Modeling and forecasting mortality with economic, environmental and lifestyle variables

Traditional stochastic mortality models tend to extrapolate, to focus on identifyingtrends in mortality without explaining them. Those that do link mortality with othervariables usually limit themselves to GDP. This article presents a novel stochasticmortality model that incorporates a wide range of variables related to economic,environmental and lifestyle factors to predict mortality. The model uses principalcomponents derived from these variables, extending the Niu and Melenberg (Demog-raphy 51(5):1755–1773, 2014) model to variables other than GDP, and is applied to37 countries from the Human Mortality Database. Model fit is superior to the Lee—Carter model for 18 countries. The forecasting accuracy of the proposed model isbetter than that of the Niu–Melenberg model for half of the countries analyzed undervarious jump-off years. The model highlights the importance of economic prosperityand healthy lifestyle choices in improving lifespan, while the effect of environmentalvariables is mixed. By clarifying the specific contributions of different factors and thusmaking trade-offs explicit, the model is designed to facilitate scenario building andpolicy planning.