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.
Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Factor Models
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.
Inequality is a major concern in many of the world’s developing regions. South Africa is no exception, as the voluminous literature on the subject attests to (see Bhorat and Kanbur 2006, for example). Indeed, modern South Africa is one of the most unequal societies in the world, primarily as a result of institutionalised inequality under colonial segregation and Apartheid, but potentially also stemming from the set of institutions created much earlier under Dutch and British colonial rule (Terreblanche 2002). This paper will investigate inequality in the early colonial period.
Globalisation brought about worldwide changes, including economic and financial integration between countries. This integration implied, in business cycle theory, the emergence of a common business cycle. Most developed economies seem to follow the world business cycle most of the time. However, there is little evidence of the co-movement between emerging markets, such as South Africa, and the common cycle. Factor models, using principal component analysis, were constructed for developed and developing countries with output, consumption and investment data.