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on Technology and Industrial Dynamics |
| By: | Carolina Castaldi; Nicola Cortinovis; Milene S. Tessarin |
| Abstract: | Economic geography has offered several insights to understand the role of geography in shaping creativity, innovation and the way they are connected in space. Unfortunately, most attention has been devoted to analyzing cities and urban regions as the ideal context where creativity and innovation come together. Emerging counter-narratives are challenging this urban perspective and proposing that creativity-led innovation can also thrive in rural, often more peripheral, places. Theoretically, different arguments have been proposed, yet a clear conceptualization is lacking. We propose to link these arguments to two complementary ways in which creativity-led innovation might be at play, either as innovation in creative industries or as creative workers contributing to innovation across industries. Methodologically, most evidence comes from intriguing case studies and country-specific surveys, yet comparative quantitative evidence is missing or misleading. In this study, we propose to use trademarks as an alternative indicator to patents, better fitting creativity-led innovation. We illustrate the opportunities from our conceptualization and measurement with a comparative study of European regions. Using a database combining large scale occupational data with patent and trademark activity for the period 2011-2019, we analyze the relationship between creative occupations and innovation activity in rural regions. Our findings suggest that creativity-led innovation processes operate in rural regions but can only be uncovered when using trademarks as innovation indicators. These findings bear key policy implications, as they inform efforts towards formulating and monitoring the role of creativity and innovation for rural contexts. |
| Keywords: | creativity, innovation, regions, rural, urban, creative occupations, patents, trademarks |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2517 |
| By: | Francesco de Cunzo; Aurelio Patelli; Angelica Sbardella; Andrea Tacchella |
| Abstract: | This paper presents new evidence on how countries are innovating in response to the growing strategic importance of critical raw materials (CRMs). Using millions of patent abstracts from the PATSTAT database, we apply a large language model (LLM) to classify CRM-related inventions into four functional roles: use, refine, recycle, and remove. A fifth category, wrong, flags false positives and improves classification accuracy. This approach moves beyond simple patent counts by identifying the specific roles CRMs play in technological development, enabling a more nuanced view of innovation strategies. Our classification reveals a significant increase in CRM-related innovation over the past two decades, with notable variation across materials, functions, and countries. While use-related patents remain dominant, recent growth in recycle and remove functions points to a shifting emphasis on circularity. Geographically, China leads across all functions, while an upward trend in recycling activity is observed across several advanced economies. A panel data analysis reveals that innovation in refining, recycling, and removing CRMs is positively associated with innovation in their use, suggesting functional complementarities that can enable both technological progress and more sustainable material strategies. These findings have important implications for policy, highlighting the value of supporting functionally diverse CRM innovation, fostering international coordination, and adopting tools for real-time innovation monitoring. By combining text mining with AI-driven functional classification of patented inventions, this study offers a scalable method for tracking material-related innovation and informing policies aimed at sustainability and technological resilience. |
| Keywords: | Critical Raw Materials, Green and Digital Technologies, Large Language Models, Text Mining |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2516 |
| By: | Giuseppe Berlingieri; Maarten De Ridder; Danial Lashkari; Davide Rigo |
| Abstract: | In theories of creative destruction, product innovation is a key driver of aggregate growth. In this paper, we confront the predictions of these theories about product dynamics with empirical patterns in product-level data on the near-universe of French manufacturing firms. We find that the process of product innovation frequently exhibits bursts-episodes in which firms rapidly add multiple products to their portfolio. Such bursts lead to substantial shifts in revenue and explain the majority of the variance in firm-level growth. We introduce a model of firm product innovation compatible with such a process that also nests the canonical models of creative destruction. We show that innovation bursts alter the equilibrium composition of age, size, and innovation efficiency of firms, and further explain the concentration of production among superstar firms. Our model thus enables the joint study of the determinants of industry concentration and growth in a setting consistent with the empirical patterns of product dynamics. |
| Keywords: | productivity, endogenous growth, firms, innovation |
| Date: | 2025–04–29 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2095 |
| By: | Damián Tojeiro-Rivero (Employment observatory, Department of Economics, University Rovira i Virgili, Spain.); Rosina Moreno (AQR-IREA Research Group, Department of Econometrics, Statistics and Applied Economics, Universitat de Barcelona, Spain.) |
| Abstract: | Prior literature has argued that, although both captive knowledge sourcing (CKS) and non-captive knowledge sourcing (NCKS) are effective strategies for enhancing firm innovativeness, the former plays a more defined role in determining the likelihood of a firm achieving product innovations. However, we contend that the focus should not only be on the decision to innovate but, more importantly, on the profitability firms derive from such innovations. Given that knowledge acquired from external sources can provide firms with ideas that differ from their existing competencies, NCKS may be more advantageous, as the resulting innovations are likely to exhibit higher levels of novelty. Additionally, we examine the complementarity or substitutability between CKS and NCKS in driving innovation. Our findings for Spanish firms suggest that NCKS yields greater benefits than CKS. Moreover, adopting both strategies simultaneously does not result in higher benefits; instead, a minimum threshold of NCKS, above the median, is necessary to realize observable gains. This indicates that firms must demonstrate a substantial level of commitment to NCKS to effectively exploit its potential for generating returns from their most novel innovations. |
| Keywords: | Radical Innovation, Captive Knowledge Sourcing; Non-Captive Knowledge Sourcing; Spanish firms; Panel data; Complementarity/Substitutability. JEL classification: |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:ira:wpaper:202508 |
| By: | Alessia Matano (Dipartimento di Economia e Diritto, Università di Roma “La Sapienza”, Italy. AQR-IREA, Universitat de Barcelona, Spain.); Paolo Naticchioni (Roma Tre University and IZA, Italy.) |
| Abstract: | This paper investigates the relationship between China’s import competition and the innovation strategies of domestic firms. Using firm level data from Italy spanning 2005-2010 and employing IV fixed effects estimation techniques, we find that the impact of China’s import competition on innovation varies depending on the type of goods imported (intermediate vs. final). Specifically, imports of final goods boost both product and process innovation, while imports of intermediate goods reduce both. Additionally, we extend the analysis to consider the role of unions in moderating these responses. We find that, in unionized firms, imports' impact on innovation is mitigated, specifically to protect workers' employment prospects. |
| Keywords: | China’s Import Competition; Final and Intermediate Goods; Product and Process Innovation; Unions; IV Fixed effects estimations. JEL classification: C33, L25, F14, F60, O30, J50. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:ira:wpaper:202502 |
| By: | Drake Mullens; Stella Shen |
| Abstract: | This study introduces the AI-Accentuated Career Transitions framework, advancing beyond binary automation narratives to examine how distinct AI usage patterns reshape occupational mobility. Analyzing 545 occupations through multivariate modeling, we identify six qualitatively distinct human-AI usage patterns that differentially predict placement across job preparation zones. Our findings empirically validate the "missing middle" hypothesis: automation-focused usage strongly predicts lower job zone placement while augmentative usage predicts higher zones. Most significantly, we identify specific Knowledge, Skill, and Abilities combinations with AI usage patterns that function as "skill bridges" facilitating upward mobility. The interaction between task iteration AI usage and cognitive skills emerges as the strongest advancement predictor, creating pathways across traditionally disconnected occupational categories. Counterintuitively, despite directive AI's negative main effect, its interaction with technical knowledge positively predicts advancement in specialized domains. Comparative model testing confirms that AI usage patterns represent a distinct dimension of occupational classification that adds significant explanatory power beyond traditional skill measures. These findings reveal AI as a skill amplifier that widens capability gaps rather than an equalizing force. The 2ACT framework provides strategic guidance for workers, curriculum designers, policymakers, and organizations navigating increasingly AI-mediated career pathways. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.07914 |
| By: | Philippe Aghion; Antonin Bergeaud; Mathias Dewatripont; Johannes Matt |
| Abstract: | We develop a model of endogenous growth and firm dynamics with soft budget constraints, where firms differ in their innovation speed and slower firms need additional financing in order to eventually innovate. As creditors cannot anticipate refinancing needs in advance nor credibly commit to withholding future refinancing, a Soft Budget Constraint Syndrome emerges, causing excessive entry by slow firms and crowding out potentially more efficient innovators. The resulting trade-off between the positive effects of budget constraint softening on innovation by incumbents and slow-type entrants and its negative effects on entry by fast innovators, generates a hump-shaped relationship between refinancing costs and aggregate growth. Calibrating the model to French firm-level data, we show that the budget constraint softening associated with the decline in interest rates in the aftermath of the Global Financial Crisis accounts for 54% of the observed drop in the aggregate growth rates post-crisis. Although the softening in budget constraints has had a positive effect on incumbent innovation, this was more than offset by the resulting decrease in the entry rates of good firms (by 61% relative to the pre-crisis steady state). |
| Keywords: | firm dynamics, credit growth, soft budget constraint |
| Date: | 2025–04–10 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2091 |
| By: | Anders Humlum; Emilie Vestergaard |
| Abstract: | We examine the labor market effects of AI chatbots using two large-scale adoption surveys (late 2023 and 2024) covering 11 exposed occupations (25, 000 workers, 7, 000 workplaces), linked to matched employer-employee data in Denmark. AI chatbots are now widespread—most employers encourage their use, many deploy in-house models, and training initiatives are common. These firm-led investments boost adoption, narrow demographic gaps in take-up, enhance workplace utility, and create new job tasks. Yet, despite substantial investments, economic impacts remain minimal. Using difference-in-differences and employer policies as quasi-experimental variation, we estimate precise zeros: AI chatbots have had no significant impact on earnings or recorded hours in any occupation, with confidence intervals ruling out effects larger than 1%. Modest productivity gains (average time savings of 3%), combined with weak wage pass-through, help explain these limited labor market effects. Our findings challenge narratives of imminent labor market transformation due to Generative AI. |
| JEL: | J23 J24 J31 O33 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33777 |
| By: | Melanie Arntz; Michael J. Bohm; Georg Graetz; Terry Gregory; Florian Lehmer; Cacilia Lipowski |
| Abstract: | We investigate the diffusion of frontier technologies across German firms before and during the Covid-19 crisis. Our analysis tracks the nature, timing, and pandemic-related motivations behind technology investments, using tailor-made longitudinal survey data linked to administrative worker-firm records. Technologies adopted after the onset of the pandemic increasingly facilitated remote work and mitigated the negative employment effects of the crisis. Overall, however, investments in frontier technologies declined sharply, equivalent to a loss of 1.4 years of pre-pandemic investment activity. This procyclical adoption pattern is particularly striking since the pandemic created clear incentives to experiment with new technologies. Our findings highlight how short-run fluctuations may influence medium-run economic growth through their impact on technology diffusion. |
| Keywords: | frontier technology investments, firm-level survey data, cyclicality of technology adoption, Covid-19 crisis |
| Date: | 2025–04–16 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2093 |
| By: | Caldarola Bernardo (European Commission - JRC); Cresti Lorenzo; Mazzilli Dario; Napolitano Lorenzo (European Commission - JRC); Patelli Aurelio; Sbardella Angelica; Tacchella Andrea |
| Abstract: | This policy brief investigates the structural vulnerabilities and competitive dynamics of the EU27 automotive sector, with a focus on the complexity and the fragmentation of production processes across global value chains. The analysis integrates input-output tables to quantify the automotive sector's reliance on non-EU economic branches, alongside an economic complexity framework to assess the underlying productive capabilities of European countries in automotive-related industries. The findings indicate an increasing dependency on extra-EU suppliers, particularly China, for critical components such as lithium-ion batteries, which heightens supply chain risks. Currently, Eastern European countries-most notably Poland, Czechia, and Hungary-have enhanced their competitiveness in the production of automotive components, surpassing traditional leaders such as Germany. The policy brief offers new insights into the challenges posed by the ongoing electric mobility transition in the European Union, particularly in relation to electric accumulators. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc142111 |