Modeling Key Strategies for Reducing Socio-Economic and Health Crisis: Perspective from COVID-19 Pandemic.

The pandemic outbreak has dramatically changed every sector and walk of life. Specifically, the developing countries with scarce resources are facing unprecedented crises that further jeopardize efforts to achieve sustainable life. Considering the case of a developing country, Pakistan, this study empirically identifies the most important strategies to reduce the socio-economic and health challenges during COVID-19. Initially, the study identified 14 key strategies from the prior literature. Later, these strategies were determined with the help of the interpretive structural modeling (ISM) approach through expert suggestions. The ISM model represents seven levels of pandemic containment strategies based on their significance level. The strategies existing at the top level of ISM model are the least important, while the strategies at the bottom of hierarchy levels are highly significant. Therefore, the study results demonstrated that "strong leadership and control" and "awareness on social media" play significant roles in reducing pandemic challenges, while "promoting online purchase behavior" and "online education" are the least important strategies in tackling pandemic crisis. This study will benefit government authorities and policymakers, enabling them to focus more on significant measures in battling this ongoing crisis.

Interest rate volatility and financing of Islamic banks.

Despite a direct ban on charging interest, interest-based benchmarks are used as a pricing reference by a majority of Islamic banks, due in part to the absence of stable and widely- published alternatives. Benchmarking interest rate exposes Islamic banks to the problems of conventional banks, particularly the interest rate risk. Against this backdrop, the present study empirically examines the dynamic linkage between the interest rate volatility and the financing of Islamic banks. The empirical analysis is carried using evidence from the Islamic banking industry of Pakistan during the time period 2006-2020. The multivariate Johansen and Jusiles Co-integration test and Vector Error Correction Model (VECM) are used as the baseline econometric models. Moreover, the DCC-GARCH model is employed for robustness and ensuring the consistency of results. The results indicate that a significant long-term and short-term relationship exists between the interest rate volatility and the financing of Islamic banking industry providing significant evidence for co-movements and convergence. These findings suggest that paradoxical as it may seem, the financing of Islamic banks operating within a dual banking system is subject to interest rate risk, mainly due to benchmarking interest rate, which in-turn makes Islamic banks vulnerable to the rate of return risk and withdrawal risk. Moreover, corporate financing, in particular, is more vulnerable to interest rate risk.