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on Innovation |
| By: | Gu, Grace (University of California, Santa Cruz); Mulalic, Ismir (Department of Economics, Copenhagen Business School); Pozzoli, Dario (Department of Economics, Copenhagen Business School); Wu, Jinhong (The Technical University of Denmark) |
| Abstract: | Climate-related risks have increased significantly over the past two decades, including both physical risks (such as extreme weather events) and transition risks (arising from climate change mitigation policies). This paper examines how these risks relate to firms’ innovation outcomes, including those related to green technologies. We first develop a model in which firms choose how many workers to employ for R&D and production activities in response to rising climate risks. The model predicts an increase in green innovation and overall innovation under certain conditions. Empirical evidence from Danish administrative data generally supports these predictions, showing that firms exposed to climate risks exhibit higher innovation activity, especially in green technologies. |
| Keywords: | Climate change; Physical risks; Transition risks; Firms’ innovation |
| JEL: | Q54 Q55 Q56 |
| Date: | 2026–01–23 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:cbsnow:2026_003 |
| By: | Tate, Anya |
| Abstract: | The late 19th-century reforms to the British patenting system reduced the cost of obtaining a patent from over £100 in 1851 to just £4 by 1883. While increasing accessibility, this cost reduction led to an increase of low-quality patents often replicating previous inventions, raising concerns about the system's effectiveness. As a result, the 1902 policy proposed novelty examination for the first time, increasing the cost by 25%. This paper examines whether the implementation of this policy in 1905 had a differential effect on patenting activity across British regions. Despite the significance of this policy, it has received extremely limited academic attention. This research aims to fill this gap and add to the literature on the regional impacts of patent system reforms in this period. This study employs panel regressions using data on every geocoded patent sealed between 1895-1915 in the PatentCity database with regional employment in 28 industries as controls. Results indicate no change in the regional distribution of patenting activity as a result of the novelty examination. These findings are consistent with those of Nicholas (2011) for the 1883 policy and have important implications for the geography of inventive activity and the distributional impacts of invention policies. |
| JEL: | O30 R10 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:wpaper:129440 |
| By: | Aldasoro, Iñaki; Gambacorta, Leonardo; Pal, Rozalia; Revoltella, Debora; Weiss, Christoph; Wolski, Marcin |
| Abstract: | This paper provides new evidence on how the adoption of artificial intelligence (AI) affects productivity and employment in Europe. Using matched EIBIS-ORBIS data on more than 12, 000 non-financial firms in the European Union (EU) and United States (US), we instrument the adoption of AI by EU firms by assigning the adoption rates of US peers to isolate exogenous technological exposure. Our results show that AI adoption increases the level of labor productivity by 4%. Productivity gains are due to capital deepening, as we find no adverse effects on firm-level employment. This suggests that AI increases worker output rather than replacing labor in the short run, though longer-term effects remain uncertain. However, productivity benefits of AI adoption are unevenly distributed and concentrate in medium and large firms. Moreover, AI-adopting firms are more innovative and their workers earn higher wages. Our analysis also highlights the critical role of complementary investments in software and data or workforce training to fully unlock the productivity gains of AI adoption. |
| Keywords: | Artificial intelligence, firm productivity, Europe, digital transformation |
| JEL: | D22 J24 L25 O33 O47 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:eibwps:335876 |
| By: | Griesshaber, Niclas; Streb, Jochen |
| Abstract: | We leverage multimodal large language models (LLMs) to construct a dataset of 306, 070 German patents (1877-1918) from 9, 562 archival image scans using our LLM-based pipeline powered by Gemini-2.5-Pro and Gemini-2.5-Flash-Lite. Our benchmarking exercise provides tentative evidence that multimodal LLMs can create higher quality datasets than our research assistants, while also being more than 795 times faster and 205 times cheaper in constructing the patent dataset from our image corpus. About 20 to 50 patent entries are embedded on each page, arranged in a double-column format and printed in Gothic and Roman fonts. The font and layout complexity of our primary source material suggests to us that multimodal LLMs are a paradigm shift in how datasets are constructed in economic history. We open-source our benchmarking and patent datasets as well as our LLM-based data pipeline, which can be easily adapted to other image corpora using LLM-assisted coding tools, lowering the barriers for less technical researchers. Finally, we explain the economics of deploying LLMs for historical dataset construction and conclude by speculating on the potential implications for the field of economic history. |
| Keywords: | Multimodal Large Language Models, Information Extraction, Dataset Construction, German Patents |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:safewp:335887 |
| By: | Daron Acemoglu (MIT, Department of Economics); Ufuk Akcigit (University of Chicago - Department of Economics); Simon Johnson (MIT, Sloan School of Management) |
| Abstract: | This chapter presents a tractable framework for the study of technology adoption and diffusion in the context of economic development. Firms in countries behind the world technology frontier can rapidly adopt new techniques from the world frontier. Lower absorptive capacity (because of weak education systems, poor management practices, or barriers to technology adoption), institutional distortions, mismatch between frontier technologies and the needs of firms in the country (i.e., “inappropriate technology†), and credit market frictions slow down technology adoption and cause the economy in question to have a greater distance to the frontier and thus lower income per capita—although the long-run growth rate of the country still remains equal to that of the frontier. This framework is extended to study the choice between innovation and imitation, as well as the role of selection for higher-productivity and higher-absorptive capacity firms during the process of economic development. We illustrate the main comparative statics of our framework with a number of correlations based on cross-country and firm-level data. The tractability of the framework makes it amenable to a range of additional extensions. |
| Keywords: | technology adoption, innovation, income gap, institutions, economic growth, development, productivity |
| JEL: | O1 O3 O4 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:bfi:wpaper:2026-12 |
| By: | Jiandong Ju; Yuankun Li; Shang-Jin Wei |
| Abstract: | We document and characterize a new history of U.S. federal-level industrial policies by scanning all 12, 167 Congressional Acts and 6, 030 Presidential Orders from 1973 through 2022. We find several interesting patterns. First, contrary to a common perception, the United States has always been an active industrial policy nation throughout the period, regardless of which party is in power, with 5.4 laws and 3.4 Presidential Orders per year on average containing new industrial policies. Second, we identify roughly 300% more instances of industrial policies than those in the Global Trade Alert (GTA) database during 2008-2022, despite using essentially the same definition. Third, industrial policies in practice are as likely to be justified by national security as by economic competitiveness. Fourth, many U.S. industrial policies incorporate design features that help mitigate potential drawbacks, such as explicit expiration dates and pilot programs for emerging technologies. Finally, based on stock market reactions and firm performance, the identified policies are recognized as economically significant in shifting resource allocations. |
| JEL: | F1 H20 H4 K20 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34744 |