In North America, professional sports leagues operate mostly as cartels. They employ certain policies such as revenue sharing,
salary caps to ensure that teams get high revenues and players get high wages. There are two major hypotheses regarding the talent
distribution among the teams that would maximize the total revenues, dominant teams rule and equal strength team rule. This paper
examines the revenue structure of National Football League and proposes policy recommendations regarding talent distribution among the teams.
By using a unique, rich data set on game day stadium attendance and TV ratings I am able to measure the total demand as a function of involved
teams' talent levels. Reduced form regression results indicates that TV viewers are more interested in close games, on the other hand stadium
attendees are more interested in home teams' dominance. In order to identify the true effects of possible policy experiments, I estimate the
parameters of the demand for TV as functions of team talent, fixed team and market variables by using partial linear model described as
in Yatchew (1998) which uses non-parametric regression and difference-based estimators. I then estimate the demand for stadium attendance
using random coefficients model by using normative priors for the 32 cities that hosts the teams. Estimated demand for TV ratings and
stadium attendance corroborates the findings of reduced form regressions, stadium demand and TV demand working against each other. We therefore
propose a
somewhat equal strength team policy where big market teams has a slight advantage over the others. Total revenues of the
leagues is maximized under such a policy.
