Labour Force Survey 2000, February
South Africa, 2000
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Reference ID
zaf-statssa-lfs-2000-feb-v1.1
Producer(s)
Statistics South Africa (http://www.statssa.gov.za)
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Created on
Feb 01, 2012
Last modified
May 06, 2020
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44535
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Identification
Survey ID Number
zaf-statssa-lfs-2000-feb-v1.1
Title
Labour Force Survey 2000, February
Subtitle
February
Country
| Name | Country code |
|---|---|
| South Africa | zaf |
Study type
Labor Force Survey [hh/lfs]
Abstract
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").
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").
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Dwelling units (households) and individuals
Version
Version Description
v1.1: Edited, anonymised dataset for licensed distribution
Version Date
2000-02
Version Notes
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:
1. The suffix ” Feb2000” no longer appears on all variable names
2. Year and Month variables were added
3. Variable labels were altered. Previously, all variable labels were literal questions. Now the variable labels describe the variables.
1. The suffix ” Feb2000” no longer appears on all variable names
2. Year and Month variables were added
3. Variable labels were altered. Previously, all variable labels were literal questions. Now the variable labels describe the variables.
Scope
Notes
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
Topics
| Topic | Vocabulary | URI |
|---|---|---|
| employment [3.1] | CESSDA | Link |
| in-job training [3.2] | CESSDA | Link |
| labour relations/conflict [3.3] | CESSDA | Link |
| retirement [3.4] | CESSDA | Link |
| unemployment [3.5] | CESSDA | Link |
| working conditions [3.6] | CESSDA | Link |
| LABOUR AND EMPLOYMENT [3] | CESSDA | Link |
| TRADE, INDUSTRY AND MARKETS [2] | CESSDA | Link |
| DEMOGRAPHY AND POPULATION [14] | CESSDA | Link |
Coverage
Geographic Coverage
National Coverage
Geographic Unit
Province (variable name: "Prov")
Universe
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.
Producers and sponsors
Primary investigators
| Name |
|---|
| Link |
Sampling
Sampling Procedure
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.
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.
Weighting
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).
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 Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2000-02 | 2000-02 |
Data Collection Mode
Face-to-face [f2f]
Questionnaires
Questionnaires
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.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Manager, DataFirst | University of Cape Town | info@data1st.org | Link |
Access conditions
Licensed dataset, accessible under conditions.
Citation requirements
Statistics South Africa. Labour Force Survey Pilot: February 2000. [dataset]. Version 1.1. Pretoria: Statistics South Africa [producer], 2001. Cape Town: DataFirst [distributor], 2011. DOI: https://doi.org/10.25828/ft1v-w181
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst | University of Cape Town | info@data1st.org | Link |
Disclaimer and copyrights
Copyright
Copyright, Statistics South Africa
Metadata production
DDI Document ID
zaf-statssa-lfs-2000-feb-v1.1
Producers
| Name | Affiliation | Role |
|---|---|---|
| DataFirst | University of Cape Town | DDI Producer |
Date of Metadata Production
2020-03-29
DDI Document version
Version 2