Academic Journal
BIAS-CORRECTED INFERENCE FOR A MODIFIED LEE–CARTER MORTALITY MODEL.
| Τίτλος: | BIAS-CORRECTED INFERENCE FOR A MODIFIED LEE–CARTER MORTALITY MODEL. |
|---|---|
| Συγγραφείς: | Liu, Qing1 qliu8310@aliyun.com, Ling, Chen2 cling5@gsu.edu, Li, Deyuan3 deyuanli@fudan.edu.cn, Peng, Liang2 lpeng@gsu.edu |
| Πηγή: | Astin Bulletin. May2019, Vol. 49 Issue 2, p433-455. 23p. |
| Θεματικοί όροι: | *Life insurance companies, *Mortality -- Mathematical models, Death rate, Least squares, Mortality |
| Γεωγραφικοί όροι: | United States |
| Εταιρία/Οντότητα: | American Statistical Association 070110986 |
| Περίληψη: | As a benchmark mortality model in forecasting future mortality rates and hedging longevity risk, the widely employed Lee–Carter model (Lee, R.D. and Carter, L.R. (1992) Modeling and forecasting U.S. mortality. Journal of the American Statistical Association , 87 , 659–671.) suffers from a restrictive constraint on the unobserved mortality index for ensuring model's identification and a possible inconsistent inference. Recently, a modified Lee–Carter model (Liu, Q., Ling, C. and Peng, L. (2018) Statistical inference for Lee–Carter mortality model and corresponding forecasts. North American Actuarial Journal , to appear.) removes this constraint and a simple least squares estimation is consistent with a normal limit when the mortality index follows from a unit root or near unit root AR(1) model with a nonzero intercept. This paper proposes a bias-corrected estimator for this modified Lee–Carter model, which is consistent and has a normal limit regardless of the mortality index being a stationary or near unit root or unit root AR(1) process with a nonzero intercept. Applications to the US mortality rates and a simulation study are provided as well. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Business Source Index |
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