1. i
The University of Southampton
Academic Year (2014/2015)
Faculty of Social, Human and Mathematical
Sciences
MSc Dissertation
Mortality Modelling and Projection
by
Jekaterina Pasecnika
A dissertation submitted in partial fulfilment of the MSc in
Actuarial Science
I am aware of the requirements of good academic practice and the potential
penalties for any breaches. I confirm that this dissertation is all my own work.

2. ii
Abstract
The purpose of this study is to evaluate the goodness-of-fit and forecast
accuracy of four stochastic mortality models: Lee-Carter, Lee-Miller, Booth-
Maindonald-Smith and weighted Hyndman-Ullah in order to check how well the
models capture mortality trends and features of the data.
The gender- particular populations of the five following countries were used:
The results of the Bayesian information criterion revealed the Booth-Maindonald-
Smith, as the model with best score in all countries except Latvia, where the
Hyndman-Ullah weighted model was the leader. However, the plots of residual
mortality rates with age, residuals heat plots and observed versus fitted plots
imply the Hyndman-Ullah model to fit the data better. In terms of forecasting, the
models chosen underestimate the male mortality rates for the most countries
except Latvia (in the LC and the BMS) and overestimate the female mortality for
the UK, Canada, Australia and Latvia

3. 3
1.1 BackgroundInformation
Recently, mortality modelling has generally received a significant amount of
attention, as it is not only important for actuarial analysis, but as well for population
changes research, and public benefits planning (Li et al., 2015). Mortality rates
directly influence the life expectancy, consequently, the lifespan, has increased with
the decrease of mortality rates. In last couple of decades the mortality rates have
decreased at an approximate rate of three years per decade and as a result,
mortality matter has as well become a matter of governmental interest, as a
considerable burden was placed on public benefits planning (Li et al., 2015).
Because of the decline in tax revenue, as one of the effects of ageing population,
there is a significant interest in accurate modelling and forecasting of mortality rates,
as it can be of great step forward in decision-making concerning the resources
distribution in the future for both, governmental and private benefits planning (Shang
et al., 2011). Consequently, it is essential to understand the behavior and trends for
mortality rates in order to adequately model and project them in the future (Renshaw
& Haberman, 2006). An effect of failure to select an appropriate mortality model can
be unpleasant, as if the insurer overestimates the risk, the consumer will suffer the
effect of overpriced insurance premiums and if the risk is underestimated, the insurer
suffers from money and potential investors loss (Melnikov & Romaniuk, 2006).
The main question to be answered is how the mortality rates evolves/improves in the
future, as this could help to avoid deficits in public and private benefits. (OECD,
2014)
1.2 Objectives
Primarily, the objective of this project is to compare how accurate the selected
models can capture the essence of mortality improvements and trends in general.
The analysis is performed by evaluating the goodness-of-fit and by assessing the
forecast accuracy (back-testing) for each model and country (by gender).