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on Technology and Industrial Dynamics |
| By: | Nicol\`o Barbieri; Kerstin H\"otte; Peter Persoon |
| Abstract: | Green patents are a key indicator to track technological efforts aimed at fighting climate change. Using an original dataset that merges different Patstat releases, we identify three mechanisms that may bias green patent statistics, potentially leading to contradictory findings. First, patent reclassifications due to updates in (green) classification codes result in an 9.2\% increase in the number of green patents when using the most recent classification structure. Second, delays in the adoption of the Cooperative Patent Classification (CPC) system introduce regional biases, as approximately 10\% of green patents from late-adopting countries remain undetected in less recent versions of the database. Third, we provide evidence that quality thresholds used to identify high-value inventions significantly shape observed trends in green patenting. Analyzing these mechanisms, our paper reveals that in many studies a substantial number of green patents is systematically overlooked, with the strongest effects observed for recent years and patents originating from Asian patent offices. These findings lead to relevant policy implications. Our results indicate not only that the global rate of green innovation has accelerated, but also that its epicenter has shifted, with an increasing share of green patents originating from emerging technological leaders, particularly in Asia. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2503.21310 |
| By: | Carolina Castaldi; Milad Abbasiharofteh; Sergio Petralia |
| Abstract: | The sustainability transition is high on the European agenda, with an emerging understanding that focusing on green technologies is not enough to achieve disruptive sustainability. An overall green transformation of current systems of production and consumption also requires market formation processes whereby green markets become viable economic opportunities for regions to specialize in. In this study, we draw on insights from evolutionary economic geography and geography of transitions to understand how regions develop green market specializations. To do so, we investigate two key sets of factors. First, we consider the evolutionary capability development process whereby new specializations emerge from existing related regional capabilities, in a path-dependent way. Second, we account for green public procurement initiatives to capture path-creation efforts in the form of deliberate regional policy directed towards green market formation. Our empirical analysis focuses on European regions in the period 2000-2020. We employ original trademark-based metrics to capture regional specializations in green markets and combine them with patent data to construct relatedness linkages between technologies and markets. Our results reveal that only a few regions have been able to develop specializations in green markets. We find that both prior capabilities in related technological domains and markets are positively associated with the emergence of these regional specializations. In addition, we also find that green public procurement is positively associated with the emergence of regional green market specializations. Our findings bear relevance for policy and research alike. |
| Keywords: | sustainability; regions; green markets; relatedness; public procurement; trademarks; patents |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2512 |
| By: | Federico Riccio; Jacopo Staccioli; Maria Enrica Virgillito |
| Abstract: | Does labour-saving technological change pose a threat to European employment, and if so, to what extent? This study investigates the degree of employment exposure to labour-saving technological change across NUTS-2 regions in Europe. We construct a cross-walked metric between the SOC and ISCO classification systems to adapt the direct measure of occupational exposure developed by Montobbio et al. (2024) for the US economy and apply it to the European context. This methodology enables us to generate detailed insights into the exposure of European occupations by leveraging the similarity rankings between technological classifications in the USPTO (CPCs) and task descriptions. To evaluate the transmission from occupational exposure to employment outcomes, we utilise data from the European Structure of Earnings Survey (EU-SES), thereby constructing exposure indices at both sectoral and regional levels. Finally, we examine the industrial and geographical diffusion of labour-saving technological change in recent years and provide robust econometric evidence indicating that low-wage regions, as well as deindustrialising areas heavily integrated into global value chains, are disproportionately vulnerable to the threat of substitution. |
| Keywords: | regional disparities, manufacturing downgrading, automation, global value chains |
| Date: | 2025–05–07 |
| URL: | https://d.repec.org/n?u=RePEc:ssa:lemwps:2025/19 |
| By: | Hunt, Jennifer; Cockburn, Iain; Bessen, James |
| Abstract: | Using our own data on artificial intelligence publications merged with Burning Glass vacancy data for 2007-2019, we investigate whether online vacancies for jobs requiring AI skills grow more slowly in US locations farther from pre-2007 AI innovation hotspots. We find that a commuting zone which is an additional 200km (125 miles) from the closest AI hotspot has 17% lower growth in AI jobs' share of vacancies. This is driven by distance from AI papers rather than AI patents. Distance reduces growth in AI research jobs as well as in jobs adapting AI to new industries, as evidenced by strong effects for computer and mathematical researchers, developers of software applications, and the finance and insurance industry. 20% of the effect is explained by the presence of state borders between some commuting zones and their closest hotspot. This could reflect state borders impeding migration and thus flows of tacit knowledge. Distance does not capture difficulty of in-person or remote collaboration nor knowledge and personnel flows within multi-establishment firms hiring in computer occupations. |
| Keywords: | technological change; economic geography; growth; technology adoption and diffusion |
| JEL: | O33 R12 |
| Date: | 2024–10–01 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:126840 |
| By: | Kristina McElheran; Mu-Jeung Yang; Zachary Kroff; Erik Brynjolfsson |
| Abstract: | We examine the prevalence and productivity dynamics of artificial intelligence (AI) in American manufacturing. Working with the Census Bureau to collect detailed large-scale data for 2017 and 2021, we focus on AI-related technologies with industrial applications. We find causal evidence of J-curve-shaped returns, where short-term performance losses precede longer-term gains. Consistent with costly adjustment taking place within core production processes, industrial AI use increases work-in-progress inventory, investment in industrial robots, and labor shedding, while harming productivity and profitability in the short run. These losses are unevenly distributed, concentrating among older businesses while being mitigated by growth-oriented business strategies and within-firm spillovers. Dynamics, however, matter: earlier (pre-2017) adopters exhibit stronger growth over time, conditional on survival. Notably, among older establishments, abandonment of structured production-management practices accounts for roughly one-third of these losses, revealing a specific channel through which intangible factors shape AI’s impact. Taken together, these results provide novel evidence on the microfoundations of technology J-curves, identifying mechanisms and illuminating how and why they differ across firm types. These findings extend our understanding of modern General Purpose Technologies, explaining why their economic impact—exemplified here by AI—may initially disappoint, particularly in contexts dominated by older, established firms. |
| Keywords: | Artificial Intelligence, General Purpose Technology, Manufacturing, Organizational Change, Productivity, Management Practices |
| JEL: | D24 O33 M11 L60 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:cen:wpaper:25-27 |
| By: | Pardy, Martina |
| Abstract: | his article examines the extent to which the presence of multinational enterprises (MNEs) influences the concentration of innovation among patenting firms within US states from 1976 to 2010. Merging patent and regional socioeconomic data, this study explores the effects within 50 US states over more than three decades using Ordinary-Least-Square and Instrumental Variable estimations. It shows that MNEs significantly contribute to the concentration of patenting activity, an effect predominantly driven by domestic-owned MNEs. The impact differs across space: states with a higher share of MNEs experience a sharper increase in patenting concentration. Crucially, it is the non-MNE firms that feel the squeeze the most, with those in the middle of the patenting hierarchy producing fewer patents when domestic MNEs ramp up their activity. This suggests that economic globalisation, while enhancing innovation opportunities for some, reinforces competitive pressures and barriers for others. These findings offer a new perspective on the forces shaping regional innovation dynamics, highlighting the role of MNEs in both amplifying innovation gains and exacerbating disparities in knowledge production. |
| Keywords: | globalisation; multinational enterprises; innovation; concentration; regional development |
| JEL: | J1 |
| Date: | 2025–07–31 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:127983 |
| By: | John Ham; Brian Quistorff; Bruce A. Weinberg |
| Abstract: | We draw on a recombinant view of innovation, where being in a new location and/or multiple locations leads to exposure to novel combinations of ideas that increase the creativity of top scientists. Using a rich, unique dataset we helped assemble, we estimate the empirical relationship between being in a new location and/or multiple locations and the expected interval before an eventual Nobel laureate (ENL) commences their prize-winning work. We find that being in a new location and in multiple locations are substantially and significantly associated with a shorter expected interval before ENLs commence their prize-winning work. |
| JEL: | C41 O31 O38 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33579 |
| By: | Aaron B. Flaaen; Fariha Kamal; Eunhee Lee; Kei-Mu Yi |
| Abstract: | Global value chains (GVC) are a pervasive feature of modern production, but they are hard to measure. Using confidential microdata from the U.S. Census Bureau, we develop novel measures of the linkages between U.S. manufacturing establishments’ imports and exports. We document three new GVC patterns. First, for every dollar of exports, imported inputs represent 13 cents in 2002 and 20 cents by 2017, substantially higher than what aggregate data suggests. Second, we find strong complementarities between input and output markets reflected in “round-trip” trade linkages where an establishment sources inputs from and exports output to the same country. Third, we find a strong positive association between regional trade agreements and GVC trade flows. The aggregate data used to build global input-output tables requires proportionality assumptions that we find mute these relationships. Finally, with a simple model, we show that the round-trip results are consistent with a notion of firm and country-specific fixed costs that are at least partially common between sourcing (imports) and foreign sales (exports). |
| JEL: | F1 F14 O51 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33724 |
| By: | Andrea Lanteri; Adriano A. Rampini |
| Abstract: | We analyze the adoption of clean technology by heterogeneous firms subject to financing constraints. In the model, capital goods differ in terms of their energy needs and age. In equilibrium, cleaner and newer capital requires more financial resources. Therefore, financial constraints induce an endogenous pattern in clean technology adoption: Financially constrained, smaller firms optimally invest in dirtier and older capital than unconstrained, larger firms. The model is consistent with the empirical patterns of technology adoption we document using data on commercial shipping fleets. We use a calibrated version of our model to simulate the aggregate transition dynamics to cleaner technology. |
| JEL: | E22 G31 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33545 |