Variable Selection for Functional Additive Models and an Application to the Population Age Structure Data

In this paper, we study component selection and estimation for functional additive models, which involve a scalar response and a functional predictor. Three methods are proposed to achieve a much more parsimonious model structure with better interpretation. Based on a cross-sectional data of 82 economics in 2018, we build a non-life insurance demand model with age proportion log hazard curve of the population as functional independent variable. We found that the declining demographic structure and higher proportion of people who heading for retirement has negative impact on non-life insurance demand.