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Africa's population is the second largest and fastest growing in the world after Asia, and this puts African governments under great stress in terms of increased public expenditure and is faced with a low revenue generation. Hence, the need for this study. The purpose of this paper is to examine the socio-economic determinants of public expenditure in Africa by assessing the influence of population age structure using a sample of the top ten most populous countries in Africa covering period of 1989 to 2018.

The study employed panel fully modified ordinary least square (OLS) in estimating the relevant relationship between the variables in the model. The dynamic ordinary least square (DOLS) model was also used to check the robustness of the fully modified ordinary least square (FMOLS) results.

The findings revealed that the major population age structure that influences the growth of public expenditure in Africa are population ages (0–14) and population ages (15–64), but the former poses a stronger significant influence than the latter while population ages (65 and above) has a negative and insignificant influence. Also, in terms of other socio-economic factors, self-employment has a reducing and significant influence on public expenditure. GDP per capita has a negative and insignificant influence while foreign aid and unemployment rate has an increasing influence. Finally, inflation rate and control of corruption (CC) has a negative relationship with public expenditure.

The study argues that an increase in the young and working population will put enormous pressure on the government in the provision of more jobs and other public infrastructures such as health care and education. In the context of African economy with a low revenue generation, public expenditure will be low and the desperately poor masses will be denied of these public infrastructures.

Several studies (Jibir and Aluthge, 2019; Tayeh and Mustafa, 2011; Okafor and Eiya, 2011; Obeng and Sakyi, 2017; Ofori-Abebrese, 2012) have investigated the determinants of public expenditure using total population as a variable. However, this study is unique as it focused on the influence of population age structure on public expenditure in Africa. Also, the study incorporated other socio-economic determinants of public expenditure such as self-employment, standard of living, inflation rate, unemployment rate, foreign aid and corruption in its analytical model. To the best of our knowledge, some of these variables have not been employed in previous studies.

In developing countries, banks play a major role by acting as a conduit for the effective mobilization of funds from the surplus sectors of an economy for onward lending to the deficit sectors for productive investments that will in turn increase the level of employment and economic growth. There has being a rising trend in unemployment rate in Nigeria and South Africa and hence, the need for the study to assess the effectiveness of banking system credit in curbing unemployment rate by making a comparative analysis of Nigeria and South Africa covering the period of 1991–2018.

The study employed the unit root test, Johansen cointegration test, vector error correction model and VAR impulse response function in determining the relationship between the variables.

The major findings revealed that banking system credit matters in curbing unemployment rate in South Africa than in Nigeria. Also, other macroeconomic factors such as lending rate, inflation rate, Government expenditure and population growth were significant enough in influencing unemployment rate in South Africa than in Nigeria. Foreign direct investment was a significant factor in reducing unemployment rate in Nigeria than in South Africa. The cointegration test showed a long-term relationship between the variables in both countries while the speed of adjustment coefficient of the vector error correction model is faster in South Africa than in Nigeria.

Previous empirical studies on the relationship between banking system credit and unemployment rate have focused much on other regions such as Asia and Europe. Thus, the study is unique as it focused on the African region and also made a comparative analysis by testing the Keynesian theory of employment, interest and money on two emerging African economies which are Nigeria and South Africa.

The purpose of this study is to analyze the two-way causal nexus between macroeconomic factors such as foreign aid, industrialization, economic growth, population growth, urbanization, control of corruption and the infrastructure development index of the top-ranking African countries from 2003 to 2018.

The study adopts various econometric tools such as cross-sectional dependence test, panel unit root and cointegration test and Dumitrescu and Hurlin panel Granger causality test in ascertaining the relevant relationships between the variables under consideration.

The main findings of the Granger causality test result revealed a bidirectional causal relationship between foreign aid and infrastructure and between urbanization and infrastructure. The study also found unidirectional causality running from population growth to infrastructure while a zero causal relationship existed between industrialization and infrastructure, economic growth and infrastructure and lastly, between control of corruption and infrastructure. The study concludes that the major macroeconomic factors that influence infrastructure development in these selected African countries are foreign aid, population explosion and urbanization. Also, their high infrastructure development index has causal influence in only attracting more foreign aid and also promoting urban expansion.

To the best of the author's knowledge, the study is unique as it is the first to determine the two-way causal nexus between macroeconomic factors and infrastructure development using a sample of the top ten African countries in infrastructure ranking. The findings reflect the current situation in Africa.

This study empirically assessed the influence of foreign direct investment on the manufacturing sector growth in the Middle East and North African region using panel data of 18 countries covering the period of 1975–2017.

The study employed Levin et al. (2002) test (LLC) and Im et al. (2003) panel unit root test. Furthermore, Kao’s cointegration test was applied to examine the long-run relationship between the variables. Both the Dynamic OLS and Fully modified OLS were used in estimating the short-run relationship.

The results of the DOLS and FMOLS indicate that both inward and outward FDI influence the manufacturing sector growth positively. This shows that much of the manufacturing sector growth in the MENA region is driven by both inward and outward FDI. Our findings made a strong new proposition that aside from the negative influence proposed by Stevens and Lipsey (1992), outward FDI could also have a positive influence on the manufacturing sector of a country through effective utilization of domestic raw materials that are produced locally for production of goods in a foreign country.

MENA countries should concentrate more on making policies that will encourage the effective utilization of domestic resources for outward foreign direct investment in other countries of the world as it has the capacity to boost the manufacturing sector growth. Also, policies that will attract more inflows of FDI in the region should be encouraged. Both inward and outward FDI should be considered as an integral part of MENA economic policy in order to spur the manufacturing sector growth.

Previous empirical studies on the relationship between FDI and manufacturing sector growth have focused much on the influence of inward FDI. Thus, very little attention has been paid to the contribution that the outward FDI makes to the growth of the manufacturing sector of the host country. Our empirical study focused on the influence of both inward and outward FDI on the manufacturing sector growth with specific emphasis on the MENA region that remains the center of attraction of inward FDI and a source of inward FDI to most nonoil producing developing and developed countries given the oil-rich nature of the region.

Africa and Asia are the two most populous continents in the world and are projected to increase further in the near future and this puts the governments under great stress in terms of increased public expenditure and dealing with a low revenue generation. Thus, the purpose of this study is to assess the influence of population age structure on the size of government expenditure in Africa and Asia covering the period 1990–2018.

The study employed panel fully modified ordinary least squares (FMOLS) estimation in estimating the relevant relationship between the variables in the model.

The key findings revealed that the major population age structures that influence the size of government expenditure in Africa are population aged 0–14 years and population aged 15–64 years, while that of Asia are population aged 15–64 years and population aged 65 years and above. The findings provided strong support for the Population Reference Bureau report (2019) that countries in Africa are home to some of the world's youngest population, that is, those aged 15 years or below, while Asia is home to some of the world's oldest population, that is, those aged 65 years and above.

While generalized method of moments (GMM) estimation is beneficial in the presence of endogeneity, it is only designed for situations with a small time period (T) and a large number of cross sections (N). Hence, the estimation technique was limited only to FMOLS as the number of the cross sections or countries which is ten for Africa and ten for Asia is lower than the time period which is 29 years (1990–2018).

Empirical literature investigating the influence of population age structure on the size of government expenditure has focussed mainly on one aspect of the population age structure and government expenditure, which is the influence of ageing population on government expenditure on health. Hence, this study focussed on assessing the influence of population age structure on the size of government expenditure. The study is unique as it compared the two most populous continents in the world, which are Africa and Asia to determine which of the population age structures have the most significant influence on the size of government expenditure.

The purpose of this study is to examine whether the state of infrastructure development in Sub-Saharan Africa actually stimulates industrial sector productivity, using a panel data set of 17 countries spanning from 2003 to 2018.

The study used panel least square estimation technique to examine the relationship between the variables.

The result of the study indicates that the major factor that influences industrial sector productivity in Sub-Saharan Africa is their quantity and quality of telecommunication infrastructure. Analysis shows that the relatively low level of industrial sector productivity in Sub-Saharan Africa is largely due to their poor electricity and transport infrastructure and underutilization of water supply and sanitation infrastructure.

The government should partner with other developed countries of the world such as Germany, Japan, Sweden, Netherlands, Austria, Singapore, United States of America, United Kingdom, Switzerland and United Arab Emirates, which are the top ten countries in infrastructure ranking as currently released by the World Bank, to equally extend their quality infrastructure to their own country for enhanced industrialization.

The novelty of this research lies on the fact it is a cross-country study as against the few empirical studies that focused only on a single country. Also, the study made use of the four main indicators of infrastructure development in an economy, which are electricity infrastructure, transport infrastructure, telecommunication infrastructure and water supply and sanitation infrastructure, to examine its effect on industrial sector productivity in Sub-Saharan Africa.