The authors examine 19 factors to determine which were most closely linked to permanent and term life insurance premiums sold in the United States in 2020. With spatial regression analysis using multi-scale geographically weighted regression (MGWR) approach, the authors find the following 5 covariates to be the most statistically significant for and positively correlated with permanent insurance sold: household income, percentage of the population that is African American, education, health insurance, and Gini index (a statistical measure of wealth inequality). For term insurance sold, the 5 most significant covariates are household income, education, Gini index, percentage of households with no vehicles, and health insurance. Their relationships with term insurance sold are positive except for the percentage of households with no vehicles.
Publication Date: August 2022
Publication Site: SOA