, Volume 55, Issue 6, pp 2025–2044 | Cite as

Separating the Signal From the Noise: Evidence for Deceleration in Old-Age Death Rates

  • Dennis M. FeehanEmail author


Widespread population aging has made it critical to understand death rates at old ages. However, studying mortality at old ages is challenging because the data are sparse: numbers of survivors and deaths get smaller and smaller with age. I show how to address this challenge by using principled model selection techniques to empirically evaluate theoretical mortality models. I test nine models of old-age death rates by fitting them to 360 high-quality data sets on cohort mortality after age 80. Models that allow for the possibility of decelerating death rates tend to fit better than models that assume exponentially increasing death rates. No single model is capable of universally explaining observed old-age mortality patterns, but the log-quadratic model most consistently predicts well. Patterns of model fit differ by country and sex. I discuss possible mechanisms, including sample size, period effects, and regional or cultural factors that may be important keys to understanding patterns of old-age mortality. I introduce mortfit, a freely available R package that enables researchers to extend the analysis to other models, age ranges, and data sources.


Mortality Aging Longevity Statistics Model selection 



The author thanks Vladimir Canudas-Romo, Scott Lynch, Matthew J. Salganik, and three anonymous reviews for helpful comments on early drafts of the manuscript.

Supplementary material

13524_2018_728_MOESM1_ESM.pdf (395 kb)
ESM 1 (PDF 394 kb)


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Copyright information

© Population Association of America 2018

Authors and Affiliations

  1. 1.Department of DemographyUniversity of CaliforniaBerkeleyUSA

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