Some Empirical Evidence on the Need of More Advanced Approaches in Mortality Modeling

4 Pages Posted: 26 Jan 2018

See all articles by Asmerilda Hitaj

Asmerilda Hitaj

Università degli Studi di Milano-Bicocca - Dipartimento di Statistica e Metodi Quantitativi

Lorenzo Mercuri

University of Milan

Edit Rroji

Polytechnic University of Milan - Department of Mathematics; Department of Statistics and Quantitative Methods University of Milano-Bicocca

Date Written: January 19, 2018

Abstract

Recent literature on mortality modeling suggests to include in the dynamics of mortality rates the effect of time, age, the interaction of the latter two terms and finally a term for possible shocks that introduce additional uncertainty. We consider for our analysis models that use Legendre polynomials, for the inclusion of age and cohort effects, and investigate the dynamics of the residuals that we get from fitted models. Obviously, we expect the effect of shocks to be included in the residual term of the basic model.

The main finding here is that there is persistence in the residual term but the autocorrelation structure does not display a negative exponential behavior. This empirical result suggests that the inclusion of the additional shock term requires an appropriate model that displays a more flexible autocorrelation structure than the Ornstein-Uhlenbeck employed in existing models.

Keywords: Mortality Models; Autocovariance Function; Ornstein-Uhlenbeck

JEL Classification: C00; C02

Suggested Citation

Hitaj, Asmerilda and Mercuri, Lorenzo and Rroji, Edit, Some Empirical Evidence on the Need of More Advanced Approaches in Mortality Modeling (January 19, 2018). Available at SSRN: https://ssrn.com/abstract=3105499 or http://dx.doi.org/10.2139/ssrn.3105499

Asmerilda Hitaj (Contact Author)

Università degli Studi di Milano-Bicocca - Dipartimento di Statistica e Metodi Quantitativi ( email )

Milano, 20126
Italy

Lorenzo Mercuri

University of Milan ( email )

Via Festa del Perdono, 7
Milan, 20122
Italy

Edit Rroji

Polytechnic University of Milan - Department of Mathematics ( email )

Via Bonardi, 9
Milano, MI 20133
Italy

Department of Statistics and Quantitative Methods University of Milano-Bicocca ( email )

Piazza dell’Ateneo Nuovo 1, 20126 Milano
Milano, 20126
Italy

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