Search Results

Showing results 1 to 7 of approximately 7.

(refine search)
SORT BY: PREVIOUS / NEXT
Author:Buzard, Kristy 

Working Paper
The Agglomeration of American Research and Development Labs
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 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, one mile, five 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).
AUTHORS: Carlino, Gerald A.; Carr, Jake; Smith, Tony E.; Hunt, Robert M.; Buzard, Kristy
DATE: 2017-07-18

Working Paper
Localized Knowledge Spillovers: Evidence from the Spatial Clustering of R&D Labs and Patent Citations
Patent citations are a commonly used indicator of knowledge spillovers among inventors, while clusters of research and development labs are locations in which knowledge spillovers are particularly likely to occur. In this paper, we assign patents and citations to newly defined clusters of American R&D labs to capture the geographic extent of knowledge spillovers. Our tests show that the localization of knowledge spillovers, as measured via patent citations, is strongest at small spatial scales and diminishes rapidly with distance. On average, patents within a cluster are about three to six times more likely to cite an inventor in the same cluster than one in a control group. At the same time, the strength of knowledge spillovers varies widely between clusters. The results are robust to the specification of patent technological categories, the method of citation matching and alternate cluster definitions.
AUTHORS: Smith, Tony E.; Carlino, Gerald A.; Carr, Jake; Hunt, Robert M.; Buzard, Kristy
DATE: 2017-10-03

Working Paper
The geography of research and development activity in the U.S.
This study details the location patterns of R&D labs in the U.S., but it differs from past studies in a number of ways. 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.
AUTHORS: Carlino, Gerald A.; Buzard, Kristy
DATE: 2009

Working Paper
Localized Knowledge Spillovers: Evidence from the Agglomeration of American R&D Labs and Patent Data
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, Trajtenberg, and Henderson (1993, hereafter JTH) provide an aggregate measure of the importance of knowledge spillovers at either the state or metropolitan area level. However, much information is lost regarding differences in the localization of knowledge spillovers in specific geographic areas. In this article, we show that such differences can be quite substantial. Instead of using fixed spatial boundaries, we develop a new procedure ? the multiscale core-cluster approach ? for identifying the location and size of specific R&D clusters. This approach allows us to better capture the geographic extent of knowledge spillovers. We examine the evidence for knowledge spillovers within R&D clusters in two regions: the Northeast Corridor and California. In the former, we find that citations are from three to six times more likely to come from the same cluster as earlier patents than in comparable control samples. Our results are even stronger for labs located in California: Citations are roughly 10 to 12 times more likely to come from the same cluster. Our tests reveal evidence of the attenuation of localization effects as distance increases: The localization of knowledge spillovers is strongest at small spatial scales (5 miles or less) and diminishes rapidly with distance. At the smallest spatial scales, our localization statistics are generally much larger than JTH report for the metropolitan areas included in their tests.
AUTHORS: Hunt, Robert M.; Carr, Jake; Carlino, Gerald A.; Buzard, Kristy; Smith, Tony E.
DATE: 2015-01-01

Working Paper
LOCALIZED KNOWLEDGE SPILLOVERS: EVIDENCE FROM THE AGGLOMERATION OF AMERICAN R&D LABS AND PATENT DATA
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 clusters at various scales, such as a half mile, 1 mile, 5 miles, and more. Assigning patents and citations to these clusters, we capture the geographic extent of knowledge spillovers within them. Our tests show that the localization of knowledge spillovers, as measured via patent citations, is strongest at small spatial scales and diminishes rapidly with distance.
AUTHORS: Smith, Tony E.; Hunt, Robert M.; Buzard, Kristy; Carr, Jake; Carlino, Gerald A.
DATE: 2016-10-13

Journal Article
The geography of research and development activity in the U.S.
In the U.S., metropolitan areas contain the largest concentrations of people and jobs. Despite some drawbacks, these so-called agglomeration economies also have benefits, such as the cost savings that result from being close to suppliers and workers. Spatial concentration is even more pronounced among establishments that do basic research and development (R&D). In "The Geography of Research and Development Activity in the U.S.," Kristy Buzard and Jerry Carlino show that geographic concentration of R&D extends beyond locations such as Silicon Valley. In fact, many types of R&D establishments are highly concentrated geographically.
AUTHORS: Buzard, Kristy; Carlino, Gerald A.
DATE: 2008-07

Working Paper
Localized Knowledge Spillovers: Evidence from the Spatial Clustering of R&D Labs and Patent Citations
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 political or administrative boundaries that have predominantly been used in previous studies. In this paper, we assign patents and citations to these newly defined clusters of R&D labs. Our tests show that the localization of knowledge spillovers, as measured via patent citations, is strongest at small spatial scales and diminishes with distance. On average, patents within a cluster are about two to four times more likely to cite an inventor in the same cluster than one in a control group. Of import, we find that the degree of localization of knowledge spillovers will be understated in samples based on metropolitan area definitions compared to samples based on the R&D clusters. At the same time, the strength of knowledge spillovers varies widely between clusters. The results are robust to the specification of patent technological categories, the method of citation matching, and alternate cluster definitions.
AUTHORS: Carr, Jake; Hunt, Robert M.; Carlino, Gerald A.; Smith, Tony E.; Buzard, Kristy
DATE: 2017-09-01

FILTER BY year

FILTER BY Series

FILTER BY Content Type

FILTER BY Author

FILTER BY Jel Classification

O31 5 items

R12 5 items

PREVIOUS / NEXT