IDEAS home Printed from https://ideas.repec.org/p/cwl/cwldpp/2100.html
   My bibliography  Save this paper

Estimating Aging Effects in Running Events

Author

Listed:

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 non-parametric model. Two estimation methods are used: 1) minimizing the squared difference between the observed records and the modeled biological frontier and 2) 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 there is linear percentage decline up to the late 70's and quadratic decline after that. The extreme value estimates suggest that the true biological frontier is on average about 8 percent below the existing world records. The estimated age factors are also compared to the World Master Athletics (WMA) age factors. The two sets of age factors are close except at the old ages, where the WMA factors are noticeably smaller. Also, the WMA age factors do not meet an important biological constraint.

Suggested Citation

  • Ray C. Fair & Edward H. Kaplan, 2017. "Estimating Aging Effects in Running Events," Cowles Foundation Discussion Papers 2100, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:2100
    as

    Download full text from publisher

    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d21/d2100.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fair, Ray C, 1994. "How Fast Do Old Men Slow Down?," The Review of Economics and Statistics, MIT Press, vol. 76(1), pages 103-118, February.
    2. Ray Fair, 2004. "Estimated Age Effects in Athletic Events and Chess," Yale School of Management Working Papers amz2481, Yale School of Management, revised 01 Aug 2007.
    3. Einmahl, John H. J. & Magnus, Jan R., 2008. "Records in Athletics Through Extreme-Value Theory," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1382-1391.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ray C. Fair & Edward H. Kaplan, 2017. "Estimating Aging Effects in Running Events," Cowles Foundation Discussion Papers 3000, Cowles Foundation for Research in Economics, Yale University.
    2. Börsch-Supan, Axel & Weiss, Matthias, 2016. "Productivity and age: Evidence from work teams at the assembly line," The Journal of the Economics of Ageing, Elsevier, vol. 7(C), pages 30-42.
    3. Chen, Yu-Fu & Zoega, Gylfi, 2010. "Life-Cycle, Effort and Academic Deadwood," SIRE Discussion Papers 2010-28, Scottish Institute for Research in Economics (SIRE).
    4. Fair Ray C, 2008. "Estimated Age Effects in Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 4(1), pages 1-41, January.
    5. Maennig Wolfgang & Stobernack Michael, 2011. "Do men slow down faster than women?," Review of Economics, De Gruyter, vol. 62(3), pages 263-278, December.
    6. Yu-Fu Chen & Gylfi Zoega, 2012. "Slowing Down," Dundee Discussion Papers in Economics 266, Economic Studies, University of Dundee.
    7. Nieswiadomy Michael L. & Strazicich Mark C. & Clayton Stephen, 2012. "Was There a Structural Break in Barry Bonds's Bat?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(3), pages 1-19, October.
    8. Chen, Yu-Fu & Zoeg, Gylfi, 2011. "Life-Cycle, Effort and Academic Inactivity," SIRE Discussion Papers 2011-27, Scottish Institute for Research in Economics (SIRE).
    9. Lee, R., 2016. "Macroeconomics, Aging, and Growth," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 59-118, Elsevier.
    10. Wang, Bing Xing & Yu, Keming & Coolen, Frank P.A., 2015. "Interval estimation for proportional reversed hazard family based on lower record values," Statistics & Probability Letters, Elsevier, vol. 98(C), pages 115-122.
    11. David J. Berri & Christian Deutscher & Arturo Galletti, 2015. "Born in the USA: National Origin Effects on Time Allocation in US and Spanish Professional Basketball," National Institute Economic Review, National Institute of Economic and Social Research, vol. 232(1), pages 41-50, May.
    12. Benoit Dostie, 2011. "Wages, Productivity and Aging," De Economist, Springer, vol. 159(2), pages 139-158, June.
    13. Daniel S. Hamermesh & Lea‐Rachel Kosnik, 2024. "Why do older scholars slow down?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 488-499, January.
    14. Berna Demiralp & Christopher Colburn & James Koch, 2012. "The effects of age, experience and managers upon baseball performance," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(2), pages 481-498, April.
    15. Paul Hek & Daniel Vuuren, 2011. "Are older workers overpaid? A literature review," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 18(4), pages 436-460, August.
    16. Clifford B. Sowell & Wm. Stewart Mounts Jr., 2005. "Ability, Age, and Performance," Journal of Sports Economics, , vol. 6(1), pages 78-97, February.
    17. Ana Cardoso & Paulo Guimarães & José Varejão, 2011. "Are Older Workers Worthy of Their Pay? An Empirical Investigation of Age-Productivity and Age-Wage Nexuses," De Economist, Springer, vol. 159(2), pages 95-111, June.
    18. Yao, Rui & Sharpe, Deanna L. & Wang, Feifei, 2011. "Decomposing the age effect on risk tolerance," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(6), pages 879-887.
    19. Sumit Agarwal & John C. Driscoll & Xavier Gabaix & David I. Laibson, 2007. "The age of reason: financial decisions over the lifecycle," Working Paper Series WP-07-05, Federal Reserve Bank of Chicago.
    20. de Valk, Cees, 2016. "A large deviations approach to the statistics of extreme events," Other publications TiSEM 117b3ba0-0e40-4277-b25e-d, Tilburg University, School of Economics and Management.

    More about this item

    Keywords

    Aging effects; Running events;

    JEL classification:

    • H19 - Public Economics - - Structure and Scope of Government - - - Other
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • Z2 - Other Special Topics - - Sports Economics

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cwl:cwldpp:2100. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Brittany Ladd (email available below). General contact details of provider: https://edirc.repec.org/data/cowleus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.