Abstract
We use a spatial hierarchical regression model to isolate the effects of spatial contagion and urban hierarchy on population levels and apply this model to a unique dataset of American urban areas from 1990 to 2010 that includes all but the smallest rural communities. By disentangling the effects of urban hierarchy and spatial contagion on population levels, we find that large cities are characterized by urban agglomeration and spatial complementarity, while small cities are characterized by a greater degree of spatial complementarity and position in the urban hierarchy.
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