Professional athletes are a scalable occupation that potentially allows them to make money without an equivalent increase in labor and time because they become celebrity influencers. Earnings above medians of scalable occupations show considerable variation because the right tail of their distributions decays as a power law. This fact implies that professional athletes’ labor markets are of the winner-take-all type. We take data from Forbes magazine of the world’s top 100 highest-paid athletes from 2012 to 2020 and calculate Pareto exponents by ordinary least squares and maximum likelihood. We find we cannot dismiss their distribution of earnings following a power law. This result means we cannot explain the mega-earnings of the highest-paid athletes by merit in sports alone.
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