This paper constructs a patent assignee-firm longitudinal bridge between U.S. patent assignees and firms using firm-level administrative data from the U.S. Census Bureau. We match granted patents applied between 1976 and 2016 to the U.S. firms recorded in the Longitudinal Business Database (LBD) in the Census Bureau. Building on existing algorithms in the literature, we first use the assignee name, address (state and city), and year information to link the two datasets. We then introduce a novel search-aided algorithm that significantly improves the matching results by 7% and 2.9% at the patent and the assignee level, respectively. Overall, we are able to match 88.2% and 80.1% of all U.S. patents and assignees respectively. We contribute to the existing literature by 1) improving the match rates and quality with the web search-aided algorithm, and 2) providing the longest and longitudinally consistent crosswalk between patent assignees and LBD firms.
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Business Dynamics of Innovating Firms: Linking U.S. Patents with Administrative Data on Workers and Firms
July 2015
Working Paper Number:
CES-15-19
This paper discusses the construction of a new longitudinal database tracking inventors and patent-owning firms over time. We match granted patents between 2000 and 2011 to administrative databases of firms and workers housed at the U.S. Census Bureau. We use inventor information in addition to the patent assignee firm name to and improve on previous efforts linking patents to firms. The triangulated database allows us to maximize match rates and provide validation for a large fraction of matches. In this paper, we describe the construction of the database and explore basic features of the data. We find patenting firms, particularly young patenting firms, disproportionally contribute jobs to the U.S. economy. We find patenting is a relatively rare event among small firms but that most patenting firms are nevertheless small, and that patenting is not as rare an event for the youngest firms compared to the oldest firms. While manufacturing firms are more likely to patent than firms in other sectors, we find most patenting firms are in the services and wholesale sectors. These new data are a product of collaboration within the U.S. Department of Commerce, between the U.S. Census Bureau and the U.S. Patent and Trademark Office.
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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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An 'Algorithmic Links with Probabilities' Crosswalk for USPC and CPC Patent Classifications with an Application Towards Industrial Technology Composition
March 2016
Working Paper Number:
CES-16-15
Patents are a useful proxy for innovation, technological change, and diffusion. However, fully exploiting patent data for economic analyses requires patents be tied to measures of economic activity, which has proven to be difficult. Recently, Lybbert and Zolas (2014) have constructed an International Patent Classification (IPC) to industry classification crosswalk using an 'Algorithmic Links with Probabilities' approach. In this paper, we utilize a similar approach and apply it to new patent classification schemes, the U.S. Patent Classification (USPC) system and Cooperative Patent Classification (CPC) system. The resulting USPC-Industry and CPC-Industry concordances link both U.S. and global patents to multiple vintages of the North American Industrial Classification System (NAICS), International Standard Industrial Classification (ISIC), Harmonized System (HS) and Standard International Trade Classification (SITC). We then use the crosswalk to highlight changes to industrial technology composition over time. We find suggestive evidence of strong persistence in the association between technologies and industries over time.
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R&D or R vs. D?
Firm Innovation Strategy and Equity Ownership
April 2020
Working Paper Number:
CES-20-14
We analyze a unique dataset that separately reports research and development expenditures
for a large panel of public and private firms. Definitions of 'research' and 'development' in this dataset, respectively, correspond to definitions of knowledge 'exploration' and 'exploitation' in the innovation theory literature. We can thus test theories of how equity ownership status relates to innovation strategy. We find that public firms have greater research intensity than private firms, inconsistent with theories asserting private ownership is more conducive to exploration. We also find public firms invest more intensely in innovation of all sorts. These results suggest relaxed financing constraints enjoyed by public firms, as well as their diversified shareholder bases, make them more conducive to investing in all types of innovation. Reconciling several seemingly conflicting results in prior research, we find private-equity-owned firms, though not less innovative overall than other private firms, skew their innovation strategies toward development and away from research.
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Competition, Firm Innovation, and Growth under Imperfect Technology Spillovers
July 2024
Working Paper Number:
CES-24-40
We study how friction in learning others' technology, termed 'imperfect technology spillovers,' incentivizes firms to use different types of innovation and impacts the implications of competition through changes in innovation composition. We build an endogenous growth model in which multi-product firms enhance their products via internal innovation and enter new product markets through external innovation. When learning others' technology takes time due to this friction, increased competitive pressure leads firms with technological advantages to intensify internal innovation to protect their markets, thereby reducing others' external innovation. Using the U.S. administrative firm-level data, we provide regression results supporting the model predictions. Our findings highlight the importance of strategic firm innovation choices and changes in their composition in shaping the aggregate implications of competition.
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Patents, Innovation, and Market Entry
September 2023
Working Paper Number:
CES-23-45
Do patents facilitate market entry and job creation? Using a 2014 Supreme Court decision that limited patent eligibility and natural language processing methods to identify invalid patents, I find that large treated firms reduce job creation and create fewer new establishments in response, with no effect on new firm entry. Moreover, companies shift toward innovation aimed at improving existing products consistent with the view that patents incentivize creative destruction.
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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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Matching State Business Registration Records
to Census Business Data
January 2020
Working Paper Number:
CES-20-03
We describe our methodology and results from matching state Business Registration Records (BRR) to Census business data. We use data from Massachusetts and California to develop methods and preliminary results that could be used to guide matching data for additional states. We obtain matches to Census business records for 45% of the Massachusetts BRR records and 40% of the California BRR records. We find higher match rates for incorporated businesses and businesses with higher startup-quality scores as assigned in Guzman and Stern (2018). Clerical reviews show that using relatively strict matching on address is important for match accuracy, while results are less sensitive to name matching strictness. Among matched BRR records, the modal timing of the first match to the BR is in the year in which the BRR record was filed. We use two sets of software to identify matches: SAS DQ Match and a machine-learning algorithm described in Cuffe and Goldschlag (2018). We find preliminary evidence that while the ML-based method yields more match results, SAS DQ tends to result in higher accuracy rates. To conclude, we provide suggestions on how to proceed with matching other states' data in light of our findings using these two states.
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USING LINKED CENSUS R&D-LRD DATA TO ANALYZE THE EFFECT OF R&D INVESTMENT ON TOTAL FACTOR PRODUCTIVITY GROWTH
January 1989
Working Paper Number:
CES-89-02
Previous studies have demonstrated that productivity growth is positively correlated with the intensity of R&D investment. However, existing studies of this relationship at the micro (firm or line of business) level have been subject to some important limitations. The most serious of these has been an inability to adequately control for the diversified activities of corporations. This study makes use of linked Census R&D - LRD data, which provides comprehensive information on each firms' operations at the 4-digit SIC level. A marked improvement in explaining the association between R&D and TFP occurs when we make appropriate use of the data by firm by industry. Significant relationships between the intensities of investment in total, basic, and company-funded R&D, and TFP growth are confirmed.
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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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