In cross-sectional American census data, we document that isolated cities tend to have less wage inequality. To explain this correlation and other correlations between population and wages, we build an equilibrium empirical model that incorporates high and low-skill labor, costly trade, and both agglomeration and congestion forces. The model bridges the gap between the spatial inequality literature which abstracts from geography, and the economic geography literature which abstracts from inequality. We find that geographical location explains 9.2% of observed variation in wage inequality across American cities. In counterfactual experiments, we find that reductions in domestic trade costs benefit all American workers and decrease welfare inequality. We also examine the effects on inequality and welfare of both regional and national skill-biased technology shocks. We find that in larger cities wage inequality grows more than welfare inequality.

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This paper develops a spatial equilibrium model with skill heterogeneity and endogenous agglomeration to study distributional welfare consequences of spatial policies. I show empirically that the relationship between log worker productivity and log city population is nonlinear in city size and in worker's skill. The model predicts these nonlinearities through local idea exchange between workers. I structurally estimate the model to match US Census employment and wage data, and use the estimates for decomposition and counterfactual exercises. A policy, with zero aggregate welfare effect, that favors smaller cities at the expense of larger cities, would notably reduce welfare inequality.

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