The Black Swan: The Impact of the Highly Improbable · chapter 7 · id the-black-swan-c7-02-wealth-book-sales-and-city-siz

“Wealth, book sales, and city sizes follow power laws (Pareto/Zipf distributions) in Extremistan, not Gaussian distributions. A single observation can dominate the total.”

contestedconfidence: high⚠ extracted by pipeline, re-audit pending

Receipts

Gabaix (2009), 'Power Laws in Economics and Finance', Annual Review of Economicssource alive

Power laws describe upper tails of wealth (Pareto exponent ~1.5-2.5), city sizes (Zipf exponent ~1), and firm sizes reasonably well.

Clauset, Shalizi & Newman (2009), SIAM ReviewDOI registry: valid

Only 7 of 24 tested datasets showed statistically significant power-law behavior. Many claimed power laws are better explained by log-normal or stretched exponential distributions.

Font-Clos et al. (2012), 'There is More than a Power Law in Zipf', Scientific Reportssource alive

Zipf's law is an approximation. Empirical rank-frequency distributions show systematic deviations from pure power laws.

This claim is a stable, citable object. If you can falsify a verdict, tell us — corrections are loud here.