We investigate the dynamic volatility connectedness of geopolitical risk, stocks, bonds, bitcoin, gold, and oil from January 2018 to April 2022 in this study. We look at connectivity during the Pre-COVID, COVID, and Russian-Ukraine war subsamples. During the COVID-19 and Russian-Ukraine war periods, we find that conventional, Islamic, and sustainable stock indices are net volatility transmitters, whereas gold, US bonds, GPR, oil, and bitcoin are net volatility receivers. During the Russian-Ukraine war, the commodity index (DJCI) shifted from being a net recipient of volatility to a net transmitter of volatility. Furthermore, we discover that bilateral intercorrelations are strong within stock indices (DJWI, DJIM, and DJSI) but weak across all other financial assets. Our study has important implications for policymakers, regulators, investors, and financial market participants who want to improve their existing strategies for avoiding financial losses.
23 May 2022 in Environmental Science and Pollution Research
Achieving sustainable economic growth by addressing structural and environmental issues has become a top priority for decision-makers worldwide. This study investigates the impacts of renewable energy use, export diversification, and agricultural growth on sustainable economic development among G-20 economies. The analysis employs panel data from 1990 to 2021 with second-generation panel econometric methods, such as the PMG-ARDL test and dynamic panel estimation techniques, to elucidate both short- and long-term relationships. To examine the stationarity of the data series and identify cross-sectional dependence, this study applies some panel unit root tests, including the Cross-Sectionally Augmented Im and Pesaran test, the cross-sectional dependence (CSD) test, the Cross-Sectional Augmented Dickey–Fuller (CADF) test, and the Im, Pesaran, and Shin (IPS) test. The Westerlund co-integration test is employed to explore long-term relationships among the variables. To assess the prolonged impact of these factors, this study adopts the Pooled Mean Group–Autoregressive Distributed Lag (PMG-ARDL) approach. Findings reveal a statistically significant and persistent relationship between the variables, indicating that agricultural growth, renewable energy utilisation, and export diversification negatively affect economic growth. All insights highlight critical implications for G-20 policymakers; countries can develop a more resilient and sustainable economic pathway by addressing obstacles in agriculture, clean energy, and trade diversification.
This study aims to develop a specialized scale to measure educational quality in Saudi Arabia. Normally the SERVQUAL scale is used to measure the quality in education sectors, but few studies have attempted to modify the scale to accommodate the distinct features of the education sector. Using factor analysis, the study identifies three factors to be added to SERVQUAL, namely academic, non-academic, and curriculum dimensions. Recommendations for improving the variety of courses and programs, curriculum, and student workload are based on the gap scores obtained by subtracting students' expectations from their perceptions.