Working Paper: NBER ID: w21363
Authors: Xavier Gabaix; Jean-Michel Lasry; Pierre-Louis Lions; Benjamin Moll
Abstract: The past forty years have seen a rapid rise in top income inequality in the United States. While there is a large number of existing theories of the Pareto tails of the income and wealth distributions at a given point in time, almost none of these address the fast rise in top inequality observed in the data. We show that standard theories, which build on a random growth mechanism, generate transition dynamics that are an order of magnitude too slow relative to those observed in the data. We then suggest parsimonious deviations from the basic model that can explain such changes, namely heterogeneity in mean growth rates or deviations from Gibrat's law. These deviations are consistent with theories in which the increase in top income inequality is driven by the rise of "superstar" entrepreneurs or managers.
Keywords: Inequality; Income Distribution; Wealth Distribution; Random Growth Models
JEL Codes: D31; E24
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| economic shocks (F69) | speed of convergence to a new steady state in income inequality (F62) |
| speed of convergence to a new steady state in income inequality (F62) | higher top income inequality (D31) |
| heterogeneity in mean growth rates (O41) | fast rise in income inequality (D31) |
| superstar entrepreneurs (M13) | heterogeneity in mean growth rates (O41) |
| deviations from Gibrat's law (F12) | infinitely fast transitions in income inequality (D31) |
| superstar shocks (Y60) | deviations from Gibrat's law (F12) |