A multi-parameter-level model for simulating future mortality scenarios with COVID-alike effects

IF 1.5 Q3 BUSINESS, FINANCE
Rui Zhou, J. S. Li
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引用次数: 6

Abstract

Abstract There has been a growing interest among pension plan sponsors in envisioning how the mortality experience of their active and deferred members may turn out to be if a pandemic similar to the COVID-19 occurs in the future. To address their needs, we propose in this paper a stochastic model for simulating future mortality scenarios with COVID-alike effects. The proposed model encompasses three parameter levels. The first level includes parameters that capture the long-term pattern of mortality, whereas the second level contains parameters that gauge the excess age-specific mortality due to COVID-19. Parameters in the first and second levels are estimated using penalised quasi-likelihood maximisation method which was proposed for generalised linear mixed models. Finally, the third level includes parameters that draw on expert opinions concerning, for example, how likely a COVID-alike pandemic will occur in the future. We illustrate our proposed model with data from the United States and a range of expert opinions.
模拟具有类似新冠肺炎影响的未来死亡率情景的多参数水平模型
摘要养老金计划发起人越来越有兴趣设想,如果未来发生类似新冠肺炎的大流行,他们的活跃成员和延期成员的死亡经历可能会如何。为了满足他们的需求,我们在本文中提出了一个随机模型,用于模拟具有类似新冠肺炎影响的未来死亡率情景。所提出的模型包括三个参数级别。第一级包括捕捉长期死亡率模式的参数,而第二级包括衡量新冠肺炎导致的超额年龄特异性死亡率的参数。使用针对广义线性混合模型提出的惩罚准似然最大化方法来估计第一和第二级中的参数。最后,第三个层次包括参考专家意见的参数,例如,类似新冠肺炎的大流行在未来发生的可能性。我们用美国的数据和一系列专家意见来说明我们提出的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.10
自引率
5.90%
发文量
22
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