Year: 2015
Type: dissertation
Abstract: Consistent high unemployment perpetuates inequalities in the South African society. The 2014 \ngrowth expectation for the South African economy is 1.5 per cent and this will most certainly \nnot be enough to reduce unemployment. This research aimed to create an understanding of the \nspatial intricacies related to unemployment and to create a longitudinal dataset since 1991. The \nchallenge with such a dataset is that boundaries of the enumeration and administrative areas \nhave changed continually in the past and makes it difficult to compare unemployment spatially \nover time. \nThese particular problems were addressed by aggregating data for 1991 and 1996 census from \nmagisterial districts to the 2005 municipal boundaries. Area based weighted areal interpolation \nwas used and it assumes that data is distributed homogeneously across the area of each source \nunit. The 2001 census and 2007 community survey data was available at the 2005 municipal \nlevel, and therefore a longitudinal socio-economic dataset of four time points could be created. \nThe results showed that unemployment has been spatially persistent in a number of areas. \nFurthermore, a spatial grouping of unemployment by municipality showed that metropolitan \nmunicipalities had unique unemployment characteristics whereas the remainder of the country \ncould be clustered into five distinct groups. A spatial comparison between unemployment and \npoverty at municipality level revealed that people can be poor and unemployed, but also poor \nand employed. Finally, the longitudinal data was used to do spatial forecasting of future \nunemployment trends and these accounted for up to 60 per cent of change in unemployment. \nThese national and provincial spatial unemployment models consisted of coefficients like the \npercentage of people employed in mining and agriculture. \nThis research added new knowledge in terms of the spatio-temporal understanding of \nunemployment in South Africa. It created a methodology to overcome modifiable areal unit \nproblems (MAUP) and a longitudinal dataset of unemployment and related socio-economic \nvariables. Refined spatial data was this research’s main challenge and it recommends that \nunemployment data should be released at the most detailed spatial level possible - like sub-place \nor enumeration areas. The quality and timeliness of data remain obstacles for policy-making. \nTherefore, labour market data at a sub-place level would provide a more meaningful analysis. \nThe results from census 2011 will allow the creation of longitudinal socio-economic trends at a \nspatially detailed level in South Africa in the future.
Author: Gina Weir-Smith
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2436401554