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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/139749
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- Title
- Joint mortality modeling based on Lee-Carter model
- Related
- Higher Degree Research Expo (6th : 2010) (19 November 2010 : Sydney)
- Related
- Expo 2010 Higher Degree Research : book of abstracts, p.89
- Related
- http://www.businessandeconomics.mq.edu.au/research_expo/website_administration/2010_expo_presenter_profiles2/jianhui_xu
- Publisher
- North Ryde, N.S.W : Faculty of Business and Economics, Macquarie University
- Date
- 2010
- Author/Creator
- Xu, Jianhui (Tandy)
- Description
- Purpose: This research analyses the joint behaviour of mortality in different populations, and aims to model their difference and similarities using a joint model. Originality: Existing mortality studies typically analyse single populations with each population analysed separately and without reference to other populations. Such an approach limits the pooling of common trend and cross sectional information across populations and limits the ability to discern and understand differences between populations. This research aims to develop “joint” mortality model based on the Lee-Carter framework. The multiple population framework permits detailed analyses of differences and co-integration behaviour. Key literature / theoretical perspective: The extended framework employs the Lee-Carter model as the building block, and extends a single population Least Squares Estimation method (SLSE) to a Multiple population format (MLSE). Design/methodology/approach: This research firstly deduces the MLSE framework, and then analyses data from different and similar populations. Therefore, is will focus on theoretical deduction and quantitative analysis. Findings: Similarities across populations are specified as restrictions and are tested. Combining populations makes for more efficient forecasting and the analysis and understanding of divergent trends in different populations. Research limitations/implications: Restrictions are not easy to establish, and reasons for differences may be complex and not simply quantified. Practical and Social implications: This research may lead to theoretical developments that will increase the accuracy of mortality projection. Furthermore, if a population is too small to be estimated, or its data is not reliable, it can be forecast by reference to a highly similar population.
- Description
- 1 page(s)
- Subject Keyword
- joint mortality model
- Subject Keyword
- Lee-Carter model
- Subject Keyword
- matrix computation
- Subject Keyword
- Least Squares Estimation
- Resource Type
- conference paper abstract
- Organisation
- Macquarie University. Department of Actuarial Studies
- Identifier
- http://hdl.handle.net/1959.14/139749
- Identifier
- mq:15351
- Identifier
- ISSN:1837-9214
- Identifier
- mq-rm-2010005507
- Language
- eng
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