{"type":"survey","doc_desc":{"title":"General Household Survey 2010","idno":"DDI_ZAF_2010_GHS_v01_M","producers":[{"name":"DataFirst","abbreviation":"","affiliation":"University of Cape Town","role":"DDI Producer"}],"prod_date":"2011-10-18","version_statement":{"version":"Version 1.0\nVersion 1.1  - Adapted for use by the World Bank Microdata Library - changed study ID to match Microdata Library Standard"}},"study_desc":{"title_statement":{"idno":"ZAF_2010_GHS_v01_M","title":"General Household Survey 2010","alt_title":"GHS 2010"},"authoring_entity":[{"name":"Statistics South Africa","affiliation":""}],"production_statement":{"copyright":"Copyright 2011, Statistics South Africa"},"distribution_statement":{"contact":[{"name":"Manager, DataFirst","affiliation":"University of Cape Town","email":"info@data1st.org","uri":"http:\/\/www.datafirst.uct.ac.za"}]},"series_statement":{"series_name":"Other Household Survey [hh\/oth]"},"version_statement":{"version":"v2.0 Edited, anonymised dataset for public distribution\n\nVersion 1 of the General Household Survey dataset was released on 5 May, 2011.  This version was recalled to allow Statistics SA to undertake further work on the disability data.\nVersion 2 of the dataset, with these adjustments, was released on 3 August 2011.","version_date":"2011"},"study_info":{"topics":[{"topic":"employment [3.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"unemployment [3.5]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"LABOUR AND EMPLOYMENT [3]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"DEMOGRAPHY AND POPULATION [14]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"}],"abstract":"The GHS is an annual household survey, specifically designed to measure various aspects of the living circumstances of South African households. The key findings reported here focus on the five broad areas covered by the GHS, namely: education, health, activities related to work and unemployment, housing and household access to services and facilities.","coll_dates":[{"start":"2010","end":"2010","cycle":""}],"nation":[{"name":"South Africa","abbreviation":"zaf"}],"geog_coverage":"The scope of the General Household Survey 2010 was national coverage.","geog_unit":"The lowest level of geographic aggregations covered by the General Household Survey 2010 is Province.","analysis_unit":"The units of anaylsis for the General Household Survey 2010 are individuals and households.","universe":"The survey covered 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.","data_kind":"Sample survey data [ssd]","notes":"The scope of the General Household Survey 2010 includes:\n \nHousehold characteristics: Dwelling type, home ownership, access to water and sanitation facilities, access to services, transport, household assets, land ownership, agricultural production\nIndividuals' characteristics: demographic characteristics, relationship to household head, marital status, language, education, employment, income, health, fertility, disability, access to social services, mortality."},"method":{"data_collection":{"sampling_procedure":"The sample design for the GHS 2010 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 Surveys (IES).\n\nThe 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 nonmetropolitan 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.\n\nCensus enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used:\n\u2022 Where possible, PSU sizes were kept between 100 and 500 DUs;\n\u2022 EAs with fewer than 25 DUs were excluded;\n\u2022 EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type;\n\u2022 Virtual splits were applied to large PSUs: 500 to 999 split into two; 1 000 to 1 499 split into three; and 1 500 plus split into four PSUs; and\n\u2022 Informal PSUs were segmented.\n\nA randomised-probability-proportional-to-size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.","coll_mode":"Face-to-face [f2f]","research_instrument":"The GHS 2010 questionnaire collected data on:\nHousehold characteristics: Dwelling type, home ownership, access to water and sanitation facilities, access to services, transport, household assets, land ownership, agricultural production\nIndividuals' characteristics: demographic characteristics, relationship to household head, marital status, language, education, employment, income, health, fertility, disability, access to social services, mortality.","weight":"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.\n\nMid-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\u20134, 5\u20139, 10\u201314, 55\u201359, 60\u201364; and 65 and older. The provincial level age groups are 0\u201314, 15\u201334, 35\u201364; 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.\n\nThe 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 imputation was done to retain these records."}},"data_access":{"dataset_use":{"contact":[{"name":"DataFirst","affiliation":"University of Cape Town","email":"info@data1st.org","uri":"http:\/\/www.datafirst.uct.ac.za"}],"cit_req":"Publications based on datasets distributed by DataFirst should acknowledge relevant sources by means of bibliographic citations. To ensure that such source attributions are captured for social science bibliographic utilities, citations must appear in footnotes or in the reference section of publications. The bibliographic citation for this dataset is:\n\nGeneral Household Survey 2010 [dataset]. Pretoria: Statistics South Africa [producer], 2011. Cape Town: DataFirst [distributor],2011.","conditions":"The GHS 2010 dataset is a licensed dataset, accessible under conditions.","disclaimer":"The information products and services of Statistics South Africa are protected in terms of the Copyright Act, 1978 (Act 98 of 1978). As the State President is the holder of State copyright, all organs of State enjoy unhindered use of the Department's information products and services, without a need for further permission to copy in terms of that copyright. Where a copy of the information is made available to any third party outside the State, the third party must be made aware of the existence of State copyright and ownership of the information by the State. The State (through Statistics SA) retains the full ownership of its information, products and services at all times; access to information does not give ownership of the information to the client. \n\nThe 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."}}},"schematype":"survey","data_files":[{"file_id":"F1","file_name":"GHS 2010 House_v2_20111018","description":"The GHS 2010 House_v2_20111018 data file contains household variables for the General Household Survey 2010, from Section 3 and 4 of the survey questionnaire.","case_count":25548,"var_count":224,"producer":null,"data_checks":null,"version":null,"notes":null,"metadata":null},{"file_id":"F2","file_name":"GHS 2010_Person_v2_20111018","description":"The GHS 2010 Person_v2_20111018 data file contains information on household members obtained from the Flap and Section 1 and 2 of the survey questionnaire.","case_count":95918,"var_count":153,"producer":null,"data_checks":null,"version":null,"notes":null,"metadata":null}],"variables":[{"file_id":"F1","vid":"V378","name":"UqNr","var_intrvl":"discrete","var_dcml":"0","var_wgt":null,"var_is_wgt":null,"loc_start_pos":"1","loc_end_pos":"20","loc_width":"20","loc_rec_seg_no":"1","labl":"Unique Household Identifier","var_imputation":null,"var_security":null,"var_resp_unit":null,"var_analysis_unit":null,"var_qstn_preqtxt":null,"var_qstn_qstnlit":null,"var_qstn_postqtxt":null,"var_qstn_ivuinstr":null,"var_universe":null,"var_universe_clusion":null,"var_sumstat":[{"value":"25548","type":"vald","wgtd":null},{"value":"0","type":"invd","wgtd":null}],"var_txt":null,"var_catgry":[],"var_codinstr":null,"var_concept":[],"var_format":{"type":"numeric","schema":"other","category":null,"name":null},"var_notes":null,"var_val_range":{"min":null,"max":null},"fid":"F1"},{"file_id":"F1","vid":"V2","name":"PSU","var_intrvl":"discrete","var_dcml":null,"var_wgt":null,"var_is_wgt":null,"loc_start_pos":"21","loc_end_pos":"31","loc_width":"11","loc_rec_seg_no":"1","labl":"Primary sampling unit","var_imputation":null,"var_security":null,"var_resp_unit":null,"var_analysis_unit":null,"var_qstn_preqtxt":null,"var_qstn_qstnlit":null,"var_qstn_postqtxt":null,"var_qstn_ivuinstr":null,"var_universe":null,"var_universe_clusion":null,"var_sumstat":[{"value":"25548","type":"vald","wgtd":null},{"value":"0","type":"invd","wgtd":null}],"var_txt":null,"var_catgry":[],"var_codinstr":null,"var_concept":[],"var_format":{"type":"character","schema":"other","category":null,"name":null},"var_notes":null,"var_val_range":{"min":null,"max":null},"fid":"F1"},{"file_id":"F1","vid":"V3","name":"Prov","var_intrvl":"discrete","var_dcml":"0","var_wgt":null,"var_is_wgt":null,"loc_start_pos":"32","loc_end_pos":"32","loc_width":"1","loc_rec_seg_no":"1","labl":"South African provinces","var_imputation":null,"var_security":null,"var_resp_unit":null,"var_analysis_unit":null,"var_qstn_preqtxt":null,"var_qstn_qstnlit":null,"var_qstn_postqtxt":null,"var_qstn_ivuinstr":null,"var_universe":null,"var_universe_clusion":null,"var_sumstat":[{"value":"25548","type":"vald","wgtd":null},{"value":"0","type":"invd","wgtd":null}],"var_txt":null,"var_catgry":[{"value":"1","labl":"Western Cape","is_missing":null,"stats":[{"value":"2982","type":"freq","wgtd":null}]},{"value":"2","labl":"Eastern Cape","is_missing":null,"stats":[{"value":"3045","type":"freq","wgtd":null}]},{"value":"3","labl":"Northern Cape","is_missing":null,"stats":[{"value":"1526","type":"freq","wgtd":null}]},{"value":"4","labl":"Free State","is_missing":null,"stats":[{"value":"2319","type":"freq","wgtd":null}]},{"value":"5","labl":"KwaZulu-Natal","is_missing":null,"stats":[{"value":"4121","type":"freq","wgtd":null}]},{"value":"6","labl":"North West","is_missing":null,"stats":[{"value":"2269","type":"freq","wgtd":null}]},{"value":"7","labl":"Gauteng","is_missing":null,"stats":[{"value":"3899","type":"freq","wgtd":null}]},{"value":"8","labl":"Mpumalanga","is_missing":null,"stats":[{"value":"2520","type":"freq","wgtd":null}]},{"value":"9","labl":"Limpopo","is_missing":null,"stats":[{"value":"2867","type":"freq","wgtd":null}]}],"var_codinstr":null,"var_concept":[],"var_format":{"type":"numeric","schema":"other","category":null,"name":null},"var_notes":null,"var_val_range":{"min":"1","max":"9"},"fid":"F1"},{"file_id":"F1","vid":"V4","name":"head_popgrp","var_intrvl":"discrete","var_dcml":"0","var_wgt":null,"var_is_wgt":null,"loc_start_pos":"33","loc_end_pos":"33","loc_width":"1","loc_rec_seg_no":"1","labl":"Population group of household head","var_imputation":null,"var_security":null,"var_resp_unit":null,"var_analysis_unit":null,"var_qstn_preqtxt":null,"var_qstn_qstnlit":"E. 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