level of geographic aggregation for the data is Province
The lowest level of geographic aggregation for the data is Province
Universe
The QLFS sample covers the non-institutional population except for those in workers' hostels. However, persons living in private dwelling units within institutions are 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 |
|---|
| Statistics South Africa |
Sampling
Sampling Procedure
The QLFS frame has been developed as a general purpose household survey frame that can be used by all other household surveys irrespective of the sample size requirement of the survey. The sample size for the QLFS is roughly 30 000 dwellings per quarter.
The sample is based on information collected during the 2001 Population Census conducted by Stats SA. In preparation for the 2001 Census, the country was divided into 80 787 enumeration areas (EAs). Stats SA's household-based surveys use a Master Sample of Primary Sampling Units (PSUs) which comprises of EAs that are drawn from across the country.
The sample is designed to be representative at the provincial level and within provinces at the metro/non-metro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms and tribal. This implies, for example, that within a metropolitan area the sample is representative at the different geography types that may exist within that metro.
The current sample size is 3 080 PSUs. It is divided equally into four sub-groups or panels called rotation groups. The rotation groups are designed in such a way that each of these groups has the same distribution pattern as that which is observed in the whole sample. They are numbered from one to four and these numbers also correspond to the quarters of the year in which the sample will be rotated for the particular group.
The sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of primary sampling units (PSUs) in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.
The sample is based on information collected during the 2001 Population Census conducted by Stats SA. In preparation for the 2001 Census, the country was divided into 80 787 enumeration areas (EAs). Stats SA's household-based surveys use a Master Sample of Primary Sampling Units (PSUs) which comprises of EAs that are drawn from across the country.
The sample is designed to be representative at the provincial level and within provinces at the metro/non-metro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms and tribal. This implies, for example, that within a metropolitan area the sample is representative at the different geography types that may exist within that metro.
The current sample size is 3 080 PSUs. It is divided equally into four sub-groups or panels called rotation groups. The rotation groups are designed in such a way that each of these groups has the same distribution pattern as that which is observed in the whole sample. They are numbered from one to four and these numbers also correspond to the quarters of the year in which the sample will be rotated for the particular group.
The sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of primary sampling units (PSUs) in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2015-01 | 2015-12 |
Data Collection Mode
Face-to-face [f2f]
Data Appraisal
Data Appraisal
In the report for the 2015 LMDSA Statistics South Africa have included the following "cautionary notes":
"Mining: Caution is required when making conclusions based on the industrial profile of employed persons since the clustered nature of the Mining industry means that it might not have been adequately captured by the QLFS sample. Alternative mining estimates are also included in the Quarterly Employment Statistics (QES).
2013 Master Sample: In 2015, Stats SA introduced a new master sample based on the Census 2011 data (2013 Master Sample). A number of improvements were introduced, including efforts to improve Mining estimates through the inclusion of Mining strata in provinces where employment in this industry was more than 30% of total employment. In addition, estimates of labour market indicators at a metro level was also published for the first time."
"Mining: Caution is required when making conclusions based on the industrial profile of employed persons since the clustered nature of the Mining industry means that it might not have been adequately captured by the QLFS sample. Alternative mining estimates are also included in the Quarterly Employment Statistics (QES).
2013 Master Sample: In 2015, Stats SA introduced a new master sample based on the Census 2011 data (2013 Master Sample). A number of improvements were introduced, including efforts to improve Mining estimates through the inclusion of Mining strata in provinces where employment in this industry was more than 30% of total employment. In addition, estimates of labour market indicators at a metro level was also published for the first time."
Access policy
Contacts
| Name | URL | |
|---|---|---|
| DataFirst Helpdesk | support@data1st.org | Link |
Access conditions
Public use data, available to all
Citation requirements
Statistics South Africa. Labour Market Dynamics in South Africa 2015 [dataset]. Version 1. Pretoria: Statistics South Africa [producer], 2016. Cape Town: DataFirst [distributor], 2017. DOI: https://doi.org/10.25828/s7dv-jy64
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst | University of Cape Town | support@data1st.org | Link |
Metadata production
Producers
| Name | Affiliation | Role |
|---|---|---|
| DataFirst | University of Cape Town | Metadata creator |
Date of Metadata Production
2020-03-30
DDI Document version
Version 2