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Malaysia population dynamics and the Bayesian projection modelling with functional scalable approach projection interval / Saharani Abdul Rashid

An understanding of past, present and future population dynamics is necessary for a nation in development planning. The changes in demographic component which are fertility, mor tality and migration have led to change in population dynamics. Nowadays, United Nation (UN) had emphasized on using Bayes...

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Main Author: Abdul Rashid, Saharani
Format: Thesis
Language:English
Published: 2022
Subjects:
Demography. Population. Vital events
Prediction analysis
Online Access:https://ir.uitm.edu.my/id/eprint/74318/2/74318.pdf
https://ir.uitm.edu.my/id/eprint/74318/
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id my.uitm.ir.74318
record_format eprints
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Demography. Population. Vital events
Prediction analysis
spellingShingle Demography. Population. Vital events
Prediction analysis
Abdul Rashid, Saharani
Malaysia population dynamics and the Bayesian projection modelling with functional scalable approach projection interval / Saharani Abdul Rashid
description An understanding of past, present and future population dynamics is necessary for a nation in development planning. The changes in demographic component which are fertility, mor tality and migration have led to change in population dynamics. Nowadays, United Nation (UN) had emphasized on using Bayesian models for population projection. However, not much detail description in terms of population dynamics that has been done in the past few years particularly for Malaysia population. In addition, Department of Statistics Malaysia is currently using deterministic approach which is Cohort Component method to project future population in Malaysia. Meanwhile many studies have proven a probabilistic model is better than the deterministic because the model considers uncertainty element. To date, the implementation of the probabilistic model particularly the Bayesian model is still rare. A model was first developed to project individual fertility and then extended to both fer tility and mortality. However the combination of all components (fertility, mortality and migration) for total population projection is seen lacking. Thus, this study aims to model population dynamics of Malaysian by considering simultaneously all the three important demographic components using Bayesian model. To study the structure and composition of population in Malaysia, the past and present trend of fertility, mortality as well as mi gration were examined using graphical presentations and trends analyses. The projections of the total population for 5-year intervals were then performed using two Bayesian mod els. The first projection model is based on the projected fertility and mortality while the second model is based on all the three components; fertility, mortality and migration. The projection of population was also conducted using exponential growth model. The per formance of the Bayesian projection models were compared to the results of the exponen tial growth model and cohort component method for the same interval period. Functional based discretization method was also proposed to enhance the time point of 5-year intervals projection to annual projection to enable for annual scalable values. All data used in this study were obtained from various agencies which include Department of Statistics Malaysia (DOSM) and National Population and Family Development Board (NPFDB) and cover 50- year period from 1970 to 2020. The results of the analysis indicates that Malaysia has a diverse age structure since 1970 throughout 2020. In 1970, Malaysia had experienced high fertility due to the ‘baby boom’ phenomenon which reflected the high percentage of young aged group and less percentage of the elderly. However, the age structure of Malaysia pop ulation had changed drastically in 2010 due to the swings in the fertility and mortality rate from high to low where the fertility rate reached the replacement level at 2.1. Finally, this study demonstrated that the projected of total population in Malaysia using Bayesian tech nique give a better result as compared to deterministic method. It shows that the population will increase gradually between 33.72 to 35.73 million in 2025. The projected total popu lation will increase more than four million in 2050 to reach between 36.98 to 43.89 million. Thus, the projected median age for the next 30 years where it will be increased from 29.88 years in 2015 to 40.25 years in 2050. Malaysia is expected to be an aged nation by 2025 where the ageing index is 36.10.
format Thesis
author Abdul Rashid, Saharani
author_facet Abdul Rashid, Saharani
author_sort Abdul Rashid, Saharani
title Malaysia population dynamics and the Bayesian projection modelling with functional scalable approach projection interval / Saharani Abdul Rashid
title_short Malaysia population dynamics and the Bayesian projection modelling with functional scalable approach projection interval / Saharani Abdul Rashid
title_full Malaysia population dynamics and the Bayesian projection modelling with functional scalable approach projection interval / Saharani Abdul Rashid
title_fullStr Malaysia population dynamics and the Bayesian projection modelling with functional scalable approach projection interval / Saharani Abdul Rashid
title_full_unstemmed Malaysia population dynamics and the Bayesian projection modelling with functional scalable approach projection interval / Saharani Abdul Rashid
title_sort malaysia population dynamics and the bayesian projection modelling with functional scalable approach projection interval / saharani abdul rashid
publishDate 2022
url https://ir.uitm.edu.my/id/eprint/74318/2/74318.pdf
https://ir.uitm.edu.my/id/eprint/74318/
_version_ 1761622533989203968
spelling my.uitm.ir.743182023-03-28T13:22:17Z https://ir.uitm.edu.my/id/eprint/74318/ Malaysia population dynamics and the Bayesian projection modelling with functional scalable approach projection interval / Saharani Abdul Rashid Abdul Rashid, Saharani Demography. Population. Vital events Prediction analysis An understanding of past, present and future population dynamics is necessary for a nation in development planning. The changes in demographic component which are fertility, mor tality and migration have led to change in population dynamics. Nowadays, United Nation (UN) had emphasized on using Bayesian models for population projection. However, not much detail description in terms of population dynamics that has been done in the past few years particularly for Malaysia population. In addition, Department of Statistics Malaysia is currently using deterministic approach which is Cohort Component method to project future population in Malaysia. Meanwhile many studies have proven a probabilistic model is better than the deterministic because the model considers uncertainty element. To date, the implementation of the probabilistic model particularly the Bayesian model is still rare. A model was first developed to project individual fertility and then extended to both fer tility and mortality. However the combination of all components (fertility, mortality and migration) for total population projection is seen lacking. Thus, this study aims to model population dynamics of Malaysian by considering simultaneously all the three important demographic components using Bayesian model. To study the structure and composition of population in Malaysia, the past and present trend of fertility, mortality as well as mi gration were examined using graphical presentations and trends analyses. The projections of the total population for 5-year intervals were then performed using two Bayesian mod els. The first projection model is based on the projected fertility and mortality while the second model is based on all the three components; fertility, mortality and migration. The projection of population was also conducted using exponential growth model. The per formance of the Bayesian projection models were compared to the results of the exponen tial growth model and cohort component method for the same interval period. Functional based discretization method was also proposed to enhance the time point of 5-year intervals projection to annual projection to enable for annual scalable values. All data used in this study were obtained from various agencies which include Department of Statistics Malaysia (DOSM) and National Population and Family Development Board (NPFDB) and cover 50- year period from 1970 to 2020. The results of the analysis indicates that Malaysia has a diverse age structure since 1970 throughout 2020. In 1970, Malaysia had experienced high fertility due to the ‘baby boom’ phenomenon which reflected the high percentage of young aged group and less percentage of the elderly. However, the age structure of Malaysia pop ulation had changed drastically in 2010 due to the swings in the fertility and mortality rate from high to low where the fertility rate reached the replacement level at 2.1. Finally, this study demonstrated that the projected of total population in Malaysia using Bayesian tech nique give a better result as compared to deterministic method. It shows that the population will increase gradually between 33.72 to 35.73 million in 2025. The projected total popu lation will increase more than four million in 2050 to reach between 36.98 to 43.89 million. Thus, the projected median age for the next 30 years where it will be increased from 29.88 years in 2015 to 40.25 years in 2050. Malaysia is expected to be an aged nation by 2025 where the ageing index is 36.10. 2022 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/74318/2/74318.pdf Malaysia population dynamics and the Bayesian projection modelling with functional scalable approach projection interval / Saharani Abdul Rashid. (2022) PhD thesis, thesis, Universiti Teknologi MARA (UiTM).
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