The non-monetary quality of city life in South Africa

In contrast to most research on the non-monetary quality of life, which relies on subjective indicators, we construct objective measures of the non-monetary quality of life using regression methods, for South Africa's cities. We also analyse the extent to which the various cities have been able to turn improvements in per capita incomes (monetary quality of life) into non-monetary quality of life – as reflected for instance in a better environment, higher literacy and longer lives. When monetary quality of life measures are used for South Africa's cities, the ranking in 2004 was led by Johannesburg, Tshwane, Ekurhuleni, Cape Town, Durban and Port Elizabeth. However when residuals from a regression of per capita income on (HDI) are used as a measure of non-monetary quality of life (i.e. the proportion of HDI not explained by variation in incomes), coastal cities tend to obtain generally higher rankings, with Cape Town ranked first, followed by Ekurhuleni, Durban, Port Elizabeth and then Johannesburg and Tshwane.     

Non-Economic Quality of Life and Population Density in South Africa

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. As economic or income variables have always played a significant role in this research, questions regarding the relationship between population density and non-economic quality of life has largely remained unanswered. In this light, the paper utilises a panel data set on the eight metropolitan cities in South Africa for the period 1996–2014 to determine the relationship between population density and non-economic quality of life in the South African context. In the analyses we make use of panel estimation techniques which allows us to compare changes in this relationship over time as well as adding a spatial dimension to the results. This paper contributes to the literature by firstly studying the aforementioned relationship over time and secondly conducting the analyses at a sub-national level in a developing country. Our results show that there is a significant and negative relationship between population density and non-economic quality of life. Based on our findings policy measures to encourage urbanisation should not be supported if the ultimate outcome is to increase non-economic quality of life.     

The Non-Economic Quality of Life on a Sub-National Level in South Africa

Most research on the non-economic quality of life have been (a) on a national level or performed on cross-country comparisons, and/or (b) used subjective indicators to measure how people perceive their non-economic quality of life. In this paper, our main contribution is to construct objective indicators of the non-economic quality of life for 354 sub-national magisterial districts in South Africa. We also compare changes in these indicators over time, and consider methodological issues in the construction of objective indicators of non-economic quality of life. We find that although income does matter for the overall quality of life, non-income components of the quality of life can make an important difference. We find a number of places with low incomes that have been able to achieve higher than expected outcomes in terms of the non-economic quality of life, and that some of the relative income poor areas have improved their non-economic ranking between 1996 and 2004. We also find that the geographical/environmental quality of life in South Africa is better in non-urban areas, where fewer of the country’s population is residing. Significant improvements in the overall quality of life may be achieved through improvements in the urban natural environment.

South African quotas on textile imports from China: A policy error?

In August 2006 the South African government announced quotas on the imports of clothing and textile products from China. Three questions arise. What are these expected benefits? What will be the most likely impact of the import quotas on the South African economy? And what are the policy implications? In this paper we answer these questions by using a computable general equilibrium (CGE) model. We find that, contrary to the motivations apparently underlying the quota implementation, the macro-economic, sector and household effects are negative and result in greater inequality between poorer and richer households. We refer to modeling results elsewhere in the literature which report results consistent to ours. The policy implications are that the imposition of these quotas could come to be seen as a policy mistake, and that South Africa may benefit more from considering a free trade agreement with China.