An Age-Period-Cohort model for gender gap in youth mortality

In this paper, we introduce a novel framework in longevity study, operating on the statistical approach of the Age--Period--Cohort framework by leveraging the skew-normal distribution and Bayesian estimation. We propose a specific application to gender gap analysis and forecasting.By employing mortality data from the Human Mortality Database in the USA, our study contributes a two-fold advancement. First, we present a novel perspective on gender gap analysis and forecasting, improving the current literature. Second, we contribute an improvement to the statistical framework for Age--Period--Cohort analysis.The proposed model offers invaluable insights applicable to healthcare planning and public interventions, providing a comprehensive snapshot of the gender gap across the population, and indispensable information for devising healthcare strategies.