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Estimating Aging Effects in Running Events

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  • Ray C. Fair

    (Yale University)

  • Edward H. Kaplan

    (Yale University)

Abstract

This paper uses world running records by age to estimate a biological frontier of decline rates. Two models are compared: a linear/ quadratic (LQ) model and a nonparametric model. Two estimation methods are used: (a) minimizing the squared difference between the observed records and the modeled biological frontier and (b) using extreme value theory to estimate the biological frontier that maximizes the probability of observing the existing world records by age. The results support the LQ model and suggest a linear percentage decline up to the late 70s and quadratic decline after that.

Suggested Citation

  • Ray C. Fair & Edward H. Kaplan, 2018. "Estimating Aging Effects in Running Events," The Review of Economics and Statistics, MIT Press, vol. 100(4), pages 704-711, October.
    • Handle: RePEc:tpr:restat:v:100:y:2018:i:4:p:704-711
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    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/10.1162/rest_a_00725
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    Cited by:

    1. Rachel Scarfe & Carl Singleton & Adesola Sunmoni & Paul Telemo, 2024. "The age‐wage‐productivity puzzle: Evidence from the careers of top earners," Economic Inquiry, Western Economic Association International, vol. 62(2), pages 584-606, April.

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