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on Intellectual Property Rights |
| By: | Gaetan de Rassenfosse (Ecole polytechnique federale de Lausanne); Gabriele Pellegrino (Catholic University of the Sacred Heart); Emilio Raiteri (Eindhoven University of Technology) |
| Abstract: | This paper provides empirical evidence suggesting that patents may facilitate knowledge disclosure. The analysis exploits the Invention Secrecy Act, which grants the U.S. Commissioner for Patents the right to prevent the disclosure of new inventions that represent a threat to national security. Using a two-level matching approach, we document a negative and large relationship between the enforcement of a secrecy order and follow-on inventions, as captured with patent citations and text-based measures of invention similarity. The effect carries over to after the lift of the secrecy period, suggesting a lost generation of inventions. The results bear implications for innovation and intellectual property policy. |
| Keywords: | disclosure; follow-on invention; knowledge diffusion; patent |
| JEL: | O31 O33 O34 |
| Date: | 2023–12 |
| URL: | https://d.repec.org/n?u=RePEc:iip:wpaper:26&r= |
| By: | Galasso, Alberto; Schankerman, Mark |
| Keywords: | patents; licensing; patent pool; pharmaceuticals; HIV; public health; developing countries |
| JEL: | I18 O31 O34 |
| Date: | 2022–09–27 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:123932&r= |
| By: | Gaétan de Rassenfosse (Ecole polytechnique federale de Lausanne); Adam Jaffe (Brandeis University); Joal Waldfogel (University of Minnesota) |
| Abstract: | The arrival of creative machines—software capable of producing human-like creative content—has triggered a series of legal challenges about intellectual property. The outcome of these legal challenges will shape the future of the creative industry in ways that could enhance or jeopardize welfare. Policymakers are already tasked with creating regulations for a post-generative AI creative industry. Economics may offer valuable insights, and this paper is our attempt to contribute to the discussion. We identify the main economic issues and propose a framework and some tools for thinking about them. |
| Keywords: | generative AI; machine learning; copyright; fair use |
| JEL: | O34 K20 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:iip:wpaper:27&r= |
| By: | Haruo Kakehi (Graduate School of Economics, Keio University); Ryo Nakajima (Faculty of Economics, Keio University) |
| Abstract: | This study investigates how pharmacists dispense generic drugs by considering patients' brand preferences. While the literature shows that pharmacists, as experts, underestimate brand premiums, our data show that they frequently dispense brandidentical generics, known as authorized generics. We model patients' generic drug choices and pharmacies' dispensing decisions to explain how patients' brand preferences vary across pharmacies and to determine for-profit pharmacists' heterogeneous dispensing behavior. Using Japanese pharmacists' dispensing data, our empirical results show significant variations in patients' brand preferences and perceived differences in the quality of antibiotics. Furthermore, our findings show that one of the factors behind these differences is the provision of information by pharmacists. |
| Keywords: | generic pharmaceuticals, authorized generic, brand premiums, pharmacist behavior, information provision |
| JEL: | D12 I11 I18 L65 |
| Date: | 2024–06–17 |
| URL: | https://d.repec.org/n?u=RePEc:keo:dpaper:2024-015&r= |