Fertility evolution in Italy has shown a deep drop in 1995, and up to now the fertility rate is considered among the lowest in the world. The empirical distribution of the age-specific fertility rates is characterized by a decreasing tendency of the maximum fertility rate and a simultaneous increase of the corresponding mother’s age. This tendency has been stimulating recent contributions in modelling and forecasting. The aim of this paper is to propose a dynamic model for describing and predicting the evolution of the Italian age-specific fertility rates over time. In particular, a well-documented model, such as a Gamma function, slightly modified in order to include time-varying stochastic parameters, is used to describe the systematic and macroscopic variations of the age-specific fertility rates over time, while a nonparametric geostatistical model is applied to describe the correlated residuals at microscopic level. Finally, predictions for the variable under study are provided and main empirical evidences of the temporal evolution for different mother’s ages are discussed.
A dynamic model for age-specific fertility rates in Italy
DE IACO, Sandra
;MAGGIO, Sabrina
2016-01-01
Abstract
Fertility evolution in Italy has shown a deep drop in 1995, and up to now the fertility rate is considered among the lowest in the world. The empirical distribution of the age-specific fertility rates is characterized by a decreasing tendency of the maximum fertility rate and a simultaneous increase of the corresponding mother’s age. This tendency has been stimulating recent contributions in modelling and forecasting. The aim of this paper is to propose a dynamic model for describing and predicting the evolution of the Italian age-specific fertility rates over time. In particular, a well-documented model, such as a Gamma function, slightly modified in order to include time-varying stochastic parameters, is used to describe the systematic and macroscopic variations of the age-specific fertility rates over time, while a nonparametric geostatistical model is applied to describe the correlated residuals at microscopic level. Finally, predictions for the variable under study are provided and main empirical evidences of the temporal evolution for different mother’s ages are discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
