Publication:
Forecasting the mortality rates using Lee-Carter model and Heligman-Pollard model

dc.ConferencecodeUniv Malaysia Pahang, Fac Ind Sci & Technol, Inst Teknologi Sepuluh, Soc Ind & Appl Math, Malaysian Math Sci Soc, Malaysian Inst Stat
dc.ConferencedateAUG 08-10, 2017
dc.ConferencelocationKuantan, MALAYSIA
dc.Conferencename1st International Conference on Applied and Industrial Mathematics and Statistics (ICoAIMS)
dc.contributor.authorIbrahim, RIen_US
dc.contributor.authorNgataman, Nen_US
dc.contributor.authorAbrisam, WNAWMen_US
dc.date.accessioned2024-05-29T03:26:56Z
dc.date.available2024-05-29T03:26:56Z
dc.date.issued2017
dc.description.abstractImprovement in life expectancies has driven further declines in mortality. The sustained reduction in mortality rates and its systematic underestimation has been attracting the significant interest of researchers in recent years because of its potential impact on population size and structure, social security systems, and (from an actuarial perspective) the life insurance and pensions industry worldwide. Among all forecasting methods, the Lee-Carter model has been widely accepted by the actuarial community and Heligman-Pollard model has been widely used by researchers in modelling and forecasting future mortality. Therefore, this paper only focuses on Lee-Carter model and Heligman-Pollard model. The main objective of this paper is to investigate how accurately these two models will perform using Malaysian data. Since these models involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 8.0 (MATLAB 8.0) software will be used to estimate the parameters of the models. Autoregressive Integrated Moving Average (ARIMA) procedure is applied to acquire the forecasted parameters for both models as the forecasted mortality rates are obtained by using all the values of forecasted parameters. To investigate the accuracy of the estimation, the forecasted results will be compared against actual data of mortality rates. The results indicate that both models provide better results for male population. However, for the elderly female population, Heligman-Pollard model seems to underestimate to the mortality rates while Lee-Carter model seems to overestimate to the mortality rates.
dc.identifier.doi10.1088/1742-6596/890/1/012128
dc.identifier.isbn1742-6596
dc.identifier.issn1742-6588
dc.identifier.scopusWOS:000423857800128
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/12171
dc.identifier.volume890
dc.languageEnglish
dc.language.isoen_US
dc.publisherIOP PUBLISHING LTDen_US
dc.sourceWeb Of Science (ISI)
dc.sourcetitle1ST INTERNATIONAL CONFERENCE ON APPLIED & INDUSTRIAL MATHEMATICS AND STATISTICS 2017 (ICOAIMS 2017)
dc.titleForecasting the mortality rates using Lee-Carter model and Heligman-Pollard model
dc.typeProceedings Paperen_US
dspace.entity.typePublication

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Forecasting the mortality rates using Lee-Carter model and Heligman-Pollard model