连续时间的日历年死亡率模型

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-02-22 DOI:10.1017/asb.2023.2

Donatien Hainaut

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引用次数: 0

摘要

摘要本文提出了一种基于历年的连续时间死亡率模型。死亡率属于按时间和年龄索引的均值回归随机场。为了解释预期寿命的提高，死亡率的逆转水平是年龄的确定性函数和驱动寿命进化的逐渐减少的跳跃扩散过程的产物。我们提供了生存概率的一般封闭形式表达式，并在死亡率的平均回归水平与Gompertz-Makeham定律成正比时对其进行了发展。我们开发了一种计量经济学估计方法，并对比利时人口的模型进行了验证。

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A calendar year mortality model in continuous time

Abstract This article proposes a continuous time mortality model based on calendar years. Mortality rates belong to a mean-reverting random field indexed by time and age. In order to explain the improvement of life expectancies, the reversion level of mortality rates is the product of a deterministic function of age and of a decreasing jump-diffusion process driving the evolution of longevity. We provide a general closed-form expression for survival probabilities and develop it when the mean reversion level of mortality rates is proportional to a Gompertz–Makeham law. We develop an econometric estimation method and validate the model on the Belgian population.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.