Spatial Sorting: Why New York, Los Angeles, and Detroit Attract the Greatest Minds as Well as the Unskilled

Working Paper: CEPR ID: DP8151

Authors: Jan Eeckhout; Roberto Pinheiro; Kurt Schmidheiny

Abstract: We propose a theory of skill mobility across cities. It predicts the well documented city size--wage premium: the wage distribution in large cities first-order stochastically dominates that in small cities. Yet, because this premium is reflected in higher house prices, this does not necessarily imply that this stochastic dominance relation also exists in the distribution of skills. Instead, we find there is second-order stochastic dominance in the skill distribution. The demand for skills is non-monotonic as our model predicts a ``Sinatra'' as well as an ``Eminem'' effect: both the very high and the very low skilled disproportionately sort into the biggest cities, while those with medium skill levels sort into small cities. The pattern of spatial sorting is explained by a technology with a varying elasticity of substitution that is decreasing in skill density. Using CPS data on wages and Census data on house prices, we find that this technology is consistent with the observed patterns of skills.

Keywords: cities; general equilibrium; matching theory; population dynamics; sorting; wage distribution

JEL Codes: J31; R1; R23


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
City Size (R12)Wage Distribution (J31)
City Size (R12)Skill Distribution (D39)
Larger Cities (R12)City Size-Wage Premium (R12)
Larger Cities (R12)Fatter Tails in Skill Distribution (D39)
Sorting Mechanism (C69)Fat Tails in Skill Distribution (D39)
Skill Mobility (J62)Sorting Mechanism (C69)

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