英文标题：
《Cohort effects in mortality modelling: a Bayesian state-space approach》
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作者：
Man Chung Fung and Gareth W. Peters and Pavel V. Shevchenko
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最新提交年份：
2017
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英文摘要：
  Cohort effects are important factors in determining the evolution of human mortality for certain countries. Extensions of dynamic mortality models with cohort features have been proposed in the literature to account for these factors under the generalised linear modelling framework. In this paper we approach the problem of mortality modelling with cohort factors incorporated through a novel formulation under a state-space methodology. In the process we demonstrate that cohort factors can be formulated naturally under the state-space framework, despite the fact that cohort factors are indexed according to year-of-birth rather than year. Bayesian inference for cohort models in a state-space formulation is then developed based on an efficient Markov chain Monte Carlo sampler, allowing for the quantification of parameter uncertainty in cohort models and resulting mortality forecasts that are used for life expectancy and life table constructions. The effectiveness of our approach is examined through comprehensive empirical studies involving male and female populations from various countries. Our results show that cohort patterns are present for certain countries that we studied and the inclusion of cohort factors are crucial in capturing these phenomena, thus highlighting the benefits of introducing cohort models in the state-space framework. Forecasting of cohort models is also discussed in light of the projection of cohort factors.
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中文摘要：
队列效应是决定某些国家人类死亡率演变的重要因素。文献中提出了具有队列特征的动态死亡率模型的扩展，以在广义线性建模框架下解释这些因素。在本文中，我们探讨了在状态空间方法下通过一个新的公式结合队列因素的死亡率建模问题。在这个过程中，我们证明了队列因素可以在状态空间框架下自然形成，尽管队列因素是根据出生年份而不是年份编制的。然后，基于有效的马尔可夫链蒙特卡罗采样器，对状态空间公式中的队列模型进行贝叶斯推理，从而量化队列模型中的参数不确定性以及用于预期寿命和寿命表构建的死亡率预测。我们的方法的有效性是通过对来自不同国家的男性和女性人口进行全面的实证研究来检验的。我们的结果表明，我们所研究的某些国家存在队列模式，队列因素的纳入对于捕捉这些现象至关重要，因此突出了在状态空间框架中引入队列模型的好处。根据队列因素的预测，还讨论了队列模型的预测。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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