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The main purpose of this study is to examine the impact of different dimensions of institutional quality indices on the economic growth of Sub-Saharan African (SSA) countries.

The study uses a panel data set of 31 SSA countries from 1991 to 2015 and employs a two-step system-GMM (Generalized Method of Moments) estimation technique.

The study's empirical results indicate that investment-promoting and democratic and regulatory institutions have a significant positive effect on economic growth; however, once these institutions are taken into account, conflict-preventing institutions do not have a significant impact on growth.

The study's findings suggest that countries in the region should continue their institutional reforms to enhance the region's economic growth. Specifically, institutions promoting investment, democracy and regulatory quality are crucial.

Unlike previous studies that use either composite measures of institutions or a single intuitional indicator in isolation, the present study has employed principal component analysis (PCA) to extract fewer institutional indicators from multivariate institutional indices. Thus, this paper provides important insights into the distinct role of different clusters of institutions in economic growth.

Early evidence suggests that coronavirus disease 2019 (COVID-19) caused a sharp deterioration in fiscal accounts worldwide. This paper empirically assesses the fiscal impact of previous pandemics and epidemics.

Using a large sample of 170 countries from 2000 to 2018, this study relies on Jordà's (2005) local projection method to trace pandemics' short- to medium-term dynamic impact on several fiscal aggregates.

This paper shows that (qualitatively) similar responses to those observed more recently with COVID-19 have characterized the effects of previous pandemics. While the fiscal effect has been economically and statistically significant and persistent, it varies; pandemics affect government expenditures more strongly than revenues in advanced economies, while the converse applies to developing countries. The author also finds that asymmetric responses depend on whether a country is characterized as a chronic fiscal surplus or deficit type. Another factor that generates an asymmetric fiscal response is the prevailing phase of the business cycle the economy was in when the pandemic shock hits.

This paper's findings provide a lower bound to what the current COVID-19 pandemic will inflict on countries’ fiscal situation. That said, the set of pandemics and epidemics used in this paper are geographically more concentrated and did not affect all countries in such a systemic and synchronized manner as did COVID-19 more recently.

This is the first paper to explore the fiscal side of this type of health-related shocks, as most of the literature has focused on the more traditional macroeconomic effects.

The study aims to use individuals using the internet and fixed broadband subscriptions as a proxy for digitalization to empirically assess the effects of Foreign Direct Investment (FDI), digitalization and their interaction on income inequality in developed and developing countries from 2002 to 2019.

The paper used the system general method of moments estimators for 30 developed and 35 developing countries.

FDI increases income inequality in developed countries but decreases it in developing countries, digitalization reduces income inequality in both groups and interaction term narrows income inequality in developed countries but widens it in developing countries.

The paper is the first to introduce digitalization into the FDI – income inequality relationship. Furthermore, it provides empirical evidence to show the difference in the role of digitalization in this relationship between developed and developing countries.

The study examines the impact of the preferential credit provided by the Vietnam Bank for Social Policies on poverty reduction in Ninh Binh province, Vietnam. It also identifies and ranks the barriers of accessing the credit.

The study applies fixed-effects method to handle the panel data to examine the impact of the credit on poverty reduction. It also uses face-to-face interviews and group discussions to identify and rank the barriers of accessing to the credit.

The results show that the credit (represented by loan volume) positively and significantly helps improve household income, but does not help to improve household consumption. The major barriers include the time spent to get to the nearest bank branch, banking support services provided to clients and the transparency of household poverty status assessment.

Data are collected in three years and the number of the observations is limited to 300 households.

The VBSP preferential credit may need to be modified to significantly help reduce poverty and the VBSP and involved parties may need to eliminate the barriers so that the poor can have a better access to the credit.

The VBSP preferential credit is one of the reasonable sources that can help eliminate poverty though increasing household income.

The VBSP preferential credit can help increase household income, but does not really help improve household consumption due to the small volume of loans. In addition, banking support services and the household poverty assessment are seen as barriers to the access of the poor.

The research approach is based on the concept that a failure event is rarely random and is often generated by a chain of previous events connected by a sort of domino effect. Thus, the purpose of this study is the optimal selection of the components to predictively maintain on the basis of their failure probability, under budget and time constraints.

Assets maintenance is a major challenge for any process industry. Thanks to the development of Big Data Analytics techniques and tools, data produced by such systems can be analyzed in order to predict their behavior. Considering the asset as a social system composed of several interacting components, in this work, a framework is developed to identify the relationships between component failures and to avoid them through the predictive replacement of critical ones: such relationships are identified through the Association Rule Mining (ARM), while their interaction is studied through the Social Network Analysis (SNA).

A case example of a process industry is presented to explain and test the proposed model and to discuss its applicability. The proposed framework provides an approach to expand upon previous work in the areas of prediction of fault events and monitoring strategy of critical components.

The novel combined adoption of ARM and SNA is proposed to identify the hidden interaction among events and to define the nature of such interactions and communities of nodes in order to analyze local and global paths and define the most influential entities.

Determinants of credit growth in Saudi Arabia are investigated.

A panel approach is applied to macroeconomic and bank-level data spanning 2000 ‐15.

Bank lending is supported by strong bank balance sheet conditions (high capital ratio, and growth of NPL provisioning and deposits), and higher growth of both oil prices and non-oil private sector GDP. Lower bank concentration also helps, likely through greater competition, so does stronger institution. Consistent with the literature, lending by Islamic banks may be more responsive to economic activity. Lending remained robust in 2015 despite oil prices having declined, helped by strong bank balance sheets and as banks reduced their holdings of “excess liquidity”. To support bank lending in the period ahead, bank balance sheets need to remain strong. Fiscal adjustment and a reduced reliance on banks to finance the budget deficit would support credit provision to the private sector.

The paper is first to analyze in detail determinants of bank lending in Saudi Arabia applying a panel approach to bank level data, and draws critical policy implications.

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.

As logistics talents in both Taiwan and Hong Kong are expanding their work area to Greater China, it is best to understand the competencies that logistics talents should possess. With this in mind, this study takes Mainland China, Hong Kong and Taiwan as the study scope, as well as logistics teaching and research experts and scholars as the study objects. The research findings can not only serve as informative references for universities intent on cultivating logistics talents, but as well as enhance the scope of both Taiwan and Hong Kong talents’ competence that can pave the way to the development of the logistics business in Greater China.

The paper aims to investigate the relationship between institutions and economic growth in developing countries, considering the role of financial inclusion, education spending and military spending.

The study employs dynamic panel analysis, specifically two-step system generalized method of moments (GMM), on a sample of 61 developing countries over the period 2009–2020.

The results confirm that weak institutional quality, weak financial inclusion and increased military spending are barriers to economic growth, conversely, increased spending on education and gross capital formation contribute to economic growth in developing countries. Regarding the specific institutional factor, we find that corruption, ineffective government, voice and accountability and weak rule of law contribute negatively to growth.

The study calls for strengthening institutions so that the financial system supports economic growth and suggests increasing spending on education to improve access to and the quality of human capital, which is an important determinant of economic growth.

The study contributes to scarce literature by empirically analyzing the relationship between institutions and economic growth by considering the role of financial inclusion, public spending on education and military spending, factors that have been ignored in previous studies. In addition, the study identifies the institutional dimension that contributes to reduced economic growth in developing countries.

The outbreak of COVID-19 not only had serious negative impacts on the world economy but also on the global mental health because of the psychological disorders associated with the spread of the pandemic, the increased degree of uncertainty and the unprecedented measures taken by different countries to face the pandemic’s spread. This paper analyses the mental health well-being of individuals in selected MENA countries (Jordan, Morocco, Tunisia and Egypt) during the pandemic.

The study employs a pooled OLS model using the Economic Research Forum (ERF) COVID-19 MENA Monitor Survey panel dataset collected during 2020 and 2021.

The findings show that there is no association between the mental health of individuals in the selected countries and their age, gender, family size, marital status, receipt of social support and participation in care work. Mental health improved at higher levels of education, being employed, being a rural area resident and living in Morocco or Tunisia compared to living in Jordan while it worsened as income declined, food insecurity and anxiety about being infected with Covid-19 increased, being a resident in camps, and during waves 4 and 5. Based on these results, it is recommended that suitable financial, physical and human resources should be directed towards the provision of mental health care services in the region. Also, mental health care services should be accessible to different population groups, with a special focus towards the most vulnerable since they are more prone to mental illnesses, especially during health crises and economic shocks. This should be accompanied by increasing awareness about the provided services and reducing stigma against mental illnesses. Furthermore, introduction of policies targeted towards reducing food insecurity and income instability can play a key role in enhancing mental well-being.

Although few papers have previously investigated the impact of COVID-19 on mental health in MENA countries, most of them have focused on a country-level analysis and adopted a gender perspective. Hence, this paper aims at exploring the association between mental health well-being and socio-economic factors in selected MENA countries during the pandemic.