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University Innovation, Local Economic Growth, and Entrepreneurship
June 2012
Working Paper Number:
CES-12-10
Universities, often situated at the center of innovative clusters, are believed to be important drivers of local economic growth. This paper identifies the extent to which U.S. universities stimulate nearby economic activity using the interaction of a national shock to the spread of innovation from universities - the Bayh-Dole Act of 1980 - with pre-determined variation both within a university in academic strengths and across universities in federal research funding. Using longitudinal establishment-level data from the Census, I find that longrun employment and payroll per worker around universities rise particularly rapidly after Bayh-Dole in industries more closely related to local university innovative strengths. The impact of
university innovation increases with geographic proximity to the university. Counties surrounding universities that received more pre-Bayh-Dole federal funding - particularly from the Department of Defense and the National Institutes of Health - experienced faster employment growth after the law. Entering establishments - in particular multi-unit firm expansions - over the period from 1977 to 1997 were especially important in generating long-run employment growth, while incumbents experienced modest declines, consistent with creative destruction. Suggestive of their complementarities with universities, large establishments contributed more substantially to the total 20-year growth effect than did small establishments.
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Agglomerative Forces and Cluster Shapes
June 2012
Working Paper Number:
CES-12-09
We model spatial clusters of similar firms. Our model highlights how agglomerative forces lead to localized, individual connections among firms, while interaction costs generate a defined distance over which attraction forces operate. Overlapping firm interactions yield agglomeration clusters that are much larger than the underlying agglomerative forces themselves. Empirically, we demonstrate that our model's assumptions are present in the structure of technology and labor flows within Silicon Valley and its surrounding areas. Our model further identifies how the lengths over which agglomerative forces operate influence the shapes and sizes of industrial clusters; we confirm these predictions using variations across both technology clusters and industry agglomeration.
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Growth Through Heterogeneous Innovations
June 2012
Working Paper Number:
CES-12-08
We study how exploration versus exploitation innovations impact economic growth through a tractable endogenous growth framework that contains multiple innovation sizes, multiproduct firms, and entry/exit. Firms invest in exploration R&D to acquire new product lines and exploitation R&D to improve their existing product lines. We model and show empirically that exploration R&D does not scale as strongly with firm size as exploitation R&D. The resulting framework conforms to many regularities regarding innovation and growth differences across the firm size distribution. We also incorporate patent citations into our theoretical framework. The framework generates a simple test using patent citations that indicates that entrants and small firms have relatively higher growth spillover effects.
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The Spatial Extent of Agglomeration Economies: Evidence from Three U.S. Manufacturing Industries
January 2012
Working Paper Number:
CES-12-01
The spatial extent of localized agglomeration economies constitutes one of the central current questions in regional science. It is crucial for understanding firm location decisions and for assessing the influence of proximity in shaping spatial patterns of economic activity, yet clear-cut answers are difficult to come by. Theoretical work often fails to define or specify the spatial dimension of agglomeration phenomena. Existing empirical evidence is far from consistent. Most sources of data on economic performance do not supply micro-level information containing usable geographic locations. This paper provides evidence of the distances across which distinct sources of agglomeration economies generate benefits for plants belonging to three manufacturing industries in the United States. Confidential data from the Longitudinal Research Database of the United States Census Bureau are used to estimate cross-sectional production function systems at the establishment level for three contrasting industries in three different years. Along with relevant establishment, industry, and regional characteristics, the production functions include variables that indicate the local availability of potential labor and supply pools and knowledge spillovers. Information on individual plant locations at the county scale permits spatial differentiation of the agglomeration variables within geographic regions. Multiple distance decay profiles are investigated in order to explore how modifying the operationalization of proximity affects indicated patterns of agglomeration externalities and interfirm interactions. The results imply that industry characteristics are at least as important as the type of externality mechanism in determining the spatial pattern of agglomeration benefits. The research methods borrow from earlier work by the author that examines the relationships between regional industrial structure and manufacturing production.
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NBER Patent Data-BR Bridge: User Guide and Technical Documentation
October 2010
Working Paper Number:
CES-10-36
This note provides details about the construction of the NBER Patent Data-BR concordance, and is intended for researchers planning to use this concordance. In addition to describing the matching process used to construct the concordance, this note provides a discussion of the benefits and limitations of this concordance.
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Clusters, Convergence, and Economic Performance
October 2010
Working Paper Number:
CES-10-34
This paper evaluates the role of regional cluster composition in the economic performance of industries, clusters and regions. On the one hand, diminishing returns to specialization in a location can result in a convergence effect: the growth rate of an industry within a region may be declining in the level of activity of that industry. At the same time, positive spillovers across complementary economic activities provide an impetus for agglomeration: the growth rate of an industry within a region may be increasing in the size and strength (i.e., relative presence) of related economic sectors. Building on Porter (1998, 2003), we develop a systematic empirical framework to identify the role of regional clusters ' groups of closely related and complementary industries operating within a particular region in regional economic performance. We exploit newly available data from the US Cluster Mapping Project to disentangle the impact of convergence at the region-industry level from agglomeration within clusters. We find that, after controlling for the impact of convergence at the narrowest unit of analysis, there is significant evidence for cluster-driven agglomeration. Industries participating in a strong cluster register higher employment growth as well as higher growth of wages, number of establishments, and patenting. Industry and cluster level growth also increases with the strength of related clusters in the region and with the strength of similar clusters in adjacent regions. Importantly, we find evidence that new industries emerge where there is a strong cluster environment. Our analysis also suggests that the presence of strong clusters in a region enhances growth opportunities in other industries and clusters. Overall, these findings highlight the important role of cluster-based agglomeration in regional economic performance.
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Local Industrial Conditions and Entrepreneurship: How Much of the Spatial Distribution Can We Explain?
October 2008
Working Paper Number:
CES-08-37
Why are some places more entrepreneurial than others? We use Census Bureau data to study local determinants of manufacturing startups across cities and industries. Demo- graphics have limited explanatory power. Overall levels of local customers and suppliers are only modestly important, but new entrants seem particularly drawn to areas with many smaller suppliers, as suggested by Chinitz (1961). Abundant workers in relevant occupations also strongly predict entry. These forces plus city and industry fixed effects explain between sixty and eighty percent of manufacturing entry. We use spatial distributions of natural cost advantages to address partially endogeneity concerns.
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Regional Industrial Dominance, Agglomeration Economies, and Manufacturing Plant Productivity
December 2007
Working Paper Number:
CES-07-31
In a seminal article, Benjamin Chinitz (1961) focused attention on the effects that industry size, structure, and economic diversification have on firm performance and regional economies. He also raised a related but conceptually distinct question that has been overlooked since: how does the extent to which a regional industry is concentrated in a single or small number of firms impact the performance of other local firms within that industry? He suggested that such regional industrial dominance may impact input prices, limit capital accessibility, deter entrepreneurial activity, and reduce the regional availability of agglomeration economies such as specialized labor and supply pools In this paper, we use an establishment-level production function to quantify the links between industrial dominance, agglomeration economies, and firm performance. We consider two questions. First, do greater levels of regional industrial dominance lead to lower economic performance by small, dominated manufacturing plants? Second, are small plants in dominated regional industries more limited in capturing regional agglomeration benefits and therefore do they face rigidities in deploying production factors to maximum advantage? Our results suggest that regional industrial organization does influence productivity but that the effect tends to be a direct one, rather than an indirect effect via its influence on agglomeration economies.
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What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns
April 2007
Working Paper Number:
CES-07-13
Many industries are geographically concentrated. Many mechanisms that could account for such agglomeration have been proposed. We note that these theories make different predictions about which pairs of industries should be coagglomerated. We discuss the measurement of coagglomeration and use data from the Census Bureau's Longitudinal Research Database from 1972 to 1997 to compute pairwise coagglomeration measurements for U.S. manufacturing industries. Industry attributes are used to construct measures of the relevance of each of Marshall's three theories of industry agglomeration to each industry pair: (1) agglomeration saves transport costs by proximity to input suppliers or final consumers, (2) agglomeration allows for labor market pooling, and (3) agglomeration facilitates intellectual spillovers. We assess the importance of the theories via regressions of coagglomeration indices on these measures. Data on characteristics of corresponding industries in the United Kingdom are used as instruments. We find evidence to support each mechanism. Our results suggest that input-output dependencies are the most important factor, followed by labor pooling.
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The Industry R&D Survey: Patent Database Link Project
November 2006
Working Paper Number:
CES-06-28
This paper details the construction of a firm-year panel dataset combining the NBER Patent Dataset with the Industry R&D Survey conducted by the Census Bureau and National Science Foundation. The developed platform offers an unprecedented view of the R&D-to-patenting innovation process and a close analysis of the strengths and limitations of the Industry R&D Survey. The files are linked through a name-matching algorithm customized for uniting the firm names to which patents are assigned with the firm names in Census Bureau's SSEL business registry. Through the Census Bureau's file structure, this R&D platform can be linked to the operating performances of each firm's establishments, further facilitating innovation-to-productivity studies.
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