Short- and Long-Term Dynamics of Cause-Specific Mortality Rates Using Cointegration Analysis

IF 1.4 Q3 BUSINESS, FINANCE
Séverine Arnold, V. Glushko
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引用次数: 7

Abstract

This article applies cointegration analysis and vector error correction models to model the short- and long-run relationships between cause-specific mortality rates. We work with the data from five developed countries (the United States, Japan, France, England and Wales, and Australia) and split the mortality rates into five main causes of death (infectious and parasitic, cancer, circulatory diseases, respiratory diseases, and external causes). We successively adopt short- and long-term perspectives, and analyze how each cause-specific mortality rate impacts and reacts to the shocks received from the rest of the causes. We observe that the cause-specific mortality rates are closely linked to each other, apart from the external causes that show an entirely independent behavior and hence could be considered as truly exogenous. We summarize our findings with the aim to help practitioners set more informed assumptions concerning the future development of mortality.
基于协整分析的病因特异性死亡率的短期和长期动态
本文应用协整分析和向量误差校正模型对特定原因死亡率之间的短期和长期关系进行建模。我们利用五个发达国家(美国、日本、法国、英格兰和威尔士以及澳大利亚)的数据,将死亡率分为五个主要死因(传染病和寄生虫病、癌症、循环系统疾病、呼吸道疾病和外部原因)。我们先后采用了短期和长期的观点,并分析了每种特定原因的死亡率如何影响和应对其他原因带来的冲击。我们观察到,除了表现出完全独立行为的外部原因外,特定原因死亡率彼此密切相关,因此可以被视为真正的外源性原因。我们总结了我们的发现,目的是帮助从业者对死亡率的未来发展做出更明智的假设。
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
2.80
自引率
14.30%
发文量
38
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