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 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 league is maximized under such a policy.
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number
17920.
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