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Thompson says America must "unchoose" policies that have led to mass incarceration

Axinn says new data on campus rape will "allow students to see for themselves the full extent of this problem"

Frey says white population is growing in Detroit and other large cities


Susan Murphy to speak at U-M kickoff for data science initiative, Oct 6, Rackham

Andrew Goodman-Bacon, former trainee, wins 2015 Nevins Prize for best dissertation in economic history

Deirdre Bloome wins ASA award for work on racial inequality and intergenerational transmission

Bob Willis awarded 2015 Jacob Mincer Award for Lifetime Contributions to the Field of Labor Economics

Next Brown Bag

Monday, Oct 5 at noon, 6050 ISR
Colter Mitchell: Biological consequences of poverty

The Law of Genius and Home Runs Refuted

Archived Abstract of Former PSC Researcher

DiNardo, John, and Jason Winfree. 2010. "The Law of Genius and Home Runs Refuted." Economic Inquiry, 48(1): 51-64.

In a lively, provocative article, DeVany claims inter alia that the size distribution of home runs follows a continuous "power law" distribution which is nested in a larger class of "stable" statistical distributions characterized by an infinite variance. He uses this putative fact about the size distribution of home runs to argue that concern about the use of steroids to enhance home run ability is necessarily misplaced. In this article, we show that the initial claim is false and argue that the subsequent claim about the potential importance of steroid use does not follow from the first. We also show that the method used to establish that the size distribution of home runs is characterized by an infinite variance is unreliable and will find evidence "consistent" with infinite variance in all but the most trivial of data sets generated by processes with finite variance. Despite a large and growing literature that spans several fields and uses methods and arguments similar to DeVany's, we argue that mere inspection of the unconditional distribution of some human phenomenon is unlikely to yield much insight.

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