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agricultural-surveys

General Household Survey 2016

South Africa, 2016
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Reference ID
ZAF_2016_GHS_v01_EN_M_v01_A_OCS
Producer(s)
Statistics South Africa
Collections
Agricultural Surveys
Metadata
Documentation in PDF DDI/XML JSON
Created on
Oct 13, 2020
Last modified
Oct 13, 2020
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  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Identification
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Data collection
  • Data appraisal
  • Data Access
  • Disclaimer and copyrights
  • Contacts
  • Metadata production
  • Identification

    Survey ID number

    ZAF_2016_GHS_v01_EN_M_v01_A_OCS

    Title

    General Household Survey 2016

    Country
    Name Country code
    South Africa ZAF
    Study type

    Living Standards Measurement Study [hh/lsms]

    Abstract

    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.

    Kind of Data

    Sample survey data [ssd]

    Unit of Analysis

    Households

    Scope

    Notes

    The scope of the General Household Survey 2016 includes:

    (a) HOUSEHOLD CHARACTERISTICS:
    Dwelling type
    Home ownership
    Access to water and sanitation
    Access to services
    Transport
    Household assets
    Land ownership
    Agricultural production

    (b) INDIVIDUALS' CHARACTERISTICS:
    Demographic characteristics
    Relationship to household head
    Marital status
    Language
    Education
    Employment
    Income
    Health
    Fertility
    Disability
    Access to social services
    Mortality

    Topics
    Topic Vocabulary
    Agriculture & Rural Development FAO
    Land (policy, resource management) FAO
    Financial Sector FAO
    Access to Finance FAO
    Health FAO
    Population & Reproductive Health FAO
    Water FAO

    Coverage

    Geographic Coverage

    National

    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

    From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

    The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

    Weighting

    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 collection

    Dates of Data Collection
    Start End
    2016-01 2016-12

    Data appraisal

    Data Appraisal

    Please note that DataFirst provides versioning at dataset and file level. Revised files have new version numbers. Files that are not revised retain their original version numbers. Changes to any of the data files will result in the dataset having a new version number. Thus, version numbers of files within a dataset may not match.

    Data Access

    Confidentiality
    Is signing of a confidentiality declaration required? Confidentiality declaration text
    yes https://microdata.worldbank.org/index.php/terms-of-use
    Access conditions

    Public use files, available to all.

    Citation requirements

    Statistics South Africa. 2017. General Household Survey 2016 [dataset]. Version 1.1. Pretoria: Statistics SA [producer], 2017. Cape Town: DataFirst [distributor], 2017.

    Disclaimer and copyrights

    Disclaimer

    The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses

    Contacts

    Contacts
    Name Affiliation Email URL
    DataFirst Helpdesk University of Cape Town [email protected] www.support.data1st.org/

    Metadata production

    DDI Document ID

    DDI_ZAF_2016_GHS_v01_EN_M_v01_A_OCS_FAO

    Producers
    Name Affiliation Role
    Office of Chief Statistician Food and Agriculture Organization Adoption of metadata for FAM
    DataFirst University of Cape Town Metadata producer

    Metadata version

    DDI Document version

    ZAF_2016_GHS_v01_EN_M_v01_A_OCS_v01

    Back to Catalog
    Food and Agriculture Organization of the United Nations

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