The Impact of Race, Performance Statistics, and Local Market Variables on NBA Player Salary: 2012-13 (2014)

Undergraduate: Vijay Gadani

Faculty Advisor: Jonathan Hill
Department: Economics

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Although racial differences among NBA player salary have been studied extensively prior to 2000, the NBA has become more diverse in the last 15 years with an influx of international players. Many advanced performance statistics have also been introduced in the last decade. Therefore, exploring the influence that these new factors have on player salary will be useful to understand the important determinants of player salary. This study aims to extend existing literature by using player performance data from the 2012-13 season. The factors that influence salary are investigated by building upon existing econometric models with additional explanatory variables. In my research, the economic model being used to estimate salary is a function of a vector of explanatory variables. These include an indicator for race, performance statistics, and local market variables such as per capita income and population in metropolitan statistical areas. The dataset consisted of 468 observations, which encompassed all players in the NBA during the 2012-13 season. A Tobit regression was performed to estimate the salary model because the dependent variable is non-negative and truncated at the NBA¿s minimum player salary. As such, 62 observations were left censored. The results indicated that significantly positive influences on salary include race, age, position, and minutes played. Significantly negative influences on salary are personal fouls and population in a metropolitan statistical area.