This paper investigates the relationship between inflation and economic growth for South Africa and Ghana using quarterly empirical data collected from 2001 to 2016 applied to the quantile regression method. For our full sample estimates we find that inflation is positively related with growth in Ghana at high inflation levels whilst inflation in South Africa exerts its least adverse effects at high inflation levels. However, when particularly focusing on the post-crisis period, we find inflation exerts negative effects at all levels of inflation for both countries with inflation having its least adverse effects at high levels for Ghana and at moderate levels for South Arica. Based on these findings bear important implications for inflation targeting frameworks adopted by Central Banks in both countries.

This study sought to contribute to the growing empirical literature by investigating the effects of FDI on per capita GDP growth for South Africa using time series data collected between 1970 and 2016. Compared to the majority of previous studies, we use quantile regressions which investigates the effects of FDI on economic growth at different distributional quantiles. Puzzling enough, the empirical results show that FDI has a negative influence on welfare at extremely low quantiles whereas at other levels this effect turns insignificant. Contrary, the effects of domestic investment on welfare is positive and significant at all levels. Collectively, these results have important implications for policymakers in South Africa.

Background: South Africa's (SA) largest trading partner is China. The bilateral trade flows between these two economies have been increasing since the end of the global financial crisis. There are several factors that determine the trade flows between these two economies. Aim:The research studies the impact of the real exchange rate, market size and economic size on the trade flows between SA and China, applying the gravity model of trade. Time series data for the period of 1995-2014 have been used and a multiple linear regression model was employed in the evaluation process. Methods:To determine the impact of the three underlying variables on the bilateral trade flows of SA and China, the ordinary least squares method was used. The explanatory variables consist of the product of SA's gross domestic product (GDP) and China's GDP, which act as the proxy for economic size, the product of South Africa's population and China's population, which act as the proxy for market size, and the real exchange rate between SA and China.Results: Results revealed that the economic size and the market size have a strong positive impact on trade flows between SA and China and this is consistent with economic theory. On the other hand the real exchange rate has a negative impact on trade flows between SA and China. Conclusion:If two countries each have a large economic and population size trade, this results in high trade flows between the countries as compared to trading with smaller economies. Trade volume is also reduced if the countries trading have a highly volatile exchange rate. Based on the findings of the research, the article recommends that the Department of Trade and Industry should target trade with countries of big economic and market size. The research also shows that the absolute and comparative advantages are not the only basis of trade but other factors should be considered, such as exchange rate, economic size and market size. The central bank should maintain a stable exchange rate between the SA rand and partner countries' currencies before trading. This enhances trade and leads to strong economic growth.

Lack of access to reliable electricity to both rural and urban Zimbabweans is negatively affecting the quality of people's life. The country has been experiencing extended hours of load shedding which result in the population having more hours without electricity per day than with electricity. Access to electricity complimented by droughts, natural disasters has impacted on production activities for the people hence causing poverty to many. The study used time series data for the period 1992-2018. The Dynamic Ordinary Least Squares (DOLS) was used as the main model of assess electricity access on economic growth. The results reveals that electricity access to urban population and electricity access to population (EAP) have positive significant impact on economic growth. However, electricity access to rural population was found to be statistically insignificant reflecting that electricity is not always available when it is needed in the rural areas. The study recommends that there is need to improve electricity access for both urban and rural population through on-grid and off-grid systems and expanded electricity generation to meet demand. This will improve socio-economic activities people would be able to carry out productive activities such as irrigation, processing and manufacturing or value addition of certain agriculture out.

The cohort of high inequality African regions have jointly served to restrict the aggregate decline of the African inequality, in particular the Sub-Saharan region. This article investigates the determinants of economic inequality in the African regions of high inequality. We empirically test for the Kuznets’ inverted-U curve relationship in these regions. We construct a country-year panel for Middle and Southern African countries from 2000 to 2019 and employ the fixed effect panel regression model. Our results reveal an anti-Kuznets U-shaped relationship between inequality and economic growth for both regions. The numerical estimates for all specifications are however diminutive. The results depict that the drivers for reducing economic inequality in Southern Africa region are society rights and equality - an attribute of democracy and education. In the case of Middle Africa, the drivers for reduction in inequality are domestic government health expenditure, financial globalisation, social rights and equality. The results imply that economic growth is inadequate, hence additional policy levers are required to tackle the problem of economic inequality in these regions. JEL Classifications: D63, O4, C13