zaf-statssa-ghs-2016-v1.1
General Household Survey 2016
Name | Country code |
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South Africa | zaf |
Household Survey [hh]
The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.
Sample survey data [ssd]
Households and individuals
v1.1: Edited, anonymised dataset for public distribution
2018
Version1:
Weights in General Household Survey 2016 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.
Person file contains 2 duplicate persons - uqnr: they are person number 7 from house “361101460000026201” and person 06 from house “593101670000005401”.
Version 1.1:
GHS 2016 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.
Apart from reweighting, the following changes were made by StatsSA in v1.1:
The scope of the General Household Survey 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, mortality, disability, access to social services
The General Household Survey has national coverage.
The lowest level of geographic aggregation for the data is Province (and metropolitan municipality, where this applies)
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.
Name | Affiliation |
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Statistics South Africa | Government of South Africa |
The sample design for the GHS 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 sample weights were constructed in order to account for the following: the original selection probabilities (design weights), adjustments for PSUs that were sub-sampled or segmented, excluded population from the sampling frame, non-response, weight trimming, and benchmarking to known population estimates from the Demographic Analysis Division within Stats SA.
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.
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 over. The provincial level age groups are 0–14, 15–34, 35–64; and 65 years and over. The calibrated weights were constructed such that all persons in a household would have the same final weight.
The Statistics Canada software StatMx was used for constructing calibration weights. The population controls at national and provincial level were used for the cells defined by cross-classification of Age by Gender by Race. Records for which the age, population group or sex had item non-response could not be weighted and were therefore excluded from the dataset. No additional imputation was done to retain these records.
Household estimates that were developed using the UN headship ratio methodology were used to weight household files. The databases of Census 1996, Census 2001, Community Survey 2007 Census 2011 were used to analyse trends and develop models to predict the number of households for each year. The weighting system was based on tables for the expected distribution of household heads for specific age categories, per population group and province.
Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.
Start | End |
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2016-01 | 2016-12 |
Name | Affiliation | URL | |
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DataFirst | University of Cape Town | www.support.datafirst.org | support@data1st.org |
Public access data, available to all
Statistics South Africa. General Household Survey 2016 [dataset]. Version 1.1. Pretoria: Statistics SA [producer], 2017. Cape Town: DataFirst [distributor], 2017. DOI: https://doi.org/10.25828/ka3w-rg96
Copyright 2014, Statistics South Africa
ddi-zaf-datafirst-ghs-2016-v1.1
Name | Affiliation | Role |
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DataFirst | University of Cape Town | Metadata Producer |
2021-12-14
Version 5