Exchange rate volatility, or a continuous fluctuation in the currency rate has been a major concern in recent years due to its impact on economic activities. No wonder concerns have been raised regarding the connection between exchange rate fluctuations and their effects on the overall economy. The motivation for the study is based on the fact that most emerging economies experiencing inflationary tendencies are more likely to experience a high degree of exchange rate volatility persistence. Such a scenario seems catastrophic to developing economies where large currency movement are more frequent. BEKK-GARCH and DCC-GARCH models were utilized to estimate volatility transmission and persistence respectively in selected African countries. Results show there is presence of spill-over effect in exchange rates of all countries. BEKK-GARCH estimates show that negative effects of exchange rate of one country had deleterious effect on exchange rate of another. We found evidence in favour of bidirectional exchange rate volatility transmission amongst all exchange rates of countries in the study. Dynamic conditional correlation (DCC) model estimates further revealed Ghanaian cedi top list of countries exchange rate volatility persistence followed by naira with a value of 1.0974. Efficient structural transformation is needed to mitigate structural problems that generate inflation in these countries.

In this paper, the Extended Exponentiated Exponential distribution was developed from the New Extended Exponentiated-G family of distributions. Some mathematical properties of the newly derived distribution such as moment, moment generating function, quantile function, hazard function, survival function, odd function, distribution of order statistic and maximum likelihood estimation were all derived. An acceptance sampling plan based on truncated life tests was also developed for the distribution. The minimum size, operating characteristic function values and minimum ratio of the sampling plan required to confirm the specified mean life are also presented. Real-life example was used to illustrate the results. A comparison study with different sampling plans and distributions by earlier authors is also carried out to demonstrate the advantage of the new plan over existing plans. The findings revealed that the proposed plan is better and can be conveniently useful by researchers and Quality Control Personnel in product acceptance sampling inspection.

This study evaluated the cost and outcomes of healthcare services in some African countries with a particular focus on the sub-Saharan African (SSA) regions. It carried out analyses of fixed, random, and dynamic effect of lagged cost of healthcare on health outcomes. To achieve the study’s objective, cross-sectional data from eight (8) African countries were obtained from secondary sources. Panel regression econometric techniques and panel generalised moment/dynamic (PGMM/D) methods were used to determine the lagged effects among the study variables. This study identified the pooled, fixed, and random effects of healthcare costs on health outcomes. It was statistically significant at a 5 percent level. This study documented a positive relationship between health outcomes needs and healthcare costs. The behaviour exhibited by the variables was symmetrical, as revealed by the mean and the standard deviation of the descriptive analysis estimates. The findings of the regression analysis confirmed the peculiarity of the health outcomes and healthcare cost positions among the selected countries. The health outcomes estimate constituted strong drivers of healthcare costs. Therefore, in line with the findings of Healthcare Value Hub (2018), optimal interventions to address technological inadequacy and inefficient system performance to achieve quality health outcomes are recommended

Given that volatility influences decisions about currency rates, monetary policy, and macroeconomic policy, it is crucial to predict and anticipate volatility in emerging economies. The study employed generalized autoregressive conditional heteroskedasticity (GARCH) asymmetric models to estimate and forecast exchange rate dynamics in developing countries. We found that South Africa model had similar variance and covariance proportion of 0.99356 percent and 0.995901 percent respectively and the exchange rate could rise or fall by 2 to 6 units of rand, in exchange for USD. In Kenya, exchange rates continually exhibited steady rise monthly with extremely low mean absolute percentage error of 0.01568 percent and this demonstrates how strongly the model predicts Kenya’s future currency rates while the variance chart supports absence of persistence. In Ghana, exchange rates are projected to increase significantly as 99.5 percent of unsystematic error was un accounted for in the model. Volatility is highly persistent in Nigeria; hence the forecasting model reported a high error rate by taking 1.06 percent of the symmetric error into cognizance. Kenya, Ghana, and Mauritius had asymmetry in currency volatility, revealing turbulence in exchange rates when the bad news hit the market. Hence, local currencies are rendered worthless in the foreign exchange market.

When an economy does well as a result of crude oil proceeds, it is expected that its financial market records a boost. So, when the economy regresses due to fluctuations in oil prices, its financial market also reacts in tandem. To shed light on the uninterrupted fluctuations, we empirically estimated the effect of changes in exchange rates and oil prices on stock returns in developing countries using the nonlinear autoregressive distributed lag (NARDL) methodology. Results reveal that a 1 percent negative shock to the exchange rate diminished returns significantly by 1.015 percent and 2.191 percent for Egypt and Nigeria respectively whereas, in Tunisia, Morocco, and Tanzania, stock returns increased significantly by 0.118 percent, 0.176 percent, and 1.145 percent respectively. For every 1 percent positive shock to exchange rates in Egypt, Nigeria, Tunisia, Morocco, and Tanzania, returns declined by 1.012 percent, 1.04 percent, 0.015 percent, 0.112 percent, and 0.214 percent respectively. A 1 percent positive shock in oil price negatively influences returns by 0.02 percent, 0.05 percent, 0.18% percent, 1.09 percent, and 0.25 percent in Egypt, Nigeria, Tunisia, Morocco, and Tanzania while a 1 percent negative shock stimulated stock returns by 1.02 percent, 0.128 percent, 0.199 percent, 1.029 percent and 0.091 percent in Egypt, Nigeria, Tunisia, Morocco, and Tanzania respectively. Different policy reaction functions should be executed differently for depreciation, appreciation, and oil price shock to enhance the favorable flow of returns in stock markets