Demographic literature is rich of empirical analyses showing how women have historically experienced lower mortality rates than men. In this paper, we consider a measure of the gender gap in mortality rates, the Gender Gap Ratio, across a wide range of populations collected in the Human Mortality Database. With the aim of highlighting similarities and differences between the countries considered, we apply a functional clustering method to the multivariate time series of Gender Gap. We reconstruct the functional form of the trends from the available discrete observations and derive the curves through non-parametric smoothing. Results for 65-years-old people from 1965 to 2014 are presented and discussed.
The Functional Clustering of the Mortality Gender Gap: a multi- country analysis / Apicella, G.; Di Lorenzo, E.; Piscopo, G.; Sibillo, M.. - (2023), pp. 13-14. (Intervento presentato al convegno 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).
The Functional Clustering of the Mortality Gender Gap: a multi- country analysis
E. Di Lorenzo;G. Piscopo;
2023
Abstract
Demographic literature is rich of empirical analyses showing how women have historically experienced lower mortality rates than men. In this paper, we consider a measure of the gender gap in mortality rates, the Gender Gap Ratio, across a wide range of populations collected in the Human Mortality Database. With the aim of highlighting similarities and differences between the countries considered, we apply a functional clustering method to the multivariate time series of Gender Gap. We reconstruct the functional form of the trends from the available discrete observations and derive the curves through non-parametric smoothing. Results for 65-years-old people from 1965 to 2014 are presented and discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
