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政大機構典藏 > 商學院 > 風險管理與保險學系 > 期刊論文 > Item 140.119/140164

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/140164

Title:	Multi-population Mortality Modeling: When the Data is Too Much and Not Enough
Authors:	蔡政憲;郭維裕 Tsai, Chenghsien Jason;Kuo, Weiyu Kung, Ko-Lun;MacMinn, Richard D.
Contributors:	風管系
Keywords:	Multi-population mortality;Approximate factor model;Idiosyncratic heteroskedasticity;Correlation;Mahalanobis distance
Date:	2022-03
Issue Date:	2022-05-26 16:16:19 (UTC+8)
Abstract:	A large number of mortality rates yield estimation issues in a mortality model. The first issue is about the consistency of factor estimates when the number of mortality rates is more than the number of observations. The second issue concerns the heterogeneity among multiple populations or within a single population. We apply the framework of the approximate factor model to resolve these issues. The empirical tests on individual and multiple populations show that incorporating idiosyncratic heteroskedasticities and correlations into estimations improves in-sample fitting and out-of-sample forecasting. By comparing with existing models, we conclude that the improvements come from capturing the heteroskedasticities and correlations in the higher-order idiosyncratic errors.
Relation:	Insurance: Mathematics and Economics, 103, pp. 41-55
Data Type:	article
DOI 連結:	https://doi.org/10.1016/j.insmatheco.2021.12.005
DOI:	10.1016/j.insmatheco.2021.12.005
Appears in Collections:	[風險管理與保險學系] 期刊論文 [國際經營與貿易學系 ] 期刊論文

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