Cause-Specific Mortality Forecasting. A Constrained Penalized Regression Model

Carlo Giovanni Camarda , Institut National d'Études Démographiques (INED)
Mari´a Durbán, Department of Statistics, Universidad Carlos III de Madrid

Cause of death data provides additional insight on the future trends of mortality, as well as provide valuable information for governments and insurance companies. Models that fit and forecast by cause of death come across several methodological problems, one of them being the inconsistency between individual estimation and forecast of mortality per cause of death and an all-cause scenario. We propose a clear-cut and fast method to obtain coherent cause-specific mortality trajectories based on Lagrange multipliers. We apply the method proposed to fit and forecast mortality of males in USA for the most five leading causes of death.

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 Presented in Session 96. Modelling and Forecasting Mortality