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    Home / Data Portal / STATSSA / ZAF-STATSSA-GHS-2006-V1.4
StatsSA

General Household Survey 2006

South Africa, 2006
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Reference ID
zaf-statssa-ghs-2006-v1.4
Producer(s)
Statistics South Africa
Collections
Statistics South Africa
Metadata
Documentation in PDF DDI/XML JSON
Created on
Oct 13, 2011
Last modified
Oct 22, 2020
Page views
92797
Downloads
34332
  • Study Description
  • Data Description
  • Downloads
  • Get Microdata
  • Related Publications
  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Data Collection
  • Questionnaires
  • Data Appraisal
  • Access policy
  • Metadata production

Identification

Survey ID Number
zaf-statssa-ghs-2006-v1.4
Title
General Household Survey 2006
Country
Name Country code
South Africa zaf
Study type
Household Survey [hh]
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 uses old weights that are no longer available for download on Statistics South Africa's website.

Version 1.2:

Version 1.2 includes new weights for comparability across GHS 2002-2008 released at the same time as GHS 2008 (in 2009). 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".

As part of the reweighting, if individuals or household heads have missing values for age, sex or population group, these missing values were imputed. Where imputation could not be managed, these records were discarded. These demographic variables were also renamed.

v1.2 uses the new provincial boundaries for the province variable, as revised by the SA government in 2005. Mismatch in province variable between v1 and v1.2 is to be expected.

There is quality issue with the variable "uqnr" in GHS 2006 v1 files. This was fixed in v1.2.

Version 1.3:

Version 1.3 includes 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.

There is quality issue with the variable "psu" in both v1 and v1.2 files for GHS 2006. This was fixed in v1.3.

In the ghs 2006 tourism file v1.3, the values for the variable "q3125nrn" is labelled differently from tourism file of version 1.2.

There is quality issue with the weight variable in the person file of version 1.3. The person file that was originally given to DataFirst did not match on weight with the later revised person file of the same version.

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 mid-year population estimation in the previous version with a the more recent 2017 series mid-year population estimation as benchmarks for weighting the GHS data files. Household files were weighted independently of person files.

As mentioned in the previous entry of version notes, in the ghs-2006-tourism-v1.3, the values for the variable "q3125nrn" is labelled differently from its previous version v1.2. This was fixed in v1.4 tourism file. As a result, "q3125nrn" variable in tourism file v1.2 is identical to that in tourism file v1.4, but both of them are different from that in v1.3.

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

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

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
2006-07 2006-07
Data Collection Mode
Face-to-face [f2f]

Questionnaires

Questionnaires
GHS uses questionnaires as data collection instruments

Data Appraisal

Data Appraisal
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.

Access policy

Contacts
Name Affiliation Email URL
Manager, DataFirst University of Cape Town support@data1st.org Link
Access conditions
Public use files, available to all
Citation requirements
Statistics South Africa. General Household Survey 2006 [dataset]. Version 1.4. Pretoria. Statistics South Africa [producer]. 2017. Cape Town. DataFirst [distributor], 2020. DOI: https://doi.org/10.25828/xjc1-fg13
Access authority
Name Affiliation Email URL
DataFirst University of Cape Town support@data1st.org Link

Metadata production

Producers
Name Affiliation Role
DataFirst University of Cape Town Metadata Producer
Date of Metadata Production
2020-10-10
DDI Document version
Version 3
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