Several approaches have been developed for forecasting mortality using the stochastic model. In particular, the Lee–Carter model has become widely used and there have been various extensions and modifications proposed to attain a broader interpretation and to capture the main features of the dynamics of the mortality intensity. Hyndman–Ullah show a particular version of the Lee–Carter methodology, the so-called Functional Demographic Model, which is one of the most accurate approaches as regards some mortality data, particularly for longer forecast horizons where the benefit of a damped trend forecast is greater. The paper objective is properly to single out the most suitable model between the basic Lee–Carter and the Functional Demographic Model to the Italian mortality data. A comparative assessment is made and the empirical results are presented using a range of graphical analyses.

The mortality of the Italian population: Smoothing techniques on the Lee-Carter Model

RUSSOLILLO, Maria;D'AMATO, VALERIA
2011-01-01

Abstract

Several approaches have been developed for forecasting mortality using the stochastic model. In particular, the Lee–Carter model has become widely used and there have been various extensions and modifications proposed to attain a broader interpretation and to capture the main features of the dynamics of the mortality intensity. Hyndman–Ullah show a particular version of the Lee–Carter methodology, the so-called Functional Demographic Model, which is one of the most accurate approaches as regards some mortality data, particularly for longer forecast horizons where the benefit of a damped trend forecast is greater. The paper objective is properly to single out the most suitable model between the basic Lee–Carter and the Functional Demographic Model to the Italian mortality data. A comparative assessment is made and the empirical results are presented using a range of graphical analyses.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/3018713
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