Modeling and Forecasting Mortality with Economic, Environmental and Lifestyle Variables

Matteo Dimai , Università degli Studi di Trieste

Traditional stochastic mortality models tend to extrapolate trends without exploring underlying drivers. Those that do link mortality with other variables usually limit themselves to GDP. This article introduces a novel stochastic mortality model that incorporates a broad spectrum of variables related to economic, environmental, and lifestyle factors to predict mortality. The model uses principal components derived from these variables in an extension of the Niu and Melenberg (2014) model and is applied to 37 countries from the Human Mortality Database. Model fit is superior to the Lee-Carter model for 18 countries and closely matches it in others. The forecasting accuracy of the proposed model improves on the Niu-Melenberg model for half of the countries studied under various jump-off years. Sustainable populations require an intricate understanding of the interplay between mortality and its determinants. The model is designed to facilitate scenario building and policy planning, including strategies for population sustainability. By examining a comprehensive array of variables, this model contributes to a holistic comprehension of population dynamics.

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 Presented in Session P2. Health, Mortality, Ageing - Aperitivo