Location, Location, Location
October 2021
Working Paper Number:
CES-21-32R
Abstract
We use data from the Longitudinal Employer-Household Dynamics program to study the causal effects of location on earnings. Starting from a model with employer and employee fixed effects, we estimate the average earnings premiums associated with jobs in different commuting zones (CZs) and different CZ-industry pairs. About half of the variation in mean wages across CZs is attributable to differences in worker ability (as measured by their fixed effects); the other half is attributable to place effects. We show that the place effects from a richly specified cross sectional wage model overstate the causal effects of place (due to unobserved worker ability), while those from a model that simply adds person fixed effects understate the causal effects (due to unobserved heterogeneity in the premiums paid by different firms in the same CZ). Local industry agglomerations are associated with higher wages, but overall differences in industry composition and in CZ-specific returns to industries explain only a small fraction of average place effects. Estimating separate place effects for college and non-college workers, we find that the college wage gap is bigger in larger and higher-wage places, but that two-thirds of this variation is attributable to differences in the relative skills of the two groups in different places. Most of the remaining variation reflects the enhanced sorting of more educated workers to higher-paying industries in larger and higher-wage CZs. Finally, we find that local housing costs at least fully offset local pay premiums, implying that workers who move to larger CZs have no higher net-of-housing consumption.
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:
industrial,
earnings,
employee,
employ,
employed,
labor,
establishment,
heterogeneity,
metropolitan,
unobserved,
workplace,
workforce,
wage effects,
industry wages,
wage gap,
occupation,
wage differences,
wage industries,
housing,
regress,
rent
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identified to contain references to specific institutions, datasets, and other organizations.
:
Ordinary Least Squares,
National Longitudinal Survey of Youth,
Urban Institute,
North American Industry Classification System,
American Community Survey,
Longitudinal Employer Household Dynamics,
AKM,
UC Berkeley,
Census Bureau Disclosure Review Board,
Federal Reserve Board of Governors
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