The algorithm we propose retains the parametric structure of the Lee Carter model, extending the basic framework to include some cross dependence in the error term. As far as time dependence is concerned, we allow for all idiosyncratic components considering a highly flexible specification for the serial dependence structure of our data. We also relax the assumption of normality. The empirical results show that the Multiple Lee Carter Approach works well in presence of dependence.
Multiple Population Projections by Lee Carter Models / D'Amato, Valeria; Haberman, Steve; Piscopo, Gabriella; Russolillo, Maria; Trapani, Lorenzo. - Book of Abstracts of the 15th Applied Stochastic Models and Data Analysis International Conference (ASMDA2013):(2013), pp. 59-60.
Multiple Population Projections by Lee Carter Models
Valeria D'Amato;Gabriella Piscopo
;Maria Russolillo;
2013
Abstract
The algorithm we propose retains the parametric structure of the Lee Carter model, extending the basic framework to include some cross dependence in the error term. As far as time dependence is concerned, we allow for all idiosyncratic components considering a highly flexible specification for the serial dependence structure of our data. We also relax the assumption of normality. The empirical results show that the Multiple Lee Carter Approach works well in presence of dependence.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
