The Industry R&D Survey: Patent Database Link Project
November 2006
Working Paper Number:
CES-06-28
Abstract
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.
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
manufacturing,
industrial,
company,
invention,
manufacturer,
corporation,
corporate,
venture,
incorporated,
innovation,
inventory,
patent,
patenting,
trademark,
developed,
innovative,
innovation productivity,
corp,
firm patenting
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
Metropolitan Statistical Area,
Standard Statistical Establishment List,
Standard Industrial Classification,
Service Annual Survey,
Longitudinal Research Database,
National Science Foundation,
Current Population Survey,
Longitudinal Business Database,
Chicago Census Research Data Center,
Patent and Trademark Office,
Business Register,
Limited Liability Company
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'The Industry R&D Survey: Patent Database Link Project' are listed below in order of similarity.
-
Working PaperNBER 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.View Full Paper PDF
-
Working PaperBusiness 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.View Full Paper PDF
-
Working PaperCharacteristics 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.View Full Paper PDF
-
Working PaperGrowth 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.View Full Paper PDF
-
Working PaperImproving Patent Assignee-Firm Bridge with Web Search Results
August 2022
Working Paper Number:
CES-22-31
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.View Full Paper PDF
-
Working PaperDocumenting the Business Register and Related Economic Business Data
March 2016
Working Paper Number:
CES-16-17
The Business Register (BR) is a comprehensive database of business establishments in the United States and provides resources for the U.S. Census Bureau's economic programs for sample selection, research, and survey operations. It is maintained using information from several federal agencies including the Census Bureau, Internal Revenue Service, Bureau of Labor Statistics, and the Social Security Administration. This paper provides a detailed description of the sources and functions of the BR. An overview of the BR as a linking tool and bridge to other Census Bureau data for additional business characteristics is also given.View Full Paper PDF
-
Working PaperUSING 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.View Full Paper PDF
-
Working PaperMatching Compustat Data to the Longitudinal Business Database, 1976-2020
September 2025
Working Paper Number:
CES-25-65
This paper details the methodology for creating an updated Compustat-Longitudinal Business Database (LBD) bridge, facilitating linkage between company identifiers in Compustat and firm identifiers in the LBD. In addition to data from Compustat, we incorporate historical data on public companies from various public and private sources, including information on executive names. Our methodology involves a series of stages using fuzzy name and address matching, including EIN, telephone number, and industry code matching. Qualified researchers with approved proposals can access this bridge though the Federal Statistical Research Data Centers. The Compustat-SSL bridge serves as a crucial resource for longitudinal studies on U.S. businesses, corporate governance, and executive compensation.View Full Paper PDF
-
Working PaperAn '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.View Full Paper PDF
-
Working PaperConcentration, Diversity, and Manufacturing Performance
July 2010
Working Paper Number:
CES-10-14
Regional economist Benjamin Chinitz was one of the most successful proponents of the idea that regional industrial structure is an important determinant of economic performance. His influential article in the American Economic Review in 1961 prompted substantial research measuring industrial structure at the regional scale and examining its relationships to economic outcomes. A considerable portion of this work operationalized the concept of regional industrial structure as sectoral diversity, the degree to which the composition of an economy is spread across heterogeneous activities. Diversity is a relatively simple construct to measure and interpret, but does not capture the implications of Chinitz's ideas fully. The structure within regional industries may also influence the performance of business enterprises. In particular, regional intra-industry concentration'the extent to which an industry is dominated by a few relatively large firms in a locality'has not appeared in empirical work studying economic performance apart from individual case studies, principally because accurately measuring concentration within a regional industry requires firm-level information. Multiple establishments of varying sizes in a given locality may be part of the same firm. Therefore, secondary data sources on establishment size distributions (such as County Business Patterns or aggregated information from the Census of Manufactures) can yield only deceptive portrayals of the level of regional industrial concentration. This paper uses the Longitudinal Research Database, a confidential establishment-level dataset compiled by the United States Census Bureau, to compare the influences of industrial diversity and intra-industry concentration upon regional and firm-level economic outcomes. Manufacturing establishments are aggregated into firms and several indicators of regional industrial concentration are calculated at multiple levels of industrial aggregation. These concentration indicators, along with a regional sectoral diversity measure, are related to employment change over time and incorporated into plant productivity estimations, in order to examine and distinguish the relationships between the differing aspects of regional industrial structure and economic performance. A better understanding of the particular links between regional industrial structure and economic performance can be used to improve economic development planning efforts. With continuing economic restructuring and associated workforce dislocation in the United States and worldwide, industrial concentration and over-specialization are separate mechanisms by which regions may 'lock in' to particular competencies and limit the capacity to adjust quickly and efficiently to changing markets and technologies. The most appropriate and effective policies for improving economic adaptability should reflect the structural characteristics that limit flexibility. This paper gauges the consequences of distinct facets of regional industrial structure, adding new depth to the study of regional industries by economic development planners and researchers.View Full Paper PDF
