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Stochastic mortality forecasts for Bangladesh

Mortality forecasts are essential part for policymaking in any aging society. In recent years, methods to model and forecast mortality have improved considerably. Among them, Lee-Carter method is one of the most influential method. In this paper, Lee-Carter method is applied to forecast mortality an...

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Detalles Bibliográficos
Autores principales: Fazle Rabbi, Ahbab Mohammad, Khan, Hafiz T. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648772/
https://www.ncbi.nlm.nih.gov/pubmed/36355800
http://dx.doi.org/10.1371/journal.pone.0276966
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author Fazle Rabbi, Ahbab Mohammad
Khan, Hafiz T. A.
author_facet Fazle Rabbi, Ahbab Mohammad
Khan, Hafiz T. A.
author_sort Fazle Rabbi, Ahbab Mohammad
collection PubMed
description Mortality forecasts are essential part for policymaking in any aging society. In recent years, methods to model and forecast mortality have improved considerably. Among them, Lee-Carter method is one of the most influential method. In this paper, Lee-Carter method is applied to forecast mortality and life expectancy of Bangladesh. A functional data analysis approach is used to decompose the smoothed log-mortality rates in Lee-Carter framework for higher goodness-of-fit of the models and for longer forecast horizons. Bangladesh has been experiencing a mortality transition and has gained life expectancy in last few decades. The fitted model here showed higher pace of mortality decline for women in Bangladesh than that of men. The forecasts showed continuation of mortality improvement in long run and by 2060 life expectancy at birth is expected to reach over 80 years for both sexes in Bangladesh. The study also predicts the effect of reduction in infant mortality on the life expectancy in Bangladesh.
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spelling pubmed-96487722022-11-15 Stochastic mortality forecasts for Bangladesh Fazle Rabbi, Ahbab Mohammad Khan, Hafiz T. A. PLoS One Research Article Mortality forecasts are essential part for policymaking in any aging society. In recent years, methods to model and forecast mortality have improved considerably. Among them, Lee-Carter method is one of the most influential method. In this paper, Lee-Carter method is applied to forecast mortality and life expectancy of Bangladesh. A functional data analysis approach is used to decompose the smoothed log-mortality rates in Lee-Carter framework for higher goodness-of-fit of the models and for longer forecast horizons. Bangladesh has been experiencing a mortality transition and has gained life expectancy in last few decades. The fitted model here showed higher pace of mortality decline for women in Bangladesh than that of men. The forecasts showed continuation of mortality improvement in long run and by 2060 life expectancy at birth is expected to reach over 80 years for both sexes in Bangladesh. The study also predicts the effect of reduction in infant mortality on the life expectancy in Bangladesh. Public Library of Science 2022-11-10 /pmc/articles/PMC9648772/ /pubmed/36355800 http://dx.doi.org/10.1371/journal.pone.0276966 Text en © 2022 Fazle Rabbi, Khan https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Fazle Rabbi, Ahbab Mohammad
Khan, Hafiz T. A.
Stochastic mortality forecasts for Bangladesh
title Stochastic mortality forecasts for Bangladesh
title_full Stochastic mortality forecasts for Bangladesh
title_fullStr Stochastic mortality forecasts for Bangladesh
title_full_unstemmed Stochastic mortality forecasts for Bangladesh
title_short Stochastic mortality forecasts for Bangladesh
title_sort stochastic mortality forecasts for bangladesh
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648772/
https://www.ncbi.nlm.nih.gov/pubmed/36355800
http://dx.doi.org/10.1371/journal.pone.0276966
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