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on Innovation |
| By: | Kazuyuki MOTOHASHI; Naotoshi TSUKADA; Kenta IKEUCHI |
| Abstract: | Corporate scientists that are involved in scientific activities, often leading to research paper publications, are important for corporate innovation, since science-based innovation tends to be transformative, spanning the boundaries of existing R&D pipelines. Such scientists can also play a role as a bridge between academic researchers, injecting scientific knowledge from outside the firm. However, the publication of internal corporate scientific activities could benefit competitor firms, providing them with input towards their own transformative innovation. In this study, we analyze this trade-off using a linked dataset of research papers and patents (disambiguated by paper author and patent inventor information and patent citation in research papers) of Japanese firms. Specifically, we analyzed two aspects, (1) contribution of corporate scientist research papers to in-house innovation (patent) and (2) capacity of corporate scientists to absorb scientific findings from outside their firms to obtain high quality patents. Our findings indicate that corporate scientists contribute to both aspects of innovation in their firms. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:25089 |
| By: | Gaétan de Rassenfosse (Ecole polytechnique federale de Lausanne); Ling Zhou (Ecole polytechnique federale de Lausanne); |
| Abstract: | A patent system is a central tool in innovation policy. The prospect of monopolistic pricing supposedly encourages firms to innovate. However, there is scant empirical evidence supporting the existence of higher markups for patent-protected products. Using an original dataset that links consumer products to the patents that protect them, we study the impact of patent protection on product prices. Exploiting exogenous variations in patent status, we find that a loss of patent protection leads to an 8–10 percent drop in product prices. The price drop is larger for more important patents and is more pronounced in more competitive product markets. |
| Keywords: | innovation; markup; patent system; product; R&D incentive |
| JEL: | O31 O34 L11 D42 K11 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:iip:wpaper:29 |
| By: | Atsuki KOTANI; Kentaro NAKAJIMA; Tetsuji OKAZAKI; Yukiko SAITO |
| Abstract: | Innovations in military technology potentially drive significant societal transformations through applications to civilian use. This study aims to quantitatively measure the impact of military technology development on civilian innovation activities using prewar and wartime Japanese patent data from 1916 to 1945. By exploiting Japan's secret patent system, which classified particularly critical military-related technologies not disclosed to the public, we identify important technological developments. The result shows that the filing of secret patents led to a significant increase in the number of patents within the corresponding technological classifications. Furthermore, this effect is not limited to organizations that registered secret patents; a significant impact is also observed among organizations that did not register secret patents. This suggests that the development of militarily important technologies generates a substantial spillover effect on other organizations. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:25093 |
| By: | Ufuk Akcigit; Harun Alp; Jeremy Pearce; Marta Prato |
| Abstract: | This paper studies how individuals sort into entrepreneurship and invention-related occupations and how their interactions shape innovation and economic growth. We develop an endogenous growth model in which occupational sorting jointly determines the supply of R&D talent and entrepreneurs’ demand for it. Empirically, using Danish microdata, we show that transformative entrepreneurs—those who hire R&D workers—tend to have higher IQ and education and build faster-growing firms than other entrepreneurs. Quantitatively, the estimated model indicates that financial barriers to education misallocate talent; alleviating them through education subsidies increases both demand and supply of R&D workers, raising innovation and long-run growth. Broad startup subsidies are ineffective. |
| Keywords: | entrepreneurship; R&D Policy; innovation; IQ; endogenous growth |
| JEL: | O31 O38 O47 J24 |
| Date: | 2025–09–01 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednsr:101780 |
| By: | Becker, Annette; Hottenrott, Hanna; Mukherjee, Anwesha |
| JEL: | L26 O32 O33 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:vfsc25:325401 |
| By: | Keuschnigg, Christian; Stalenis, Giedrius |
| JEL: | D21 D62 H23 O33 Q41 Q43 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:vfsc25:325400 |
| By: | Di Carlo, Donato; Moretti, Lorenzo; Moschella, Manuela |
| Abstract: | This article examines the political foundations of industrial policy amid the return of state economic interventionism. Comparing the United States' Inflation Reduction Act (IRA) and the European Union's Green Deal Industrial Plan (GDIP), it shows that contrasting industrial policy strategies were ultimately shaped by differences in the two polities' legislative rules. In both cases, geopolitical pressures sparked renewed interest in green industrial policymaking. However, procedural mechanisms for majoritarian decision‐making in the U.S. Senate enabled the government to overcome partisan veto players and compelled the design of the IRA as a budgetary instrument centered on fiscal subsidies. By contrast, unanimity requirements in the EU's joint decision‐making system prevented the Commission from overcoming Member State veto players in the Council, precluding supranational fiscal instruments and resulting in a regulation‐based, decentralized approach via national state aid. The findings contribute to the burgeoning debates on the return of industrial policy and state activism by showing how political institutions contribute to shaping not only the scope but also the form of economic interventionism within different polities. |
| Keywords: | economic interventionism; green deal industrial plan; green industrial policy; inflation reduction act (IRA); political institutions |
| JEL: | J1 |
| Date: | 2025–10–31 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:129545 |
| By: | Van-Thien Nguyen; Rene Carraz |
| Abstract: | This study expands on the patent-paper pair (PPP) detection model developed by Nguyen and Carraz (2025, Scientometrics) by systematically comparing it with two prominent large-scale approaches: Marx and Scharfmann (2024) and Wang et al. (2025). Although these models all aim to identify instances where the same research result is disclosed through both a patent and a scientific paper, they differ substantially in scope, design, and methodological assumptions. The Nguyen and Carraz model is designed for the Japanese academic context and integrates inventor–author matching, citation overlap, and semantic and lexical similarity within a supervised learning framework. In contrast, Marx and Scharfmann rely on detecting long identical word sequences (“self-plagiarism”) via a random forest classifier, and Wang et al. implement an inventor-centric clustering method with logistic regression applied to title and abstract similarity. We directly compare the Nguyen and Carraz dataset with those of Marx and Scharfmann and Wang et al., focusing on PPPs involving Japanese academic assignees. Despite the shared national context, there is minimal overlap: only 168 PPPs overlap with the Marx and Scharfmann model and 425 overlap with the Wang et al. model. When evaluated on a shared validation set, the Nguyen and Carraz model outperforms both alternatives in the Japanese academic context, especially with logistic regression features. Feature extensions such as self-plagiarism and geographic distance offer only modest improvements under non-linear models. These findings highlight the importance of designing context-specific models and exercising caution when applying global PPP datasets to localized settings. |
| Keywords: | Patent Paper Pair; Methodology; Matching algorithm; Academic patent;Japan |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ulp:sbbeta:2025-27 |