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Mortality: modelling, socio-economic differences and basis risk

Villegas Ramirez, Andres (2015). Mortality: modelling, socio-economic differences and basis risk. (Unpublished Doctoral thesis, City University London)


During the last two centuries the developed world experienced a persistent increase in life expectancy. Although past trends suggests that life expectancy will continue to increase, there is considerable uncertainty surrounding the future evolution of mortality. In addition, past mortality improvements have not been shared equally across the population, resulting in a widening of socio-economic inequalities in mortality. The uncertainty and socio-economic variability of life expectancy pose a challenge for the design of pension systems and the management of longevity risk in pension funds and annuity portfolios.
This thesis is devoted to the investigation of the trends and financial implications of socio-economic differences in mortality. It comprises three parts. The first part introduces new modelling techniques for the quantification of socio-economic mortality differentials in aggregate and cause-specific mortality, which are applied in the study of the relationship between mortality and deprivation in the English population. The second part evaluates the suitability of several multipopulation stochastic mortality models for assessing basis risk in longevity hedges and provides guidelines on how to use these models in practical situations. Finally, the third part introduces new modelling tools which aim to permit a more effective and widespread use of stochastic mortality models.

Publication Type: Thesis (Doctoral)
Additional Information: Chapter 2 previously published as: Villegas, A. M., Haberman, S. (2014) On the modelling and forecasting of socio-economic mortality differentials: an application to deprivation and mortality in England. North American Actuarial Journal 18 (1), 168–193. doi:10.1080/10920277.2013.866034. Chapter 6 previously published as: Hunt, A., Villegas, A.M., 2015. Robustness and convergence in the Lee-Carter model with cohort effects. Insurance: Mathematics and Economics 64 186-202 doi:10.1016/j.insmatheco.2015.05.004.
Subjects: H Social Sciences > HG Finance
Departments: Bayes Business School > Actuarial Science & Insurance
Doctoral Theses
Bayes Business School > Bayes Business School Doctoral Theses
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