R11

Policymakers need better information regarding wellbeing inequality to ascertain the contributing factors and to determine whether policy has been successful in improving the spread over time. In this paper, we construct a multidimensional composite wellbeing measure, at a micro level, which includes “economic and non-economic” and “objective and subjective measures” of wellbeing. We use NIDS data spanning the period 2008 – 2015. We compare the results on measuring wellbeing inequality using the composite index and income.

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.

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.

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.