Estimated Age Effects in Baseball
AbstractAge 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.
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Bibliographic InfoPaper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1536.
Length: 46 pages
Date of creation: Oct 2005
Date of revision: Mar 2007
Publication status: Published in Journal of Quantitative Analysis in Sports (2008), 4(1): Article 1
Note: CFP 1255.
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Other versions of this item:
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- J00 - Labor and Demographic Economics - - General - - - General
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Fair, Ray C, 1994.
"How Fast Do Old Men Slow Down?,"
The Review of Economics and Statistics,
MIT Press, vol. 76(1), pages 103-18, February.
- Turner, Chad & Hakes, Jahn, 2007.
"Pay, productivity and aging in Major League Baseball,"
4326, University Library of Munich, Germany.
- 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.
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