The dynamics of life insurance demand in Bangladesh: An empirical analysis of socio-economic influences

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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.

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    • Figure 1. Theory-driven conceptual framework of life insurance demand
    • Table 1. Variables description
    • Table 2. Descriptive statistics
    • Table 3. Correlation matrix
    • Table 4. Regression result of the impact of socio-economic variables on life insurance demand using the Panel-Corrected Standard Errors (PCSE) model
    • Table 5. Regression result of the impact of socio-economic variables on life insurance demand using the stepwise regression model
    • Table A1. List of commercial life insurance companies that are part of the sample
    • Conceptualization
      Shaikh Masrick Hasan, Sonia Munmun, Priya Saha
    • Formal Analysis
      Shaikh Masrick Hasan, Priya Saha
    • Funding acquisition
      Shaikh Masrick Hasan, Sonia Munmun
    • Investigation
      Shaikh Masrick Hasan, Sonia Munmun, Priya Saha
    • Methodology
      Shaikh Masrick Hasan
    • Project administration
      Shaikh Masrick Hasan
    • Resources
      Shaikh Masrick Hasan, Sonia Munmun, Priya Saha
    • Software
      Shaikh Masrick Hasan
    • Supervision
      Shaikh Masrick Hasan
    • Validation
      Shaikh Masrick Hasan, Priya Saha
    • Visualization
      Shaikh Masrick Hasan, Priya Saha
    • Writing – original draft
      Shaikh Masrick Hasan, Sonia Munmun, Priya Saha
    • Writing – review & editing
      Shaikh Masrick Hasan, Sonia Munmun, Priya Saha
    • Data curation
      Priya Saha