Get access

Testing the Determinants of Income Distribution in Major League Baseball

Authors

  • R. Todd Jewell,

    1. Jewell: Associate Professor, Department of Economics, University of North Texas, Denton, TX 76203. Phone 1–940–565–3337, Fax 1–940–565–4426, E-mail tjewell@unt.edu
    Search for more papers by this author
  • Michael A. McPherson,

    1. McPherson: Associate Professor, Department of Economics, University of North Texas, Denton, TX 76203. Phone 1–940–565–2270, Fax 1–940–565–4426, E-mail mcpherson@unt.edu
    Search for more papers by this author
  • David J. Molina

    1. Molina: Associate Professor, Department of Economics, University of North Texas, Denton, TX 76203. Phone 1–940–565–4543, Fax 1–940–565–4426, E-mail dmolina@unt.edu
    Search for more papers by this author
    • *

      We wish to thank Rod Fort for assistance in finding and cleaning the salary data. We also thank David Berri, Rod Fort, Brad Humphreys, Daniel Slottje, Steve Walters, and two anonymous referees for helpful comments and suggestions. The usual caveats hold.


Abstract

Using data from U.S. Major League Baseball, this article compares parametric and nonparametric Gini coefficients for each team and year. We employ a panel-data model to investigate the time-series and cross-sectional factors affecting the Gini coefficients and the parameters of the preselected distribution. We find that much of within-team income distribution is determined by time-related variables, with the 1994 MLB strike having an especially strong effect. A team's market potential does not seem to affect its salary distribution, but the average age of the players on a team's roster does. Furthermore, inequality first increases with team payroll, then decreases before increasing again.

Ancillary