General Household Survey 2013
South Africa, 2013
Statistics South Africa
Created on
November 22, 2020
Last modified
November 22, 2020
Page views
55896
Download
7978
Documentation in PDF
Metadata
DDI/XML
JSON
Identification
Survey ID Number
zaf-statssa-ghs-2013-v1.2
Title
General Household Survey 2013
Country
| Name | Country code |
|---|---|
| South Africa | zaf |
Study type
Household Survey [hh]
Series Information
Statistics South Africa. General Household Survey 2013 [dataset]. Version 1.2. Pretoria: Statistics South Africa [producer], 2017. Cape Town. DataFirst [distributor], 2020. DOI: https://doi.org/10.25828/a704-wm31
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, health and social development, housing, household access to services and facilities, food security, and agriculture.
Kind of Data
Sample survey data
Unit of Analysis
Households and individuals
Version
Version Description
v1.2: Edited, anonymised dataset for public distribution
Version Date
2017
Version Notes
Version 1:
Weights in General Household Survey 2013 v1 are based on figures provided by the 2013 mid-year population estimation model that incorporates the demographic findings of Census 2012. Household files were weighted independently of person files.
Version 1.1:
GHS 2013 version 1.1 includes revised weights. This version was 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.
In the version 1.1 of the GHS 2013 household file, the variable "UqNr" (unique identifier for households) does not uniquely identify households.
Version 1.2:
As noted in the version note for v1.1, the household identifier in the household file does not uniquely identify households. This was fixed by DataFirst. The new household file has therefore been versioned at v1.2. Note that DataFirst version at file level.
In the household file v1.2, you can find two identifiers for the households. The first one is called “UqNr” - this is the revised and unique household identifier. The second one is called “UqNr_error”, this is the erroneous uqnr that does not uniquely identify the GHS households. Both variables are included in the datafile for users. For more information, please contact DataFirst.
Weights in General Household Survey 2013 v1 are based on figures provided by the 2013 mid-year population estimation model that incorporates the demographic findings of Census 2012. Household files were weighted independently of person files.
Version 1.1:
GHS 2013 version 1.1 includes revised weights. This version was 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.
In the version 1.1 of the GHS 2013 household file, the variable "UqNr" (unique identifier for households) does not uniquely identify households.
Version 1.2:
As noted in the version note for v1.1, the household identifier in the household file does not uniquely identify households. This was fixed by DataFirst. The new household file has therefore been versioned at v1.2. Note that DataFirst version at file level.
In the household file v1.2, you can find two identifiers for the households. The first one is called “UqNr” - this is the revised and unique household identifier. The second one is called “UqNr_error”, this is the erroneous uqnr that does not uniquely identify the GHS households. Both variables are included in the datafile for users. For more information, please contact DataFirst.
Scope
Notes
The scope of GHS includes:
Demographic information: name, sex, age, population group, etc.
Biographic information: education, health, disability, welfare
Tourism information: non-remunerated trips undertaken in the 12 months prior to the survey.
Household information: type of dwelling, ownership of dwelling and other assets, electricity, water and sanitation, environmental issues, services, transport, expenditure etc.
Demographic information: name, sex, age, population group, etc.
Biographic information: education, health, disability, welfare
Tourism information: non-remunerated trips undertaken in the 12 months prior to the survey.
Household information: type of dwelling, ownership of dwelling and other assets, electricity, water and sanitation, environmental issues, services, transport, expenditure etc.
Coverage
Geographic Coverage
The survey is representative at national level and at provincial level.
Geographic Unit
The lowest level of geographic aggregations is province. The information of geo-type and metro is also present in the data.
Universe
The survey covers 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 student hostels, old age homes, hospitals, prisons and military barracks.
Producers and sponsors
Primary investigators
| Name |
|---|
| Statistics South Africa |
Sampling
Sampling Procedure
The sample design for the GHS 2013 was based on a master sample (MS) that was originally designed for the Quarterly Labour Force Survey (QLFS) and was used for the first time for the GHS in 2008. This master sample is shared by the QLFS, GHS, Living Conditions Survey (LCS), Domestic Tourism Survey (DTS) and the Income and Expenditure Survey (IES).
The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of primary sampling units (PSUs) from within strata, and systematic sampling of dwelling units (DUs) from the sampled PSUs. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income.
The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of primary sampling units (PSUs) from within strata, and systematic sampling of dwelling units (DUs) from the sampled PSUs. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income.
Weighting
The sampling weights for the data collected from the sampled households were constructed so that the responses could be properly expanded to represent the entire civilian population of South Africa. The design weights, which are the inverse sampling rate (ISR) for the province, are assigned to each of the households in a province. These were adjusted for four factors: Informal PSUs, Growth PSUs, Sample Stabilisation, and Non-responding Units.records.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2013-01 | 2013-12 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
The General Household Survey was conducted in July of each year from 2002 to 2008. From 2009-2012 the data was collected between July-September. From 2013 onwards Statistics South Africa changed their Social Statistics surveys to continuous collection (January-December) to better account for seasonality in surveys such as the Domestic Tourism Survey, use resources more efficiently, and work towards
greater integration of the GHS with, for example the Living Conditions Survey and the Income and Expenditure Survey. In the case of collection taking place over more than one month, bench-marking would take place to the middle of that period, e.g. July - September collection was benchmarked to mid-August. January - December collection would be benchmarked to the mid-year estimates.
greater integration of the GHS with, for example the Living Conditions Survey and the Income and Expenditure Survey. In the case of collection taking place over more than one month, bench-marking would take place to the middle of that period, e.g. July - September collection was benchmarked to mid-August. January - December collection would be benchmarked to the mid-year estimates.
Data Collectors
| Name |
|---|
| Statistics South Africa |
Questionnaires
Questionnaires
GHS uses questionnaires as data collection instruments
Data Appraisal
Data Appraisal
In GHS 2009-2015:
The variable on land size in the General Household Survey questionnaire for 2009-2015 should be used with caution. The data comes from questions on the households' agricultural activities in Section 8 of the GHS questionnaire: Household Livelihoods: Agricultural Activities. Question 8.8b asks:
“Approximately how big is the land that the household use for production? Estimate total area if more than one piece.” One of the response category is worded as:
1 = Less than 500m2 (approximately one soccer field)
However, a soccer field is 5000 m2, not 500, therefore response category 1 is incorrect. The correct category option should be 5000 sqm. This response option is correct for GHS 2002-2008 and was flagged and corrected by Statistics SA in the GHS 2016.
The variable on land size in the General Household Survey questionnaire for 2009-2015 should be used with caution. The data comes from questions on the households' agricultural activities in Section 8 of the GHS questionnaire: Household Livelihoods: Agricultural Activities. Question 8.8b asks:
“Approximately how big is the land that the household use for production? Estimate total area if more than one piece.” One of the response category is worded as:
1 = Less than 500m2 (approximately one soccer field)
However, a soccer field is 5000 m2, not 500, therefore response category 1 is incorrect. The correct category option should be 5000 sqm. This response option is correct for GHS 2002-2008 and was flagged and corrected by Statistics SA in the GHS 2016.
Access policy
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst | University of Cape Town | support@data1st.org | http://support.data1st.org |
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst Helpdesk | University of Cape Town | support@data1st.org | http://support.data1st.org/ |
Access conditions
Public use files, available to all
Citation requirements
Statistics South Africa. General Household Survey 2013 [dataset]. Version 1.2. Pretoria: Statistics South Africa [producer], 2017. Cape Town. DataFirst [distributor], 2020. DOI: https://doi.org/10.25828/a704-wm31
Metadata production
Producers
| Name | Affiliation | Role |
|---|---|---|
| DataFirst | University of Cape Town | Metadata Producer |
Date of Metadata Production
2020-11-22
DDI Document version
Version 5