Volume 19, Issue 1

This study explores how technological diversification affects financial performance in Iran’s insurance industry. Using semi-structured interviews with six experts, including CEOs and faculty members, key indicators of technological diversification were identified, such as new underwriting software and digital advertising platforms. A 33-item questionnaire was developed based on these insights and distributed to top managers of Iranian insurance companies, with secondary financial data sourced from the Central Insurance of Iran. The study employes regression analysis and Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the impact of technological diversification on financial performance, controlling for firm size, debt ratio, and company age. Findings indicate a significant negative relationship between technological diversification and both Return on Equity (ROE) and Return on Assets (ROA), suggesting that the costs of adopting new technologies may outweigh their short-term financial benefits. Additionally, high debt ratios were found to adversely affect ROA, highlighting the financial risks of excessive borrowing.

This paper investigates the relation between medical insurance contribution and firm-level total factor productivity in China. Using a sample of Chinese A-share companies from 2007 to 2022, we find robust evidence that firms exhibit lower total factor productivity when medical insurance contribution is increasing. Specifically, we also show that this negative effect is more profound for state-owned enterprises, enterprises with lower employee compensation, and labor-intensive enterprises. Meanwhile, our findings remain valid after a series of robustness tests and controlling for endogeneity. Finally, we propose that the decreasing employees’ disposable income is plausible channel through which medical insurance contribution discourages firm-level total factor productivity in China. Overall, these results shed light on the real effects of medical insurance contribution and the determinants of firm-level total factor productivity.

This study examines the effect of telematics devices on the automobile insurance market. Automobile insurance using these devices is marketed as pay-how-you-drive (PHYD) automobile insurance. Insurers can directly monitor the insured’s vehicle for risky driving behaviors such as speeding. Some of insureds receive discounts on their premiums for driving more cautiously. On the other hand, accumulating the insured’s driving skills, insurers may be able to only sign up insureds with low accident rates, widely known as cream skimming. By applying Hodgson (2014. “Adverse Selection in Health Insurance Markets: A Classroom Experiment.” The Journal of Economic Education 45 (2): 90–100), we tested whether PHYD programs makes it easier for insurers to contract with low-risk drivers. Repeated cream skimming suggests that only high-risk drivers remain in the market and a residual market cannot be established, which could lead to adverse selection and market failure in the absence of any regulations. However, the experiment revealed that low-risk but highly risk-averse subjects tend to dislike the fluctuation in premiums by enrolling in PHYD programs. The results could be effective in future regulatory construction.

This study employs a Poisson model with Generalized Estimating Equations (GEE) to identify the key factors in the Moroccan auto insurance rating system. Crucial factors identified include gender, tariff-determining usage codes, vehicle usage, and driver experience. A comparison of this study model with Morocco’s current rating system reveals the presence of pricing suboptimality, which can be improved by enhancing the incorporation of driving history and adjusting the Bonus–Malus system to better reflect actual claim patterns and risk profiles.