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Spatial aspects of unemployment in South Africa 1991-2011 (UNEMPL): Municipalities - All provinces

Version
1.0
Resource Type
Dataset
Creator
  • Weir-Smith, Gezina
  • Human Sciences Research Council
Publication Date
2014-12-14
Embargo End Date
2014-12-14
Contributor
  • Human Sciences Research Council (Producer)
Free Keywords
Schema: UK DATA ARCHIVE - HASSET
CENSUS DATA; INEQUALITY; LABOUR MARKET; MUNICIPALITY; SPATIAL; UNEMPLOYMENT
Description
  • Abstract

    Description: This is aggregated data of individuals or households. The data originates from the South African censuses of 1991, 1996, 2001 and 2011, as well as the community survey of 2007. The geographical units were standardised to the 2005 municipal boundaries so that spatial measuring was consistent. The data therefore covers the whole country at a municipal level for different time periods. The major variables focus on employment status. The data set consists of 156 variables and 257 cases. It contains the same socio-economic variables for different time periods, namely 1991, 1996, 2001, 2007 and 2011. Combined ranking - municipalities were ranked for each year, i.e. 1991, 1996, 2001, 2007 and 2011, in terms of unemployment rate and assigned a rank value. The combined unemployment ranking is calculated by adding up the ranking per individual year. Population density - this was calculated by dividing the total population of a municipality in 1991 by the area and the answer is expressed as number of people per square kilometer. Urban - the number of urban people in an area in a specific year. Rural - the number of rural people in an area in a specific year. Per capita income - the per capita income in a specific area and year. The linking of different census geographies was done by using areal interpolation to transfer data from one set of boundaries to another. The 2005 municipality boundaries were used as the common denominator and it is part of a spatial hierarchy developed by Statistics SA for the 2001 census.

    Abstract: Global unemployment has risen in the past few years and spatial data is required to address the problem effectively. South African unemployment literature focused mostly on a national level of spatial analysis. Some literature refers to spatial aspects that affect unemployment trends, but does not assign a location, e.g. a suburb or municipality. The research was conducted to obtain an understanding of geographical unemployment changes in South Africa over time. The data sets from the South African censuses of 1991, 1996, 2001 and 2011, as well as the community survey of 2007 were compared by spatial extent and associated attributes. The representation of change over time was explored and aggregation to a common boundary, such as municipalities was suggested to overcome modifiable areal unit problems. Census data is spatially more detailed than labour force survey data, and census data from pre-1991 might not reflect the post-apartheid labour trends effectively. To determine which unemployment data set is useful for a spatial understanding of unemployment in South Africa, the attributes of various datasets were compared, the completeness of the spatial data, as well as the geographic scale of presentation. South African census data represents employment statistics at the most detailed spatial level. Census data is collected every five to ten years. Initial data capture for censuses was usually at Enumerator Area (EA) level. Prior to 1991 the spatial data (EA and census district boundaries) were represented on hard copy maps only and no digital spatial data were captured. In the 1991 census, unemployment statistics were not directly calculated at EA level. To generate these statistics the number of employed people was subtracted from the economically active population. In the 1996 census, the number of unemployed, employed and economically active people per small area layer (SAL) was provided by Stats SA. The data were re-aggregated by the Human Sciences Research Council (HSRC), which could then be compared with EA data from other years. The 2001 census attribute data was not released at an EA level, and this consequently made comparisons with the previous two censuses very difficult. However, the spatial boundaries for the EAs were made available, and statistical modelling techniques were used by the HSRC to compute unemployment statistics for these boundaries. CS 2007 released statistics only at a municipality level. The linking of different census geographies was done by using areal interpolation to transfer data from one set of boundaries to another. The 2005 municipality boundaries were used as the common denominator and it is part of a spatial hierarchy developed by Statistics SA for the 2001 census. Municipalities were ranked for each year in terms of unemployment rate and assigned a rank value. There is also a combined unemployment rank value for all years and all municipalities. This resulted in a new data set of aggregated data of individuals or households. The geographical units were standardised to the 2005 municipal boundaries so that spatial measuring was consistent. The data therefore covers the whole country at a municipal level for different time periods. The major variables focus on employment status.

Geographic Coverage
  • South Africa (ZA)
Sampled Universe
All people in South Africa on the date of the census in 1991, 1996, 2001 and 2011, as well as the households at the time when the 2007 Community Survey (CS) was conducted. The South African Census 1996 covered every person present in South Africa on Census Night, 9-10 October 1996 (except foreign diplomats and their families). The South African Census 2001 and 2011 covered every person present in South Africa on Census Night, 9-10 October 2001 or 9-10 October 2011 respectively, including all de jure household members and residents of institutions. The South African Census 1991 was enumerated on a de facto basis, that is, according to the place where persons were located during the census. All persons who were present on Republic of South African territory during census night (i.e. at midnight between 7 and 8 March 1991) were therefore enumerated and included in the data. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active were enumerated and included in the figures. The Diplomatic and Consular Corps of foreign countries were not included. Crews and passengers of ships were also not enumerated, except those who were present at the harbours of the RSA on census night. Similarly, residents of the RSA who were absent from the night were not enumerated. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria). The South African Community Survey 2007 covered all de jure household members (usual residents) in South Africa. The survey excluded collective living quarters (institutions) and some households in EAs classified as recreational areas or institutions. However, an approximation of the out-of-scope population was made from the 2001 Census and added to the final estimates of the CS 2007 results.
Sampling
Sampling is not applicable since the data used here refers to aggregated data of the universe. Census 1996, 2001 and 2011 = universe Census 1991 = representative survey of South Africa and data extrapolated to all municipalities. Community Survey 2007 = household. For more information see www.statssa.gov.za.
Time Dimension
  • Time Series: Discrete
    Time Series: Discrete
Availability
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Rights
By accessing the data, you give assurance that The data and documentation will not be duplicated, redistributed or sold without prior approval from the rights holder. The data will be used for scientific research or educational purposes only. The data will only be used for the specified purpose. If it is used for another purpose the additional purpose will be registered. Redundant data files will be destroyed. The confidentiality of individuals/organisations in the data will be preserved at all times. No attempt will be made to obtain or derive information from the data to identify individuals/organisations. The HSRC will be acknowledged in all published and unpublished works based on the data according to the provided citation. The HSRC will be informed of any books, articles, conference papers, theses, dissertations, reports or other publications resulting from work based in whole or in part on the data and documentation. For archiving and bibliographic purposes an electronic copy of all reports and publications based on the requested data will be sent to the HSRC. To offer for deposit into the HSRC Data Collection any new data sets which have been derived from or which have been created by the combination of the data supplied with other data. The data team bears no responsibility for use of the data or for interpretations or inferences based upon such uses. Failure to comply with the End User License may result in sanctions being imposed.
Other

Update Metadata: 2019-09-22 | Issue Number: 1363 | Registration Date: 2015-03-09

Weir-Smith, Gezina; Human Sciences Research Council (2014): Spatial aspects of unemployment in South Africa 1991-2011 (UNEMPL): Municipalities - All provinces. Version: 1.0. HSRC - Human Science Research Council SA. Dataset. http://doi.org/10.14749/1417436222