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on Technology and Industrial Dynamics |
| By: | Hanming Fang; Xian Gu; Hanyin Yan; Wu Zhu |
| Abstract: | We develop a high-precision classifier to measure artificial intelligence (AI) patents by fine-tuning PatentSBERTa on manually labeled data from the USPTO's AI Patent Dataset. Our classifier substantially improves the existing USPTO approach, achieving 97.0% precision, 91.3% recall, and a 94.0% F1 score, and it generalizes well to Chinese patents based on citation and lexical validation. Applying it to granted U.S. patents (1976-2023) and Chinese patents (2010-2023), we document rapid growth in AI patenting in both countries and broad convergence in AI patenting intensity and subfield composition, even as China surpasses the United States in recent annual patent counts. The organization of AI innovation nevertheless differs sharply: U.S. AI patenting is concentrated among large private incumbents and established hubs, whereas Chinese AI patenting is more geographically diffuse and institutionally diverse, with larger roles for universities and state-owned enterprises. For listed firms, AI patents command a robust market-value premium in both countries. Cross-border citations show continued technological interdependence rather than decoupling, with Chinese AI inventors relying more heavily on U.S. frontier knowledge than vice versa. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.10529 |
| By: | Nigar Hashimzade; Haoran Sun |
| Abstract: | Industrial policy has returned to the centre of economic governance, particularly in the high-tech sectors where positive network externalities in demand make market dominance self-reinforcing. This paper studies the welfare effects of an industrial policy targeting a sector with network externalities in a two-country model with strategic trade and R&D investment. We show how the welfare consequences of this policy are determined by the interaction between the strength of the externality, the type of R&D, and the degree of product differentiation between the home and the imported goods. When externalities are weak or the goods are close substitutes, the business-stealing effect produces a race to the bottom that dissipates more surplus than it creates. Under sufficiently strong externalities and weak substitutability or complementarity of the goods, industrial policy competition can make both countries simultaneously better off compared to the laissez-faire outcome because of the mutual business-enhancement effect. The case is stronger for the product innovation than for the process innovation, as the former directly affects the demand and triggers a stronger network effect than the latter which operates indirectly through the supply. Thus, network externalities create an opportunity for win-win industrial policies, but its realisation depends on the market structure and the nature of innovation. |
| Keywords: | industrial policy, network externalities, R&D subsidies, strategic trade, Cournot competition |
| JEL: | F13 H25 L13 O38 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12592 |
| By: | OKAMURO, Hiroyuki; NISHIMURA, Junichi |
| Abstract: | Public R&D support attracts both academic and practical attention. Recent studies investigate the combination of different R&D policy instruments (policy mix), focusing on R&D subsidies and tax credits (“hard support”), despite the variety of actual instruments covering “soft support, ” such as matching, mediation, and consultation services. Moreover, despite the decentralization of R&D policies in several countries, few studies have addressed place-based (city-level) R&D support with a variety of policy instruments. This study fills these gaps by estimating the effects of the local R&D policy mix, covering both hard and soft instruments, based on unique panel data of 146 Japanese cities for 18 years. Using panel fixed-effects estimations, we find that hard support has positive and significant effects on patent applications per person, while soft support significantly increases productivity. Finally, the coefficient of the interaction term of hard and soft support, estimated by the system GMM, suggests their complementarity |
| Keywords: | R&D, policy mix, place-based policy, municipality, innovation |
| Date: | 2026–03–24 |
| URL: | https://d.repec.org/n?u=RePEc:hit:hiasdp:hias-e-158 |
| By: | Ron Boschma; Simona Iammarino; Agnieszka Olechnicka |
| Abstract: | Despite recognition that interregional and international linkages promote the innovative capacity of regions, their role in regional innovation policy has received limited academic attention, resulting in challenges on how to incorporate them effectively into policy. We argue that interregional linkages are not generic in nature but shaped by capabilities that are place- and activity-specific. This is clearly shown in the strengths and weaknesses in three types of regional collaborations – foreign direct investment, co-invention, and co-publication – that we identified across five EU regions that prioritized automotives in their regional smart specialisation strategies. Using mixed-methods, we show that regions differ in the intensity and nature of interregional linkages, depending on their capabilities. Regions with a strong knowledge base in automotives manage to build effectively a range of strong connections that allow them to tap into complementary capabilities in other regions that support innovation and upgrading, in contrast to regions with a weak absorptive capacity. Consequently, interregional linkages can only be effectively integrated into innovation policies when they are place-based and activity-specific. We argue that, in the absence of targeted incentives to foster interregional connectivity, a substantial share of its potential for local innovation and regional upgrading remains untapped. |
| Keywords: | Regional strategy, International and interregional linkages, Foreign direct investment, Global value chains, Smart Specialisation Strategy, Place-based policy |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2603 |
| By: | Michele Battisti (University of Palermo); Antonio Francesco Gravina (University of Messina); Matteo Lanzafame (Asian Development Bank) |
| Abstract: | Structural transformation is a central driver of economic development, yet recent challenges such as premature deindustrialization have raised critical questions about whether low-income economies can still follow traditional growth paths that rely on manufacturing expansion to drive productivity gains. Building on a theoretical model that incorporates learning-by-doing mechanisms, sectoral employment reallocation, and factor accumulation, we examine labor productivity growth trajectories using a panel of 31 developing and emerging economies over 1960–2019, detecting a data-driven structural break in 1982 that fundamentally altered productivity growth dynamics. To account for the potential heterogeneity in how structural transformation affects different types of economies, we employ quantile-based techniques to examine effects across different segments of the productivity growth distribution, moving beyond conventional approaches that focus on average effects and may obscure important distributional patterns. The unconditional quantile regression results identify manufacturing expansion as a key driver of productivity growth, with employment reallocation in this sector delivering twice the productivity benefits for slower-growing economies compared to high performers. The quantile decomposition further shows that observable characteristics and unobservable factors became increasingly important determinants of productivity performance following the structural break, with substantial heterogeneity across the distribution. Moreover, we construct counterfactual scenarios to investigate what outcomes low-performing economies could have attained had they adopted the characteristics, returns to factors, and unobservable capabilities of top performers. These scenarios unveil substantial untapped growth potential, with bottom-quartile economies potentially achieving average productivity growth improvements of up to 2.7 percentage points |
| Keywords: | structural transformation;quantile analysis;decomposition;counterfactual scenarios |
| JEL: | O11 O14 O25 |
| Date: | 2026–04–07 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:022426 |
| By: | Nuriye Melisa Bilgin; Gianmarco Ottaviano |
| Abstract: | We study how digital infrastructure relaxes constraints on the diffusion and economic impact of artificial intelligence (AI). Using administrative data and a nationally representative enterprise survey from Turkey (2021-2024), we document significant disparities in AI adoption. Adoption is concentrated among large firms and in regions with high-speed broadband and proximity to data centers, particularly for software-intensive and cloud-based applications. To identify causal effects, we exploit the staggered expansion of Turkey's national natural gas pipeline network, which serves as a conduit for fiber-optic deployment. Because pipeline routing is determined by energy distribution priorities rather than digital demand, it provides plausibly exogenous variation in connectivity. Difference-in-differences estimates show that improved connectivity significantly increases AI adoption, particularly for software-intensive technologies and among small and medium-sized enterprises. Instrumental-variable estimates indicate that infrastructure-driven AI adoption raises labor productivity and export intensity while shifting labor composition toward ICT-related roles. These findings highlight digital infrastructure as a primary determinant of both the pace of AI diffusion and its resulting economic returns. |
| Keywords: | artificial intelligence, digital infrastructure, broadband, technology diffusion, firm productivity, cloud computing |
| Date: | 2026–04–15 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2172 |
| By: | Hiroshi IYETOMI; Yuta ARAI; Yuichi IKEDA |
| Abstract: | The ongoing geopolitical tensions between the United States and China are reshaping global production networks, particularly in the electronics industry, where East Asia serves as a central manufacturing hub. This study empirically examines Japan's position within the evolving East Asian electronics value chain using firm-level supply chain data. We construct a global supply chain network consisting of 15, 292 nodes (firms) and 27, 751 links (transactional relationships), centered on the electronics industry along with its two closely related sectors: the automotive and aerospace-defense industries. Our findings indicate that Japan continues to occupy an important upstream position, particularly in electronic components, manufacturing equipment, and precision instruments. However, a decline in the relative market share and network centrality of Japanese firms in the mainstream semiconductor industry suggests a departure from Japan's former dominance. In contrast, we identify a distinct automotive cluster in which Japanese firms remain highly competitive. The analysis also reveals an aerospace and defense community dominated by U.S. and European firms, characterized by limited participation from Japanese firms and the potential strategic exclusion of China. Furthermore, we uncover a separate cluster linking electronics, automation, and utilities, where Japanese firms play a prominent role with a 58% share. This cluster highlights a unique structural feature of industrial organization in Japan. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:26025 |
| By: | Giendl, Clara; Schwarzbauer, Wolfgang |
| Abstract: | This paper examines how regional economic diversity shapes economic resilience across European regions during major crises. Using sectoral diversity indicators at the NUTS-2 level, we analyze the impact of diversity on three dimensions of resilience: the depth of economic downturns, the strength of the initial recovery, and the duration of recovery, focusing on the 2008 financial crisis and the COVID-19 pandemic. Our results show that higher economic diversity consistently mitigates the severity of economic shocks, reducing the immediate decline in regional economic activity in both crises. However, this stabilizing effect comes with a trade-off: More diversified regions tend to exhibit weaker short-term recovery dynamics and longer recovery periods. In contrast, regions characterized by higher innovation intensity and productivity-driven specialization recover more quickly. These findings highlight the importance of balancing structural diversity and innovation. While diversity enhances shock absorption, innovation and specialization appear crucial for accelerating recovery. The paper contributes to the literature on regional resilience by providing EU-wide evidence across multiple crises and offers policy-relevant insights on how structural economic characteristics shape regional responses to shocks. |
| Abstract: | Wirtschaftskrisen treffen Regionen unterschiedlich stark. Warum kommen manche Regionen besser durch Krisen als andere? Das EcoAustria Research Paper untersucht, welche Rolle die wirtschaftliche Struktur - insbesondere die sektorale Diversität - für die Krisenresilienz von Regionen spielt. Auf Basis von Daten für europäische Regionen analysieren wir die Auswirkungen zweier großer Krisen: der Finanzkrise 2008 und der COVID-19-Pandemie. Dabei betrachten wir drei zentrale Dimensionen der Resilienz: die Tiefe des Einbruchs, der Beginn der ersten Erholung sowie die Dauer bis zur vollständigen Erholung. Die Ergebnisse zeigen ein klares Muster: Regionen mit einer stärker diversifizierten Wirtschaftsstruktur sind besser in der Lage, wirtschaftliche Schocks abzufedern. Da ihre Wertschöpfung auf mehrere Sektoren verteilt ist, sind sie weniger anfällig für Einbrüche in einzelnen Branchen. Allerdings geht diese Stabilität mit einem Zielkonflikt einher: Diversifizierte Regionen erholen sich tendenziell langsamer, während stärker spezialisierte Regionen häufig schneller und dynamischer aus der Krise herauswachsen. Eine wichtige Rolle spielt zudem Innovation. Regionen mit höherer Innovationskraft und Produktivität weisen schnellere Erholungsprozesse auf Insgesamt zeigen die Ergebnisse: Diversität und Innovation sind beide entscheidend für Resilienz, wirken jedoch unterschiedlich. Eine ausgewogene Kombination aus wirtschaftlicher Vielfalt und Innovationsstärke kann daher einen guten Schutz vor zukünftigen Krisen bieten. |
| Keywords: | regional economics, resilience, COVID-19, Economic and financial crisis 2008 |
| JEL: | R11 R15 N41 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:ecoarp:340006 |
| By: | Vladislav Morozov; Andrea Sy |
| Abstract: | Firms in denser areas are more productive, a pattern attributed to agglomeration economies and firm selection. To disentangle these two channels, the popular approach of Combes et al. (2012, ECTA) critically assumes that total factor productivity (TFP) distributions between denser and less dense areas are the same up to mean, variance, and left-tail truncation. We empirically validate this assumption using Spanish administrative firm-level data and recent econometric methods adapted to noisy TFP estimates. Our results find that TFP distributions are indeed statistically identical up to these parameters, validating the use of such productivity decompositions. Furthermore, using only the mean and variance is sufficient to capture differences for all sectors. Accordingly, the productivity advantage of cities may be entirely due to agglomeration rather than stronger selection, suggesting that policymakers should focus on policies targeting agglomeration. Finally, our approach extends to related contexts like differences in worker skill distributions. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.13188 |