Multi-population mortality model in a state-space framework

Recent developments in several countries have brought forth two critical issues which are unexpected increases in life expectancy and gap in life expectancy between populations. These two issues have led to the study of mortality rates modelling. It began with the single-population regression model...

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Main Author:	Mohd. Nor, Siti Rohani
Format:	Thesis
Language:	English
Published:	2018
Subjects:	QA Mathematics
Online Access:	http://eprints.utm.my/id/eprint/81405/1/SitiRohaniMohdPFS2018.pdf
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id	my-utm-ep.81405
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spelling	my-utm-ep.814052019-08-23T04:07:09Z Multi-population mortality model in a state-space framework 2018 Mohd. Nor, Siti Rohani QA Mathematics Recent developments in several countries have brought forth two critical issues which are unexpected increases in life expectancy and gap in life expectancy between populations. These two issues have led to the study of mortality rates modelling. It began with the single-population regression model which comprises of the single age and time effect parameters. The single factor is limited by the fact that, firstly, the parameter is unable to capture the variances across ages and therefore tend to produce inaccurate forecasts. Secondly, the indicated model does not incorporate the inter- relationship between populations, therefore fails to produce coherent forecast in the long run. Finally, there are two-steps of separate estimations involved in the modelling procedure which are estimation procedure for Poisson regression approach and estimation procedure for forecast model. To overcome these limitations, this study proposed an extended version of multi-population mortality model. This extended model takes into account the quadratic age-effect parameter which captures the relevant information across age-groups and will help to ensure more coherent way of forecast in the future. In addition, the proposed multi-population mortality model is reformulated into the state-space framework by combining the Poisson regression and forecasting procedures into a single estimate. The mortality model in a unified estimation is proposed to avoid unreliable forecasts. This study produces a cohort mortality life table based on the assumptions of future mortality improvements. The proposed methods were applied to the Malaysian mortality data for male and female. The proposed methods are then compared with the other existing methods. The results have shown that it is vital to incorporate accurate information across ages in order to obtain accurate mortality rates forecast. Other than that, this thesis has shown that the mortality model in a state-space framework could significantly improve the independent estimation method. 2018 Thesis http://eprints.utm.my/id/eprint/81405/ http://eprints.utm.my/id/eprint/81405/1/SitiRohaniMohdPFS2018.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:124970 phd doctoral Universiti Teknologi Malaysia Mathematics
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA Mathematics
spellingShingle	QA Mathematics Mohd. Nor, Siti Rohani Multi-population mortality model in a state-space framework
description	Recent developments in several countries have brought forth two critical issues which are unexpected increases in life expectancy and gap in life expectancy between populations. These two issues have led to the study of mortality rates modelling. It began with the single-population regression model which comprises of the single age and time effect parameters. The single factor is limited by the fact that, firstly, the parameter is unable to capture the variances across ages and therefore tend to produce inaccurate forecasts. Secondly, the indicated model does not incorporate the inter- relationship between populations, therefore fails to produce coherent forecast in the long run. Finally, there are two-steps of separate estimations involved in the modelling procedure which are estimation procedure for Poisson regression approach and estimation procedure for forecast model. To overcome these limitations, this study proposed an extended version of multi-population mortality model. This extended model takes into account the quadratic age-effect parameter which captures the relevant information across age-groups and will help to ensure more coherent way of forecast in the future. In addition, the proposed multi-population mortality model is reformulated into the state-space framework by combining the Poisson regression and forecasting procedures into a single estimate. The mortality model in a unified estimation is proposed to avoid unreliable forecasts. This study produces a cohort mortality life table based on the assumptions of future mortality improvements. The proposed methods were applied to the Malaysian mortality data for male and female. The proposed methods are then compared with the other existing methods. The results have shown that it is vital to incorporate accurate information across ages in order to obtain accurate mortality rates forecast. Other than that, this thesis has shown that the mortality model in a state-space framework could significantly improve the independent estimation method.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mohd. Nor, Siti Rohani
author_facet	Mohd. Nor, Siti Rohani
author_sort	Mohd. Nor, Siti Rohani
title	Multi-population mortality model in a state-space framework
title_short	Multi-population mortality model in a state-space framework
title_full	Multi-population mortality model in a state-space framework
title_fullStr	Multi-population mortality model in a state-space framework
title_full_unstemmed	Multi-population mortality model in a state-space framework
title_sort	multi-population mortality model in a state-space framework
granting_institution	Universiti Teknologi Malaysia
granting_department	Mathematics
publishDate	2018
url	http://eprints.utm.my/id/eprint/81405/1/SitiRohaniMohdPFS2018.pdf
_version_	1747818323874152448

Multi-population mortality model in a state-space framework

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