Demographers have always held great interest in extremal phenomena. Extreme value distributions are tailor made to model extremes but demographers do not often take advantage of them. We argue that demographers would benefit by using these models more often and present one potential usage: the Extreme Value Distribution as a candidate for modelling the error distribution in time series models. As an example, we use the so called best practice life expectancy. The residuals from the fitted models are tested for Normality. They are also fitted with Gaussian and Generalized Extreme Value distributions and the fit of these two distributions is compared. The results suggest that demographers ought to further explore and take greater advantage of extreme value models.

中文翻译：

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极端现象是不正常的：提醒人口统计学家

人口统计学家一直对极端现象非常感兴趣。极限值分配是为模拟极限值而量身定制的，但人口统计学家并不经常利用它们。我们认为，人口统计学家将通过更频繁地使用这些模型而受益，并提出一种潜在的用法：将极值分布作为对时间序列模型中的误差分布进行建模的候选对象。例如，我们使用所谓的最佳实践预期寿命。对拟合模型的残差进行正态性测试。他们还拟合了高斯分布和广义极值分布，并比较了这两个分布的拟合度。结果表明，人口统计学家应进一步探索并充分利用极值模型。