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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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INNOVATION, REALLOCATION AND GROWTH
April 2013
Working Paper Number:
CES-13-23
We build a model of firm-level innovation, productivity growth and reallocation featuring endogenous entry and exit. A key feature is the selection between high- and low-type firms, which differ in terms of their innovative capacity. We estimate the parameters of the model using detailed US Census micro data on firm-level output, R&D and patenting. The model provides a good fit to the dynamics of firm entry and exit, output and R&D, and its implied elasticities are in the ballpark of a range of micro estimates. We find industrial policy subsidizing either the R&D or the continued operation of incumbents reduces growth and welfare. For example, a subsidy to incumbent R&D equivalent to 53 of GDP reduces welfare by about 1.53 because it deters entry of new high-type firms. On the contrary, substantial improvements (of the order of 53 improvement in welfare) are possible if the continued operation of incumbents is taxed while at the same time R&D by incumbents and new entrants is subsidized. This is because of a strong selection effect: R&D resources (skilled labor) are inefficiently used by low-type incumbent firms. Subsidies to incumbents encourage the survival and expansion of these firms at the expense of potential high-type entrants. We show that optimal policy encourages the exit of low-type firms and supports R&D by high-type incumbents and entry.
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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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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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Do Market Leaders Lead in Business Process Innovation? The Case(s) of E-Business Adoption
April 2011
Working Paper Number:
CES-11-10
This paper investigates the relationship between market position and the adoption of IT-enabled process innovations. Prior research has focused overwhelmingly on product innovation and garnered mixed empirical support. I extend the literature into the understudied area of business process innovation, developing a framework for classifying innovations based on the complexity, interdependence, and customer impact of the underlying business process. I test the framework's predictions in the context of ebuying and e-selling adoption. Leveraging detailed U.S. Census data, I find robust evidence that market leaders were significantly more likely to adopt the incremental innovation of e-buying but commensurately less likely to adopt the more radical practice of e-selling. The findings highlight the strategic significance of adjustment costs and co-invention capabilities in technology adoption, particularly as businesses grow more dependent on new technologies for their operational and competitive performance.
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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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Characteristics of the Top R&D Performing Firms in the U.S.: Evidence from the Survey of Industrial R&D
September 2010
Working Paper Number:
CES-10-33
Innovation drives economic growth and productivity growth, and as such, indicators of innovative activity such as research and development (R&D) expenditures are of paramount importance. We combine Census confidential microdata from two sources in order to examine the characteristics of the top R&D performing firms in the U.S. economy. We use the Survey of Industrial Research and Development (SIRD) to identify the top 200 R&D performing firms in 2003 and, to the extent possible, to trace the evolution of these firms from 1957 to 2007. The Longitudinal Business Database (LBD) further extends our knowledge about these firms and enables us to make comparisons to the U.S. economy. By linking the SIRD and the LBD we are able to create a detailed portrait of the evolution of the top R&D performing firms in the U.S.
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What Happens When Firms Patent? New Evidence from U.S. Economic Census Data
January 2008
Working Paper Number:
CES-08-03
In this study, we present novel statistics on the patenting in US manufacturing and new evidence on the question of what happens when firms patent. We do so by creating a comprehensive firm-patent matched dataset that links the NBER patent data (covering the universe of patents) to firm data from the US Census Bureau (which covers the universe of all firms with paid employees). Our linked dataset covers more than 48,000 unique assignees (compared to about 4,100 assignees covered by the Compustat-NBER link), representing almost two-thirds of all non-individual, non-university, non-government assignees from 1975 to 1997. We use the data to present some basic but novel statistics on the role of patenting in US manufacturing, including strong evidence confirming the highly skewed nature of patenting activity. Next, we examine what happens when firms patent by looking at a large sample of first time patentees. We find that while there are significant cross-sectional differences in size and total factor productivity between patentee firms and non-patentee firms, changes in patentownership status within firms is associated with a contemporaneous and substantial increase in firm size, but little to no change in total factor productivity. This evidence suggests that patenting is associated with firm growth through new product innovations (firm scope) rather than through reduction in the cost of producing existing products (firm productivity). Consistent with this explanation, we find that when firms patent, there is a contemporaneous increase in the number of products that the firms produce. Estimates of (within-firm) elasticity of firm characteristics to patent stock confirm our results. Our findings are robust to alternative measures of size and productivity, and to various sample selection criteria.
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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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