Publication:
Health Status, Mortality Heterogeneity and Implications for Post Retirement Product Innovation

dc.contributor.advisor Sherris, Michael
dc.contributor.advisor Ziveyi, Jonathan
dc.contributor.advisor Villegas Ramirez, Andres
dc.contributor.author Li, Yulong
dc.date.accessioned 2023-03-13T06:21:35Z
dc.date.available 2023-03-13T06:21:35Z
dc.date.issued 2023
dc.date.submitted 2023-03-09T06:09:29Z
dc.description.abstract Mortality modelling and projection is important for actuarial science and significant amount of research has been done in this regard. In addition to the systematic uncertainty over time, mortality risk can also vary across individuals of the same age, a phenomenon known as mortality heterogeneity. In this thesis, I propose and establish a mortality model incorporating health heterogeneity, based on which I assess the positive impact of considering health effects on both government and individual retirement finances. I also incorporate systematic mortality by health state and extend the estimation of cohort mortality models to incomplete cohort data. In cohort mortality modelling, the traditional Kalman Filter Algorithm (KFA) uses the complete older cohort data while ignoring the recent incomplete cohort data. The calibrated mortality model can lead to unreliable mortality projections especially for long-term projections. In the first part of the thesis, I extend the traditional KFA by incorporating recent incomplete cohort data in the model fitting process, ensuring the mortality model projection is more accurate and better captures cohort mortality developments. Then in the second part, I propose and estimate a finite-state Markov Ageing Model (MAM) incorporating health heterogeneity, which is calibrated based on Australian cohort mortality and health condition data. This model better captures both the mortality and health developments for individuals with different initial health status. We capture the feature that healthier individuals are more likely to survive, while less healthy individuals are more likely to die based on the calibrated model. Allowing for health heterogeneity when make retirement planning is important because of these differences. In the last part, I provide an impact analysis of the MyRetirement system (CIPRs) from two perspectives: first, I use the multi-state health mortality model with which we consider both systematic mortality and health heterogeneity. Second, I add health-linked components (deferred health annuities) to the CIPRs' portfolio framework, aiming to provide health-linked income streams for retirees when their health costs increase significantly. I show how this extension is beneficial both to the government, in terms of Age Pension payments, and to retirees, in terms of retirement incomes.
dc.identifier.uri http://hdl.handle.net/1959.4/101022
dc.language English
dc.language.iso en
dc.publisher UNSW, Sydney
dc.rights CC BY 4.0
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject.other Health Status
dc.subject.other Mortality Heterogeneity
dc.subject.other Post Retirement Product Innovation
dc.title Health Status, Mortality Heterogeneity and Implications for Post Retirement Product Innovation
dc.type Thesis
dcterms.accessRights embargoed access
dcterms.rightsHolder Li, Yulong
dspace.entity.type Publication
unsw.accessRights.uri http://purl.org/coar/access_right/c_f1cf
unsw.date.embargo 2024-12-13
unsw.date.workflow 2023-03-13
unsw.description.embargoNote Embargoed until 2024-12-13
unsw.description.notePublic None
unsw.identifier.doi https://doi.org/10.26190/unsworks/24729
unsw.relation.faculty Business
unsw.relation.school School Risk & Actuarial Studies
unsw.relation.school School Risk & Actuarial Studies
unsw.relation.school School Risk & Actuarial Studies
unsw.relation.school School Risk & Actuarial Studies
unsw.subject.fieldofresearchcode 440304 Mortality
unsw.subject.fieldofresearchcode 420301 Aged health care
unsw.thesis.degreetype PhD Doctorate
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