To test and replicate the superstar effect reported by Brown, we empirically study contests where a single entrant has an exogenously higher probability of winning. Unlike the previous literature, we test for the presence of the superstar effect in several new contexts. Ultimately, we collect and explore data from four sources: men’s and women’s professional golf, and men’s and women’s professional alpine skiing. Empirically, we find little robust evidence of the superstar effect in any of our data sets. In our replication exercise, we approximate the findings of Brown; however, we cannot reject the null that the presence of a superstar has no impact on high ranked competitors. In our new settings, we cannot reject the null that superstars have no influence on the performances of highly ranked competitors.
We provide a command, locmtest, that implements a test for exogeneity that is robust when the true relationship between the outcome variable and a discrete potentially endogenous variable is nonlinear. This test was developed in Lochner and Moretti (2015, Review of Economics and Statistics 97: 387-397), and it can be implemented even when only a single valid instrument is available. We present the motivation and general idea of the test. We also describe locmtest, which calculates the test, and provide empirical applications of the test and the command.
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