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We employ a unique data set to examine the spatial clustering of about 1,700 private research and development (R&D) labs in California and across the Northeast corridor of the United States. Using these data, which contain the R&D labs' complete addresses, we are able to more precisely locate...
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Supercedes 15-03 We employ a unique data set to examine the spatial clustering of private R&D labs. Instead of using fixed spatial boundaries, we develop a new procedure for identifying the location and size of specific R&D clusters. Thus, we are better able to identify the spatial locations of...
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Superceded by 16-25. This working paper supersedes WP 12-22, WP 11-42, and WP 10-33. We employ a unique data set to examine the spatial clustering of private R&D labs, and, using patent citations data, we provide evidence of localized knowledge spillovers within these clusters. Jaffe,...
Persistent link: https://www.econbiz.de/10012937041
We employ a unique data set to examine the spatial clustering of private R&D labs, and, using patent citations data, we provide evidence of localized knowledge spillovers within these clusters. Jaffe, Trajtenberg, and Henderson (1993, hereafter JTH) provide an aggregate measure of the importance...
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SUPERCEDES EORKING PAPER 17-32 Buzard et al. (2017) show that American R&D labs are highly spatially concentrated even within a given metropolitan area. We argue that the geography of their clusters is better suited for studying knowledge spillovers than are states, metropolitan areas, or other...
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