The agglomeration of American R&D labs
Kristy Buzard (),
Gerald Carlino (),
Robert Hunt (),
Jake K. Carr and
Tony E. Smith
Journal of Urban Economics, 2017, vol. 101, issue C, 14-26
We employ a unique data set to examine the spatial clustering of about 1700 private R&D labs in California and in the U.S. Northeast Corridor. Using these data, which contain the R&D labs’ complete addresses, we are able to more precisely locate innovative activity than with patent data, which only contain zip codes for inventors’ residential addresses. We avoid the problems of scale and borders associated with using fixed spatial boundaries, such as zip codes, by developing a new point-pattern procedure. Our multiscale core-cluster approach identifies the location and size of significant R&D clusters at various scales, such as a half mile, 1 mile, 5 miles, and more. Our analysis identifies four major clusters in the Northeast Corridor (one each in Boston, New York–Northern New Jersey, Philadelphia–Wilmington, and Washington, D.C.,) and three major clusters in California (one each in the Bay Area, Los Angeles, and San Diego).
Keywords: Spatial clustering; Geographic concentration; R&D labs; Innovation (search for similar items in EconPapers)
JEL-codes: O31 R12 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:juecon:v:101:y:2017:i:c:p:14-26
Access Statistics for this article
Journal of Urban Economics is currently edited by S.S. Rosenthal and W.C. Strange
More articles in Journal of Urban Economics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().