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.
The objective of the QLFS is to collect quarterly information about persons in the labour market, i.e., those who are employed; those who are unemployed and those who are not economically active.
This information will be published as core labour market indicators2 four weeks after the end of each quarter and an annual report and supplementary data will be published six months after the end of each calendar year.
Kind of data
Sample survey data [ssd]
v2.0: Edited, anonymised dataset for public distribution
This version of the QLFS 2012 Q3 was downloaded from the Statistics South Africa (Stats SA) website in April 2014 as a revision to the version previously downloaded in August 2013.
The two versions have different weights. Stats SA updated the QLFS results (2008-2013) to reflect the new population benchmarks from Census 2011. Although the weighting changes are not clearly documented by Stats SA, users are advised to remain aware of these slight calibration differences when employing weights.
in-job training [3.2]
labour relations/conflict [3.3]
working conditions [3.6]
LABOUR AND EMPLOYMENT 
TRADE, INDUSTRY AND MARKETS 
DEMOGRAPHY AND POPULATION 
Provincial and metropolitan level
Unit of analysis
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 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 30000 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 3080 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.
Each quarter, a ¼ of the sampled dwellings rotate out of the sample and are replaced by new dwellings from the same PSU or the next PSU on the list. Thus, sampled dwellings will remain in the sample for four consecutive quarters. It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, say two quarters, and a new household moves in, the new household will be enumerated for the next two quarters. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (unoccupied).
Response rates by province
Province Jul–Sep 2012 (Percent)
Western Cape 90.8
Eastern Cape 98.6
Northern Cape 91.3
Free State 96.9
North West 92.8
South Africa 92.7
Stats SA updated the QLFS results (2008-2013) to reflect the new population benchmarks from Census 2011. Although the weighting changes are not clearly documented by Stats SA, users are advised to remain aware of these slight calibration differences between the previous version and the current (revised) data version when employing weights.
The sampling weights for the data collected from the sampled households are constructed in such a manner that the responses could be properly expanded to represent the entire civilian population of South Africa. The weights are the result of calculations involving several factors, including original selection probabilities, adjustment for non-response, and benchmarking to known population estimates from the Demographic division of Stats SA.
Final survey weights
The final survey weights are constructed using regression estimation to calibrate to the known population counts at the national level population estimates (which are supplied by the Demography division) crossclassified by 5-year age groups, gender and race, and provincial population estimates by broad age groups. The 5-year age groups are: 0–4, 5–9, 10–14, etc., and 65 years and above. The provincial level age groups are: 0–14, 15–34, 35–64, and 65 years and over. The calibrated weights are constructed such that all persons in a household would have the same final weight.
Since estimates are based on sample data, they differ from figures that would have been obtained from complete enumeration of the population using the same instrument. Results are subject to both sampling and non-sampling errors. Non-sampling errors include biases from inaccurate reporting, processing, and tabulation, etc., as well as errors from non-response and incomplete reporting. These types of errors cannot be measured readily. However, to some extent, non-sampling errors can be minimised through the procedures used for data collection, editing, quality control, and non-response adjustment. The variances of the survey estimates are used to measure sampling errors.
University of Cape Town
Public use files, accessible to all
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Statistics South Africa. South Africa Quarterly Labour Force Survey (QLFS-Q3) 2012, Third Quarter 2012. Ref. ZAF_2012_QLFS-Q3_v02_M. Dataset downloaded from [url] on [date].
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
University of Cape Town
World Bank Microdata Library
University of Cape Town
Version 01 (August 2013). Edited version based on Version 01 DDI (DDI-ZAF-DATAFIRST-QLFS-2012-Q3-V1) that was done by DataFirst.
Version 02 (April 2014): This version is identical to Version 01, with revisions to data.