How Local are Spatial Density Externalities? evidence from square grid data
AbstractWe analyze the geographic scale at which density externalities operate and their attenuation with distance. Using square grid data at a fine spatial resolution, we find that a doubling of neighborhood density, measured as the density of 1 km2 squares, yields an increase in the overall wage-level of a square in the order of 3 percent. The density of the wider region to which the neighborhood belongs shows a significantly smaller effect. Highly educated workers gain more from proximity to others, and when we decrease the sizes of the squares the effect is still stronger for such workers. Density effects operate simultaneously at different spatial levels, and we argue that the neighborhood effects are more prone to capture localized non-market effects, such as knowledge spillovers driven by face-to-face interaction.
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Bibliographic InfoPaper provided by Lund University, CIRCLE - Center for Innovation, Research and Competences in the Learning Economy in its series CIRCLE Electronic Working Papers with number 2012/10.
Length: 24 pages
Date of creation: 01 Dec 2012
Date of revision:
spatial scale; density; productivity; spatial dependence; geo-coded data; external scale economies; agglomeration externalities; Sweden; Modifiable Areal Unit Problem (MAUP);
Find related papers by JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
- R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
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- Larsson, Johan P., 2013. "The Neighborhood or the Region? Untangling the density-productivity relationship using geocoded data," Working Paper Series in Economics and Institutions of Innovation 318, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
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