Firoze Miah

Purpose: The COVID-19 pandemic has harmed the socioeconomic well-being of millions of low-income people across the globe. The study is to examine the financial strategies adopted by Char dwellers in Bangladesh to deal with the global pandemic’s shock. Design/methodology/approach: A quantitative survey was conducted for data collection, and respondents were chosen through a multistage sampling technique. Binary logistic model, probit model and multinomial logit models and Bayesian multinomial logistic models have been conducted to achieve the objectives. The objective of incorporating Bayesian models is to evaluate the probabilistic certainty and robustness of estimates in the presence of uncertainty and sparse data. Findings: Findings from the binary logit model, probit model, Bayesian logit model and Bayesian probit model show that income, income instability, number of dependents in a family, shrinking work opportunities, financial contributions to family, savings and a comparison of household expenses to pre-pandemic expenses influence the households’ daily financial management strategies. The multinomial logit model and Bayesian multinomial logit model results, on the other hand, show that education, savings, employment status and major sources of expenditure influenced the choice of financial strategies mostly. Practical implications: This research offers policy recommendations that might alleviate the financial challenges of extremely poor people posed by global crises such as the COVID-19 pandemic. Policymakers can use the results of this study to improve social safety nets, diversify livelihoods and provide char dwellers with banking services. Community leaders and organizations can learn from char dwellers’ coping strategies to improve financial hardship. By sharing lessons learned and best practices during the COVID-19 epidemic, stakeholders may better help vulnerable communities like char dwellers. Originality/value: To the best of the authors’ knowledge, this is the first study, in Bangladesh to investigate how financially disadvantaged people living in the char region have dealt with the COVID-19 pandemic and thus this paper presents new background information on strategies adopted by poor to cope up with COVID-19 pandemic using both frequentist and Bayesian modeling approaches. A methodological breakthrough, the incorporation of Bayesian analysis strengthens and probabilistically illuminates studies of socio-economic crises. This research clarified about vulnerable groups’ crisis response, financial situations and adaptive behaviors.

A stable and healthy insurance industry plays a vital role in sustaining an economy resistant to economic shocks by providing an efficient risk-transition mechanism. There is a relative scarcity of research inspecting the impact of insurers’ financial insolvency on the profitability of insurance firms. Employing 2011–2019 panel data of 16 non-life insurance companies operating in Bangladesh, this research endeavors to examine the impacts of insurers’ financial insolvency on the profitability of insurance companies measured by return ratios, return on assets (ROA), and return on equity (ROE). Fixed-effect regression outcome implies that insurers’ financial insolvency has a significant adverse influence on non-life insurance companies’ profitability. Further findings indicate that financial leverage, technical provision, age, and inflation have a noteworthy adverse influence on profitability. The outcomes of this research are of greater significance for policymakers in tackling insolvency and formulating policies to boost the growth of insurance profitability. In addition, this study aims to serve as a benchmark for other countries’ insurance industries to emulate recovery strategies from financial insolvency.