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Pay, productivity and aging in Major League Baseball

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  • Turner, Chad
  • Hakes, Jahn

Abstract

Using panels of player pay and performance from Major League Baseball (MLB), we examine trends in player productivity and salaries as players age. Pooling players of all ability levels leads to a systematic bias in regression coefficients. After addressing this problem by dividing players into talent quintiles, we find that the best players peak about two years later than marginal players, and development and depreciation of ability appear to be more pronounced for players with the highest peak ability levels. Within-career variation, however, is less pronounced than between-player variation, and the talent level of players within a given quintile will typically remain lower than the talent level for rookies in the next higher quintile. Free agents are paid proportionately with their production at all ability levels, whereas young players’ salaries are suppressed by similar amounts.

Suggested Citation

  • Turner, Chad & Hakes, Jahn, 2007. "Pay, productivity and aging in Major League Baseball," MPRA Paper 4326, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:4326
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    10. Jahn K. Hakes & Raymond D. Sauer, 2006. "An Economic Evaluation of the Moneyball Hypothesis," Journal of Economic Perspectives, American Economic Association, vol. 20(3), pages 173-186, Summer.
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    Cited by:

    1. Chih-Hai Yang & Hsuan-Yu Lin & Chiang-Ping Chen, 2014. "Measuring the efficiency of NBA teams: additive efficiency decomposition in two-stage DEA," Annals of Operations Research, Springer, vol. 217(1), pages 565-589, June.
    2. 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.
    3. 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.
    4. Wiseman Frederick & Chatterjee Sangit, 2010. "Negotiating Salaries through Quantile Regression," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(1), pages 1-15, January.
    5. Martina Gianecchini & Alberto Alvisi, 2015. "Late career of superstar soccer players: win, play, or gain?," "Marco Fanno" Working Papers 0192, Dipartimento di Scienze Economiche "Marco Fanno".
    6. Nikolaos, Chatzistamoulou & Theodoros, Antonakis & Konstantinos, Kounetas, 2020. "Salary cap and National Basketball Association teams' productive performance. A two stage Data Envelopment Analysis approach under a metatechnology framework," MPRA Paper 98811, University Library of Munich, Germany.
    7. Nikos Chatzistamoulou & Kounetas Kostas & Antonakis Theodor, 2022. "Salary Cap, Organizational Gap, and Catch-up in the Performance of NBA Teams: A Two-Stage DEA Model Under Heterogeneity," Journal of Sports Economics, , vol. 23(2), pages 123-155, February.
    8. Michael R. Ward & Alexander D. Harmon, 2019. "ESport Superstars," Journal of Sports Economics, , vol. 20(8), pages 987-1013, December.
    9. R Simmons & D Berri, 2007. "Does it pay to specialize? The story from the Gridiron," Working Papers 591134, Lancaster University Management School, Economics Department.
    10. Brian M. Mills, 2017. "Policy Changes In Major League Baseball: Improved Agent Behavior And Ancillary Productivity Outcomes," Economic Inquiry, Western Economic Association International, vol. 55(2), pages 1104-1118, April.
    11. Turner, Chad & Hakes, Jahn Karl, 2007. "The Collective Bargaining Effects of NBA Player Productivity Dynamics," MPRA Paper 5058, University Library of Munich, Germany.
    12. Jahn K. Hakes & Chad Turner, 2008. "Long-Term Contracts in Major League Baseball," Working Papers 0831, International Association of Sports Economists;North American Association of Sports Economists.

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    Keywords

    Major League Baseball (MLB); career dynamics; player salaries and performance; quintile analysis;
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    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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