Shifting attention to old age: detecting mortality deceleration using focused model selection
arXiv e-prints 1905.05760
Ithaca, NY, arXiv / Cornell University
preprint (2019), unpublished
The decrease in the increase in death rates at old ages is a phenomenon that has repeatedly been discussed in demographic research. While mortality deceleration can be explained in the gamma-Gompertz model as an effect of selection in heterogeneous populations, this phenomenon can be difficult to assess statistically because it relates to the tail of the distribution of the ages at death. By using a focused information criterion (FIC) for model selection, we can directly target model performance at those advanced ages. The gamma-Gompertz model is reduced to the competing Gompertz model without mortality deceleration if the variance parameter lies on the boundary of the parameter space. We develop a new version of the FIC that is adapted to this non-standard condition. In a simulation study, the new FIC is shown to outperform other methods in detecting mortality deceleration. The application of the FIC to extinct French-Canadian birth cohorts demonstrates that focused model selection can be used to rebut previous assertions about mortality deceleration.