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General Household Survey 2015

South Africa, 2015
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Reference ID
ZAF_2015_GHS_v01_M
Producer(s)
Statistics South Africa
Metadata
DDI/XML JSON
Created on
Jun 26, 2017
Last modified
Jun 26, 2017
Page views
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  • Study Description
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  • Identification
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  • Coverage
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  • Sampling
  • Survey instrument
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  • Identification

    Survey ID number

    ZAF_2015_GHS_v01_M

    Title

    General Household Survey 2015

    Country
    Name Country code
    South Africa zaf
    Study type

    Other Household Survey [hh/oth]

    Series Information

    The GHS is an annual household survey conducted by Stats SA since 2002. The survey replaced the October Household Survey (OHS) which was introduced in 1993 and was terminated in 1999.
    The survey is an omnibus household-based instrument aimed at determining the progress of development in the country. It measures, on a regular basis, the performance of programmes as well
    as the quality of service delivery in a number of key service sectors in the country. The GHS covers six broad areas, namely education, health and social development, housing, household access to services and facilities, food security, and agriculture.

    Abstract

    The GHS is an annual household survey conducted by Stats SA since 2002. The survey replaced the October Household Survey (OHS) which was introduced in 1993 and was terminated in 1999.
    The survey is an omnibus household-based instrument aimed at determining the progress of development in the country. It measures, on a regular basis, the performance of programmes as well
    as the quality of service delivery in a number of key service sectors in the country. The GHS covers six broad areas, namely education, health and social development, housing,
    household access to services and facilities, food security, and agriculture. This report has three main objectives: firstly, to present the key findings of GHS 2015. Secondly, it provides trends across a fourteen year period, i.e. since the GHS was introduced in 2002; and
    thirdly, it provides a more in-depth analysis of selected service delivery issues. As with previous reports, this report will not include tables with specific indicators measured, as these will be included in a more comprehensive publication of development indicators, entitled Selected development
    indicators (P0318.2).

    Kind of Data

    Sample survey data [ssd]

    Unit of Analysis

    The units of anaylsis for the General Household Survey 2015 are individuals and households.

    Version

    Version Description

    v1.0: Edited, anonymised dataset for public distribution
    DDI obtained from DataFrist, UCT, South Africa: ddi-zaf-datafirst-ghs-2015-v1

    Version Date

    2016-09-20

    Version Notes

    Version 1 of the General Household Survey 2015 was acquired from the Statistics South Africa on the 7th of June 2016. Version 1.1 is this dataset, with value and variable labels added by DataFirst.

    Scope

    Notes

    The scope of the General Household Survey 2015 includes:

    Education, health, disability, social security, religious affiliation and observance, housing, energy, access to and use of water and sanitation, environment, refuse removal, telecommunications, transport, household income, access to food, and agriculture. Some
    topic covered such as religious affiliation and observance are totally new, whilst others, such as education, were deepened by focusing on access to work- and textbooks.

    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

    Topics
    Topic Vocabulary URI
    employment [3.1] CESSDA http://www.nesstar.org/rdf/common
    unemployment [3.5] CESSDA http://www.nesstar.org/rdf/common
    LABOUR AND EMPLOYMENT [3] CESSDA http://www.nesstar.org/rdf/common
    DEMOGRAPHY AND POPULATION [14] CESSDA http://www.nesstar.org/rdf/common

    Coverage

    Geographic Coverage

    The General Household Survey 2015 had national coverage.The lowest level of geographic aggregation for this dataset is Province and Metro.

    Geographic Unit

    The lowest level of geographic aggregation for the data is Province and, within the Provinces, at the level of Metropolitan and Non-Metropolitan Area. StatsSA used a new master sample from GHS 2015. This is weighted to metro level and data is provided at this level (data for earlier years is only reliable at the level of Province).

    Universe

    The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers’ hostels. The survey does not cover other collective living quarters such as students’ hostels, old-age homes, hospitals, prisons and military barracks, and is therefore
    only representative of non-institutionalised and non-military persons or households in South Africa.

    Producers and sponsors

    Primary investigators
    Name Affiliation
    Statistics South Africa Government of South Africa

    Sampling

    Sampling Procedure

    The General Household Survey (GHS) uses the Master Sample frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys having design requirements that are reasonably compatible with the GHS.
    The GHS 2015 collection was based on the 2013 Master Sample.
    This 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.

    Caution must be exercised when interpreting the results of the GHS at low levels of disaggregation. The sample and reporting are based on the provincial boundaries as defined in December/January 2006.
    These new boundaries resulted in minor changes to the boundaries of some provinces, especially Gauteng, North West, Mpumalanga, Limpopo, Eastern Cape and Western Cape.
    In previous reports the sample was based on the provincial boundaries as defined in 2001, and there will therefore be slight comparative differences in terms of provincial boundary definitions.

    Details of the sampling proceedure can be found in Report No. P0318 available from Statistics Souoth Africa and attached to this Survey as an external resource.

    Response Rate

    Province / Metropolitan Area Response Rates
    National 90,48
    Western Cape 91,67
    Non Metro 93,17
    City of Cape Town 91,03
    Eastern Cape 94,77
    Non Metro 96,66
    Buffalo City 92,54
    Nelson Mandela Bay 89,52
    Northern Cape 95,00
    Free State 95,00
    Non Metro 95,37
    Mangaung 94,07
    KwaZulu-Natal 95,23
    Non Metro 96,58
    eThekwini 92,87
    North West 94,99
    Gauteng 78,01
    Non Metro 93,62
    Ekurhuleni 81,76
    City of Johannesburg 71,11
    City of Tshwane 75,47
    Mpumalanga 97,24
    Limpopo 98,83

    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 (of Stats SA) 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 a way 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 levels were used for the cells defined by cross-classification of Age by Gender and Race (i.e. population group).
    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 imputation was done to retain these records

    Survey instrument

    Questionnaires

    A single survey was adminsitered for each household.

    Teh Questionnaire comprises the following main sections:

    A: Particulars of the dwelling
    B: Households at the selected dwelling unit
    C: Field staff
    D: Survey period
    E: Response details

    Section 1: Household Specific Functioning
    Section 2: Health and General Functioning
    Section 3: Social Security and Religion
    Section 4: Economic Activities
    Section 5: General Household Information and Service Delivery
    Section 6: Communication and Transport
    Section 7: Health, welfare and Food Security
    Section 8: Household Livelihoods
    Section 9: Mortality in the last 12 months
    Section 10: Interviewer summary section

    Data collection

    Dates of Data Collection
    Start End
    2015-01 2015-12

    Data Access

    Access authority
    Name Affiliation URL Email
    DataFirst University of Cape Town http://www.support.datafirst.uct.ac.za support@data1st.org
    Access conditions

    Public use data, available to all.

    Users may apply or process this data, provided Statistics South Africa (Stats SA) is acknowledged as the original source of the data; that it is specified that the application and/or analysis is the result of the user's independent
    processing of the data; and that neither the basic data nor any reprocessed version or application thereof may be sold or offered for sale in any form whatsoever without prior permission from Stats SA.

    Citation requirements

    Statistics South Africa. General Household Survey 2015 [dataset]. Version 1.1. Pretoria: Statistics South Africa [producer], 2016. Cape Town: DataFirst [distributor], 2016.

    Disclaimer and copyrights

    Disclaimer

    The use of any data is subject to acknowledgement of Stats SA as the supplier and owner of copyright. Statistics South Africa (Stats SA) will not be liable for any damages or losses, except to the extent that such losses or damages are attributable to a breach by Stats SA of its obligations in terms of an existing agreement or to the negligence or wilful act or omissions of the Stats SA, its servants or agents, arising out of the supply of data and or digital products in terms of that agreement. The user indemnifies Stats SA against any claims of whatsoever nature (including legal costs) by third parties arising from the reformatting, restructuring, reprocessing and/or addition of the data, by the user.

    Copyright

    Copyright 2015, Statistics South Africa

    Contacts

    Contacts
    Name Affiliation Email URL
    DataFirst Helpdesk University of Cape Town support@data1st.org http://support.data1st.org/
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