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on Technology and Industrial Dynamics |
| By: | Bernhard Ganglmair; Alexander Kann |
| Keywords: | defensive publications, disclosure, open innovation, patents, R&D, text-asdata We study the content, novelty, and value of defensive publications relative to patents. We use a large language model (LLM) to apply the cooperative patent classification (CPC) system to a set of defensive publications (from 1962 to 2022) from the journal Research Disclosure, thus mapping such research disclosures and patents into a common space and allowing for a direct evaluation of textual similarities between these two types of R&D outputs. We find that while in some technologies, patents and research disclosures follow similar aggregate trends, some exhibit diverging developments over time. We also document shifts in the position of research disclosures in the patenting space that are indicative of changes in the technological landscape not captured in patents. We further show that substantial numbers of research disclosures are published before their closest patents are filed, and many contain terminology before it is first used in patents. Last, we find that in several technology areas, research disclosures have evolved from being an outlet for niche results to a vehicle to publicize technological developments of high practical relevance and value. Our results imply that when we draw conclusions about the nature of technological progress or the direction of innovation based solely on patent data, we obtain an incomplete picture. |
| JEL: | C81 O32 O34 O36 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2025_656 |
| By: | Zhang, Yun; Samaniego, Roberto; Rodrigo, Rodimiro |
| Abstract: | We examine the impact of industrial robots on wage inequality both between and within occupations. Analyzing two decades of U.S. data, we find that moving from the 25th to the 75th percentile of industry-level robot adoption reduces the within-occupation wage inequality by 16% and increases the between-occupation inequality by 7% of their respective standard deviations. These results are robust to confounding factors, different inequality measures, and instrumental variables. Our evidence shows that robots compress within-occupation wage inequality by lowering wages at the top of the distribution while increasing between-occupation inequality by impacting the middle of the distribution. We show that these findings are consistent with a standard wage-posting model incorporating endogenous robot adoption. Overall, our results suggest that robots exacerbate wage polarization while reducing the rents of the highest-paid workers in the occupations most vulnerable to automation. |
| Date: | 2025–02–17 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:gtbm4_v1 |
| By: | Menaka Hampole; Dimitris Papanikolaou; Lawrence D.W. Schmidt; Bryan Seegmiller |
| Abstract: | We leverage recent advances in NLP to construct measures of workers' task exposure to AI and machine learning technologies over the 2010 to 2023 period that vary across firms and time. Using a theoretical framework that allows for a labor-saving technology to affect worker productivity both directly and indirectly, we show that the impact on wage earnings and employment can be summarized by two statistics. First, labor demand decreases in the average exposure of workers' tasks to AI technologies; second, holding the average exposure constant, labor demand increases in the dispersion of task exposures to AI, as workers shift effort to tasks that are not displaced by AI. Exploiting exogenous variation in our measures based on pre-existing hiring practices across firms, we find empirical support for these predictions, together with a lower demand for skills affected by AI. Overall, we find muted effects of AI on employment due to offsetting effects: highly-exposed occupations experience relatively lower demand compared to less exposed occupations, but the resulting increase in firm productivity increases overall employment across all occupations. |
| JEL: | E20 J01 J24 O3 O33 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33509 |
| By: | Yonggyun Kim; Francisco Poggi |
| Abstract: | We introduce a dynamic innovation game where participants race to develop a product using alternative technologies. Race participants dynamically allocate resources across (i) developing the product with the currently available technology and (ii) obtaining a faster technology for posterior development. When firm’s available technologies are publicly observable, there is a unique MPE in which firms react to a rivals’ technological discovery by increasing the share of resources allocated to development. However, without frictions, the firms file patents and license technologies to their rivals. When firm’s available technologies are private information, firms conceal their discoveries by forgoing patenting, even when patent holders retain all bargaining power in licensing negotiations. |
| Keywords: | Direction of Innovation, Patent, License, Trade Secret |
| JEL: | C73 D21 O30 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2025_648 |
| By: | Draca, Mirko; Nathan, Max; Nguyen, Viet Nguyen-Tien; Oliveira Cunha, Juliana; Rosso, Anna; Sivropoulos-Valero, Anna Valero |
| Abstract: | Which types of human capital influence the adoption of advanced technologies? We study the skill biased adoption of information and communication technologies (ICT) across two waves in the UK. Specifically, we compare the 'new wave' of cloud and machine learning / AI technologies during the 2010s - pre-LLM - with the previous wave of personal computer adoption in the 1990s and early 2000s. At the area-level we see the emergence of a distinct STEM-biased adoption effect for the second wave of cloud and machine learning / AI technologies (ML/AI), alongside a general skill-biased effect. A one-standard deviation increase in the baseline share of STEM workers in areas is associated with around 0.3 of a standard deviation higher adoption of cloud and ML/AI. We find similar effects at the firm level where we are able to test for the influence of a wide range of skills. In turn, this STEM-biased adoption pattern has encouraged the concentration of these technologies, leading to more acute differences between high-tech and low-tech areas and firms. In contrast with classical technology diffusion, recent cloud and ML/AI adoption in the UK seems more likely to widen inequalities than reduce them. |
| Keywords: | technology diffusion; ICT; human capital; stem; technological change; AI |
| JEL: | J24 O33 R11 |
| Date: | 2024–10–10 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:126769 |
| By: | Fontanelli, Luca; Calvino, Flavio; Criscuolo, Chiara; Nesta, Lionel; Verdolini, Elena |
| Abstract: | We leverage a uniquely comprehensive combination of data sources to explore the enabling role of human capital in fostering the adoption of predictive AI systems in French firms. Using a causal estimation approach, we show that ICT engineers play a key role for AI adoption by firms. Our estimates indicate that raising the current average share of ICT engineers in firms not using AI (1.66%) to the level of AI users (6.7%) would increase their probability to adopt AI by 0.81 percentage points - equivalent to an 8.43 percent growth. However, this would imply substantial investments to fill the existing gap in ICT human capital, amounting to around 450.000 additional ICT engineers. We also explore potential mechanisms, showing that the relevance of ICT engineers for predictive AI is driven by the innovative nature of its use, make-vs-buy choices, large availability of data, ICT and R&D intensity. |
| Keywords: | artificial intelligence; human capital; technological diffusion |
| JEL: | J24 O33 |
| Date: | 2024–11–18 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:126787 |
| By: | Bøler, Esther Ann; Holtsmark, Katinka; Ulltveit-Moe, Karen Helene |
| Abstract: | We analyze how a major negative shock to the producers of fossil fuels may lead to a shift from dirty to clean R&D along the supply chain. First, we develop a theoretical framework of directed technical change, showing that adjustment costs in R&D activity can lead fossil energy sector suppliers to shift their R&D activity towards clean innovation more than other firms, as a consequence of a negative oil price shock. Second, we investigate the impact of a major drop in the oil price in 2014 on clean R&D. Relying on rich firm level trade data, we propose a novel method of identifying firms' exposure to the price shock. We find that more exposed firms increased their clean R&D investments more than less exposed firms. Our findings contribute to the understanding of the drivers of clean technological change, which is vital to assess the effectiveness of different climate policy measures, including carbon pricing. |
| Keywords: | clean innovation; supply chains; carbon pricing |
| JEL: | F18 O31 Q55 Q58 |
| Date: | 2024–12–13 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:126766 |
| By: | Johannes Gessner |
| Keywords: | environmental regulation, global value chains, innovation, fuel economy standards, directed technological change Decarbonizing industries to mitigate climate change requires technological change. Innovation by suppliers can play a crucial role in the technological transition, particularly when suppliers have expertise in zero-emission technologies. In this paper, I study the effect of environmental regulation in a downstream industry on the innovation outcomes of suppliers in the context of the European CO2 emission standard for passenger cars. I construct a novel data set that links administrative data on car manufacturer compliance to supplier patent data using information on automotive supply chains. To identify the causal effect of changes in the stringency of the emission standard, I leverage the heterogeneous exposure of automotive suppliers to changes in the composition of the European car market in the aftermath of the 2015 Volkswagen diesel scandal. Exposure to more stringent environmental regulation increases innovation for zero-emission vehicle technologies among existing suppliers. In addition, the likelihood that car manufacturers form new supply chain links to firms with expertise in technologies to reduce vehicle emissions increases in response to more stringent environmental regulation. These results suggest that environmental regulation induces economically significant technology spillovers to the regulated firms. |
| JEL: | O30 Q55 Q58 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2025_654 |
| By: | Antonin Bergeaud; Max Deter; Maria Greve; Michael Wyrwich |
| Abstract: | We investigate the causal relationship between inventor migration and regional innovation in the context of the large-scale migration shock from East to West Germany between World War II and the construction of the Berlin Wall in 1961. Leveraging a newly constructed, century-spanning dataset on German patents and inventors, along with an innovative identification strategy based on surname proximity, we trace the trajectories of East German inventors and quantify their impact on innovation in West Germany. Our findings demonstrate a significant and persistent boost to patenting activities in regions with higher inflows of East German inventors, predominantly driven by advancements in chemistry and physics. We further validate the robustness of our identification strategy against alternative plausible mechanisms. We show in particular that the effect is stronger than the one caused by the migration of other high skilled workers and scientists. |
| Keywords: | patents, migration, Germany, iron curtain, innovation |
| Date: | 2025–02–19 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2076 |
| By: | Leone, Fabrizio |
| Abstract: | The diffusion of automation technology raises questions about the future of work, leading to calls for policy interventions. The ongoing debate centers on the decisions made by technology adopters. In this paper, I study supply-side adjustments and their role in shaping policy outcomes. I focus on the global market for industrial robots, a leading type of automation technology, where a few multinational enterprises (MNEs) dominate sales. To evaluate how these MNEs respond to policy changes, I collect new data on their characteristics and global sales networks. I then develop and estimate a multi-country general equilibrium model featuring oligopolistic multinational robot sellers. Using this model, I find that MNEs' market entry and pricing responses transmit internationally and amplify the aggregate and distributional effects of policies targeting robots. |
| Keywords: | multinational enterprises; market power; automation |
| JEL: | F1 F16 F23 L13 O33 |
| Date: | 2024–12–03 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:126784 |
| By: | James Bessen; Xiupeng Wang |
| Abstract: | Investments in software, R&D, and advertising have surged, nearing half of U.S. private nonresidential investment. Yet just a few hundred firms dominate this growth. Most firms, including large ones, regularly invest little in capitalized software and R&D, widening this “intangible divide” despite falling intangible prices. Using comprehensive US Census microdata, we document these patterns and explore factors associated with intangible investment. We find that firms invest significantly less in innovation-related intangibles when their rivals invest more. One firm’s investment can obsolesce rivals’ investments, reducing returns. This negative pecuniary externality worsens the intangible divide, potentially leading to significant misallocation. |
| Keywords: | intangibles, R&D, software, innovation, obsolescence |
| JEL: | E22 O31 O32 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:cen:wpaper:25-15 |
| By: | Lehmann-Hasemeyer, Sibylle H.; Morell, Alexander |
| Abstract: | Using data on all patent cases in front of German courts between 2010 and 2015 we find that plaintiffs in patentinfringement cases mainly chose the venue where to sue by the speed with which courts dispose of their cases. We also find that quality - measured, both, as the fraction of cases challenged in the next instance and the ratio of successful appeals in the year before filing - has an impact on court choice by patent plaintiffs. We can further show that plaintiffs merely shop between three German courts, namely Duesseldorf, Munich and Mannheim. Moreover, we find that once one of these three courts introduces an additional panel of three judges, thereby working faster, the other two courts increase their working speed, too. This indicates that, indeed, courts actively compete for cases. However, we do not find evidence for courts reacting to a competitor's increase in speed by deciding in the plaintiffs favor more often or by deteriorating quality of decisions. We thank the ministries of justice of the 16 German Laender for the detailed data on patent cases. Moreover, we thank Stefan Bechtold, Fabian Gaessler, Dietmar Harhoff, Lea Tochtermann, Mike Schuster, Holger Spamann, the participants of the network meeting of the DFG network "Conflict Strategies in Innovation Markets" in Mannheim (Dec. 2023), the participants of the International Meeting of Law and Economics in Bruges (Apr. 2024), seminar participants at the ETH Zurich (Apr. 2024), participants of the CELS 2024 at Emory Law School, Atlanta (Nov. 2024), and the participants of the SAFE 2025 research retreat (Jan. 2025) for their valuable comments. |
| Keywords: | Organizational Behavior, Intellectual Property, Litigation, Patents and Innovation |
| JEL: | D23 K11 K41 O34 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:safewp:312400 |