Sonia Munmun

Type of the article: Research Article

Abstract
This study examines the influence of socio-economic factors on life insurance demand in Bangladesh using annual data from 18 life insurance companies between 2014 and 2023. Life insurance demand is assessed using life insurance penetration and life insurance density; GDP per capita, inflation, healthcare spending to GDP, and education spending to GDP serve as proxies for socio-economic variables. This study employs a dynamic Panel-Corrected Standard Errors (PCSE) method to handle cross-sectional dependence in panel data. Stepwise regression is further applied as a robustness check. The findings exhibit that GDP per capita has a statistically significant negative impact on insurance density (β = –0.0003, P < 0.001) and insurance penetration (β = –0.000002, P < 0.001). This suggests that income growth does not facilitate increased insurance adoption. In contrast, inflation has a significant positive influence on both insurance density (β = 0.0310, P < 0.001) and insurance penetration (β = 0.0001, P < 0.001), emphasizing the influence of inflationary pressure on life insurance demand. Similarly, healthcare expenditure exhibits a significant positive effect on life insurance demand, influencing both insurance density (β = 2.0560, P < 0.01) and insurance penetration (β = 0.0024, P < 0.05), possibly due to rising healthcare costs prompting individuals to seek financial security. However, education spending does not show a statistically significant effect on life insurance demand. The results indicate that demand for life insurance in Bangladesh is influenced more by financial insecurity than by income increases, emphasizing the impact of inflation and healthcare expenses on insurance adoption.

Type of the article: Research Article

Abstract
This study investigates the determinants influencing life insurance demand across 38 OECD countries over the period 2009 to 2022, with the data sourced from OECD Insurance Statistics, the World Bank, and the World Development Indicators (WDI). The purpose is to identify and analyze the determinants that shape life insurance penetration (premiums as a percentage of GDP) and density (premiums per capita), providing a comprehensive understanding of market dynamics. Using panel data, the study employs a dynamic regression model with Panel-Corrected Standard Errors (PCSE) to ensure accuracy and reliability, complemented by Pooled Ordinary Least Squares (OLS) for robustness. The findings indicate that economic, demographic, and social factors significantly impact life insurance demand. GDP per capita, poverty rates, and healthcare expenditure to GDP significantly stimulate life insurance demand. Life expectancy positively correlates with insurance penetration, whereas a higher dependency ratio adversely affects it. In contrast, inflation and education expenditure to GDP are found to reduce demand. However, urbanization is found to have no significant influence. The study provides actionable insights for policymakers to design strategies that safeguard consumer interests while promoting market expansion. Furthermore, OECD countries stand out as appealing investment destinations within the stable insurance sector. These findings highlight opportunities for insurance companies to adapt offerings to evolving consumer needs, boosting competitiveness and profitability.

Acknowledgment
The authors gratefully acknowledge Dr. Anup Kumar Saha, Lecturer in Accounting at Keele University, United Kingdom, for his valuable intellectual input and constructive feedback.