Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors

We propose a new model in a Bayesian hierarchical framework to project mortality at both national and subnational levels based on sparse or missing data. The new model, which has a country–region–province structure, uses common factors to pool information at the national level and within regions con...

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Autores principales:	Qian Lu, Katja Hanewald, Xiaojun Wang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	mortality modelling Bayesian framework subnational populations life expectancy Insurance HG8011-9999
Acceso en línea:	https://doaj.org/article/99696d9f30e54c27a7e13cc61ea03178
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id	oai:doaj.org-article:99696d9f30e54c27a7e13cc61ea03178
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spelling	oai:doaj.org-article:99696d9f30e54c27a7e13cc61ea031782021-11-25T18:56:12ZSubnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors10.3390/risks91102032227-9091https://doaj.org/article/99696d9f30e54c27a7e13cc61ea031782021-11-01T00:00:00Zhttps://www.mdpi.com/2227-9091/9/11/203https://doaj.org/toc/2227-9091We propose a new model in a Bayesian hierarchical framework to project mortality at both national and subnational levels based on sparse or missing data. The new model, which has a country–region–province structure, uses common factors to pool information at the national level and within regions consisting of several provinces or states. We illustrate the model’s use by drawing on a new database containing provincial-level mortality data for China from four censuses conducted during the period 1982–2010. The new model provides good estimates and reasonable forecasts at both the country and provincial levels. The model’s forecast intervals reflect provincial- and regional-level uncertainty. Using subnational data for the period 1999–2018 from the Centers for Disease Control and Prevention (CDC), we also apply the model to the United States. We use mortality forecasts to compute and compare national and subnational life expectancies for China and the United States. The model predicts that, in 2030, China will have a similar national life expectancy at age 60 and a similar heterogeneity in subnational life expectancy as the United States.Qian LuKatja HanewaldXiaojun WangMDPI AGarticlemortality modellingBayesian frameworksubnational populationslife expectancyInsuranceHG8011-9999ENRisks, Vol 9, Iss 203, p 203 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	mortality modelling Bayesian framework subnational populations life expectancy Insurance HG8011-9999
spellingShingle	mortality modelling Bayesian framework subnational populations life expectancy Insurance HG8011-9999 Qian Lu Katja Hanewald Xiaojun Wang Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors
description	We propose a new model in a Bayesian hierarchical framework to project mortality at both national and subnational levels based on sparse or missing data. The new model, which has a country–region–province structure, uses common factors to pool information at the national level and within regions consisting of several provinces or states. We illustrate the model’s use by drawing on a new database containing provincial-level mortality data for China from four censuses conducted during the period 1982–2010. The new model provides good estimates and reasonable forecasts at both the country and provincial levels. The model’s forecast intervals reflect provincial- and regional-level uncertainty. Using subnational data for the period 1999–2018 from the Centers for Disease Control and Prevention (CDC), we also apply the model to the United States. We use mortality forecasts to compute and compare national and subnational life expectancies for China and the United States. The model predicts that, in 2030, China will have a similar national life expectancy at age 60 and a similar heterogeneity in subnational life expectancy as the United States.
format	article
author	Qian Lu Katja Hanewald Xiaojun Wang
author_facet	Qian Lu Katja Hanewald Xiaojun Wang
author_sort	Qian Lu
title	Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors
title_short	Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors
title_full	Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors
title_fullStr	Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors
title_full_unstemmed	Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors
title_sort	subnational mortality modelling: a bayesian hierarchical model with common factors
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/99696d9f30e54c27a7e13cc61ea03178
work_keys_str_mv	AT qianlu subnationalmortalitymodellingabayesianhierarchicalmodelwithcommonfactors AT katjahanewald subnationalmortalitymodellingabayesianhierarchicalmodelwithcommonfactors AT xiaojunwang subnationalmortalitymodellingabayesianhierarchicalmodelwithcommonfactors
_version_	1718410542621655040

Subnational Mortality Modelling: A Bayesian Hierarchical Model with Common Factors

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