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Negotiating Salaries through Quantile Regression

Author

Listed:
  • Wiseman Frederick

    (Northeastern University)

  • Chatterjee Sangit

    (Northeastern University)

Abstract

Estimating the salaries of professional athletes has received a substantial amount of attention both in the press and in academic journals. A statistical technique that can be used to obtain an estimate of a player's salary with a given set of performance characteristics is the classical least squares regression analysis. This technique does not work well, however, if the data upon which the model is based contain outliers or are not normally distributed. In this paper we focus our attention on the salaries of American League baseball players in 2007 and demonstrate the usefulness of an alternative estimation approach - that of quantile regression analysis. Our results indicate that ordinary least squares regression overestimates the salaries of poor players, and underestimates the salaries of star players. This, we believe, is a compelling reason to apply quantile regression in the prediction of baseball player salaries.

Suggested Citation

  • 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.
    • Handle: RePEc:bpj:jqsprt:v:6:y:2010:i:1:n:7
    DOI: 10.2202/1559-0410.1177
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    References listed on IDEAS

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    1. Anthony C. Krautmann & Margaret Oppenheimer, 2002. "Contract Length and the Return to Performance in Major League Baseball," Journal of Sports Economics, , vol. 3(1), pages 6-17, February.
    2. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    3. 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.
    4. 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.
    5. Herbert F. Lewis & Thomas R. Sexton & Kathleen A. Lock, 2007. "Player Salaries, Organizational Efficiency, and Competitiveness in Major League Baseball," Journal of Sports Economics, , vol. 8(3), pages 266-294, June.
    6. Karl W. Einolf, 2004. "Is Winning Everything?," Journal of Sports Economics, , vol. 5(2), pages 127-151, May.
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