Financial Stability of European Insurance Companies during the COVID-19 Pandemic

Financial resilience of insurance network during Covid-19 pandemic

We provide a novel approach for analysing the financial resilience of the insurance sector during coronavirus pandemic. To this end, we build temporal directed and weighted networks where the weights on the arcs take into account the tail dependence between couple of firms. To assess the resilience of the network, we provide a new global indicator, aimed at capturing the impact on the clustering coefficient of a shock affecting in turn each firm and diffusing in the network via shortest paths. A local measure of resilience is also provided by quantifying the contribution of each firm to the global indicator. In this way, we are able to detect most critical firms in the system. A numerical application has been developed in order to test the proposed approach. The results show that the proposed resilience measure appears able to detect main periods of financial crises. The first wave of COVID-19 pandemic results as a extreme phenomenon in the market and the lowest resilience is associated to the period in which COVID-19 has been declared pandemic.

Impacts of Insurers’ Financial Insolvency on Non-Life Insurance Companies’ Profitability: Evidence from Bangladesh

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.

Dynamic Causality Analysis of COVID-19 Pandemic Risk and Oil Market Changes

Crude oil draws attention in recent research as its demand may indicate world economic growth trend in the post-COVID-19 era. In this paper, we study the dynamic lead–lag relationship between the COVID-19 pandemic and crude oil future prices. We perform rolling-sample tests to evidence whether two pandemic risk scores derived from network analysis, including a preparedness risk score and a severity risk score, Granger-cause changes in oil future prices. In our empirical analysis, we observe 49% to 60% of days in 2020 to 2021 during which the pandemic scores significantly affected oil futures. We also find an asymmetric lead–lag relationship, indicating that there is a tendency for oil futures to move significantly when the pandemic is less severe but not when it is more severe. This study adopts preparedness risk score and severity risk score as proxy variables to measure the impact of the COVID-19 pandemic risk on oil market. The asymmetric lead–lag behavior between pandemic risk and oil future prices provides insights on oil demand and consumption during the COVID-19 pandemic.

Determinants of Sustainable Profitability of the Serbian Insurance Industry: Panel Data Investigation

This paper aims to investigate the main drivers of sustainable profitability trends in the Serbian insurance industry over the years 2008–2019 (inclusive). Our study is motivated by the fact that insurance companies contribute to economic growth, and thus it is essential to understand the factors that contribute to their financial strength and stability. We use a set of standard panel regression models, including the mixed-effects model, followed by a more robust GMM estimation to uncover the linkage between selected micro-specific, macroeconomic, and institutional factors, and return of assets (ROA) and return on total premiums (ROTP). The present paper constitutes a significant contribution to the existing literature on the account of its comprehensiveness both in terms of the institutional datasets that we use, and in terms of the methodologies we apply (in particular, mixed effects and the generalized method of moments (GMM)). The estimated parameters are model-specific, and we find that firm size, GDP, the population growth rates, political stability, and the degree of specialization (in some empirical models) all lead to higher profitability. On the other hand, we observe that excessive risk-taking and inflation (in some specifications) are inversely related to profitability. Finally, we note that regulatory quality, average wage, and life expectancies are found to be not statistically significant. Accordingly, we argue that a profitability-centric managerial strategy should be based on expanded market share and stringent risk management protocols. At the macro level, we conclude that pro-growth and pro-population policies, combined with a well-oiled institutional setting that ensures political stability, constitute the best possible prescription for strong operational performance and profit sustainability in the Serbian insurance industry.