General Household Survey 2014
South Africa, 2014
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Reference ID
zaf-statssa-ghs-2014-v1.1
Producer(s)
Statistics South Africa
Metadata
Created on
Jul 01, 2015
Last modified
Dec 14, 2021
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64271
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10750
Identification
Survey ID Number
zaf-statssa-ghs-2014-v1.1
Title
General Household Survey 2014
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, 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
v1.1: Edited, anonymised dataset for public distribution.
Version Date
2017
Version Notes
Version 1:
Weights in General Household Survey 2014 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.
DataFirst added value labels to geotype variables in v1 person and house files. StatsSA released the data file without their value labels: 1 -“Urban formal” 2- “Urban informal” 4 “tribal areas” 5 “rural formal”
Version 1.1:
GHS 2014 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 person file v1.1, the values for "personnr" 1-9 in v1 became 01-09 in v1.1.
In the house file v1.1, the value labels for q530cut was fixed.
Weights in General Household Survey 2014 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.
DataFirst added value labels to geotype variables in v1 person and house files. StatsSA released the data file without their value labels: 1 -“Urban formal” 2- “Urban informal” 4 “tribal areas” 5 “rural formal”
Version 1.1:
GHS 2014 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 person file v1.1, the values for "personnr" 1-9 in v1 became 01-09 in v1.1.
In the house file v1.1, the value labels for q530cut was fixed.
Scope
Notes
The scope of the General Household Survey 2014 includes:
Household characteristics: Dwelling type, home ownership, access to water and sanitation, 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, fertility, disability, access to social services, mortality.
Household characteristics: Dwelling type, home ownership, access to water and sanitation, 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, fertility, disability, access to social services, mortality.
Coverage
Geographic Coverage
The General Household Survey 2014 had national coverage.
Geographic Unit
The lowest level of geographic aggregations covered by the General Household Survey 2014 is Province.
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 | Affiliation |
|---|---|
| Statistics South Africa | Government of South Africa |
Sampling
Sampling Procedure
The sample design for the GHS 2014 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.
Mid-year population estimates produced by the Demographic Analysis division were used for benchmarking. The final survey weights were constructed using regression estimation to calibrate to national level population estimates cross-classified by 5-year age groups, gender and race, and provincial population estimates by broad age groups. The 5-year age groups are: 0–4, 5–9, 10–14, 55–59, 60–64; and 65 and older. The provincial level age groups are 0–14, 15–34, 35–64; and 65 years and older. The calibrated weights were constructed in such away that all persons in a household would have the same final weight. These weights were later recalibrated.
Mid-year population estimates produced by the Demographic Analysis division were used for benchmarking. The final survey weights were constructed using regression estimation to calibrate to national level population estimates cross-classified by 5-year age groups, gender and race, and provincial population estimates by broad age groups. The 5-year age groups are: 0–4, 5–9, 10–14, 55–59, 60–64; and 65 and older. The provincial level age groups are 0–14, 15–34, 35–64; and 65 years and older. The calibrated weights were constructed in such away that all persons in a household would have the same final weight. These weights were later recalibrated.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2014-01 | 2014-12 |
Data Collection Mode
Face-to-face [f2f]
Questionnaires
Questionnaires
Questionnaire
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 conditions
Public use files, available to all
Citation requirements
Statistics South Africa. General Household Survey 2014 [dataset]. Version 1.1. Pretoria: Statistics South Africa [producer], 2017. Cape Town. DataFirst [distributor], 2018. DOI: https://doi.org/10.25828/nkvx-r352
Access authority
| Name | Affiliation | 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
2021-12-14
DDI Document version
Version 6