PRODUCTIVITY AND THE DENSITY OF HUMAN CAPITAL*
The authors would like to thank the editor, Marlon Boarnet, and three anonymous referees for insightful comments that helped improve the paper. Jeff Lin, Clément Bosquet, and participants at the 2009 Federal Reserve System Applied Microeconomics Annual Research Conference, 49th Annual Meetings of the Southern Regional Science Association, and Barcelona Institute of Economics (IEB) I Workshop on Urban Economics also offered several useful suggestions. Jonathan Hastings provided excellent research assistance. Gabe's participation in this research was supported, in part, by the Maine Agricultural and Forest Experiment Station, MAFES External Publication 3231. The views and opinions expressed here are solely those of the authors and do not necessarily reflect those of the Federal Reserve Bank of New York, the Federal Reserve System, the University of Georgia, or the University of Maine.
Abstract
ABSTRACT We estimate a model of urban productivity in which the agglomeration effect of density is enhanced by a metropolitan area's stock of human capital. Estimation accounts for potential biases due to the endogeneity of density and industrial composition effects. Using new information on output per worker for U.S. metropolitan areas along with a measure of density that accounts for the spatial distribution of population, we find that a doubling of density increases productivity by 2–4 percent. Consistent with theories of learning and knowledge spillovers in cities, we demonstrate that the elasticity of average labor productivity with respect to density increases with human capital. Metropolitan areas with a human capital stock one standard deviation below the mean realize no productivity gain, while doubling density in metropolitan areas with a human capital stock one standard deviation above the mean yields productivity benefits that are about twice the average. These patterns are particularly pronounced in industries where the exchange of information and sharing of ideas are important parts of the production process.
