In the Southern African Development Community, the relationships between exchange rate instability, inflation and economic growth remain at the forefront of economic debate because of the historical antecedent and economic clustering of member countries. Nonetheless, much is not known regarding the complexity, complementarity or substitutability of exchange rate instability and inflation on economic growth for SADC countries. This article examined the influence of exchange rate instability on the inflation–growth nexus of the region for the period of 2000 to 2018. Three major techniques of analyses, Pooled Mean Group (PMG), Generalised Moments (GM) and Dynamic Fixed Effect (DFE), were employed in achieving the goal of the study, but the Pooled Mean Group estimator of the Panel Autoregressive Distributed Lag was favoured by the Hausman test as the main instrument. The GARCH (1, 1) was also employed to generate exchange rate instability. The findings of the study showed that exchange rate instability and inflation have a negative relationship with economic growth of the region. Results further show evidence that economic growth of the region is adversely influenced by the consequential effect of exchange rate instability on inflation: the higher the level of instability in exchange rate, the worse the inflationary-growth relationship of the region. This confirms the menu cost theory of price setting: the higher the rate of inflation, the quicker the exchange rate pass-through effect. It is therefore recommended that policies to ensure appreciation of local currencies should be the priority of member nations.

Resulting from the incessant political and economic uncertainty that bedevils the EAC region in the recent past, the various governments have used monetary policy changes in response to shocks from macroeconomic variables. However, the available literature shows a non-agreement by scholars as far as the dynamics in monetary policy, external shocks and macroeconomic activity connections are concerned, for both country-by-country analyses and regional assessments. This article widens the frontiers of knowledge about how the dynamics of monetary policy, external shocks and macroeconomic performance interact within the EAC economic region. We adopted the S-VAR method because of its contemporary nature as far as a transmission of monetary policy approach is concerned. The interconnectivity among the countries of EAC is an indication that any shock to the price of commodities (non-oil commodities) has significant implication on the exchange rate, which will be channelled through the supply of money and monetary policy to the GDP. The need to diversify the productive and export base of member countries, compared to the continuous dependence on one or a few products as the major source of income, is hereby advocated.

Finance, incubation, managerial support initiatives, and technological innovation have all been identified as major drivers of SMEs’ business location. Despite the importance of SMEs, little attention has been paid to business research regarding the impact of government support, business style, and entrepreneurial sustainability on SME activities in rural, semi-urban, and urban areas. Identifying the necessary support for SMEs in rural, semi-urban, and urban areas is critical for the government as well as stakeholders and SME owners in assessing their survival status and other goal-setting achievements. The article’s central question is whether government support, business style, and entrepreneurship sustainability affect SME operations differently depending on location (rural, semi-urban, or urban). The MANOVA technique was used for the analysis to determine whether there is a significant difference between groups on a composite dependent variable as well as the univariate results for each dependent variable separately. Because conducting a series of studies (ANOVA) reveals the possibility of an inflated Type 1 error, MANOVA is preferred. The test re-test reliability method (trustworthiness assessment of the questionnaire) and the Cronbach Alpha test (internal consistency of instrument sections) yielded satisfactory results of 0.70 and 0.875, respectively. Government support (GS), business style (BS), and entrepreneurial sustainability were used as dependent variables (SE). The independent variable was the business location. On the combined dependent variables, there was a statistically significant difference between SME location: F (3, 902) = 20.388, p = 0.001, Wilks’ Lambda = 0.88, partial eta squared = 0.06. When the results for the dependent variables were considered separately, they all reached statistical significance, using a Bonferroni adjusted alpha level of 0.017. BS: F (1, 904) = 13.29, p ≤ 001, partial eta squared = 0.03. GS: F (1, 904) = 30.28, p ≤ 0.001, partial eta squared = 0.06. SE: F (1, 904) = 8.08, p ≤ 0.001, partial eta squared = 0.02. The findings show that locational effects on government support have a knock-on effect on the business plan and long-term entrepreneurship. As a result, the government must reconsider its rural activities to ensure that support is distributed equitably across levels of location.

Financing has been identified as a major stumbling block to the effective launch and long-term success of SMEs, particularly in emerging economies. However, little is known about the impact of capital startups on SMEs’ performance in South Africa. Thus, the aim of this article is to compare differences in business success for three different levels of Capital startups and to determine the impact of capital startups on SMEs’ performance. The analysis was premised on a two-tail hypothesis test that the average weights of the three groups are different. The Cronbach Alpha test and the test–re-test reliability approach on the survey instrument indicated values of 0.70 and 0.875, respectively. A one-way between-groups analysis of variance was conducted startup. There was a statistically significant difference at the p < 0.05 level in scores for the three groups (F (2, 477) = 12.967 p = 0.0000). Post hoc comparisons using the Tukey HSD test indicated that the mean scores for Group 1 (M = 19.93, SD = 6.343) were significantly different from Group 2 (M = 20.94, SD = 2.309) and Group 3 (M = 21.73, SD = 2.880). Despite reaching statistical significance, the actual difference in mean scores between the groups was quite small. The one-way ANOVA approach indicates that finance (startup capital) remains a significant impediment to the effective launch of service-providing SMEs. It is recommended that SMEs who want to raise startup capital must create a solid business plan or build a prototype to sell the idea. This will assist them in discussions with venture capitalists, angel investors, banks, or other financial institutions.

Although there is a wealth of evidence on the relationship between economic growth and poverty or poverty and information and communication technology (ICT), there are few studies on the interaction between the three factors. The triangle relationship between poverty, information and communication technology, and economic growth in SADC were investigated in this study from 2005 to 2019. The research looked at how ICT and economic growth impact poverty in SADC countries, using the instruments of the Mean-Group FMOLS, Mean-Group DOLS, and Robustness Mean-Group Estimators in achieving its major objective. The principal component analysis was employed in generating a single index value for ICT and the data were subjected to relevant econometric tests to achieve robust results. Findings showed that all the variables exhibited poverty-reducing effects in SADC except inflation. Results confirm the existence of the “leapfrogging” hypothesis for the region. It is necessary to strengthen existing bilateral links among member nations of the area to maintain the benefits of ICT’s poverty-reducing impacts, economic growth, financial development, and trade openness. As applicable in other advanced and some emerging economies, the digital competence of the region needs to be synchronized for effective ICT service delivery.

Studies conducted in South Africa have revealed that despite SMEs’ contributions to economic growth, financing is still a problem, and business supports such as management and business development training and the creation of business plans are additional obstacles to their expansion and survival. This article specifically investigates the combined effects of financing and business support on the business environment of South African SMEs. We calculated a necessary sample size of 1937 using a sample size calculator, a margin of error of 2%, a confidence level of 95%, and a response rate of 20%. As a result, 2200 questionnaires were distributed, the target population was split into 3 strata, and then samples were chosen for the survey from each stratum. The SPSS version 25.0 was employed to analyze the data in three parts, namely, descriptive, correlation, and the outcome of the regression (coefficients/model summary/ANOVA). The level of significance was determined at 5%. The test–re-test reliability method (trustworthiness assessment of the questionnaire) and Cronbach Alpha test (internal constancy) resulted in values of 0.70 and 0.875, respectively, which were regarded as satisfactory. The SME business ecosystem in South Africa was positively and significantly impacted by each of these financial and business support components. The findings also give policymakers vital information about the need for more research into how money and business assistance interact throughout the business ecosystem. It is advised that the South African government intensify its current policies and programs on SMEs’ access to financing, particularly in the areas of grants, equity financing, and loan financing. Additionally, it is necessary to build an adequate information system that ensures unrestricted information flow to rural areas.