Spatial Mortality Modeling in Actuarial Science

• Other Authors: Cupido, Kyran (Author)
• Format: Doctoral Thesis
• Language: English
• Published: 2020
• Subjects: Statistics
• Online Access: http://hdl.handle.net/2286/R.I.57335

abstract: Modeling human survivorship is a core area of research within the actuarial com munity. With life insurance policies and annuity products as dominant financial instruments which depend on future mortality rates, there is a risk that observed human mortality experiences will differ from projected when they are sold. From an insurer’s portfolio perspective, to curb this risk, it is imperative that models of hu man survivorship are constantly being updated and equipped to accurately gauge and forecast mortality rates. At present, the majority of actuarial research in mortality modeling involves factor-based approaches which operate at a global scale, placing little attention on the determinants and interpretable risk factors of mortality, specif ically from a spatial perspective. With an abundance of research being performed in the field of spatial statistics and greater accessibility to localized mortality data, there is a clear opportunity to extend the existing body of mortality literature to wards the spatial domain. It is the objective of this dissertation to introduce these new statistical approaches to equip the field of actuarial science to include geographic space into the mortality modeling context. First, this dissertation evaluates the underlying spatial patterns of mortality across the United States, and introduces a spatial filtering methodology to generate latent spatial patterns which capture the essence of these mortality rates in space. Second, local modeling techniques are illustrated, and a multiscale geographically weighted regression (MGWR) model is generated to describe the variation of mortality rates across space in an interpretable manner which allows for the investigation of the presence of spatial variability in the determinants of mortality. Third, techniques for updating traditional mortality models are introduced, culminating in the development of a model which addresses the relationship between space, economic growth, and mortality. It is through these applications that this dissertation demonstrates the utility in updating actuarial mortality models from a spatial perspective. === Dissertation/Thesis === Doctoral Dissertation Statistics 2020