Volume 12, Issue 1 (11-2012)
2012, 12(1): 281-294 |
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Iranpanah N, Tavasoli H. Bootstrap Prediction Intervals for Mortality Probability of Iran. Journal title 2012; 12 (1) :281-294
URL: http://jsci.khu.ac.ir/article-1-1464-en.html
URL: http://jsci.khu.ac.ir/article-1-1464-en.html
Abstract: (7078 Views)
Mortality forecasts are nowadays widely used to create and modify retirement pension schemes, disability insurance systems and other social security programmers. Experience shows that static life tables overestimate death probabilities. The reason for this overestimation is that static life tables, through being computed for a specific period of time, cannot take into account the decreasing mortality trend over time. Dynamic life tables overcome this problem by incorporating the influence of the calendar when graduating mortality.
In this paper, we first apply the Lee-Carter model for estimation of mortality rate. Then, we use parametric and semi parametric bootstrap prediction intervals for mortality trend. Finally, these methods are applied for analysis of mortality data of Iran.
In this paper, we first apply the Lee-Carter model for estimation of mortality rate. Then, we use parametric and semi parametric bootstrap prediction intervals for mortality trend. Finally, these methods are applied for analysis of mortality data of Iran.
Keywords: Dynamic Life Tables, Lee-Carter Model, Spatial Statistics, Variogram, Parametric bootstrap, Semi Parametric Bootstrap
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