Our demographic study provides a detailed picture of the short-term, weekly, mortality fluctuations charactering females and males over more than a decade. We follow an evidence-based approach, since we use data from the Human Mortality Database to detect stylized empirical evidence about the behaviour of mortality, during normal times and in the most recent time span, highly affected by the COVID-19 pandemic disease. Our study relies on time-series mortality data collected at a finer scale than traditionally done in the actuarial literature and encompasses different age groups, countries, and gender. The empirical evidence represents the starting point for exploring the future mortality patterns. Our quantitative analysis, namely based on stochastic mortality modelling, indeed, answers the question whether accounting for higher frequency mortality data delivers more reliable mortality projections, namely projections that approximate more closely the realized mortality phenomenon.
Longevity comparison by gender: exploring the future through an evidence-based approach / Apicella, G.; Di Lorenzo, E.; Magni, G.; Sibillo, M.. - (2023), pp. 13-13. (Intervento presentato al convegno the 20th Conference of the Appllied Stochastic Models and Data Analysis International Society ASMDA2023 and Demographics2023 Worksop tenutosi a Heraklion, Crete, Greece nel 6-9 June 2023).
Longevity comparison by gender: exploring the future through an evidence-based approach
E. Di Lorenzo;
2023
Abstract
Our demographic study provides a detailed picture of the short-term, weekly, mortality fluctuations charactering females and males over more than a decade. We follow an evidence-based approach, since we use data from the Human Mortality Database to detect stylized empirical evidence about the behaviour of mortality, during normal times and in the most recent time span, highly affected by the COVID-19 pandemic disease. Our study relies on time-series mortality data collected at a finer scale than traditionally done in the actuarial literature and encompasses different age groups, countries, and gender. The empirical evidence represents the starting point for exploring the future mortality patterns. Our quantitative analysis, namely based on stochastic mortality modelling, indeed, answers the question whether accounting for higher frequency mortality data delivers more reliable mortality projections, namely projections that approximate more closely the realized mortality phenomenon.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
