- Position: PhD Student - Department of Applied Finance and Actuarial Studies
- Principal supervisor: Professor Piet de Jong
- Associate supervisor: Associate Professor Leonie Tickle
- Date of submission: 01/01/2003
- Thesis title: Joint Mortality Modelling
- 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 populations 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. The multiple population framework permits detailed analyses of differences and co-integration behaviour.
- Key Literature/theoretical perspective: Three main joint mortality models, based on the original Lee-Carter model, Li and Lee (2005), Debón et al. (2010), Russolillo (2011) Wang Transform, are considered in this paper. Then, the extended format or applications of the three models are proposed here. Especially, the Wang transform method to project the mortality, proposed by Jong and Marshall (2007), is included in this paper, and an extension of the application of mortality forecasting based on Wang Transform, the linear framework of Wang Transform.
- Design/methodology/approach: Wang Transform has been proposed to forecast mortality. This research extends this application to a multiple population framework, and improves the different types of joint Lee-Carter models in formats and applications, 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 derive a new method to describe the mortality of a group of populations. 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.
- Keywords: Joint mortality model, joint Lee-Carter model, Wang Transform, Linear Framework, Combined Population