Working Paper: NBER ID: w14299
Authors: Xavier Gabaix
Abstract: A power law is the form taken by a large number of surprising empirical regularities in economics and finance. This article surveys well-documented empirical power laws concerning income and wealth, the size of cities and firms, stock market returns, trading volume, international trade, and executive pay. It reviews detail-independent theoretical motivations that make sharp predictions concerning the existence and coefficients of power laws, without requiring delicate tuning of model parameters. These theoretical mechanisms include random growth, optimization, and the economics of superstars coupled with extreme value theory. Some of the empirical regularities currently lack an appropriate explanation. This article highlights these open areas for future research.
Keywords: scaling; fat tails; superstars; crashes
JEL Codes: E0; F1; G1; R0
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| proportional random growth (O40) | power law distribution (C46) |
| size of entities (e.g., cities, firms) (R12) | rank follows power law (C69) |
| Gibrat's law (R12) | steady-state distribution adheres to Zipf's law (D39) |
| stock market returns (G17) | power law distribution (C46) |
| extreme events (crashes) (G01) | part of statistical framework (C46) |