Modeling time to death for retirees in Kenya
Mwakala, Margaret Ndisha
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Many countries have studied the life of retirees, with special attention given to the quality of life of these individuals. In Kenya, no work has been done on the determinants of time to death after retirement. The average age of survival after retirement in Kenya is also not known. It is necessary to determine the causes, if any, of mortality in the retirement years and necessary interventions put in place to address them. The life expectancy of a retiree in Kenya is also a key matter, especially in life annuity programs in the insurance companies in Kenya, with the mortality and longevity risks being of great interest to actuaries and financial professionals. This study attempts to determine the life expectancy of a retiree in Kenya, both for men and women, by using the life table methods, widely used to determine the life expectancy. This information will be very useful in determining the cessation of life annuities, used usually to determine the end of guarantee period, which is calculated with the life expectancy in mind. As we determine the life expectancy, the determinants of time to death is also key, to shed light on what makes one retiree live longer compared to another retiree. Information like this can assist employers to advise their employees well on better planning, to ensure that retirement doesn’t lead to death, as has been seen over the years . Previous work on time to death after retirement has been done in other countries, specifically, developed countries, . Most studies associated early retirement, by extension age at retirement, gender and the socio-economic status of the retirees’ with mortality. To date no consensus has been reached on the survival or mortality of people who retire early compared to those who retire later. Some researchers concluded that early retirement harms health, attributing this to illness before retirement or the change of life events associated with retirement. On the other hand, there is a widespread perception that early retirement is associated with longer life expectancy and that retiring later leads to early death. The possible health benefits of retirement, such as reduced role demand and a more relaxed lifestyle, have been postulated to improve longevity among people who retire early . While the average years lived has been seen to generally increase in both developed and developing countries over time, determinants to death after retirement can hardly be assumed to be the same in the different set-ups, given the resources and medical provisions in the different set-ups . This study, in view of the finding of other studies done, attempts to check the validity of the models used elsewhere to determine time and the determinants to death in the Kenyan set- up, taking into consideration the age at retirement, socio-economic status, derived from the monthly pension paid to the retiree and gender, the time to death will be determined, thus observing the impact of certain factors as will be described below. The cox proportional hazard regression model has been used widely to determine survival time, taking into considerations its strength of considering individuals who had the event of interest (death) and those who were censored . In this study, we apply this model, to further explain the determinants of time to death after retirement in Kenya, i.e. sex, age-at-retirement and socio- economic status. This study showed that there is a significant difference between the survival times between male and female retirees, in fact showing that male retirees are 2.1 times more likely to die, compared to their female counterparts. This therefore leading us to conclude that gender does indeed determine the rate of survival after retirement in Kenya. Socio-economic status and age-at- retirement were also found to be significant determinants to time to death after retirement. This study concluded that early retirement does indeed increase the chances of early death, though the study also suggests that more information on the health status of the early retirees should be used as a covariate during such a study, to eliminate the possibility that the early retirees were already sick, thus their health status rather that their age cause the early death. Retirees should be advised to plan for their retirement since those retirees who earned less were 25% more likely to die than their counterparts who earned more. The standards of living after retirement can be boosted by a better savings plan that ensures that the life after retirement is catered for therefore employers should educate their employees on planning for this.