Insurance density is defined as the ratio between total insurance premium and population of a country. Therefore, insurance density is one of indicators that can be used as a proxy for measuring insurance demand. This research was conducted to examine what factors determines the density of sharia life insurance in Indonesia and how the prediction of these variables for the next 10 years. The independent variables utilized in this study are life expectancy, dependency ratio, income per capita, savings, education, urban population, interest rates, unemployment and inflation. The analytical method applied in this study is to select the best model using best subset regression. The benefit of best subset regression is to determine which independent variables would be included in the regression model so as to explain the behavior of sharia life insurance density appropriately. The findings show that the best model is a model that contains 4 independent variables and the influence of them, namely income per capita, age dependency ratio, and education is significantly positive towards the density of sharia life insurance at the alpha level of 5% while unemployment also has a significant and negative impact on insurance density at the alpha level of 5%.
|Number of pages||13|
|Journal||International Journal of Psychosocial Rehabilitation|
|Publication status||Published - Feb 2020|
- Insurance Density
- Sharia Insurance