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on Technology and Industrial Dynamics |
| By: | Maczulskij, Terhi |
| Abstract: | Abstract This study examines the effects of the 2004 European Union enlargement on firm productivity and innovation in Finland. Using linked employer–employee and firm-level data, the analysis exploits increased access to workers from the ten new EU member states (EU10). To address the endogenous geographic distribution of immigrants, I construct an instrumental variable based on historically predetermined migration patterns. The results show that increased EU10 employment raises firm labor productivity, the probability of having a granted patent, and STEM employment, while effects on other innovation outcomes are more limited. The responses also differ across sectors. In manufacturing, EU10 employment increases process innovation but reduces STEM employment, whereas in services it increases labor productivity and the probability of having granted patents. Overall, the findings suggest that immigration-induced labor-supply changes can improve firm performance and affect selected dimensions of innovation, with the effects varying across sectors and innovation margins. |
| Keywords: | EU enlargement, Firms, Immigration, Innovation, Instrumental variables, Productivity |
| JEL: | D22 F22 O30 |
| Date: | 2026–08–27 |
| URL: | https://d.repec.org/n?u=RePEc:rif:wpaper:145 |
| By: | Ina Ganguli; Jeffrey Lin; Vitaly Meursault; Nicholas F. Reynolds |
| Abstract: | Over nearly two centuries, US inventions have become increasingly dissimilar: not just fewer head-to-head collisions between inventors, but growing distance between neighboring inventions. We document this secular decline in similarity using validated neural language models applied to the full text of claims in over 11 million US patents (1836–2023), corroborated by a 98% decline in patent interference rates, a measure of independent simultaneous invention. Measuring this correctly requires validation, since different representations of the same patent text can yield opposite conclusions about whether inventions are converging or spreading out. Our validation framework, the first systematic comparison for patent text, selects among these representations. We develop a spatial competition model in which inventors choose locations in idea space. The model explains spreading out and connects it to several independently documented patterns — rising R&D investment per inventor, increasing patent values, weakening knowledge spillovers, and declining research productivity. The mechanism is spatial; as inventors spread out to capture new territory, inventions become more valuable but also more costly for others to absorb. In doing so, the model turns spillover intensity, innovation step size, and research productivity from fixed primitives into outcomes of inventor positioning. A calibrated decomposition attributes roughly 40% of the long-run decline in US research productivity to these spatial forces, alongside traditional explanations such as fishing out and the burden of knowledge. Where inventors stand relative to each other in idea space matters as much for growth as how many of them there are. |
| JEL: | C55 O31 O41 O47 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35499 |
| By: | Ha Minh Nguyen |
| Abstract: | How do demographic trends shape the adoption of AI and automation technologies? This paper provides the first large-scale cross-country firm-level test of the demographic–automation hypothesis using World Bank Enterprise Surveys data covering 89, 380 firms across 144 countries from 2022 to 2025. I classify adopters by applying a large language model to firms’ open-ended process innovation descriptions, identifying 1, 656 AI and automation adopters (1.9 percent of the sample). A ten-percentage-point increase in the old-age dependency ratio raises process adoption probability by approximately 0.6 percentage points, after accounting for countries’ income levels, digital infrastructure, firm size and sector, and broad regional and time differences. The result is robust across specifications and supported by an instrumental variable strategy based on predetermined demographic cohort structure. Heterogeneity analysis shows the effect concentrates in manufacturing, large firms, and developing economies for the broad adoption measure; restricting to firms with explicit references to AI reverses the sector pattern, with services firms significantly more likely to adopt than manufacturing firms, pointing to distinct sectoral profiles for software-based AI and hardware-based automation. Aging also predicts firms’ development of AI-enabled products across both manufacturing and services. The results indicate that demographic aging shapes AI and automation adoption through both process and product innovation channels: firms substitute technology for increasingly scarce and costly labor in production, and separately develop AI-enabled products for labor-constrained customers. |
| Keywords: | Aging; automation; artificial intelligence; firm-level; technology adoption; labor-saving technology; World Bank Enterprise Surveys; demographics; labor substitution |
| Date: | 2026–08–21 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2026/176 |
| By: | Galiano, Angelo Maurizio; Dell'Erba, Giuseppe; Costantiello, Alberto; Leogrande, Angelo |
| Abstract: | Europe measures the innovative performance of its regions largely by counting patents, and allocates public resources accordingly. This paper asks what regional patenting actually reflects, drawing on Regional Innovation Scoreboard data for 245 European regions observed annually between 2016 and 2023. Three candidate drivers are considered: the research effort of firms, the intensity of formal collaboration between the research base and industry, and the propensity to protect intangible assets through trademarks. Business research effort emerges as the dominant correlate throughout, science–industry collaboration as a weaker but consistent one, and trademark activity as a positive one, suggesting that firms which protect brands are not forgoing patents but exercising a single appropriation capability across several instruments. Two findings carry implications beyond measurement. Regional innovative capacity proves remarkably immobile: differences between regions account for roughly 95 per cent of the variation in the data, and differences within a region over the eight years for the remainder, so the short-run movements on which policy evaluation typically relies carry very little information, and the returns to innovation investment should be sought over horizons far longer than a programming cycle. And when the 245 regions are grouped into four innovation profiles rather than treated as a single population, the relationship that holds on average holds almost nowhere in particular: it is strong among leading and lagging regions, statistically absent in the largest group, and displaced by brand-led appropriation in a fourth group of 27 regions whose innovation is real but largely non-technological. Uniform innovation policy prescriptions and uniform managerial benchmarks are correspondingly difficult to justify. |
| Date: | 2026–08–15 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:jhr8t_v1 |
| By: | Dr Larissa Marioni; Mary O'Mahony; Patrick Serberis |
| Abstract: | This paper proposes a new approach to quantifying digital skill demands using job platform data, focusing on regions of the UK, and on industries identified by the UK government as of strategic importance. The analysis shows a concentration of the highest level digital skills required for innovation in regions around London known as the Golden Triangle, but skills required for 'business as usual' are important everywhere and growing over time. Job adverts requiring AI related skills are even more concentrated. Areas outside the Golden Triangle, especially in the second tier cities, are more likely to hire non‐graduates to fill their digital skills needs. High‐level digital skills are in much greater demand in strategic industries than in other sectors. |
| Keywords: | digital skills, regions, strategic industries, job platform data |
| JEL: | J6 O4 R1 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:nsr:niesrd:585 |
| By: | Richard Baldwin (IMD); Rebecca Freeman (Bank of England and CEP/LSE); Angelos Theodorakopoulos (Aston Business School and CBP/Aston) |
| Abstract: | This paper develops a new toolkit for analysing how global shocks affect the geographical and functional distribution of global value chains (GVCs) at the subnational level. Using the toolkit, which we call the shocks approach to indicator design, we derive a family of GVC indicators that distinguish between import and export‑side GVC exposure, direct (face‑value) and indirect (hidden exposure) linkages, and gross versus value‑added GVC trade flows. Applying the indicators to multi‑regional multi‑country input‑output data and analysing EU‑UK and EU‑China trade, we show that inferences about regional vulnerability depend critically on the type of exposure measured. The results highlight how global disruptions propagate unevenly across regions and provide a foundation for place‑based policies that strengthen resilience through targeted diversification and smarter supply‑chain monitoring. |
| Keywords: | Regional value chains;global value chains;value chain disruptions;input reliance;shocks;foreign exposure. |
| JEL: | D57 F13 F14 F15 F60 R15 |
| Date: | 2025–11–28 |
| URL: | https://d.repec.org/n?u=RePEc:boe:boeewp:023281 |
| By: | Daniel P. Gross; Bhaven N. Sampat; Hansen Zhang |
| Abstract: | Between 1945 and 1970, the U.S. Department of Defense was one of the country's largest funders of university research, and the most important in the physical sciences and engineering. Political pressures subsequently led to this funding declining nearly two-thirds by the mid-1970s and never fully recovering. We show that these cuts were felt across the U.S. research system, with ensuing declines in university scientists, PhD production, and research output. Early career scientists who were DoD-funded in 1970 were more likely than peers to leave universities, with many moving to industry. Though some became more likely to patent, in the aggregate, this appears to have reduced science-linked innovation in related technologies and compressed U.S. leadership in formerly DoD-driven fields. These effects extend to outcomes more closely related to military objectives: fewer PhDs entered the defense industrial base, and an initial increase in science-linked defense patenting in the most exposed technology areas gave way to a long-run decline. |
| JEL: | H56 I23 N42 N72 O31 O32 O33 O38 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35491 |
| By: | Yusuf Emre Akgunduz (Central Bank of Turkiye); Ayse Karasoy (Central Bank of Turkiye); Gokce Karasoy Can (Corresponding author. Bank of England); Elif Ozcan Tok (Bank of England) |
| Abstract: | This paper investigates how pre-pandemic investments in digital technologies influenced firm performance during the Covid-19 crisis and subsequent recovery, using comprehensive administrative data from Türkiye. We construct a novel firm-level digitalisation index based on firm-to-firm trade transactions, capturing a broad spectrum of digital investments including software, hardware, consultancy, and data services. Employing coarsened exact matching and a difference-in-differences framework, we find that more digitalised firms outperformed their less digitalised pairs during the pandemic and post-pandemic years. Specifically, digitalised firms exhibited 3% higher total assets, 4% higher net sales, and 2% higher employment, with even greater gains in profitability (0.44 percentage points), return on assets (0.42 percentage points), and export share (0.16 percentage points). To investigate plausible mechanisms consistent with these effects, we examine whether more digitalised firms expanded their trade networks, experienced lower worker turnover, and achieved higher productivity during the pandemic. We find that these firms added 3% more partners and traded over 2% greater distances with reduced labour churn, and higher productivity. These findings underscore the role of digitalisation in enhancing firm resilience and adaptability in the face of economic shocks. |
| Keywords: | Digitalisation;Covid-19;coarsened exact matching;differences-indifferences;firm performance |
| JEL: | C55 D22 O33 |
| Date: | 2026–05–22 |
| URL: | https://d.repec.org/n?u=RePEc:boe:boeewp:023306 |
| By: | Ruslana Datsenko (Bank of England); Martin B Holm (University of Oslo and CEPR) |
| Abstract: | Monetary policy is usually evaluated through aggregate output and inflation, with less attention to how it reallocates innovative investment across firms. Existing evidence shows that higher rates reduce innovation, but the firms driving this response remain unclear. Combining Norway’s research and development (R&D) survey with administrative data and narrative monetary shocks for 2001–18, we estimate heterogeneous firm responses. Contractionary policy reduces R&D most in high-growth firms with recent equity issuance, consistent with the asset-price channel of monetary transmission. Standard debt-based measures explain little heterogeneity. Monetary policy therefore has long-run real effects primarily by reducing R&D in high-growth innovative firms. |
| Keywords: | Monetary policy;innovation;productivity;research and development |
| JEL: | E52 O31 |
| Date: | 2026–06–26 |
| URL: | https://d.repec.org/n?u=RePEc:boe:boeewp:023314 |
| By: | Tom Coupé (University of Canterbury) |
| Abstract: | Fears that automation destroys more jobs than it creates have resurfaced with artificial intelligence. Using five Eurobarometer waves (1989–2024) covering 12 European countries, I examine the long-run evolution of perceptions of technological unemployment. Contemporary pessimism is not historically unusual, it was substantially higher in 1989, and especially 1992, than in 2024. Social divides have also changed. Pronounced educational and occupational differences in 1989 had largely disappeared by 2024. An Oaxaca–Blinder decomposition shows that changing population composition explains little of the decline. These findings show that both the level and the socioeconomic and national patterning of concerns about technological unemployment have changed substantially over time. |
| Keywords: | Artificial Intelligence, Attitudes, Employment |
| JEL: | J24 O33 J23 |
| Date: | 2026–08–01 |
| URL: | https://d.repec.org/n?u=RePEc:cbt:econwp:26/07 |
| By: | Gustavo De Souza; Andrew J. Fieldhouse; Karel Mertens; Ishan B. Nath; Valerie A. Ramey |
| Abstract: | This paper provides the first causal estimates of the global social returns to U.S. public R&D. We use a narrative identification strategy to quantify the effects of exogenous shocks to U.S. R&D appropriations on the dynamic TFP response of 69 foreign economies from 1980–2019. A U.S. R&D appropriations shock equal to 1 percent of the federal R&D capital stock raises foreign TFP by approximately 1 percent after 12 years. This response is driven primarily by nondefense rather than defense R&D and is concentrated in non-OECD economies. These patterns are most consistent with diffusion occurring through openly accessible scientific content, capital-embodied trade, and technological leapfrogging by economies further from the global frontier. A back-of-the-envelope calculation suggests that the global social returns to U.S. public nondefense R&D are roughly twice as large as the domestic returns, meaning the U.S. captures about half of these productivity benefits. |
| JEL: | E62 F62 O33 O38 O47 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35517 |
| By: | Fatima, Freeha; Ozen, Efsan Nas; Raju, Dhushyanth |
| Abstract: | This paper examines how artificial intelligence (AI) is reshaping Türkiye’s labor market by documenting patterns in skill supply, employer demand, and labor market adjustment using high-frequency digital labor market indicators from LinkedIn. The analysis focuses on the mechanisms through which AI-related change is associated with shifts in skills, hiring, occupational mobility, exposure to generative AI, and international migration. The evidence shows a relatively broad presence of foundational digital and AI literacy skills across sectors and demographic groups, alongside a persistent and increasing concentration of advanced AI engineering talent within a narrow set of occupations and industries. Measured skill penetration follows non-monotonic patterns over time, while frontier AI talent accumulates steadily, indicating a divergence between the breadth and depth of AI capability. Entry into AI roles often follows strongly path-dependent pathways, and employer demand signals for technical and AI-adjacent capabilities are only partially reflected in realized hiring, with no sustained positive divergence in AI-related hiring relative to overall labor demand. Potential exposure to generative AI varies systematically across sectors and demographic groups, with the balance between task augmentation and disruption differing across sectors rather than uniformly favoring one over the other. International migration emerges as a salient adjustment margin for highly specialized AI talent, operating alongside domestic reallocation mechanisms and influencing the availability of frontier skills within the domestic labor market. These patterns indicate that the central challenge associated with AI in Türkiye’s labor market lies not in whether AI-related capabilities will spread, but in how reallocation unfolds across skills, occupations, and workers over time. The findings highlight the role of skill formation systems, hiring and credentialing practices, occupational structures, and cross-border mobility in shaping the trajectory of labor market adju stment. The analysis also illustrates how digital labor market data can complement traditional sources by providing timely evidence on emerging skills, evolving demand, and early adjustment dynamics in middle-income economies navigating the AI transition. |
| Date: | 2026–04–01 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:hdnspu:209921 |
| By: | Hong Lee (Korea Institute for Industrial Economics and Trade) |
| Abstract: | This study analyzes the paradoxical mechanism by which one country’s protectionist industrial policy unintentionally redirects the path of technological innovation in its trading partners, often to the supplying country’s own disadvantage. Historical episodes, including the OPEC oil shock, the Soviet Union’s threats to natural gas supplies to the West, China’s rare earth embargo against Japan, and US semiconductor export controls against China, share a common pattern.<p> First, the supplying country restricts exports of the resources and technologies it holds, or manipulates their prices, inflicting a supply shock on the importing country. The relative price of the resource then surges, dramatically raising the incentives of firms and researchers in the importing country to develop substitute and workaround technologies. Private R&D combines with the government’s directed industrial policy (R&D subsidies, public procurement, and regulatory reform) to bring substitute technologies quickly to market.<p> Over the long run, the importing country’s dependence on the resource declines, and the supplying country’s bargaining power and market position erode. This study argues that a supply restriction strategy raises short-term bargaining power but can carry a self-defeating quality, eating away the supplier’s own market base. For the importing country, by contrast, a supply shock can become the occasion for a technological leap, and here the government’s directed industrial policies, R&D subsidies among them, act as complements that accelerate private innovation. |
| Keywords: | rare earths; rare earth elements; REEs; directed technological change; DTC; protectionism; industrial policy; supply chain security; resource weaponization; economic security |
| JEL: | F13 F52 L52 O33 |
| Date: | 2026–07–31 |
| URL: | https://d.repec.org/n?u=RePEc:ris:kietrp:023560 |