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Article: A Bayesian Approach to Developing a Stochastic Mortality Model for China

TitleA Bayesian Approach to Developing a Stochastic Mortality Model for China
Authors
KeywordsLee–Carter model
Multiple imputation
Sampling uncertainty
Sequential Kalman filter
Issue Date2019
PublisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/RSSA
Citation
Journal of the Royal Statistical Society. Series A: Statistics in Society, 2019, v. 182 n. 4, p. 1523-1560 How to Cite?
AbstractStochastic mortality models have a wide range of applications. They are particularly important for analysing Chinese mortality, which is subject to rapid and uncertain changes. However, owing to data‐related problems, stochastic modelling of Chinese mortality has not been given adequate attention. We attempt to use a Bayesian approach to model the evolution of Chinese mortality over time, taking into account all of the problems associated with the data set. We build on the Gaussian state space formulation of the Lee–Carter model, introducing new features to handle the missing data points, to acknowledge the fact that the data are obtained from different sources and to mitigate the erratic behaviour of the parameter estimates that arises from the data limitations. The approach proposed yields stochastic mortality forecasts that are in line with both the trend and the variation of the historical observations. We further use simulated pseudodata sets with resembling limitations to validate the approach. The validation result confirms our approach's success in dealing with the limitations of the Chinese mortality data.
Persistent Identifierhttp://hdl.handle.net/10722/280254
ISSN
2023 Impact Factor: 1.5
2023 SCImago Journal Rankings: 0.775
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, JSH-
dc.contributor.authorZhou, KQ-
dc.contributor.authorZhu, X-
dc.contributor.authorChan, WS-
dc.contributor.authorChan, FWH-
dc.date.accessioned2020-01-21T11:50:49Z-
dc.date.available2020-01-21T11:50:49Z-
dc.date.issued2019-
dc.identifier.citationJournal of the Royal Statistical Society. Series A: Statistics in Society, 2019, v. 182 n. 4, p. 1523-1560-
dc.identifier.issn0964-1998-
dc.identifier.urihttp://hdl.handle.net/10722/280254-
dc.description.abstractStochastic mortality models have a wide range of applications. They are particularly important for analysing Chinese mortality, which is subject to rapid and uncertain changes. However, owing to data‐related problems, stochastic modelling of Chinese mortality has not been given adequate attention. We attempt to use a Bayesian approach to model the evolution of Chinese mortality over time, taking into account all of the problems associated with the data set. We build on the Gaussian state space formulation of the Lee–Carter model, introducing new features to handle the missing data points, to acknowledge the fact that the data are obtained from different sources and to mitigate the erratic behaviour of the parameter estimates that arises from the data limitations. The approach proposed yields stochastic mortality forecasts that are in line with both the trend and the variation of the historical observations. We further use simulated pseudodata sets with resembling limitations to validate the approach. The validation result confirms our approach's success in dealing with the limitations of the Chinese mortality data.-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/RSSA-
dc.relation.ispartofJournal of the Royal Statistical Society. Series A: Statistics in Society-
dc.rightsPreprint This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Postprint This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.-
dc.subjectLee–Carter model-
dc.subjectMultiple imputation-
dc.subjectSampling uncertainty-
dc.subjectSequential Kalman filter-
dc.titleA Bayesian Approach to Developing a Stochastic Mortality Model for China-
dc.typeArticle-
dc.identifier.emailChan, FWH: fwhchan@hku.hk-
dc.identifier.authorityChan, FWH=rp01280-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/rssa.12473-
dc.identifier.scopuseid_2-s2.0-85066146317-
dc.identifier.hkuros309003-
dc.identifier.volume182-
dc.identifier.issue4-
dc.identifier.spage1523-
dc.identifier.epage1560-
dc.identifier.isiWOS:000492420800020-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0964-1998-

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