General Household Survey 2004
South Africa, 2004
Statistics South Africa
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October 22, 2020
Last modified
October 22, 2020
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Identification
IDNO
zaf-statssa-ghs-2004-v1.4
Title
General Household Survey 2004
Country
| Name | Country code |
|---|---|
| South Africa | zaf |
Study type
Household Survey [hh]
Series Information
Statistics South Africa. General Household Survey 2004 [dataset]. Version 1.4. Pretoria. Statistics South Africa [producer]. 2017. Cape Town. DataFirst [distributor], 2020. DOI: https://doi.org/10.25828/t155-b289
Abstract
The GHS is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, employment, health, housing and household access to services.
Kind of Data
Sample survey data
Unit of Analysis
Households and individuals
Version
Version Description
v1.4 Edited, anonymised dataset for public distribution
Version Date
2017
Version Notes
Version 1:
Version 1 of GHS 2004 uses old weights that are no longer available for download on Statistics South Africa's website.
The tourism file of version 1 suffers from quality issues. There is duplication in the househouse unique number even if it should be distinct for every observation.
Version 1.2:
Version 1.2 included new weights for comparability across GHS 2002-2008 released at the same time as the GHS 2008. Person files were reweighted to reflect Community Survey 2007 results and update the estimates of the impact of HIV/Aids on demographic trends in South Africa. Household files were weighted independently of the person files in v1.2. The reweighting procedure was discussed in the report: "Reweighting of the GHS 2002-2008 data series".
V1.2 uses the new provincial boundaries for the province variable, as revised by the government in 2005.
As part of the revision process, some observations may be removed. Demographic variables may be renamed and some values in these variables may be imputed.
The following variables were renamed not as part of the revison process: in the house file, “q442ligh” was renamed to “q444ligh”; “q442heat” was renamed to “q443heat”
The quality issue in the tourism file of version 1, as mentioned above, was fixed in v1.2.
Version 1.3:
Version 1.3 includes the new weights for comparability across GHS 2002-2011 released at the same time as the GHS 2012 (22 August 2013). Reweighting was necessary in order to maintain the comparability of population estimates used in the GHS based on figures provided by the 2013 mid-year population estimation model that incorporates the demographic findings of Census 2011. Household files were weighted independently of person files.
In the household file of v1.3, the province values for 10 observatins were changed.
Version 1.4:
Version 1.4 includes new weights for comparability across GHS 2002-2017 released at the same time as GHS 2017 (21 June 2018). It was decided to replace the 2013 series MYPEs in the previous version with a the more recent 2017 series MYPEs as benchmarks for weighting the GHS data files. Household files were weighted independently of person files.
Version 1 of GHS 2004 uses old weights that are no longer available for download on Statistics South Africa's website.
The tourism file of version 1 suffers from quality issues. There is duplication in the househouse unique number even if it should be distinct for every observation.
Version 1.2:
Version 1.2 included new weights for comparability across GHS 2002-2008 released at the same time as the GHS 2008. Person files were reweighted to reflect Community Survey 2007 results and update the estimates of the impact of HIV/Aids on demographic trends in South Africa. Household files were weighted independently of the person files in v1.2. The reweighting procedure was discussed in the report: "Reweighting of the GHS 2002-2008 data series".
V1.2 uses the new provincial boundaries for the province variable, as revised by the government in 2005.
As part of the revision process, some observations may be removed. Demographic variables may be renamed and some values in these variables may be imputed.
The following variables were renamed not as part of the revison process: in the house file, “q442ligh” was renamed to “q444ligh”; “q442heat” was renamed to “q443heat”
The quality issue in the tourism file of version 1, as mentioned above, was fixed in v1.2.
Version 1.3:
Version 1.3 includes the new weights for comparability across GHS 2002-2011 released at the same time as the GHS 2012 (22 August 2013). Reweighting was necessary in order to maintain the comparability of population estimates used in the GHS based on figures provided by the 2013 mid-year population estimation model that incorporates the demographic findings of Census 2011. Household files were weighted independently of person files.
In the household file of v1.3, the province values for 10 observatins were changed.
Version 1.4:
Version 1.4 includes new weights for comparability across GHS 2002-2017 released at the same time as GHS 2017 (21 June 2018). It was decided to replace the 2013 series MYPEs in the previous version with a the more recent 2017 series MYPEs as benchmarks for weighting the GHS data files. Household files were weighted independently of person files.
Scope
Notes
The scope of the General Household Survey includes:
Household characteristics: Dwelling type, home ownership, access to water and sanitation facilities, access to services, transport, household assets, land ownership, agricultural production
Individuals' characteristics: demographic characteristics, relationship to household head, marital status, language, education, employment, income, health, disability, access to social services, mortality.
Women's characteristics: fertility
Household characteristics: Dwelling type, home ownership, access to water and sanitation facilities, access to services, transport, household assets, land ownership, agricultural production
Individuals' characteristics: demographic characteristics, relationship to household head, marital status, language, education, employment, income, health, disability, access to social services, mortality.
Women's characteristics: fertility
Coverage
Geographic Coverage
The survey is representative at national level and at provincial level.
Geographic Unit
The lowest level of geographic aggregations is province.
Universe
The survey covered all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as students' hostels, old age homes, hospitals, prisons and military barracks.
Producers and sponsors
Primary investigators
| Name |
|---|
| Statistics South Africa |
Producers
| Name |
|---|
| Statistics South Africa (http://www.statssa.gov.za) |
Sampling
Sampling Procedure
The sample is multi-stage stratified using probability proportional to size principles. The first stage is stratification by province, then by type of area within each province. Primary sampling units (PSUs) are then selected proportionally within each stratum (urban or non-urban) in all provinces.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2004-07 | 2004-07 |
Data Collection Mode
Face-to-face [f2f]
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Statistics South Africa | SSA | Government of South Africa |
Questionnaires
Questionnaires
GHS uses questionnaires as data collection instruments
Data Appraisal
Data Quality Notes
Earlier versions of the GHS datasets 2002 to 2007 include a District Council variable. This is no longer available in the later versions issued by Statistics SA. They caution that although the GHS 2005-2007 sample was designed to report at DC level, estimations are not reliable at this level. The 2008 - 2013 sample was designed to report at provincial and metro level. However, StatsSA did not take the absent population at metro into account when weighting the data and therefore this data is not reliable at Metro level.
The new programs that were introduced for weighting of the general household surveys from 2008 onwards, discard all records with missing values for age, sex or population group (for observations at household level, they are the values for age, sex or population group of the household head). This means that missing values of those variables were imputed. The emphasis was on obtaining reliable imputations rather than a 100% imputation rate, so some persons/households were discarded during the weighting.
The new programs that were introduced for weighting of the general household surveys from 2008 onwards, discard all records with missing values for age, sex or population group (for observations at household level, they are the values for age, sex or population group of the household head). This means that missing values of those variables were imputed. The emphasis was on obtaining reliable imputations rather than a 100% imputation rate, so some persons/households were discarded during the weighting.
Access policy
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst | University of Cape Town | support@data1st.org | http://www.datafirst.uct.ac.za |
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst Helpdesk | University of Cape Town | support@data1st.org | http://support.data1st.org/ |
Confidentiality
Access conditions
Public use files, available to all
Citation requirements
Statistics South Africa. General Household Survey 2004 [dataset]. Version 1.4. Pretoria. Statistics South Africa [producer]. 2017. Cape Town. DataFirst [distributor], 2020. DOI: https://doi.org/10.25828/t155-b289
Metadata production
Producers
| Name | Affiliation | Role |
|---|---|---|
| DataFirst | University of Cape Town | Metadata Producer |
Date of Metadata Production
2020-10-08
DDI Document version
Version 4