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...

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...

Superceded by 16-25.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,...

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...

We study the location of more than 1,000 research and development (R&D) labs located in the Northeast corridor of the U.S. Using a variety of spatial econometric techniques, we find that these labs are substantially more concentrated in space than the underlying distribution of manufacturing...

The authors study the location and productivity of more than 1,000 research and development (R&D) labs located in the Northeast corridor of the U.S. Using a variety of spatial econometric techniques, they find that these labs are substantially more concentrated in space than the underlying...