Inference for the Lee-Carter Model With An AR(2) Process

被引：2

作者：

Li, Deyuan ^{[1
]}

Ling, Chen ^{[2
]}

Liu, Qing ^{[3
,4
]}

Peng, Liang ^{[2
]}

机构：

[1] Fudan Univ, Sch Management, Shanghai 200433, Peoples R China

[2] Georgia State Univ, Dept Risk Management & Insurance, Atlanta, GA 30303 USA

[3] Jiangxi Univ Finance & Econ, Sch Stat, Nanchang 330013, Jiangxi, Peoples R China

[4] Jiangxi Univ Finance & Econ, Res Ctr Appl Stat, Nanchang 330013, Jiangxi, Peoples R China

来源：

METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY | 2022年 / 24卷 / 02期

关键词：

AR(2) model; Lee-Carter model; Mortality rates; Unit root; MEASUREMENT ERROR; MORTALITY;

D O I：

10.1007/s11009-021-09898-y

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Researchers in studying longevity risk often employ the Lee-Carter model with a unit root AR(1) process for unobserved mortality indexes. When one models the mortality index by a stationary AR(1) process, the widely used two-step inference in Lee and Carter (1992) is inconsistent. Some mortality datasets reject the unit root hypothesis. This paper develops consistent statistical inferences for a modified Lee-Carter model using an AR(2) process to model unobserved mortality indexes. It also provides a simulation study to examine their finite sample performance before applying them to the US mortality rates.

引用

页码：991 / 1019

页数：29

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