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Extending the Lee-Carter model: a three-way decomposition

机译:扩展Lee-Carter模型:三向分解

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In this paper, we focus on a Multi-dimensional Data Analysis approach to the Lee-Carter (LC) model of mortality trends. In particular, we extend the bilinear LC model and specify a new model based on a three-way structure, which incorporates a further component in the decomposition of the log-mortality rates. A multi-way component analysis is performed using the Tucker3 model. The suggested methodology allows us to obtain combined estimates for the three modes: (1) time, (2) age groups and (3) different populations. From the results obtained by the Tucker3 decomposition, we can jointly compare, in both a numerical and graphical way, the relationships among all three modes and obtain a time-series component as a leading indicator of the mortality trend for a group of populations. Further, we carry out a correlation analysis of the estimated trends in order to assess the reliability of the results of the three-way decomposition. The model's goodness of fit is assessed using an analysis of the residuals. Finally, we discuss how the synthesised mortality index can be used to build concise projected life tables for a group of populations. An application which compares 10 European countries is used to illustrate the approach and provide a deeper insight into the model and its implementation.View full textDownload full textKeywordsBiplot, Mortality forecasting, Singular value decomposition, Tucker3 modelJEL ClassificationsC49, G20Related var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/03461231003611933
机译:在本文中,我们重点关注死亡率趋势的Lee-Carter(LC)模型的多维数据分析方法。特别是,我们扩展了双线性LC模型并指定了一种基于三向结构的新模型,该模型在对数死亡率的分解中包含了其他成分。使用Tucker3模型执行多路组件分析。建议的方法使我们能够获得以下三种模式的组合估计:(1)时间,(2)年龄组和(3)不同的人群。从Tucker3分解获得的结果中,我们可以通过数值和图形方式共同比较这三种模式之间的关系,并获得时间序列成分,作为一组人群死亡率趋势的主要指标。此外,我们对估计趋势进行了相关分析,以评估三向分解结果的可靠性。使用残差分析评估模型的拟合优度。最后,我们讨论如何使用综合死亡率指数为一组人群建立简洁的预计寿命表。使用一个比较了10个欧洲国家/地区的应用程序来说明该方法,并提供对该模型及其实现的更深入的了解。查看全文下载全文关键字Biplot,死亡率预测,奇异值分解,Tucker3模型JEL分类C49,G20泰勒和弗朗西斯在线”,services_compact:“ citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,更多”,发布号:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/03461231003611933

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