This thesis presents results of a research in developing a model to
forecast mortality using a combination of existing demographic and
time series models, specifically proposing a common factor model for
forecasting Malaysia mortality using the available mortality data set.
This research has been motivated by three (3) factors. Firstly, the need
for a mortality forecasting model “tailored” to Malaysia data set which
has been borne out of the scarcity of studies in forecasting Malaysia
mortality, crucial to government pensions and social security as well
as to practitioners in related fields. Secondly, over the last decades,
different models for forecasting mortality have been used to produce
mortality projections for different countries. However, no “universal”
model, applicable to all countries, has been developed, more so for
short-series historical mortality data. Hence, there is a need to develop
and apply an appropriate model to produce good forecasts of Malaysia
mortality. Thirdly, while undertaking a literature review to gain insights
into current mortality forecasting models, it became apparent that a gap
existed between the current models used for forecasting and projecting
Malaysia mortality and the current practice of incorporating state-space
methodology in mortality forecasting models, specifically in modelling
high-dimensional short series mortality data. Hence, the research gap
has to be narrowed. The first objective of this research is to establish a
comprehensive literature review on modeling and forecasting mortality
data.
