What Happens When Firms Patent? New Evidence from U.S. Economic Census Data
January 2008
Working Paper Number:
CES-08-03
Abstract
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.
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.
:
economist,
manufacturing,
researcher,
statistical,
invention,
corporation,
employee,
merger,
acquisition,
incorporated,
innovation,
inventory,
patent,
patenting,
firms patents,
patented,
patents firms
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.
:
Standard Statistical Establishment List,
Service Annual Survey,
Longitudinal Research Database,
Ordinary Least Squares,
Total Factor Productivity,
National Bureau of Economic Research,
Longitudinal Business Database,
Census of Manufacturing Firms
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 'What Happens When Firms Patent? New Evidence from U.S. Economic Census Data' 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 PaperPirate's Treasure
January 2017
Working Paper Number:
CES-17-51
Do countries that improve their protection of intellectual property rights gain access to new product varieties from technologically advanced countries? We build the first comprehensive matched firm level data set on exports and patents using confidential microdata from the US Census to address this question. Across several different estimation approaches we find evidence that these protections affect where US firms export.View Full Paper PDF
-
Working PaperR&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.View Full Paper PDF
-
Working PaperBusiness Dynamic Statistics of Innovative Firms
January 2017
Working Paper Number:
CES-17-72
A key driver of economic growth is the reallocation of resources from low to high productivity activities. Innovation plays an important role in this regard by introducing new products, services, and business methods that ultimately lead to increased productivity and rising living standards. Traditional measures of innovation, particularly those based on aggregate inputs, are increasingly unable to capture the breadth and depth of innovation in modern economies. In this paper, we describe an effort at the US Census Bureau, the Business Dynamics Statistics of Innovative Firms (BDS-IF) project, which aims to address these challenges by extending the Business Dynamics Statistics data to include new measures of innovative activity. The BDS-IF project will produce measures of firm, establishment, and employment flows by firm age, firm size, and industry for the subset of firms engaged in activities related to innovation. These activities include patenting and trademarking, the employment of STEM workers, and R&D expenditures. The exibility of the underlying data infrastructure allows this measurement agenda to be extended to include copyright activity, management practices, and high growth firms.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 PaperDo Cash Windfalls Affect Wages? Evidence from R&D Grants to Small Firms
February 2020
Working Paper Number:
CES-20-06
This paper examines how employee earnings at small firms respond to a cash flow shock in the form of a government R&D grant. We use ranking data on applicant firms, which we link to IRS W2 earnings and other U.S. Census Bureau datasets. In a regression discontinuity design, we find that the grant increases average earnings with a rent-sharing elasticity of 0.07 (0.21) at the employee (firm) level. The beneficiaries are incumbent employees who were present at the firm before the award. Among incumbent employees, the effect increases with worker tenure. The grant also leads to higher employment and revenue, but productivity growth cannot fully explain the immediate effect on earnings. Instead, the data and a grantee survey are consistent with a backloaded wage contract channel, in which employees of financially constrained firms initially accept relatively low wages and are paid more when cash is available.View Full Paper PDF
-
Working PaperHow Does Venture Capital Financing Improve Efficiency in Private Firms? A Look Beneath the Surface
June 2008
Working Paper Number:
CES-08-16
Using a unique sample from the Longitudinal Research Database (LRD) of the U.S. Census Bureau, we study several related questions regarding the efficiency gains generated by venture capital (VC) investment in private firms. First, does VC backing improve the efficiency (total factor productivity, TFP) of private firms, and are certain kinds of VCs (higher reputation versus lower reputation) better at generating such efficiency gains than others? Second, how are such efficiency gains generated: Do venture capitalists invest in more efficient firms to begin with (screening) or do they improve efficiency after investment (monitoring)? Third, how are these efficiency gains spread out over rounds subsequent to VC investment? Fourth, what are the channels through which such efficiency gains are generated: increases in product market performance (sales) or reductions in various costs (labor, materials, total production costs)? Finally, how do such efficiency gains affect the probability of a successful exit (IPO or acquisition)? Our main findings are as follows. First, the overall efficiency of VC backed firms is higher than that of non-VC backed firms. Second, this efficiency advantage of VC backed firms arises from both screening and monitoring: the efficiency of VC backed firms prior to receiving financing is higher than that of non-VC backed firms and further, the growth in efficiency subsequent to receiving VC financing is greater for such firms relative to non-VC backed firms. Third, the above increase in efficiency of VC backed firms relative to non-VC backed firms increases over the first two rounds of VC financing, and remains at the higher level till exit. Fourth, while the TFP of firms prior to VC financing is lower for higher reputation VC backed firms, the increase in TFP subsequent to financing is significantly higher for the former firms, consistent with higher reputation VCs having greater monitoring ability. Fifth, the efficiency gains generated by VC backing arise primarily from improvement in product market performance (sales); however for higher reputation VCs, the additional efficiency gains arise from both an additional improvement in product market performance as well as from reductions in various input costs. Finally, both the level of TFP of VC backed firms prior to receiving financing and the growth in TFP subsequent to VC financing positively affect the probability of a successful exit (IPO or acquisition).View Full Paper PDF
-
Working PaperHow is Value Created in Spin-Offs? A Look Inside the Black Box
July 2005
Working Paper Number:
CES-05-09
Using a unique sample of plant level data from the Longitudinal Research Database (LRD), we identify (for the first time in the literature), how (the precise channel and mechanism), where (parent or subsidiary), and when (the dynamic pattern) performance improvements arise following corporate spinoffs. We identify the source of value improvements in spin-offs by comparing the magnitude of post-spinoff changes in the wages, employment, materials costs, rental and administrative expenses, sales, and capital expenditures in the plants belonging to firms undergoing spin-offs relative to the magnitude of such changes in a control group of plants belonging to firms not undergoing spin-offs. We show that the total factor productivity (TFP) of plants belonging to spin-off firms (parent or spun-off subsidiary) increase, on average, following the spin-off. This increase in overall productivity begins immediately, starting with the first year following the spin-off, and continuing in the years thereafter. This performance improvement can be attributed to a decrease in workers' wages, employment at the plant, decrease in the cost of materials purchased, as well as a decrease in rental and office expenditures, but not from improved product market performance by these plants. Further, such productivity improvements arise primarily in plants that remain with the parent; plants belonging to the spun-off subsidiary do not experience such productivity increases. However, contrary to speculation in the previous literature, plants that are spun-off do not underperform parent plants prior to the spin-off. Finally, in our split-sample study of plants that were acquired subsequent to the spin-off and those that were not, we find that productivity increases for both groups of plants: while such productivity increases start immediately after the spin-off for the nonacquired plants, for the acquired plants they occur only after being taken over by a better management team.View Full Paper PDF
-
Working PaperINNOVATION OUTPUT CHOICES AND CHARACTERISTICS OF FIRMS IN THE U.S.
October 2014
Working Paper Number:
CES-14-42
This paper uses new business micro data from the Business Research and Development and Innovation Survey (BRDIS) for the years 2008-2011 to relate the discrete innovation choices made by U.S. companies to features of the company that have long been considered to be important correlates of innovation. We use multinomial logit to model those choices. Bloch and Lopez-Bassols (2009) used the Community Innovation Surveys (CIS) to classify companies according dual, technological or output-based innovation constructs. We found that for each of those constructs of innovation combinations considered, manufacturing and engaging in intellectual property transfer increase the odds of choosing innovation strategies that involve more than one type of categories (for example, both goods and services, or both tech and non-tech) and radical innovations, controlling form size, productivity, time and type of R&D. Company size and company productivity as well as time do not lean the choices in any particular direction. These associations are robust across the three multinomial choice models that we have considered. In contrast with other studies, we have been able to use companies that do and companies that do not innovate, and this has allowed to rule out to some extent selectivity bias.View Full Paper PDF
