对共同年龄效应模型的研究及中国应用
Research on the Common Age Effect Model and Its Application in China
DOI: 10.12677/AAM.2021.1011397, PDF,  被引量    国家自然科学基金支持
作者: 肖鸿民*, 李芳芳, 赵苗苗:西北师范大学数学与统计学院,甘肃 兰州
关键词: 共同年龄效应模型Lee-Carter模型中国多人口死亡率Common Age Effect Model Lee-Carter Model China Multi-Population Mortality
摘要: 共同年龄效应模型是一种在多个人口数据中提取所有数据对象所共有的共同年龄效应的多人口死亡率模型。我们首次运用共同年龄效应模型研究中国男女性死亡率。基于中国男女性死亡率数据,分别使用共同年龄效应模型的极大似然估计和Lee-Carter模型的最小二乘估计对数据进行了处理,结果表明共同年龄效应模型在处理中国男女性死亡率数据时,拟合和预测效果都很好。
Abstract: The common age effect model is a multi-population mortality model that extracts the common age effect shared by all data objects from multiple population data. For the first time, we use the common age effect model to study the mortality of men and women in China. Based on the Chinese male and female mortality data, the maximum likelihood estimation of the Common Age Effect model and the least square estimation of the Lee-Carter model were used to process the data. The results show that while the common age effect model processes the Chinese male and female mortality data, the effects of fitting and prediction are pretty well.
文章引用:肖鸿民, 李芳芳, 赵苗苗. 对共同年龄效应模型的研究及中国应用[J]. 应用数学进展, 2021, 10(11): 3743-3757. https://doi.org/10.12677/AAM.2021.1011397

参考文献

[1] 国务院第七次全国人口普查领导小组办公室, 第七次全国人口普查公报(第五号)——人口年龄构成情况[EB/OL]. http://www.stats.gov.cn/ztjc/zdtjgz/zgrkpc/dqcrkpc/ggl/202105/t20210519_1817698.html, 2021-05-11.
[2] Lee, R.D. and Carter, L.R. (1992) Modeling and Forecasting US Mortality. Journal of American Statistical Association, 87, 659-675. [Google Scholar] [CrossRef
[3] Currie, I.D., Durban, M. and Eilers, P.H.C. (2006) Generalized Linear Array Models with Applications to Multidimensional Smoothing. Journal of the Royal Statistical Society, 68, 259-280. [Google Scholar] [CrossRef
[4] Cairns, A.J.G., Blake, D. and Dowd, K. (2006) A Two-Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration. Journal of Risk and Insurance, 73, 687-718. [Google Scholar] [CrossRef
[5] Carter, L.R. and Lee, R.D. (1992) Modeling and Forecasting US Sex Differentials in Mortality. International Journal of Forecasting, 8, 393-411. [Google Scholar] [CrossRef
[6] Kleinow, T. (2015) A Common Age Effect Model for the Mortality of Multiple Populations. Mathematics and Economics, 63, 147-152. [Google Scholar] [CrossRef
[7] Kang, M., Liu, Y., Li, J.S.-H. and Chan, W.-S. (2018) Mortality Forecasting for Multiple Populations: An Augmented Common Factor Model with a Penalized Log-Likelihood. Communications in Statistics: Case Studies, Data Analysis and Applications, 4, 118-141. [Google Scholar] [CrossRef
[8] 李志生, 刘恒甲. Lee-Carter死亡率模型的估计与应用——基于中国人口数据的分析[J]. 中国人口科学, 2010(3): 46-56+111.
[9] 赵明, 王晓军. 多人口Lee-Carter随机死亡率模型比较与中国应用[J]. 中国人口科学, 2020(2): 81-96+128.
[10] 赵明, 王晓军. 多人口随机死亡率模型研究: 理论方法与进展综述[J]. 统计研究, 2020, 37(7): 30-41.
[11] 曹园. 基于Lee-Cater模型的我国死亡率预测[J]. 统计与决策, 2018, 34(9): 32-36.
[12] 肖鸿民, 马海飞, 康彦玲. 两种死亡率预测方法的比较[J]. 统计与决策, 2020, 36(23): 5-8.
[13] Enchev, V., Kleinow, T. and Cairns, A.J.G. (2017) Multi-Population Mortality Models: Fitting, Forecasting and Comparisons. Scandinavian Actuarial Journal, 4, 319-342. [Google Scholar] [CrossRef
[14] Simon, S., Torsten, K. and Ralf, K. (2021) Clustering-Based Extensions of the Common Age Effect Multi-Population Mortality Model. Risks, 9, 45. [Google Scholar] [CrossRef