ZAF_2000_LFS-FEB_v02_M
Labour Force Survey 2000
February
Name | Country code |
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South Africa | zaf |
Labor Force Survey [hh/lfs]
The LFS is a twice-yearly rotating panel household survey, specifically designed to measure the dynamics of employment and unemployment in South Africa. It measures a variety of issues related to the labour market,including unemployment rates (official and expanded), according to standard definitions of the International Labour Organisation (ILO).
All editions of the LFS have been updated (some more than once) since their release. These version changes are detailed in a document available from DataFirst (in the "external documents" section titled "LFS 2000-2008 Collated Version Notes on the South African LFS").
Sample survey data [ssd]
Dwelling units (households) and individuals
v1.1: Edited, anonymised dataset for licensed distribution
2000-02
The South African February 2000 LFS dataset was originally released in 2001 as 3 data files (household, worker and general). A second version was downloaded from the Statistics South Africa website on 11 August 2011 by DataFirst. This version differed slightly from the originally obtained release in the following ways:
Household characteristics, household listing, demographics, education, economic activity, work for pay, business ownership, unemployment, employers, main work activity in the past week, wages, salary, employment, migration
Topic | Vocabulary | URI |
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employment [3.1] | CESSDA | http://www.nesstar.org/rdf/common |
in-job training [3.2] | CESSDA | http://www.nesstar.org/rdf/common |
labour relations/conflict [3.3] | CESSDA | http://www.nesstar.org/rdf/common |
retirement [3.4] | CESSDA | http://www.nesstar.org/rdf/common |
unemployment [3.5] | CESSDA | http://www.nesstar.org/rdf/common |
working conditions [3.6] | CESSDA | http://www.nesstar.org/rdf/common |
LABOUR AND EMPLOYMENT [3] | CESSDA | http://www.nesstar.org/rdf/common |
TRADE, INDUSTRY AND MARKETS [2] | CESSDA | http://www.nesstar.org/rdf/common |
DEMOGRAPHY AND POPULATION [14] | CESSDA | http://www.nesstar.org/rdf/common |
National Coverage
Province (variable name: "Prov")
The LFS sample covers the non-institutional population except for workers' hostels. However, 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.
Name |
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Statistics South Africa (http://www.statssa.gov.za) |
The LFS is a twice-yearly rotating panel household survey. A rotating panel sample involves visiting the same dwelling units on a number of occasions (in this instance, five at most), and replacing a proportion of these dwelling units each round (in this instance 20%). New
dwelling units are added to the sample to replace those that are taken out. This February 2000 dataset represents the pilot study for the LFS. A sample of 10 000 households was drawn in 1 574 enumerator areas (EAs) (that is 10 households in each of the 426 non-urban EAs and 5 households in each of the 1 148 urban EAs). A two-stage sampling procedure was applied and the sample was stratified, clustered and selected to meet the requirements of probability sampling.
The sample was based on the 1996 Population Census enumerator areas and the estimated number of households from the 1996 Population Census. The sampled population excluded all prisoners in prisons, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent). The sample was explicitly stratified by province and area type (urban/rural). Within each explicit stratum the EAs were further stratified by simply arranging them in geographical order by District Council, Magisterial District and, within the magisterial district, by average household income (for formal urban areas and hostels). The allocated number of EAs was systematically selected with probability proportional to size in each stratum. The measure of size was the estimated number of households in each EA. A systematic sample of 10 households in non-urban and 5 households in urban areas was then drawn.
The 1996 population Census was used as a basis for the weighting. Household weights were calculated by using the reciprocal of the inclusion probabilities. To calculate the person weight, the data was post-stratified by province, gender and age group (5-year
age groups). The 1996 Census figures (adjusted for growth) were used as benchmarks. Relative scaling was also done on this weight to cater for the population group.
Stats SA revised their population model to produce mid-year population estimates in light of mortality data released in 2005 (see Stats SA Statistical Release P0309.3, 2005). The benchmarks for the LFS discussed in this statistical release have been adjusted accordingly. Weights were then adjusted according to those 2005 population estimates for all LFS datasets EXCEPT THIS ONE (February 2000).
Data collected includes data on households and person data (via the Flap and Section 1 of the questionnaire), worker data on persons 15-65 years (Sections 2, 3, 4 and 5). worker data collected includes labour market data, including employment in both the formal and informal sectors, and data on unemployment. Most questions in the Labour Force Survey questionnaire are pre-coded, i.e. there is a set number of choices from which one or more must be selected. Post-coding was done for open-ended questions.
Start | End |
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2000-02 | 2000-02 |
Name | Affiliation | URL | |
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DataFirst | University of Cape Town | http://www.datafirst.uct.ac.za | info@data1st.org |
Licensed dataset, accessible under conditions.
Statistics South Africa. Labour Force Survey Pilot: February 2000. [dataset]. Version 1.1. Pretoria: Statistics South Africa [producer], 2001. Cape Town: DataFirst [distributor], 2011.
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.
Copyright, Statistics South Africa
Name | Affiliation | URL | |
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Manager, DataFirst | University of Cape Town | info@data1st.org | http://www.datafirst.uct.ac.za |
ZAF_2000_LFS-FEB_v02_M
Name | Affiliation | Role |
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DataFirst | University of Cape Town | DDI Producer |
2011-09-21
Version 01 (July 2012) - Adapted version of the DDI "zaf-statssa-lfs-2000-feb-v1.1" received from Data First.