| Summary: | 碩士 === 世新大學 === 經濟學研究所(含碩專班) === 107 === As to this research, it takes all the competitions during two seasons from 2016 - 2017 and 2017 - 2018 of NBA as the sample periods, including 30 teams and 2,619 games. In this paper, it will take the method of ordinary least squares(OLS) to make research focusing on the star effects on the rate of attendance and the quantity of audience. The model of Tobit, it has research on the star effects on the rate of attendance by Tobit model analysis. Besides, it adds the new definition of stars, i.e., weekly best star effects, and the best efficiency stars in this paper. The results show, that the star effects can help to increase the quantity of audience, no matter in the form of host or guest. Taking the participation of an athlete with star effects in the All - Star game as an example, the increase of one more top 20 for the efficiency value player in one season, can help to improve 160 audiences and 1.109% attendance rate in the OLS regressions ceteris paribus. In the Tobit regressions, the increase of one more All - Star game player, can help to improve 1.111% attendance rate. Thus, the star effect has some positive externality on the quantity in the audience of NBA.
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