First, rather than looking at the geographic concentration of manufacturing firms (e.g., Ellison and Glaeser, 1997; Rosenthal and Strange, 2001; and Duranton and Overman, 2005), the authors consider the spatial concentration of private R&D activity. Second, rather than focusing on the concentration of employment in a given industry, the authors look at the clustering of individual R&D labs by industry. Third, following Duranton and Overman (2005), the authors look for geographic clusters of labs that represent statistically significant departures from spatial randomness using simulation techniques. The authors find that R&D activity for most industries tends to be concentrated in the Northeast corridor, around the Great Lakes, in California's Bay Area, and in southern California. They argue that the high spatial concentration of R&D activity facilitates the exchange of ideas among firms and aids in the creation of new goods and new ways of producing existing goods. They run a regression of an Ellison and Glaeser (1997) style index measuring the spatial concentration of R&D labs on geographic proxies for knowledge spillovers and other characteristics and find evidence that localized knowledge spillovers are important for innovative activity.

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