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on Technology and Industrial Dynamics |
| By: | Storm, Eduard; Gonschor, Myrielle; Schmidt, Marc Justin |
| Abstract: | We study how artificial intelligence (AI) affects workers' earnings and employment stability, combining German job vacancy data with administrative records from 2017-2023. Identification comes from changes in workers' exposure to local AI skill demand over time, instrumented with national demand trends. We find no meaningful displacement or productivity effects on average, but notable skill heterogeneity: expert workers with deep domain knowledge gain while non-experts often lose, with returns shaped by occupational task structures. We also document AI-driven reinstatement effects toward analytic and interactive tasks that raise earnings. Overall, our results imply distributional concerns but also job-augmenting potential of early AI technologies. |
| Keywords: | AI, Online Job Vacancies, Skill Demand, Worker-level Analysis, Employment, Earnings, Expertise |
| JEL: | D22 J23 J24 J31 O33 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:rwirep:333893 |
| By: | Maczulskij, Terhi |
| Abstract: | Abstract This paper examines how firms’ innovation activity responds to product- and destination-specific export demand shocks in their export markets. I draw on unique administrative data for Finnish manufacturing firms from 1999 onwards, matched with national customs records, patent data, and innovation and R&D surveys. The analysis reveals that positive export demand shocks significantly increase patenting activity and the likelihood of introducing new product innovations, while negative shocks reduce patenting and exports. The study finds that these innovation responses are dynamic, with patent applications rising in the short term and granted patents materializing over longer horizons. Heterogeneity analysis shows that more productive and financially stronger firms benefit disproportionately from export demand expansions. This pattern suggests that financial constraints may limit the ability of firms to adopt new innovations even as they expand production. |
| Keywords: | Export demand shock, Firm-level, Innovation, Manufacturing |
| JEL: | F14 O19 O30 |
| Date: | 2025–12–22 |
| URL: | https://d.repec.org/n?u=RePEc:rif:wpaper:134 |
| By: | Jean Xiao Timmerman |
| Abstract: | This paper examines the evolution of artificial intelligence (AI) patent rates (i.e., the number of AI patents/number of firms of the same type) and concentration metrics (i.e., the Herfindahl-Hirschman Index (HHI) and Gini coefficient) among financial market participants from 2000 to 2020. It documents the historical trajectories of AI innovation for regulated banking entities and less-regulated firms, revealing that nonfinancial companies exhibit the highest baseline AI patent rate, while banks show the highest growth in AI patent rate over time. Banks have the highest HHI, and nonfinancial companies have the highest Gini coefficient, suggesting that a small number of banks dominate AI innovation and the distribution of AI innovation at nonfinancial firms � though higher in number � is highly skewed toward a subset of players. These findings indicate that the AI technological gap between small and large banks may be widening and the diversity of nonfinancial companies serving as third-party AI service providers may be limited. |
| Keywords: | Artificial intelligence; Banking; Financial innovation; Patents; Regulatory perimeter; Technological change |
| JEL: | G21 G23 G28 O31 O33 |
| Date: | 2025–12–12 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:2025-104 |
| By: | Nguyen, Thao Trang (RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn); Domini, Giacomo; Grazzi, Marco; Moschella, D.; Treibich, Tania (RS: GSBE MORSE, Macro, International & Labour Economics) |
| Abstract: | We examine the effects of adopting automation technologies on the export performance of French manufacturing firms during the 2002–2019 period. Adoption is identified through imports of automation-related capital goods, and its effects are estimated by means of a staggered difference-in-differences method. Our results indicate that automation significantly improves export outcomes, such as export value, the export to sales ratio and particularly the number of destination countries. However, its effect on the number of exported products is limited. These results are primarily driven by single-product firms, which expand their product portfolios, often toward more complex products, and increase their presence in high-income countries. Multi-product firms, instead, tend to streamline their product offerings while targeting low-income markets. These findings underscore the distinct mechanisms of learning effects and resource reallocation that shape automation strategies and drive export success. |
| JEL: | L11 L22 L25 O14 |
| Date: | 2025–11–28 |
| URL: | https://d.repec.org/n?u=RePEc:unm:unumer:2025028 |
| By: | Rodríguez-Pose, Andrés; Lee, Neil; Xiang, Leiboyu |
| Abstract: | This paper presents the first systematic city‐level mapping of global scientific talent, analysing the top 200, 000 star scientists across 3635 cities worldwide annually between 2019 and 2023. We use a novel Knowledge Generation Index (KGI) that combines researcher quantity with research impact to reveal extreme spatial concentration in knowledge production. Just four cities—New York, Boston, London and the San Francisco Bay Area—host 12% of the world's star scientists, while much of the Global South remains virtually excluded from frontier research. Beijing's ascent into the global top 10 represents a rare challenge to established hierarchies. Our analysis uncovers striking disciplinary variations. Resource‐intensive fields like clinical medicine cluster heavily, and traditionally dispersed disciplines are increasingly gravitating towards major hubs. Despite these differences, concentration is intensifying across most scientific fields. Even the pandemic's remote collaboration experiment failed to level the playing field. Established innovation centres continued strengthening their advantages while peripheral regions fell further behind. Overall, we find that geography remains destiny, with profound implications for innovation policy confronting widening spatial inequalities in global scientific capacity. |
| Keywords: | geography of knowledge; innovation agglomeration; spatial inequality; star scientists |
| JEL: | N0 |
| Date: | 2025–12–17 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130377 |
| By: | Inmaculada C. Alvarez; Javier Barbero; Luis Orea; Andres Rodriguez-Pose |
| Abstract: | Most studies of institutional quality and regional growth assume uniform effects across territories. However, this may mask crucial regional heterogeneity, with direct policy implications. We use a latent class framework applied to 230 EU regions over 2009-2017 to identify institution-driven regional parameter groups, and to examine both average effects and catching-up effects associated with changes in the institutional environment. We demonstrate that institutional quality generates highly variable returns to investment in physical capital and innovation. Nordic and Central European regions show highest returns to physical capital and R&D investment, whereas less-developed regions benefit most from education spending. Crucially, we find that improving government quality not only raises average returns but also promotes territorial cohesion. By contrast, regional autonomy shows limited impact on returns. Our findings challenge the one-size-fits-all approach to cohesion policy and indicate that cohesion policy should explicitly promote institutional improvements in addition to capital deployment. |
| Keywords: | Institutional quality, European funds, investment, regional development |
| JEL: | O43 E61 H54 R11 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2537 |
| By: | Bisi, Davide; Landini, Fabio; Rinaldi, Riccardo |
| Abstract: | The interaction between organised employee representation (ER) and firms' engagement in the green transition remains insufficiently understood. Theoretically, two opposing mechanisms may operate. In the bargaining view, representation can slow green investments by increasing adjustment costs and exposing firms to rent-seeking pressures. In contrast, the employee voice perspective holds that ER enables sustainability by facilitating information exchange, eliciting workers' environmental preferences, and supporting joint problem-solving when organisational adaptation is required. We test these predictions using survey and administrative data from nearly 2, 000 firms in Emilia-Romagna. Firms with ER are systematically more likely to pursue green investments, especially in climate mitigation, water use, circularity, and pollution prevention. These results also hold when accounting for the endogeneity of ER via IV. Consistent with the voice mechanism, the association between ER and green investments is stronger in firms employing younger and more educated workers, who are more likely to hold proenvironmental preferences and contribute specialised knowledge relevant for organisational change. Taken together, our findings challenge the view that organised labour inhibits the green transition. Instead, ER emerges as a strategic policy lever that can foster decarbonisation pathways that are technologically feasible, socially negotiated, and democratically anchored at the workplace level. |
| Keywords: | worker voice, employee representation, sustainability, climate change, green investments |
| JEL: | J50 O33 Q50 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1699 |
| By: | M. Sadra Heydari; Zafer Kanik; Santiago Montoya-Bland\'on |
| Abstract: | We introduce heterogeneous R&D productivities into an endogenous R&D network formation model, generalizing the framework in Goyal and Moraga-Gonzalez (2001). Heterogeneous productivities endogenously create asymmetric gains for connecting firms: the less productive firm benefits disproportionately, while the more productive firm exerts greater R&D effort and incurs higher costs. For sufficiently large productivity gaps between two firms, the more productive firm experiences reduced profits from being connected to the less productive one. This overturns the benchmark results on pairwise stable networks: for sufficiently large productivity gaps, the complete network becomes unstable, whereas the Positive Assortative (PA) network -- where firms cluster by productivity levels -- emerges as stable. Simulations show that the PA structure delivers higher welfare than the complete network; nevertheless, welfare under PA formation follows an inverted U-shape in the fraction of high-productivity firms, reflecting crowding-out effects at high fractions. Altogether, a counterintuitive finding emerges: economies with higher average R&D productivity may exhibit lower welfare through (i) the formation of alternative stable R&D network structures or (ii) a crowding-out effect of high-productivity firms. Our findings highlight that productivity-enhancing policies should account for their impact on endogenous R&D alliances and effort, as such endogenous responses may offset or even reverse the intended welfare gains. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.23337 |
| By: | Zoltan Elekes; Emelie Hane-Weijman |
| Abstract: | Labour mobility plays a central role in shaping local economies. Substantial contributions have been made in the Evolutionary Economic Geography (EEG) literature to understand the dynamics and geographies of local economies. A key contribution of EEG research has been the emphasis on both the supply of work and the demand for workers, raising questions about skill matching. Building on this tradition, the aim of this chapter is twofold. First, we aim to summarize the contributions on labour mobilities and skill relatedness made by EEG. Second, we argue that the micro perspective in EEG could be enriched by focusing more on the heterogeneity of workers with respect to, for instance, gender, age or ethnicity. We then outline a future research agenda within EEG that is more attentive to the diversity of workers by exploring (1) the assortativity of skill relatedness networks, (2) the bounded mobilities of workers and (3) dimensions of proximity beyond the cognitive. |
| Keywords: | labour mobility, skill relatedness, local labour markets, spatial division of labour, skill mismatch, worker heterogeneity |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2541 |
| By: | Iacopo Maria Taddei; Giorgia Giovannetti |
| Abstract: | Industrial indicators display an inverted U-shaped relationship with income levels across both developed and developing economies. However, there is growing evidence that the deindustrialization process is accelerating in less developed countries, giving rise to the phenomenon of premature deindustrialization. This process has been shown to be one of the main drivers of growth slowdowns, particularly in middle-income economies, preventing countries from catching up and leaving them trapped in the so-called middle-income trap. Some East Asian countries, such as South Korea and Taiwan, have nevertheless managed to avoid this outcome by engaging non-linearly in global value chains, following a pattern often referred to as the ‘in–out–in again’ hypothesis. This paper provides an empirical assessment of how this alternative industrialization pathway can shield economies from the risk of premature deindustrialization, sustaining growth in middle-income countries. Using a panel of 47 emerging and developing economies over the period 1995–2020, we examine how this discontinuous engagement in global trade affects manufacturing employment and output shares, as well as countries’ capacity to move up the value chain and export more complex products. Our findings suggest that the ‘in-out-in again’ global value chain insertion pattern has been an effective mechanism for avoiding the middle-income trap in East and South Asian economies, while offering little indication of its role in preventing premature deindustrialization. |
| Keywords: | Premature deindustrialization; middle-income trap; GVC; in-out-in again. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:cca:wpaper:752 |
| By: | David Rodríguez-González (Department of Economics, Universidad EAFIT (Colombia)); Elena Huergo (ICAE – Department of Economic Analysis, Universidad Complutense de Madrid (Spain)); Mery Patricia Tamayo (Department of Economics, Universidad EAFIT (Colombia)) |
| Abstract: | This paper examines how the strength of intellectual property rights (IPR) affects offshoring between countries at different development stages. Using a panel dataset covering offshoring flows between 60 origin and 76 destination countries from 2000–2011—measured through intra-industry trade in intermediate inputs—we estimate several econometric models addressing heterogeneity, zero flows, endogeneity, and trade persistence. We find that stronger IPR protection reduces a country’s outward offshoring, especially in developing economies, while it increases inward offshoring, particularly in high-tech industries and when the destination is developing. These results show the varied role of IPR in shaping global production networks and suggest that strengthening IPR—especially in developing countries—can enhance participation in global value chains and promote technology transfer. |
| Keywords: | Offshoring flows, IPR, Development, Technology transfer. |
| JEL: | F14 F23 O34 O38 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ucm:doicae:2508 |
| By: | Filippo Bontadini; Valentina Meliciani; Maria Savona; Ariel Wirkierman |
| Abstract: | The aim of this paper is to quantitatively assess the propagation of supply shocks across European regions, triggered by the COVID-19 pandemic and diffused through Global Value Chains (GVCs). By taking advantage of the cross-country variation in policy responses to the pandemic, as well as the heterogeneity in regional productive structures, we document how downstream transmission of shocks via GVC-induced backward linkages yields differences in terms of regional resilience. By combining and adapting datasets at the NUTS2 level, classifying EU regions according to the risk of falling into a development trap, and embedding inter-regional, inter-industry indicators in a regression model estimated with a local projection method, we show that regional responses of real value added to foreign (i.e., inter-country) and domestic (i.e., intra-country yet inter- and intra-regional) shocks are far from homogeneous. The nuanced picture emerging from our findings warns against withdrawing from GVCs as an attempt to insulate from foreign shocks, as this might hamper the very forces that allow dynamic regions to withstand them. |
| Keywords: | global value chains, inter-regional connectivity, regional economic resilience, COVID-19 pandemic supply shocks, regional development trap risk |
| JEL: | C32 C67 F62 R11 R15 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12316 |