Quality of life (QoL) is now widely recognised as a multidimensional concept. This study validates an instrument to measure multidimensional QoL, and investigates the relationships between the domains thereof. The domains analysed are: health, housing and infrastructure, socio-economic status, social relationships, governance and safety. We utilise a rich household-level dataset collected by the GCRO on QoL in the Gauteng city-region of South Africa.
Economic Development: Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
The purpose of this study is to add to the empirical literature regarding quality of life convergence dynamics. It achieves this by analysing and comparing income and income-independent quality of life (IIQoL) convergence dynamics across South Africa's 234 municipalities for the period 1996-2014. The study tested for convergence and utilised dynamic panel methods (systems GMM). The results indicate unconditional convergence in both income and IIQoL but at different rates.
In this paper, we analyse the relationship between crime and the entry of firms across local municipalities in South Africa. We use data on the incidence of crime, sourced from the South African Police Service, and a unique database of business registrations over the period 2003 to 2011, to show that crime reduces business entry.
The purpose of this study is to investigate the relationship between population density and non-economic quality of life. Popular opinion has generally been that population density can be seen as beneficial for economic growth, as it allows for greater productivity, greater incomes and can be translated into higher levels of quality of life. Recently though, growing evidence tends to suggest the exact opposite in that increases in productivity and incomes are not translated into better quality of life.
This study employs a novel approach to measure and analyse quality of life in the Gauteng City-Region of South Africa. A comprehensive composite index is constructed. Comparing the quality of life of different groups, groups such as Africans, residents in urban informal settlements and females scoring relatively low. The weighting of the dimensions of quality of life is compared across groups, with ‘housing and infrastructure’ and ‘social relationships’ explaining the most variance for groups with lower and higher quality of life respectively.