Background: Since the early 1980s, many governments have investigated the possibility of utilising access to microloans as a pathway to grow economies out of unemployment and thereby improve people's quality of life. Studies that have previously investigated the impact of microloans found a positive relationship to quality of life. Unfortunately, these studies mainly measure quality of life using monetary (income) measures rather than assessing the entire multidimensionality of quality of life.
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.
This study examines the effect of financial structure on economic growth in Sub Saharan Africa. The sample consists of both low and middle income countries, whose financial systems range from poorly developed to relatively well- developed in the context of developing countries. Using dynamic panel estimation techniques, the study investigates both the short and long-run effects of financial structure on growth, focusing on 14 SSA countries over the period 1980-2014.
This paper hypothesises that the saving rate and technological progress are interdependently determined by a common exogenous source, so that an exogenous shock to the saving rate determines long-run growth transitions. In an open economy, the saving rate measures the quality of capital investment.
This paper departs from the traditional aid–economic growth studies through its examination of the impact of aid and its volatility on sectoral growth by relying on panel dataset of 37 sub-Saharan African (SSA) countries for the period 1980–2014. Findings from our system generalised methods of moments (GMM) show that, while foreign aid significantly drives economic transformation, aid volatility deteriorates sectoral value additions with huge impact on the non–tradable sector and a no apparent effect on the agricultural sector.
In the light of Africa’s palpable deficit in public infrastructure, we use System GMM to estimate a model of economic growth augmented by an infrastructure variable, for a panel of 45 Sub-Saharan African countries, over the period 2000-2011. We find that it is the spending on infrastructure and increments in the access to infrastructure that influence economic growth and development in Sub-Saharan 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.
This paper analyses the effects of the COMESA-EAC-SADC Tripartite Free Trade Agreement (TFTA) on the South African economy using a global Computable General Equilibrium (CGE) model. Simulation results show that South Africa’s economy gains from the implementation of the trade agreement with GDP rising by more than 1 per cent relative to the baseline. This win in overall economic activity occurs on the back of a terms of trade increase and a surge in regional trade, which allows for higher levels of both exports and imports.
Concerns have been expressed recently about the inability of the South African economy to provide adequate employment for the increasing number of job seekers. The rate of unemployment remains stubbornly high in spite of vastly improved macroeconomic fundamentals since the 1990s. This paper investigates how the sectoral employment intensity of output growth in the eight non-agricultural sectors of the South African economy has evolved in the period 2000:01-2012:04, with a view to identifying key growth sectors that are employment intensive.