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AN 'ALGORITHMIC LINKS WITH PROBABILITIES' CONCORDANCE FOR TRADEMARKS: FOR DISAGGREGATED ANALYSIS OF TRADEMARK & ECONOMIC DATA
September 2013
Working Paper Number:
CES-13-49
Trademarks (TMs) shape the competitive landscape of markets for goods and services in all countries through branding and conveying information and quality inherent in products. Yet, researchers are largely unable to conduct rigorous empirical analysis of TMs in the modern economy because TM data and economic activity data are organized differently and cannot be analyzed jointly at the industry or sectoral level. We propose an 'Algorithmic Links with Probabilities' (ALP) approach to match TM data to economic data and enable these data to speak to each other. Specifically, we construct a NICE Class Level concordance that maps TM data into trade and industry categories forward and backward. This concordance allows researchers to analyze differences in TM usage across both economic and TM sectors. In this paper, we apply this ALP concordance for TMs to characterize patterns in TM applications across countries, industries, income levels and more. We also use the concordance to investigate some of the key determinants of international technology transfer by comparing bilateral TM applications and bilateral patent applications. We conclude with a discussion of possible extensions of this work, including deeper indicator-level concordances and further analyses that are possible once TM data are linked with economic activity data.
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The Location of Industrial Innovation: Does Manufacturing Matter?
March 2013
Working Paper Number:
CES-13-09
What explains the location of industrial innovation? Economists have traditionally attempted to answer this question by studying firm-external knowledge spillovers. This paper shows that firm-internal linkages between production and R&D play an equally important role. I estimate an R&D location choice model that predicts patents by a firm in a location from R&D productivity and costs. Focusing on large R&D-performing firms in the chemical industry, an average-sized plant raises the firm's R&D productivity in the metropolitan area by about 2.5 times. The elasticity of R&D productivity with respect to the firm's production workers is almost as large as the elasticity with respect to total patents in the MSA, while proximity to academic R&D has no significant effect on R&D productivity in this sample. Other manufacturing industries exhibit similar results. My results cast doubt on the frequently-held view that a country can divest itself of manufacturing and specialize in innovation alone.
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Getting Patents and Economic Data to Speak to Each Other: An 'Algorithmic Links with Probabilities' Approach for Joint Analyses of Patenting and Economic Activity
September 2012
Working Paper Number:
CES-12-16
International technological diffusion is a key determinant of cross-country differences in economic performance. While patents can be a useful proxy for innovation and technological change and diffusion, fully exploiting patent data for such economic analyses requires patents to be tied to measures of economic activity. In this paper, we describe and explore a new algorithmic approach to constructing concordances between the International Patent Classification (IPC) system that organizes patents by technical features and industry classification systems that organize economic data, such as the Standard International Trade Classification (SITC), the International Standard Industrial Classification (ISIC) and the Harmonized System (HS). This 'Algorithmic Links with Probabilities' (ALP) approach incorporates text analysis software and keyword extraction programs and applies them to a comprehensive patent dataset. We compare the results of several ALP concordances to existing technology concordances. Based on these comparisons, we select a preferred ALP approach and discuss advantages of this approach relative to conventional approaches. We conclude with a discussion on some of the possible applications of the concordance and provide a sample analysis that uses our preferred ALP concordance to analyze international patent flows based on trade patterns.
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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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