Modelling Cause-of-Death Mortality and the Impact of Cause-Elimination

Daniel H. Alai, Severine Gaille and Michael Sherris

Changes in underlying mortality rates significantly impact insurance business as well as private and public pension systems. Individual mortality studies have data limitations; aggregate mortality studies omit many relevant details. The study of causal mortality represents the middle ground, where population data is used while cause-of-death information is retained. We use internationally classified cause-of-death categories and data obtained from the World Health Organization. We model causal mortality simultaneously in a multinomial logistic framework.