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    题名: Multi-population Mortality Modeling: When the Data is Too Much and Not Enough
    作者: 蔡政憲;郭維裕
    Tsai, Chenghsien Jason;Kuo, Weiyu
    Kung, Ko-Lun;MacMinn, Richard D.
    贡献者: 風管系
    关键词: Multi-population mortality;Approximate factor model;Idiosyncratic heteroskedasticity;Correlation;Mahalanobis distance
    日期: 2022-03
    上传时间: 2022-05-26 16:16:19 (UTC+8)
    摘要: 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.
    關聯: Insurance: Mathematics and Economics, 103, pp. 41-55
    数据类型: article
    DOI 連結: https://doi.org/10.1016/j.insmatheco.2021.12.005
    DOI: 10.1016/j.insmatheco.2021.12.005
    显示于类别:[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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