In this paper, the authors describe and explore a new algorithmic approach to constructing concordances between the International Patent Classification (IPC) system and industry classification systems that organize economic data. This ‘Algorithmic Links with Probabilities’ (ALP) approach incorporates text analysis software and keyword extraction programs and applies them to a comprehensive patent dataset. The authors conclude with a discussion on some of the possible applications of the concordance and provide a sample analysis that uses their preferred ALP concordance to analyze international patent flows based on trade patterns.

In this paper, the authors describe and explore a new algorithmic approach to constructing concordances between the International Patent Classification (IPC) system and industry classification systems that organize economic data. This 'Algorithmic Links with Probabilities' (ALP) approach incorporates text analysis software and keyword extraction programs and applies them to a comprehensive patent dataset. The authors conclude with a discussion on some of the possible applications of the concordance and provide a sample analysis that uses their preferred ALP concordance to analyze international patent flows based on trade patterns.

The authors propose an ‘Algorithmic Links with Probabilities’ (ALP) approach to match Trademarks (TMs) data to economic data and enable these data to speak to each other. Specifically, they 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, the authors apply this ALP concordance for TMs to characterize patterns in TM applications across countries, industries, income levels and more. They also use the concordance to investigate some of the key determinants of international technology transfer by comparing bilateral TM applications and bilateral patent applications.

Today’s production processes are fragmented across countries and industries. Intangibles play an important role, but their measurement is elusive. This paper proposes a new empirical framework to measure factor incomes in production that spans industries and countries.

Enforceability of patent rights is the backbone of the patent system. We review differences in the way patent litigation systems are designed across jurisdictions. We also discuss challenges in collecting and accessing patent litigation data as well as their economic analysis. We provide some descriptive analysis of patent litigation in the U.S. and UK for the period 2010-2016 and 2007-2013, respectively. We also analyze administrative post-grant validity challenges in form of the inter partes review in the U.S. and oppositions at the EPO.

This paper has two objectives. First, it describes a new database mapping migratory patterns of inventors, extracted from information included in patent applications filed under the Patent Cooperation Treaty. It explains in detail the information contained in the database and discusses the usefulness and reliability of the underlying data. Second, the paper provides a descriptive overview of inventor migration patterns, based on the information contained in the newly constructed database.

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.