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Giacomo Lanfiuti Baldi , La Sapienza
Andrea Nigri, University of Foggia
In this work, 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. We focused on ages 0-45 years, analysing the differences between the sexes in the, so-called, Accident hump. At these ages, male mortality is much higher, mainly due to riskier behaviours of boys. Breaking down the gender gap into its three components, we observe (for example) that: the gender gap peaks around age 23, the differences increase until 1995, after which they converge rapidly, and cohorts born in the first decade after World War II experienced an increase in mortality disparities. 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.
Presented in Session P2. Health, Mortality, Ageing - Aperitivo