A quantitative analysis and comparison on mortality in the industrialized developing economies affiliated with China (Hong Kong SAR and Taiwan) using five stochastic mortality models

• Main Authors: Tan, Jun Da, Teo, Jeremy Jun Liang, Zhang, Bernice Wanling
• Other Authors: Li Ka Ki Jackie
• Format: Final Year Project
• Language: English
• Published: 2010
• Subjects: DRNTU::Business::Finance::Actuarial science
• Online Access: http://hdl.handle.net/10356/35478
• Institution: Nanyang Technological University

The entire juxtaposition of having strong developing economies, rising standards of living as well as close geographical, political and even socio-economic proximity to developing China, makes Hong Kong SAR and Taiwan particularly interesting countries to observe in growing Asia. Specifically, stellar life expectancy results achieved by Hong Kong SAR have motivated us to delve into mortality-related comparisons between Hong Kong SAR and Taiwan; hopefully shedding light on the implications of having a fully government funded social security system like that in Hong Kong, as opposed to Taiwan’s partial-government funded system. With that, our research seeks to first explain the life expectancy conundrum through mortality modelling and analysis on economic data and thereafter, to analyse the impact of longevity risk on the social security systems in both countries. Comparing qualities of various models, a cohort-adjusted CBD model was selected as the best stochastic model for fit with both countries. We were thus able identify that Hong Kong SAR has a higher life expectancy due to the stronger trend in mortality improvements for lower ages compared to Taiwan. Thereafter, forecasting with the use of a two-dimensional random walk with drift allowed us to measure trend risk and concentration risk. Our findings revealed the precarious situation Hong Kong SAR’s social security system may possibly face. Taiwan’s social security system, on the flipside, has stronger foundations, fuelled with the huge potential for her life expectancy rates to improve.