Prediction of mortality rates using a model with stochastic parameters

Tan Chon Sern, and Pooi, Ah Hin * (2016) Prediction of mortality rates using a model with stochastic parameters. AIP Conference Proceedings, 1782 (050016). 050016-1. ISSN 1551 7616

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Prediction of future mortality rates is crucial to insurance companies because they face longevity risks while providing retirement benefits to a population whose life expectancy is increasing. In the past literature, a time series model based on multivariate power-normal distribution has been applied on mortality data from the United States for the years 1933 till 2000 to forecast the future mortality rates for the years 2001 till 2010. In this paper, a more dynamic approach based on the multivariate time series will be proposed where the model uses stochastic parameters that vary with time. The resulting prediction intervals obtained using the model with stochastic parameters perform better because apart from having good ability in covering the observed future mortality rates, they also tend to have distinctly shorter interval lengths.

Item Type: Article
Additional Information: First author is with Department of Mathematical and Actuarial Sciences, Universiti Tunku Abdul Rahman
Subjects: H Social Sciences > HA Statistics
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Divisions: Others > Non Sunway Academics
Sunway University > School of Mathematical Sciences > Department of Applied Statistics
Depositing User: Dr Janaki Sinnasamy
Date Deposited: 21 Dec 2016 02:45
Last Modified: 03 Jul 2019 08:36

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