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This is aggregated data of individuals or households. The data originates from the South African censuses of 1996 and 2001 and covers the whole country at a municipal level. In order to calculate the aggregate poverty gap a cross tabulation of household income by household size, municipality and population group was drawn from the 2001 census.

The poverty gap of each poor household was summed to arrive at the aggregate poverty gap for each municipality.

This is aggregated data of individuals or households. The data originates from the South African censuses of 1991, 1996 and 2001, 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 32 variables and 257 cases. It contains the same socio-economic variables for different time periods, namely 1991, 1996, 2001 and 2007.

Combined ranking - municipalities were ranked for each year, i.e. 1991, 1996, 2001 and 2007, in terms of unemployment rate and assigned a rank value. There is also a combined unemployment rank value for all years and all municipalities.

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.

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.

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.