IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v4y2008i1n1.html
   My bibliography  Save this article

Estimated Age Effects in Baseball

Author

Listed:
  • Fair Ray C

    (Yale University)

Abstract

Age effects in baseball are estimated in this paper using a nonlinear fixed-effects regression. The sample consists of all players who have played 10 or more "full-time" years in the major leagues between 1921 and 2004. Quadratic improvement is assumed up to a peak-performance age, which is estimated, and then quadratic decline after that, where the two quadratics need not be the same. Each player has his own constant term. The results show that aging effects are larger for pitchers than for batters and larger for baseball than for track and field, running, and swimming events and for chess. There is some evidence that decline rates in baseball have decreased slightly in the more recent period, but they are still generally larger than those for the other events. There are 18 batters out of the sample of 441 whose performances in the second half of their careers noticeably exceed what the model predicts they should have been. All but 3 of these players played from 1990 on. The estimates from the fixed-effects regressions can also be used to rank players. This ranking differs from the ranking using lifetime averages because it adjusts for the different ages at which players played. It is in effect an age-adjusted ranking.

Suggested Citation

  • Fair Ray C, 2008. "Estimated Age Effects in Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 4(1), pages 1-41, January.
  • Handle: RePEc:bpj:jqsprt:v:4:y:2008:i:1:n:1
    DOI: 10.2202/1559-0410.1074
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1559-0410.1074
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.2202/1559-0410.1074?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    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 C. Fair, 2004. "Estimated Age Effects in Athletic Events and Chess," Cowles Foundation Discussion Papers 1495, Cowles Foundation for Research in Economics, Yale University, revised Feb 2006.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Null Brad, 2009. "Modeling Baseball Player Ability with a Nested Dirichlet Distribution," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(2), pages 1-38, May.
    2. Araki, Kenji & Hirose, Yoshihiro & Komaki, Fumiyasu, 2019. "Paired comparison models with age effects modeled as piecewise quadratic splines," International Journal of Forecasting, Elsevier, vol. 35(2), pages 733-740.
    3. Anthony C. Krautmann & John L. Solow, 2009. "The Dynamics of Performance Over the Duration of Major League Baseball Long-Term Contracts," Journal of Sports Economics, , vol. 10(1), pages 6-22, February.
    4. Jahn Hakes & Chad Turner, 2011. "Pay, productivity and aging in Major League Baseball," Journal of Productivity Analysis, Springer, vol. 35(1), pages 61-74, February.
    5. Tiruneh Gizachew, 2010. "Age and Winning Professional Golf Tournaments," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(1), pages 1-16, January.
    6. Geoffrey N Tuck & Athol R Whitten, 2013. "Lead Us Not into Tanktation: A Simulation Modelling Approach to Gain Insights into Incentives for Sporting Teams to Tank," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-10, November.
    7. John L. Solow & Anthony C. Krautmann, 2020. "Do You Get What You Pay for? Salary and Ex Ante Player Value in Major League Baseball," Journal of Sports Economics, , vol. 21(7), pages 705-722, October.
    8. Brander James A. & Yeung Louisa & Egan Edward J., 2014. "Estimating the effects of age on NHL player performance," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(2), pages 1-19, June.
    9. Andrew W. Nutting, 2013. "Immediate Effects of On-The-Job Training and Its Intensity," Journal of Sports Economics, , vol. 14(3), pages 303-320, June.
    10. Michael Schuckers & Michael Lopez & Brian Macdonald, 2023. "Estimation of player aging curves using regression and imputation," Annals of Operations Research, Springer, vol. 325(1), pages 681-699, June.
    11. 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.
    12. Gerber Eric A. E. & Craig Bruce A., 2021. "A mixed effects multinomial logistic-normal model for forecasting baseball performance," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(3), pages 221-239, September.
    13. McShane Blakeley B. & Braunstein Alexander & Piette James & Jensen Shane T., 2011. "A Hierarchical Bayesian Variable Selection Approach to Major League Baseball Hitting Metrics," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(4), pages 1-26, October.
    14. Hamrick Jeff & Rasp John, 2011. "Using Local Correlation to Explain Success in Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(4), pages 1-29, October.

    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. 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.
    2. 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.
    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. Castellucci, Fabrizio & Padula, Mario & Pica, Giovanni, 2011. "The age-productivity gradient: Evidence from a sample of F1 drivers," Labour Economics, Elsevier, vol. 18(4), pages 464-473, August.
    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. 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.
    8. 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.
    9. Chen, Yu-Fu & Zoeg, Gylfi, 2011. "Life-Cycle, Effort and Academic Inactivity," SIRE Discussion Papers 2011-27, Scottish Institute for Research in Economics (SIRE).
    10. Shih-Chieh Chang & Alessandra Adami & Hsin-Chin Lin & Yin-Chou Lin & Carl P C Chen & Tieh-Cheng Fu & Chih-Chin Hsu & Shu-Chun Huang, 2020. "Relationship between maximal incremental and high-intensity interval exercise performance in elite athletes," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-18, May.
    11. 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.
    12. 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.
    13. Benoit Dostie, 2011. "Wages, Productivity and Aging," De Economist, Springer, vol. 159(2), pages 139-158, June.
    14. 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.
    15. 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.
    16. 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.
    17. Clifford B. Sowell & Wm. Stewart Mounts Jr., 2005. "Ability, Age, and Performance," Journal of Sports Economics, , vol. 6(1), pages 78-97, February.
    18. 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.
    19. 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.
    20. 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.

    More about this item

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • J00 - Labor and Demographic Economics - - General - - - General

    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:bpj:jqsprt:v:4:y:2008:i:1:n:1. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.