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on Technology and Industrial Dynamics |
| By: | Antonin Bergeaud; Ruveyda Nur Gozen; John Van Reenen |
| Abstract: | We introduce a methodology to measure cross-country trends in innovation capability - “technological trajectories” and implement this on a new rich dataset covering patents between 1836 and 2016 across multiple countries. Intuitively, trajectories are revealed by a country’s sustained increases in patenting across multiple patent offices. We first describe the data patterns, showing the relative decline of the UK, and the rise first of the US and Germany, and then later of Japan and China. We then econometrically estimate trajectories on (i) the post-1902 period for France, Germany, Japan, the UK and US, and (ii) the post-1960 period for a wider sample of 40 countries. Our trajectories are strongly positively correlated with Total Factor Productivity growth, and also (but less strongly) associated with the growth of labour productivity and capital intensity. We show that future trajectories are predicted by a country’s initial levels of R&D, education and defence spending, classic drivers of innovation in modern growth theory. |
| JEL: | O31 O33 O34 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34760 |
| By: | Jingni Zhang; David Popp |
| Abstract: | Electric vehicles (EVs) are crucial for cutting transportation emissions, yet the policy drivers of EV innovation remain underexplored. This study analyzes firm-level panel data on EV and battery patents, covering more than 4, 000 firms across 19 countries from 2010 to 2021, to assess how these policy tools and their interactions in different time horizons influence innovative activity. We test the effects of individual policy instruments that either raise demand for EVs or support the development of EV technologies. Stringent fuel-economy standards, financial incentives, adoption targets, and public R&D investments each significantly increase patenting in EV and battery technologies. Moreover, long-term EV targets amplify the innovative impact of public R&D and standards while diminishing the marginal effect of short-term price signals. The results suggest that governments can accelerate clean automotive innovation by combining long-term adoption commitments with sustained R&D investment or strong performance standards, and by managing these instruments as a coordinated policy portfolio rather than as separate tools. The study contributes cross-country, firm-level evidence that links policy design to the direction of clean technology innovation. |
| JEL: | O31 O38 Q55 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34763 |
| By: | Antonin Bergeaud; Julia Schmidt; Riccardo Zago |
| Abstract: | Technology standards are defined by national and international organizations to select and disseminate the best technologies and practices. Using a measure of patent quality and a novel measure of the semantic proximity between patents and standards documents, this paper exploits the standardization process to disentangle the respective contributions of innovation and diffusion to firm value. Producing a patent increases a firm’s book value by 0.8% over the first eight years following the patent grant. However, this value deteriorates when the patent is not incorporated into a standard and diffused. In contrast, only firms whose patent specifications are included in a standard experience an additional increase in firm value of about 0.4% thereafter. Similar results are obtained when examining firms’ market-value and net worth. Finally, by studying firm-level productivity and markups, we show that the value gains associated with innovation stem from productivity improvements, whereas those associated with diffusion arise from rent extraction. |
| Keywords: | Standardization, Patents, Innovation, Firm Value |
| JEL: | G30 O31 O33 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:bfr:banfra:1031 |
| By: | Ajay K. Agrawal; John McHale; Alexander Oettl |
| Abstract: | The task-based approach has become the dominant framework for studying the labor-market effects of artificial intelligence (AI), typically emphasizing the replacement of human workers by machines. Motivated by growing empirical evidence that contemporary AI is more often used as a tool that augments workers, this paper develops two related task-based models in which AI enhances worker productivity without automating tasks. Abstracting from capital, we develop a pair of related task-based models that examine how technological progress in AI that provides new tools to augment workers affects aggregate productivity and wage inequality. Both models emphasize the role of human capital in intermediating the effects of AI-related technological shocks. In the first model, AI use requires specialized expertise, and technological progress expands the set of tasks for which such expertise is effective. We show that a larger supply of AI expertise amplifies the productivity gains from improvements in AI technology while attenuating its adverse effects on wage inequality. The second model focuses on non-AI skills, allowing AI tools to alter the set of tasks that workers can perform given their skills. In equilibrium, workers allocate across tasks in response to wages, generating an endogenous distribution of skills across the task space. A central result is that aggregate productivity and wage inequality depend on different global properties of this equilibrium distribution: productivity is particularly sensitive to thinly staffed tasks that create bottlenecks, while wage inequality is driven by the concentration of workers in a narrow set of tasks. As a result, improvements in AI tools can induce non-monotonic co-movement between productivity and inequality. By linking these mechanisms to multidimensional human capital---including AI expertise and higher-order non-AI skills---the paper highlights the role of education and training policies in shaping the economic consequences of AI-driven technological change. |
| JEL: | J24 O33 O41 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34781 |
| By: | Vasilios Kanellopoulos |
| Abstract: | The present paper examines the effect of R&D spillovers on regional innovation in Greece over the 2002-2010 period. The approach taken goes beyond a regional knowledge production function and draws possible explanations from a more extensive pool of R&D related and regional structural variables. Having employed game theory techniques in order to describe the licensing of the patents through royalties and derived the subgame perfect Nash equilibrium under a Stackelberg duopoly, the results obtained accord with findings of previous studies when it comes R&D expenditure related variables and further suggest that the role of highly-qualified employment is instrumental in promoting regional innovation. The results also suggest the benefits of synergies between R&D personnel in manufacturing and other measures of highly-qualified employment as well as R&D expenditure of the public sector and employment in manufacturing business R&D for regional innovation. |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2602.02274 |
| By: | Bastianin, Andrea; Castelnovo, Paolo; Frattini, Federico Fabio; Vona, Francesco |
| Abstract: | This paper develops a novel text-based approach to identify CRM-saving innovation using patent data and studies how mineral price signals shape the direction of technological change. Using patent data from 1978–2020, we distinguish technologies that rely on CRMs from those that explicitly aim to reduce their use through efficiency improvements, substitution, or recycling. We provide evidence consistent with the induced-innovation hypothesis: higher mineral prices reallocate inventive effort toward CRM-saving technologies, while having little effect on CRM-reliant innovation. The response strengthens over time and is especially pronounced for battery minerals and rare earth elements. These findings are robust to alternative specifications and are reinforced by complementary identification strategies, including a falsification test and the use of plausibly exogenous supply-side price variation. |
| Keywords: | Climate Change, Environmental Economics and Policy, Resource/Energy Economics and Policy, Sustainability |
| Date: | 2026–01–30 |
| URL: | https://d.repec.org/n?u=RePEc:ags:feemwp:391378 |
| By: | Ryan Stevens |
| Abstract: | Generative AI has the potential to transform how firms produce output. Yet, credible evidence on how AI is actually substituting for human labor remains limited. In this paper, we study firm-level substitution between contracted online labor and generative AI using payments data from a large U.S. expense management platform. We track quarterly spending from Q3 2021 to Q3 2025 on online labor marketplaces (such as Upwork and Fiverr) and leading AI model providers. To identify causal effects, we exploit the October 2022 release of ChatGPT as a common adoption shock and estimate a difference-in-differences model. We provide a novel measure of exposure based on the share of spending at online labor marketplaces prior to the shock. Firms with greater exposure to online labor adopt AI earlier and more intensively following the shock, while simultaneously reducing spending on contracted labor. By Q3 2025, firms in the highest exposure quartile increase their share of spending on AI model providers by 0.8 percentage points relative to the lowest exposure quartile, alongside significant declines in labor marketplace spending. Combining these responses yields a direct estimate of substitution: among the most exposed firms, a \$1 decline in online labor spending is associated with approximately \$0.03 of additional AI spending, implying order-of-magnitude cost savings from replacing outsourced tasks with AI services. These effects are heterogeneous across firms and emerge gradually over time. Taken together, our results provide the first direct, micro-level evidence that generative AI is being used as a partial substitute for human labor in production. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2602.00139 |
| By: | Diego Ocampo-Corrales (AQR-IREA, University of Barcelona); Rosina Moreno (AQR-IREA, University of Barcelona) |
| Abstract: | This paper investigates the role of regions’ recombinatorial technological capacity in shaping the technological space. To do so, we identify novel combinations of technologies and track their evolution by tracing all subsequent inventions that incorporate the same combination. Building on the concepts of relatedness and geographical proximity, we focus on the relevance of the technological antecedents of a pair of technologies combined for the first time in determining their success. This is due through the estimation of the likelihood of a new technological combination eventually becoming embedded within the broader knowledge space. Using patent data from 1976 to 2022 in the case of the European regions, we find strong evidence that a higher degree of relatedness between the technological antecedents of the two combined technologies significantly increases the likelihood that the combination will be reused in future inventions. Additionally, we find that the success of a new combination also benefits from the presence of dissimilar knowledge—not directly involved in the combination’s antecedents but accessible within the surrounding technological environment. In these cases, the greater the relatedness between the new invention’s antecedents and the broader regional knowledge base, the more likely it is to generate a high number of follow-on inventions and contribute meaningfully to the formation of the technological space |
| Keywords: | New combination of technologies, Regional innovation, European regions, Recombination capacity, Knowledge space, Technological antecedents JEL classification:O18, O31, O33, R11 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:aqr:wpaper:202511 |
| By: | Mazen Fathy (Egypt Impact Lab); Chahir Zaki (Laboratoire d’Economie d’Orleans) |
| Abstract: | Despite rising levels of Global Value Chains (GVC) integration in several emerging and developing economies, the latter failed to experience a significant structural change. Thus, this paper examines how participating in global supply chains can have implications on labor reallocation in the economy, and to what extent technological advances can alter this effect. To do that, we use the EORA database and calculate structural change variables. Moreover, we control for the endogeneity between these two variables. Our main findings show that overall, global value chains participation has an insignificant effect on structural change. This result holds for different measures of GVC (backward and forward) and of structural change (static and dynamic). Several mechanisms explain the missing link between GVC and structural change, namely their inability to create enough jobs, the increase in capital intensive industries, the dominance of natural resources and the skill bias technological change. |
| Date: | 2025–06–20 |
| URL: | https://d.repec.org/n?u=RePEc:erg:wpaper:1778 |
| By: | Michael Balzer; Adhen Benlahlou |
| Abstract: | This paper develops a theory of scientific and technological peer effects to study how individuals' productivity responds to the behavior and network positions of their collaborators across both scientific and inventive activities. Building on a simultaneous equation network framework, the model predicts that productivity in each activity increases in a variation of the Katz-Bonacich centrality that captures within-activity and cross-activity strategic complementarities. To test these predictions, we assemble the universe of cancer-related publications and patents and construct coauthorship and coinventorship networks that jointly map the collaboration structure of researchers active in both spheres. Using an instrumental-variables approach based on predicted link formation from exogenous dyadic characteristics, and incorporating community fixed effects to address endogenous network formation, we show that both authors' and inventors' outputs rise with their network centrality, consistent with the theory. Moreover, scientific productivity significantly enhances technological productivity, while technological output does not exert a detectable reciprocal effect on scientific production, highlighting an asymmetric linkage aligned with a science-driven model of innovation. These findings provide the first empirical evidence on the joint dynamics of scientific and inventive peer effects, underscore the micro-foundations of the co-evolution of science and technology, and reveal how collaboration structures can be leveraged to design policies that enhance collective knowledge creation and downstream innovation. |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2602.02403 |
| By: | Seong-Young Kim (Rennes SB - Rennes School of Business); Phillip H Kim |
| Abstract: | We study how and why firms shift their interfirm network positions during the routinized regime of a mature high-technology industry. Firms seek benefits from network positions (structural holes or centrality) by forming alliances that move them into these positions and increase their innovation performance. However, during the routinized technology regime, inertia impedes such movements, leading firms a dilemma: whether to continue shifting between two network positions and determine if such shifts yield better outcomes. We analyzed firm network positioning behavior in the semiconductor industry from 1991-2007. Our findings indicate that firms shift toward more central positions, which, in turn, improves innovation performance. These results explain how firms actively shape their network strategy when external conditions discourage such shifts. |
| Keywords: | semiconductor industry, routinized technology regime, high-technology industries, innovation performance, interfirm network positioning |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05410602 |
| By: | Sebastian Ritter (AQR-IREA, University of Barcelona); Vicente Royuela (AQR-IREA, University of Barcelona) |
| Abstract: | As the EU races to meet its 2030 emissions reduction target, regional disparities in transition progress threaten to leave some territories behind. We introduce the Regional Green Transition Performance Index (RGTP), a novel composite measure capturing progress across seven pillars (environmental; energy; circular economy and waste; sustainable development; just transition; innovation and policy; and transport and mobility) for 232 European NUTS2 regions over 14 years. Drawing on 31 indicators, we map spatial patterns and dynamic processes. Furthermore, we argue that the green transition acts as a structural force whose potential effects on regional development can be expressed along two axes: vulnerability and opportunity. We propose an alternative measure of Regional Green Transition Opportunity index (RGTO) which we combine with the existent Regional Green Transition Vulnerability index (RGTV) of RodríguezPose & Bartalucci (2024) to construct a simple 2×2 typology of regions. We translate this evidence into a policy playbook: pair risk-mitigation with opportunity-creation and embed diffusion mechanisms so gains propagate beyond individual regions. The paper contributes an open dataset, a transparent methodology to separate performance, opportunities, and vulnerabilities which responds to the EU’s performance-based policy agenda by offering a region-level monitoring tool that complements cohesion instruments (ERDF/CF/JTF/ESF+) and flags where to reduce vulnerabilities while mobilizing opportunities in the green transition. |
| Keywords: | green transition; European Union; regional inequality; green transition index. JEL classification: C43; Q56; R11; R12 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:aqr:wpaper:202601 |
| By: | Philipp Jonas Kreutzer; Josef Taalbi |
| Abstract: | Collaboration is expected to play a central role in the transition to a bioeconomy - a central pillar of a green economy. Such collaboration is supposed to connect traditional biomass processing firms with diverse actors in fields where biomass ought to substitute existing or create novel products and processes. This study analyzes the network of technology collaborations among innovating firms in Sweden between 1970 and 2021. The results reveal generally positive associations between direct and indirect ties, with meaningful increases in innovation output for each additional direct collaboration partner. Relationships between brokerage positions and innovation output were statistically insignificant, and cognitive proximity - while following theoretical expectations - materially insignificant. These associations are mostly equal between actors heavily invested in the bioeconomy and those focusing on other innovation areas, indicating that these actors operate under largely similar mechanisms linking collaboration and subsequent innovation output. These results suggest that stimulating collaboration broadly - rather than attempting to optimize collaboration compositions - could result in higher number of significant Swedish innovations, for bioeconomy and other sectors alike. |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2602.05112 |
| By: | Yoshimichi Murakami (Research Institute for Economics and Business Administration, Kobe University, JAPAN) |
| Abstract: | Although upstream positions in GVCs are expected to expand unskilled-intensive activities and reduce wage inequality in developing countries, empirical studies based on cross-country analysis have largely failed to provide evidence supporting the theoretical prediction. Employing exogenous industry-level variations and combining industry-level GVC indicators with plant-level detailed panel data, this study empirically analyzes whether upstream positions in GVCs are negatively associated with skilled labor wage share in Chile from 1995 to 2006. The results revealed that upstream positions in GVC were negatively associated with skilled labor wage share, indicating that upstream activities are related to unskilled- intensive tasks, as expected. Although the upstream positions were positively associated with skilled labor wage share in highly technological-intensive plants, the number of such plants was very limited. The findings were robust to the exclusion of affiliates with changing their industry affiliations and control for the persistent effect of the dependent variable and endogeneity of plant-level variables. Additionally, we found that the negative effects of the upstream positions in GVCs are primarily derived from plants operating in industries that were initially located in downstream position and shifted towards upstream position. |
| Keywords: | Global value chains; Upstream positions; Wage inequality; Chile |
| JEL: | D24 F14 F16 F66 J31 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:kob:dpaper:dp2026-04 |