In a nonparametric quantile-on-quantile regression model, we analyze the asymmetric financial impact of the Russian-Ukrainian conflict-induced geopolitical risk (GPR) on the top-seven emerging (E7) and developed (G7) stock markets. Our findings indicate that the impact of GPR on stock markets is not only market-specific but also asymmetric. Except for Russia and China, all E7 and G7 stocks respond positively to GPR in normal conditions. Among the E7 (G7) countries, stock markets from Brazil, China, Russia, and Turkey (France, Japan, and the US) are resilient to GPR in bearish stages. The portfolio and policy implications of our findings have been highlighted.

This study investigated the impact of the novel coronavirus disease 2019 (COVID‐19) outbreak on prices of maize, sorghum, imported rice and local rice in sub‐Saharan Africa (SSA). We estimated dynamic panel data models with controls for macroeconomic setting using general method of moments estimation. The study found that the COVID‐19 outbreak led to increases in food prices of the sampled countries. Restrictions on movements or lockdowns in the wake of COVID‐19 was associated with an increase in the price of maize only. We also found that exchange rate, inflation and crude oil prices exerted a detrimental effect on food prices. We recommend that governments of SSA countries invest in infrastructure that improves efficiencies in the food supply chain during pandemics. Providing adequate support to industries in the value chain will also improve food availability and food price stability post‐COVID‐19.

This study investigates the dynamic connectedness and spillovers between Islamic and conventional stock markets to reveal the time- and frequency-domain dynamics of the two asset classes under various market conditions. Using the spillover index of Baruník and Křehlík (2018), supplemented by the time-varying parameter vector autoregressions (TVP-VAR) connectedness model, we employ daily stock market indices for Islamic and conventional (G7) markets from November 23, 2015, to September 8, 2021. The findings explicate that the volatility spillovers across and within Islamic and/or G7 markets are time-varying and frequency-dependent but during market turbulences, the conventional stocks are prone to more volatilities than the Islamic stocks. Our findings additionally divulge contagious spillovers among Islamic and conventional stocks during Brexit and the studied COVID-19 period. Relative to mid-and long-term spillovers, we underscore the supremacy of short-term spillovers between Islamic and G7 markets. In turbulent trading periods, investors should utilise knowledge about market patterns and volatility to hedge their positions against lower stock returns, when spillover is more intense. Regulators should pay close attention to spillovers since they undermine cross-market connections. Intriguing findings and their implications are further discussed.

E-learning is soon expected to be widely used as a teaching and learning method in the mainstream for educational institutions. Given the relative preparedness of advanced economies, the conclusions about their implementation level with e-learning are incomparable with emerging countries. Emerging economies must, therefore, be aware of the issues to consider when formulating successful adoption or implementation strategies. However, empirical studies that bring forth these relevant factors are out of context. In a single framework, we model the structural relationships between the drivers of e-learning satisfaction and the performance of distance learning students in a frontier economy, Ghana. With 388 validated responses gathered from an online survey across the country between 29 May 2021 and 25 June 2021, we employ the Smart-PLS estimator to process and analyse the data. We explicate that the substantial drivers of e-learning satisfaction and performance among distance learning students include technology anxiety, instructor factors, course quality, technology quality, and ease of use. Our findings divulge that perceived learner satisfaction mediates the relationships between the drivers of satisfaction and learning outcomes of distance learning students in Ghana such that technology anxiety and instructor factors would not essentially enhance learner performance in the absence of e-learning satisfaction. Consequently, system quality, reflected by the information system success model must be supplemented by satisfaction, drawn from the expectation-confirmation theory, to fully explain the impact of efficient e-learning systems on learning outcomes. Not only does ease of use create satisfaction, but it also boosts performance. We, therefore, recommend institutions to develop regular training for both facilitators and students and also adopt user-friendly online platforms to aid patronage by learners.