Life insurance demand in OECD economies: New insights into economic, demographic, and social drivers

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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.

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    • Figure 1. Theoretical framework for life insurance demand
    • Table 1. Description of variables
    • Table 2. Descriptive statistics
    • Table 3. Correlation matrix
    • Table 4. Regression results of determinants of insurance demand in OECD countries using the Panel-Corrected Standard Errors (PCSE) model
    • Table 5. Regression results of determinants of insurance demand in OECD countries using the Pooled Ordinary Least Squares (OLS) model
    • Data curation
      Sonia Munmun, Priya Saha
    • Formal Analysis
      Sonia Munmun, Shaikh Masrick Hasan
    • Funding acquisition
      Sonia Munmun, Priya Saha
    • Investigation
      Sonia Munmun, Priya Saha, Shaikh Masrick Hasan
    • Resources
      Sonia Munmun, Priya Saha, Shaikh Masrick Hasan
    • Validation
      Sonia Munmun, Shaikh Masrick Hasan
    • Visualization
      Sonia Munmun, Shaikh Masrick Hasan
    • Writing – original draft
      Sonia Munmun, Priya Saha, Shaikh Masrick Hasan
    • Writing – review & editing
      Sonia Munmun, Priya Saha, Shaikh Masrick Hasan
    • Conceptualization
      Priya Saha, Shaikh Masrick Hasan
    • Methodology
      Shaikh Masrick Hasan
    • Project administration
      Shaikh Masrick Hasan
    • Software
      Shaikh Masrick Hasan
    • Supervision
      Shaikh Masrick Hasan