nep-ipr New Economics Papers
on Intellectual Property Rights
Issue of 2023‒11‒06
four papers chosen by
Giovanni Ramello, Università degli Studi del Piemonte Orientale “Amedeo Avogadro”

  1. How Patent Rights Affect University Science By Laurent R. Bergé; Thorsten Doherr; Katrin Hussinger
  2. Fuzzy firm name matching: Merging Amadeus firm data to PATSTAT By Leon Bremer
  3. Extensions of intellectual property in Media Industry: The Korean case By Jang, Chaeyun; Kim, Seongcheol
  4. When Product Markets Become Collective Traps: The Case of Social Media By Leonardo Bursztyn; Benjamin R. Handel; Rafael Jimenez; Christopher Roth

  1. By: Laurent R. Bergé (Université de Bordeaux); Thorsten Doherr (ZEW, Centre for European Economic Research); Katrin Hussinger (Université du Luxembourg)
    Abstract: How do intellectual property rights influence academic science? We investigate the consequences of the introduction of software patents in the U.S. on the publications of university researchers in the field of computer science. Difference-indifference estimations reveal that software scientists at U.S. universities produced fewer publications (both in terms of quantity and quality) than their European counterparts after patent rights for software inventions were introduced. We then introduce a theoretical model that accounts for substitution and complementarity between patenting and publishing as well as for the direction of research. In line with the model’s prediction, further results show that the decrease in publications is largest for scientists at the bottom of the ability distribution. Further, we evidence a change in the direction of research following the reform towards more applied research.
    Keywords: patent rights, publications, economics of science, difference-indifference, estimation, model of science production.
    JEL: I23 O31 O34 O38 L38
    Date: 2022
  2. By: Leon Bremer (Vrije Universiteit Amsterdam)
    Abstract: When merging firms across large databases in the absence of common identifiers, text algorithms can help. I propose a high-performance fuzzy firm name matching algorithm that uses existing computational methods and works even under hardware restrictions. The algorithm consists of four steps, namely (1) cleaning, (2) similarity scoring, (3) a decision rule based on supervised machine learning, and (4) group identification using community detection. The algorithm is applied to merging firms in the Amadeus Financials and Subsidiaries databases, containing firm-level business and ownership information, to applicants in PATSTAT, a worldwide patent database. For the application the algorithm vastly outperforms an exact string match by increasing the number of matched firms in the Amadeus Financials (Subsidiaries) database with 116% (160%). 53% (74%) of this improvement is due to cleaning, and another 41% (50%) improvement is due to similarity matching. 18.1% of all patent applications since 1950 are matched to firms in the Amadeus databases, compared to 2.6% for an exact name match.
    Keywords: Fuzzy name matching, supervised machine learning, name disambiguation, patents
    JEL: C81 C88 O34
    Date: 2023–10–12
  3. By: Jang, Chaeyun; Kim, Seongcheol
    Abstract: Content-based IP is the core engine to create a ripple effect in the media industry, distinctive from a prevalent distribution strategy of contents. Despite being the latecomer in the IP business, The Korean media industry recognizes the importance of a content-based IP extension strategy. Therefore, this case study aims to identify common factors of successful IP extension cases in Korea and propose a typology of successful IP extension paths. Utilizing the resource-based theory (RBV) and knowledge-based view (KBV) to redefine content based-IP as intangible resources owned by the media industry, this study proposes this theoretical framework for the case study of IP extension analysis. The case study of IP extensions in Korea, which emerged from the broadcasting, web comics and web novels, provides implications for media industries seeking content-based IP extension strategies.
    Keywords: IP(Intellectual property), Content-based IP, IP extension, Korean media industry, RBV (resource-based view), Case study
    Date: 2023
  4. By: Leonardo Bursztyn; Benjamin R. Handel; Rafael Jimenez; Christopher Roth
    Abstract: Individuals might experience negative utility from not consuming a popular product. For example, being inactive on social media can lead to social exclusion or not owning luxury brands can be associated with having a low social status. We show that, in the presence of such spillovers to non-users, standard measures that take aggregate consumption as given fail to appropriately capture welfare. We propose a new methodology to measure welfare that accounts for these consumption spillovers, which we apply to estimate the consumer surplus of two popular social media platforms, TikTok and Instagram. In large-scale, incentivized experiments with college students, we show that, while the standard welfare measure suggests a large and positive surplus, our measure accounting for consumption spillovers indicates a negative surplus, with a large share of active users deriving negative utility. We also shed light on the drivers of consumption spillovers to non-users in the case of social media and show that, in this setting, the “fear of missing out” plays an important role. Our framework and estimates highlight the possibility of product market traps, where large shares of consumers are trapped in an inefficient equilibrium and would prefer the product not to exist.
    JEL: D62 D91
    Date: 2023–10

This nep-ipr issue is ©2023 by Giovanni Ramello. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.