{"type":"survey","doc_desc":{"title":"Labour Force Survey 2000, September","idno":"DDI_ZAF_2000_LFS-SEP_v02_M","producers":[{"name":"DataFirst","abbreviation":"","affiliation":"University of Cape Town","role":"DDI Producer"}],"prod_date":"2011-11-17","version_statement":{"version":"Version 01 (July2012) - Adapted from the DDI \"ddi-zaf-datafirst-lfs-2000-sep-v1.1\" received from Data First."}},"study_desc":{"title_statement":{"idno":"ZAF_2000_LFS-SEP_v02_M","title":"Labour Force Survey 2000","sub_title":"September","alt_title":"LFS 2000_2"},"authoring_entity":[{"name":"Statistics South Africa","affiliation":""}],"production_statement":{"copyright":"Copyright, 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":"Labor Force Survey [hh\/lfs]"},"version_statement":{"version":"v2.1: Edited, anonymised data, dataset for licensed distribution","version_date":"2011","version_notes":"The South African September 2000 LFS dataset was originally released in 2001 as 4 data files (household, worker, person and stratum\\_psu). A second version was downloaded from the Statistics South Africa website subsequent to that in March 2006 by DataFirst. This version differed slightly from the originally obtained release. Most notably, weights were recast to reflect population estimates released in February 2005. This version was also benchmarked to the 2001 South African census (whereas previously it had been benchmarked to the 1996 South African census). As a result, the weight variables in each data file differ between versions 1.0 and 2.0. The second version (version 2.0) also has several extra observations. The source of these extra data is unclear. Specifically,\n\n1) 31 extra observations are in the household data file\n2) 1 extra observation are in the person data file\n3) 18 extra observations are in the worker data file\n\nA third version (version 2.1) was downloaded by DataFirst on 11 August 2011 as 3 data files (the other three data files subsumed the, originally separately released, stratum\\_psu datafile) which differed slightly from version 2.0 in the following ways:\n\n1) The suffix \"\\_Sep2000\" no longer appears on all variable names\n2) Year and Month variables were added\n3) Variable labels were altered. Previously, all variable labels were literal questions. Now the variable labels describe the variables.\n4) A number of variables were renamed (beyond dropping the suffix \u201c\\_Sep2000\u201d). For example, Q710Lght\\_Sep2000 in version 2.0 is now Q710Ligh in version 2.1. This could prove confusing when comparing between current and previous versions of the data file(s).\n5) Version 2.1 and 2.0 also have some substantive differences:\n\nThe most significant of these is the apparent switch of one of the variable names and labels in the household\/general data files. To clarify, Question 7.25 in the LFS Household questionnaire pertains to proximity to transport. Version 1.1 has entries for question 7.25a that relate respondent proximity to trains, but in the later version this variable relates proximity to taxis. The same is true for question 7.25b (i.e. the converse is also true). Summarily, the data relating respondent proximity to trains and taxis has been muddled up in version 2.0. This mistake would seem to be within version 2.0 only, as version 2.1 agrees with the original (version 1.0).\n\nFurthermore, the variable reflecting the way in which the household receives mail (in the household data file) in version 2.0 has no value labels and does not match up with the values in version 2.1. Version 2.1 aggregates the value labels of version 2.0 in groups of 10. For example, in version 2.0 there are variables labelled 11, 12 and 19, which are grouped into decades in version 2.1. So entries of 11, 12 and 19 all take on the value 1 in the later version. In version 2.0, the sum of the number of observations within decades equals the sum of observations equal to 1 in version 2.0 (value label: \"Delivered to the dwelling\"). It is unclear as to the source of the distinction between these variables (it may be arbitrary, an artifact of ASCII to STATA conversion for example).\n\nThe South African September 2000 LFS dataset was originally released in 2001 as 4 data files (household, worker, person and stratum psu). A second version was downloaded from the Statistics South Africa website subsequent to that in March 2006 by DataFirst. This version differed slightly from the originally obtained release. Most notably, weights were recast to reflect population estimates released in February 2005. This version was also benchmarked to the 2001 South African census (whereas previously it had been benchmarked to the 1996 South African census). As a result, the weight variables in each data file differ between versions 1.0 and 2.0. The second version (version 2.0) also has several extra observations. The source of these extra data is unclear. Specifically,\n\n \u2022 31 extra observations are in the household data file\n \u2022 1 extra observation are in the person data file\n \u2022 18 extra observations are in the worker data file\n\nA third version (version 2.1) was downloaded by DataFirst on 11 August 2011 as 3 data files (the other three data files subsumed the, originally separately released, stratum psu datafile) which differed slightly from version 2.0 in the\nfollowing ways:\n\n 1. The suffix \u201d Sep2000\u201d no longer appears on all variable names\n 2. Year and Month variables were added\n 3. Variable labels were altered. Previously, all variable labels were literal questions. Now the variable labels describe the variables.\n 4. A number of variables were renamed (beyond dropping the suffix Sep2000). For example, Q710Lght Sep2000 in version 2.0 is now Q710Ligh in version 2.1. This could prove confusing when comparing between current and previous versions of the data file(s).\n\nVersion 2.1 and 2.0 also have some substantive differences:\n\nHousehold\/general data file\nThe most significant of these is the apparent switch of one of the variable names and labels in the household\/general data files. To clarify, Question 7.25 in the LFS Household questionnaire pertains to proximity to transport. Version 1.1 has entries for question 7.25a that relate respondent proximity to trains, but in the later version this variable relates proximity to taxis. The same is true for question 7.25b (i.e. the converse is also true). Summarily, the data relating respondent proximity to trains and taxis has been muddled up in version 2.0. This mistake would seem to be within version 2.0 only, as version 2.1 agrees with the original (version 1.0).\n\nFurthermore, the variable reflecting the way in which the household receives mail (in the household data file) in version 2.0 has no value labels and does not match up with the values in version 2.1. Version 2.1 aggregates the value labels\nof version 2.0 in groups of 10. For example, in version 2.0 there are variables labelled 11, 12 and 19, which are grouped into decades in version 2.1. So entries of 11, 12 and 19 all take on the value 1 in the later version. In version 2.0, the sum of the number of observations within decades equals the sum of observations equal to 1 in version 2.0 (value label: \u201dDelivered to the dwelling\u201d). It is unclear as to the source of the distinction between these variables (it may be arbitrary, an artifact of ASCII to STATA conversion for example)."},"study_info":{"topics":[{"topic":"employment [3.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"in-job training [3.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"labour relations\/conflict [3.3]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"retirement [3.4]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"unemployment [3.5]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"working conditions [3.6]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"LABOUR AND EMPLOYMENT [3]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"TRADE, INDUSTRY AND MARKETS [2]","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 LFS is a twice-yearly rotating panel household survey, specifically designed to measure the dynamics of employment and unemployment in South Africa. It measures a variety of issues related to the labour market,including unemployment rates (official and expanded), according to standard definitions of the International Labour Organisation (ILO).\n\nAll editions of the LFS have been updated (some more than once) since their release. These version changes are detailed in a document available from DataFirst (in the \"external documents\" section titled \"LFS 2000-2008 Collated Version Notes on the South African LFS\").","coll_dates":[{"start":"2000-09","end":"2000-09","cycle":""}],"nation":[{"name":"South Africa","abbreviation":"zaf"}],"geog_coverage":"National Coverage","geog_unit":"Province (variable name: \"Prov\")","analysis_unit":"Households (dwellings) and individuals","universe":"The LFS sample covers the non-institutional population except for workers' hostels. However, persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.","data_kind":"Sample survey data [ssd]","notes":"Household characteristics, household listing, demographics, education, economic activity, work for pay, business ownership, unemployment, employers, main work activity in the past week, wages, salary, employment, migration"},"method":{"data_collection":{"sampling_procedure":"The LFS is a twice-yearly rotating panel household survey. A rotating panel sample involves visiting the same dwelling units on a number of occasions (in this instance, five at most), and replacing a proportion of these dwelling units each round. New \ndwelling units are added to the sample to replace those that are taken out. The pilot round of LFS fieldwork took place in February 2000, based on a probability sample of 10 000 dwelling units. This survey took place six months later, using a larger probability sample of 30,000 dwelling units. Among the 10,000 households visited in February, approximately 40% were re-visited in September 2000. The fieldworkers had some difficulty in identifying certain dwelling units in the sample, particularly in those areas where there are no addresses.\n\nThe Master Sample is based on the 1996 Population Census of enumeration areas (EA) and the estimated number of dwelling units from the 1996 Population Census. All 3000 PSUs included in the Master Sample were used in the Labour Force Survey. A PSU is either one EA or several EAs when the number of dwelling units in the base or originally selected EA was found to have less than 100 dwelling units. Each EA had to have approximately 150 dwelling units but it was discovered that many contained less. Thus, in some cases, it has been found necessary to add EAs to the original (census) EA to ensure that the minimum requirement of 100 dwellings, in the first stage of forming the PSUs, was met. The size of the PSUs in the Master Sample varied from 100 to 2445 dwelling units. Special dwellings such as prisons, hospitals, boarding houses, hotels, guest houses (whether catering or self-catering), schools and churches were excluded from the sample.\n\nExplicit stratification of the PSUs was done by province and area type (urban\/rural). Within each explicit stratum, the PSUs were implicitly stratified by District Council, Magisterial District and, within the magisterial district, by average household income (for formal urban areas and hostels) or EA. The allocated number of EAs was systematically selected with \"probability proportional to size\" in each stratum. Once the PSUs included in the sample were known, their boundaries had to be identified on the ground. After boundary identification, the next stage was to list accurately all the dwelling units in the PSUs. \n\nThe second stage of the sample selection was to draw from the dwelling units listing whereby a systematic sample of 10 dwelling units was drawn from each PSU. As a result, approximately 30,000 households (units) were interviewed. However, if there was growth of more than 20% in a PSU, then the sample size was increased systematically according to the proportion of growth in the PSU.","coll_mode":"Face-to-face [f2f]","research_instrument":"Data collected includes data on households and person data (via the Flap and Section 1 of the questionnaire), worker data on persons 15-65 years (Sections 2, 3, 4 and 5). worker data collected includes labour market data, including employment in both the formal and informal sectors, and data on unemployment. Most questions in the Labour Force Survey questionnaire are pre-coded, i.e. there is a set number of choices from which one or more must be selected. Post-coding was done for open-ended questions.","weight":"The initial weights (household weights), based on the sample design, were equal to the inverse of the probability of selection. The initial weight for each member of the household was the same as the weight for the household itself. Further adjustment factors were then calculated within PSUs to account for non-response. To adjust for under-enumeration and to align survey estimates with independent population estimates, the weights were calibrated against Person benchmarks. A software package called CALMAR was used to perform this calibration. Using an iterative procedure, CALMAR adjusted the weights so that Person estimates conformed as closely as possible to external Person benchmarks. Gender, race and age group parameters were used for the Person cross-classification of the population.\n\nStats SA revised their population model to produce mid-year population estimates in the light of mortality data released in 2005 (see Stats SA Statistical Release P0309.3, 2005). The benchmarks for the LFS discussed in this statistical release have been adjusted accordingly. Weights were then adjusted according to those 2005 population estimates."}},"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":"Statistics South Africa. Labour Force Survey, September 2000. [dataset]. Version 2.1. Pretoria: Statistics South Africa [producer], 2001. Cape Town: DataFirst [distributor], 2011.","conditions":"Licensed dataset, accessible under conditions","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."}}},"schematype":"survey","data_files":[{"file_id":"F5","file_name":"LFS 2000_2 House_v2","description":null,"case_count":26648,"var_count":68,"producer":null,"data_checks":null,"version":null,"notes":null,"metadata":null},{"file_id":"F6","file_name":"LFS 2000_2 Person_v2","description":null,"case_count":105370,"var_count":41,"producer":null,"data_checks":null,"version":null,"notes":null,"metadata":null},{"file_id":"F7","file_name":"LFS 2000_2 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