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Extremes are not normal: a reminder to demographers

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  • Anthony Medford

    (University of Southern Denmark)

  • James W. Vaupel

    (University of Southern Denmark)

Abstract

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.

Suggested Citation

  • Anthony Medford & James W. Vaupel, 2020. "Extremes are not normal: a reminder to demographers," Journal of Population Research, Springer, vol. 37(1), pages 91-106, March.
    • Handle: RePEc:spr:joprea:v:37:y:2020:i:1:d:10.1007_s12546-019-09231-y
    DOI: 10.1007/s12546-019-09231-y
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    References listed on IDEAS

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    5. Gbari, Kock Yed Ake Samuel & Poulain, Michel & Dal, Luc & Denuit, Michel, 2017. "Extreme Value Analysis of Mortality at the Oldest Ages: A Case Study Based on Individual Ages at Death," LIDAM Reprints ISBA 2017028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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    Cited by:

    1. Anthony Medford, 2021. "Modeling Best Practice Life Expectancy Using Gumbel Autoregressive Models," Risks, MDPI, vol. 9(3), pages 1-10, March.

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