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Threshold effect for the life insurance industry: evidence from OECD countries


We investigate the impact of new financial and economic determinants on life insurance demand for 29 OECD countries for the period 2005–2017 while controlling for a set of widely used socio-demographic and economic characteristics. Based on a panel smooth transition regression model, we find a regime-switching effect characterising the impact of bank concentration and interest rate on the size of the life insurance market, in light of the old-age dependency ratio as the threshold variable. We also show that life insurance development is boosted in countries with high scores for investment freedom and with high levels of foreign direct investment rates, regardless of the level of the old-age dependency ratio. The impact of GDP per capita on the demand for life insurance products is positive and statistically significant, regardless of the level of the threshold variable.

Investment guarantees in financial products: an analysis of consumer preferences


We analyze the preferences of 1180 German consumers for investment guarantees in financial products by means of choice-based conjoint and latent class analysis. Based on the segment-level partworth utility profiles, we then identify the most important investment guarantee features, analyze consumer demand in a realistic market setting, and test whether individual purchasing behavior can be explained by socioeconomic characteristics. Our results show that two buyer and two nonbuyer segments exist. Although their willingness to buy varies significantly, we document only a small degree of heterogeneity with respect to the individual guarantee attributes and levels. Across the sample, the guarantee period is most important, followed by the volatility of the underlying fund, and the up-front premium. Finally, we illustrate that particularly those socioeconomic characteristics with an impact on individuals’ financial situation are promising predictors of their willingness to purchase investment guarantees.

Solvency determinants: evidence from the Takaful insurance industry


This paper contributes to the nascent literature on Takaful by investigating the solvency determinants for Takaful firms in both the Gulf Cooperation Council (GCC) and Malaysian economies. Our main objective is to develop a deeper understanding of the solvency determinants of these firms. Using hand- collected microdata for the period 2011 to 2016 for 52 Takaful firms, we document that firm size and wakalah fees significantly decrease solvency. From a regulatory point of view, this finding underscores that the percentage of wakalah fees should be closely monitored. Moreover, we find that other explanatory variables, including return on assets and the risk retention and investment income ratios, are not significantly associated with solvency. Overall, our results remain robust to many different model specifications. Further analysis indicates significant differences between the GCC and Malaysian Takaful firms. This may be explained by the different stages of financial development in the two markets.

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Correction to: Optimal insurance coverage of low-probability catastrophic risks

Optimal unemployment accounts based on observable parameters


Baily (1978)’s model provides an observable condition of optimality for unemployment benefits (“b”). We add unemployment accounts (UAs) into the model, where employed individuals deposit a “s” saving rate and UAs finance unemployment benefits until their funds are exhausted and tax-financed benefits begin. The idea is that UAs reduce the distortion caused by pooling financed benefits, but in doing so they lower consumption smoothing across states of nature. We found that Baily (1978)’s rule for optimal benefits remains unchanged if UAs are added into his model, and we found a simple and easily observable rule for the optimal saving rate into UAs: the proportion of unemployment to be self-financed should equal the ratio of unemployment duration elasticity with respect to s and b.

Insurance wage-offer disparities by gender: random forest regression and quantile regression evidence from the 2010–2018 American Community Surveys


This paper examines differences in the wage-offer functions between males and females in the insurance industry. The results of random forest regression (RFR) residual analysis and quantile regressions (QRs) by gender indicate considerable inequities for underwriters, sales agents, and claims adjusters. We find relatively modest wage inequities among actuaries. Underwriters’ and adjusters’ gender wage inequality lies between the actuaries and sales agents. Across the specifications (RFR, QR, and the OLS benchmark), males benefit more from experience than females except for actuaries. In addition, males generally have a greater return to education than females (except for actuaries). Sales agents’ jobs exhibit the greatest inequality, with extremely high values for the regression Gini index of inequality at the upper quantiles. Actuaries exhibit the least amount of gender inequality across the board, with demographic responses suggesting competitive pressures across states yielding the least wage-offer inequality across gender. In summary, taste-based discrimination, social employment networks, difficulties in assessing productivity in heterogeneous work situations, competitiveness in the labor market, and the flexibility of work hours help explain our findings for different occupations in the insurance industry.