Working papers

Office of the Chief Economist (OCE) economists and their collaborators conduct a variety of policy relevant research and make their preliminary findings available as working papers.

Technical Documentation for Matching Patents and Trademarks to the 2017 National Establishment Time Series Database

Ryan Hughes, Charles deGrazia, and Julian Kolev
USPTO Economic Working Paper No. 2021-4
September 2021
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This paper documents the matching procedures used to generate crosswalks between the USPTO’s patent and trademark datasets and the 2017 National Establishment Time Series (NETS) database. The matching procedures implement a combination of entity resolution techniques including name and address standardization, heuristic matching, hierarchical disambiguation, and manual verification. Using these methods, the Office of the Chief Economist (OCE) matched 88% of patents granted and 73% of trademarks from 1990 through 2016 to entities in the NETS database. The resulting crosswalks offer a foundation for a wide range of work to investigate the relationship between intellectual property and firm establishments.

Software Piracy and IP Management Practices: Strategic Responses to Product-Market Imitation

Wendy A. Bradley and Julian Kolev
USPTO Economic Working Paper No. 2021-3
August 2021
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How do firms’ IP strategies respond to sudden increases in product-market imitation? Using a 2001 technological shock that enabled rising software piracy, we implement an instrumental-variables estimator to compare a treatment group of at-risk-of-piracy firms with matched not-at-risk control firms. We find that rising piracy increases subsequent R&D spending, copyrights, trademarks, and patents for large, incumbent software firms. Furthermore, copyright and trademark filings precede those of patents, and firms with large patent portfolios disproportionately increase copyrights and trademarks following the shock. We conclude that piracy and similar competitive shocks push firms to innovate to stay ahead of imitator products, and that this effect is moderated by their existing patent portfolios. Our findings have implications for managers seeking to capture value from IP in knowledge-based industries.

Artificial Intelligence Patent Dataset (AIPD) on a blue background with an outline of a head.

Identifying artificial intelligence (AI) invention: A novel AI patent dataset

Alexander V. Giczy, Nicholas A. Pairolero, and Andrew Toole
USPTO Economic Working Paper No. 2021-2
June 2021
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To help researchers, policymakers, and the public explore the determinants and impacts of artificial intelligence (AI) invention, OCE released a dataset identifying AI in over 13.2 million USPTO patents and pre-grant publications (PGPubs). The dataset, called the Artificial Intelligence Patent Dataset (AIPD), was constructed using machine learning models for eight AI component technologies. The working paper presents the methodology used and several evaluation metrics based on a manual review by patent examiners with focused expertise in AI, and shows that OCE’s machine learning approach achieves superior performance relative to existing alternatives in the literature.

PatentsView: An open data platform to advance science and technology policy

Andrew Toole, Christina Jones, and Sarvothaman Madhavan
USPTO Economic Working Paper No. 2021-1
June 2020
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What are the connections between science and improvements in economic and social outcomes that drive the “value” of science? Most of the time, these connections are circuitous, varied, diffuse, and opaque. Patent data offer an opportunity to expose new connections between science and technology as well as exposing links to downstream economic and social outcomes. The PatentsView open data platform performs data preparation, visualization, and adds helpful features to USPTO’s administrative data. PatentsView is fundamentally a free “intermediate good” that provides the needed materials for researchers, policymakers, and students to conduct their own analyses, make their own linkages, and derive their own insights. This paper provides a quick tour of the PatentsView platform.

Technical Documentation for the 2019 Patent Examination Research Dataset (Patex) Release

Richard Miller
USPTO Economic Working Paper No. 2020-4
August 2020
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This new version of the Patent Examination Research Dataset (PatEx) is based on data that the Office of the Chief Economist downloaded from Patent Examination Data System (PEDS) on April 26, 2020. We parsed the XML and organized the data into the familiar PatEx data files, following the organization of the Public PAIR portal. However, there are some minor differences between the new PatEx release and the previous ones. This is the main rationale behind the new technical documentation for this release and we advise users to read the relevant sections to better acclimate themselves to the new data.

U.S. Intellectual Property and Counterfeit Goods—Landscape Review of Existing/Emerging Research

Vega Bharadwaj, Marieke Brock, Bridey Heing, Ramon Miron, and Noor Mukarram
USPTO Economic Working Paper No. 2020-3
April 2020
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This report provides an overview of the international market for counterfeit goods. Specifically, the report details the overall magnitude of international counterfeit trade, and explains how counterfeit goods affect the U.S. economy. It highlights the role of the private sector in combatting counterfeits, and the rising trend of counterfeit trade via small parcels. Last, it reviews trends in consumer attitudes towards counterfeit goods, and assesses the facilitating role of social media.

Piracy Landscape Study: Analysis of Existing and Emerging Research Relevant to Intellectual Property Rights (IPR) Enforcement of Commercial-Scale Piracy

Brett Danaher, Michael D. Smith, and Rahul Telang
USPTO Economic Working Paper No. 2020-2
April 2020
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This report provides an overview of the actors involved in the generation and distribution of pirated content, how these actors are organized, and their financial motivations. It further reviews the peer-reviewed academic literature analyzing the harm caused by digital piracy, both to revenue in legal channels and to creative output in the entertainment sector. Finally, it reviews the peer-reviewed academic literature analyzing the effectiveness of both industry- and government-initiated anti-piracy efforts.

The Promise of Machine Learning for Patent Landscaping

Andrew A. Toole, Nicholas Pairolero, James Forman, and Alexander V. Giczy
USPTO Economic Working Paper No. 2020-1
March 2020
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Patent landscaping involves the identification of patents in a specific technology area to understand the business, economic, and policy implications of technological change. Traditionally, patent landscapes were constructed using keyword and classification queries, a labor-intensive process that produced results limited to the scope of the query. In this paper, we discuss the advantages and disadvantages of using machine learning to produce patent landscapes. Machine learning leverages traditional queries to construct the data necessary to train the machine learning models, and the models allow the resultant landscapes to extend more broadly into areas of technology not expected a priori. The models, however, are “black boxes” that limit transparency into their underlying reasoning. To illustrate these points, we summarize two landscapes we recently conducted, one in mineral mining and another in artificial intelligence.

USPTO Patent Number and Case Code File Dataset Documentation

David L. Schwartz, Ted M. Sichelman, and Richard Miller
USPTO Economic Working Paper No. 2019-5
December 2019
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Researchers studying the U.S. patent litigation system have typically had to rely on proprietary, commercial databases to retrieve comprehensive lists of litigated patents and associated case information, precluding publication of underlying data and the verification of study results. In other situations, researchers have used incomplete datasets, potentially resulting in biased results. In order to overcome these limitations, the authors and their research teams reviewed every available initial complaint and related documents in roughly 99 percent of all patent cases filed in U.S. district courts between 2003 and 2016 in order to generate a comprehensive list of litigated patents in those cases. In addition, the authors and their teams coded the case “type” for all of these actions, such as infringement, declaratory judgment, false marking, ownership dispute, malpractice, among others. The resulting dataset can be downloaded in bulk and be used and reproduced with no licensing restrictions. These data have been married to USPTO’s Patent Litigation Docket Reports Dataset, which provides full case and docket information for every one of these cases. Thus, for the first time, researchers can now use a single, comprehensive dataset of patents, case types, and related case information to conduct empirical studies of patent litigation in the U.S. district courts.

Innovation Activities and Business Cycles: Are Trademarks a Leading Indicator?

Charles A.W. deGrazia, Amanda Myers, and Andrew Toole
USPTO Economic Working Paper No. 2019-4
June 2019
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Despite the widespread use of economic information to anticipate changes in business conditions, innovation metrics are not considered to be leading indicators. We argue that aggregate trademark data reflect firm-level choices that can help predict business cycles. In addition to establishing the conceptual basis for considering trademarks, our statistical evaluations, using turning point analysis and a novel machine learning method, find that trademark filings for product and service offerings in commercial use outperform many of the conventional leading indicators. Our work suggests that including trademark metrics in composite indexes could improve recession forecasting performance.

Shorter Patent Pendency Without Sacrificing Quality: The Use of Examiner's Amendments at the USPTO

Charles A.W. deGrazia, Nicholas A. Pairolero, and Mike H.M. Teodorescu
USPTO Economic Working Paper No. 2019-3
June 2019
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Prior research argues that USPTO first-action allowance rates increase with examiner seniority and experience, suggesting lower patent quality. However, we show that the increased use of examiner's amendments account for this prior empirical finding. Further, the mechanism reduces patent pendency by up to fifty percent while having no impact on patent quality, and therefore likely benefits innovators and firms. Our analysis suggests that the policy prescriptions in the literature regarding modifying examiner time allocations should be reconsidered. In particular, rather than re-configuring time allocations for every examination promotion level, researchers and stakeholders should focus on the variation in outcomes between junior and senior examiners and on increasing training for examiner's amendment use as a solution for patent grant delay.

Using Intellectual Property Data to Measure Cross-border Knowledge Flows

Jake Dubbert, Alexander V. Giczy, Nicholas A. Pairolero, and Andrew A. Toole
USPTO Economic Working Paper No. 2019-2
March 2019
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This paper surveys the landscape of empirical studies on cross-border trade in knowledge that use IPRs data. Based on a thorough search of the literature, we identify and categorize the types and uses of IPRs data. Our discussion critically evaluates whether these data support the empirical findings in the studies by identifying where IPRs data are particularly useful and where these data have limitations. The final section of the paper discusses the potential value of making greater use of IPRs assignment data. The goal is to provide a reference to help policymakers evaluate the trade in knowledge literature, particularly the interpretation of IPRs-based evidence for policy decisions.

The Miner Act of 2006: Innovating for Safety and Health in U.S. Mining

Andrew A. Toole, James Forman, and Asrat Tesfayesus
USPTO Economic Working Paper No. 2019-1
January 2019
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The working paper uses patent data to explore the levels and trends in technological innovations in U.S. mineral mining with a particular focus on safety and health. We present four types of patent-based evidence on the impact of the 2006 MINER Act. While this evidence does not include a randomized or natural experiment to establish causality, all four types of evidence point to a positive and significant effect of the MINER Act on patenting in safety-related mineral mining technologies as well as reduced injuries and lost workdays among mine workers.

Previous working papers

2013-2018

An Anatomy of U.S. Firms Seeking Trademark Registration
Emin M. Dinlersoz, Nathan Goldschlag, Amanda Myers, and Nikolas Zolas
May 2018
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Embracing Invention Similarity for the Measurement of Vertically Overlapping Claims
Charles deGrazia, Jesse Frumkin, and Nicholas Pairolero
April 2018
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USPTO Patent Prosecution Research Data: Unlocking Office Action Traits
Qiang Lu, Amanda F. Myers, and Scott Beliveau
August 2017
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USPTO Patent Prosecution and Examiner Performance Appraisal
Alan C. Marco, Andrew A. Toole, Richard Miller, and Jesse Frumkin
June 2017
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Patent Examination Quality and Litigation: Is There a Link?
Alan C. Marco and Richard Miller
June 2017
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Individual versus Institutional Ownership of University-Discovered Inventions
Dirk Czarnitzki, Thorsten Doherr, Katrin Hussinger, Paula Schliessler, and Andrew A. Toole
June 2017
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Patent Litigation Data from US District Court Electronic Records (1963-2015)
Alan C. Marco, Asrat Tesfayesus, and Andrew A. Toole
March 2017
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The Law and Economics of Concealing Health and Safety Information
Daniel E. Ingberman and Asrat Tesfayesus
January 2017
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Patent Claims and Patent Scope
Alan C. Marco, Joshua D. Sarnoff, and Charles deGrazia
October 2016
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Liberalization Agreements in the GATT/WTO and the Terms-of-trade Externality Theory: Evidence from Three Developing Countries
Asrat Tesfayesus
June 2016
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Knowledge Creates Markets: The Influence of Entrepreneurial Support and Patent Rights on Academic Entrepreneurship
Dirk Czarnitzki, Thorsten Doherr, Katrin Hussinger, Paula Schliessler, and Andrew A. Toole
April 2016
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The Dynamic Relationship between Investments in Brand Equity and Firm Profitability: Evidence using Trademark Registrations
Dirk Crass, Dirk Czarnitzki, and Andrew A. Toole
January 2016
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The Bright Side of Patents
Joan Farre-Mensa, Deepak Hegde, and Alexander Ljungqvist
December 2015
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The USPTO Patent Examination Research Dataset: A Window on the Process of Patent Examination
Stuart Graham, Alan C. Marco, and Richard Miller
November 2015
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Business Dynamics of Innovating Firms: Linking U.S. Patents with Administrative Data on Workers and Firms
Stuart Graham, Cheryl Grim, Tariqul Islam, Alan C. Marco, and Javier Miranda
July 2015
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The USPTO Patent Assignment Dataset: Descriptions and Analysis
Alan Marco, Stuart Graham, Amanda F. Myers, Paul D’Agostino, and Kirsten Apple
June 2015
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The USPTO Historical Patent Data Files: Two Centuries of Innovation
Alan Marco, Michael Carley, Steven Jackson, and Amanda F. Myers
June 2015
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The USPTO Trademark Assignment Dataset: Descriptions and Insights
Stuart Graham, Alan Marco, Amanda F. Myers, and Kirsten Apple
April 2014
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Perspectives on the growth in Chinese patent applications to the USPTO
Alan Marco, Richard Miller and Jay Kesan
February 2014
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What is the Probability of Receiving a US Patent?
Michael Carley, Deepak Hegde and Alan Marco
December 2013
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What is behind the growth in trademark filings? An analysis of United States data
Amanda F. Myers
October 2013
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