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on Technology and Industrial Dynamics |
| By: | Costanza Bosone; Leonardo Gambacorta; Paolo Giudici; Enisse Kharroubi; Ulf Lewrick |
| Abstract: | We study how robot adoption and investment in information and communication technologies (ICT) jointly shape sectoral employment across 20 European Union (EU) countries over the period 1995-2020. Using a cross-sectional regression design that interacts changes in robot adoption with ICT investment, we find that increases in robot adoption are associated with higher employment in sectors that either entered the period without robots or invested little in ICT. By contrast, robot adoption is associated with lower employment in sectors that initially had some robots and high ICT investment. These findings highlight the importance of both initial conditions and complementary technology investment in shaping labour-market outcomes, suggesting that the employment effects of technology are highly context-dependent. |
| Keywords: | ICT capital, employment, labour market, technology adoption, European Union |
| JEL: | E23 O33 J24 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:bis:biswps:1334 |
| By: | Christian Gschwendt; Claudio Schilter |
| Abstract: | Generative AI (GenAI) adoption is spreading rapidly and reshaping work, yet its implications for firms' training decisions remain largely unexplored. This paper examines how automation in the post-GenAI era affects firms' entry-level training positions using a vignette experiment with recruiters at over 2, 800 Swiss firms, covering more than 100 distinct occupations. Firms plan to reduce training positions in response to automation prospects, with larger reductions the greater the expected automated task share and the earlier the expected implementation. Effects are markedly stronger in routine-intensive and AI-exposed occupations, as well as among large firms. Our experiment allows us to disentangle an "erosion of the training pipeline, " where firms reduce training even though demand for trained specialists remains, from an overall decline in occupational labor demand. We find that pipeline erosion accounts for less than one third of the average reduction in training, but substantially more when automation is particularly intensive - measured by a high share of tasks being automated - and in routine-intensive and AI-exposed occupations. Overall, the results suggest that GenAI adoption is likely to reallocate firms' human capital investment with potential downstream implications for early career formation, and to reinforce labor market de-routinization trends. |
| Keywords: | Automation, firm training, technological change, generative AI, artificial intelligence, entry-level employment |
| JEL: | J24 M53 O33 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:iso:educat:0252 |
| By: | Juan S. Mora-Sanguinetti (BANQUE DE FRANCE AND BANCO DE ESPAÑA); Cristina Peñasco (BANQUE DE FRANCE AND UNIVERSITY OF CAMBRIDGE); Rok Spruk (UNIVERSITY OF LJUBLJANA) |
| Abstract: | This paper analyses the impact of “green regulations” - i.e. those aimed at mitigating the effects of climate change and environmental externalities - on innovation, using a novel regulatory database covering the period 008-2022 for Spain. The database identifies regulations at both the national and regional levels through textual analysis. Employing a panel data approach, we assess how different types of environmental regulations - particularly those related to renewable energy - affect firm-level innovation activities. Our findings indicate that national-level green regulations have a positive effect on innovation, whereas regional-level regulations show mixed or negligible impacts. Importantly, the interaction between national and regional regulations, measuring the simultaneous production of legal texts at both levels, can foster innovation but at a reduced pace with respect to the sole production of regulation at the national level. Given the results for regional-level regulation, our findings provide evidence in favour of the hypothesis that regulatory fragmentation due to unequal, overlapping, inconsistent or conflicting procedure across jurisdictions may diminish these benefits. |
| Keywords: | green regulation, innovation, Porter hypothesis, renewable energy, business |
| JEL: | K32 Q5 O44 O13 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:bde:wpaper:2611 |
| By: | Sandra Baquie; Yueling Huang; Ms. Florence Jaumotte; Jaden Kim; Rafael Machado Parente; Samuel Pienknagura |
| Abstract: | This paper presents a global empirical analysis of how industrial policies (IPs) affect patent applications, with an instrumental-variable strategy that addresses selection in policy targeting by leveraging retaliatory dynamics. On average, IPs do not increase domestic patent applications over a four-year period, except when they target sectors with potential distortions or externalities, such as infant industries or low-carbon technologies. However, IPs temporarily boost foreign patent filings within the same timeframe, consistent with strategic front-loading by foreign inventors seeking to secure technology protection, and perhaps market access, in the IP-targeted sector. This link between foreign patent applications and IPs is stronger for export-oriented policies compared to domestic subsidies, for IPs targeting innovation-central sectors, and in emerging markets and developing economies. |
| Keywords: | Industrial Policies; Innovation; Patents; Networks; Low-carbon technology |
| Date: | 2026–03–13 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2026/047 |
| By: | João Bento; Miguel Matos Torres; Hicham Nachit |
| Abstract: | We are exploring the interplay between inequality and foreign direct investment (FDI) and green technology innovation, an area that remains underexplored in international business (IB) research. This study examines how green technology innovation moderates the relationship between FDI, proxied by the performance and operational outcomes of majority-owned U.S. foreign affiliates, and income inequality, measured by the Gini coefficient of equivalised disposable income from the Luxembourg Income Study (LIS) database. We employ OECD patent data on green innovations to construct a panel dataset of 28 high-income OECD countries from 2000 to 2020. Using fixed-effects panel regressions and quantile models with bootstrapped inference, the results indicate that FDI has a significant inequality-reducing effect, and green innovation moderates this relationship, reducing income inequality. Firm investment, profitability, efficiency, and innovation interact with green innovation to reduce inequality, highlighting the role of MNEs in fostering equitable outcomes. These findings contribute to a better understanding of IB activity by unpacking the interdependent dynamics between firm performance and national competitiveness, offering policy insights to promote FDI and green innovation and mitigate inequality. |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:lis:liswps:914 |
| By: | Océane Vernerey (LISA - Laboratoire « Lieux, Identités, eSpaces, Activités » (UMR CNRS 6240 LISA) - CNRS - Centre National de la Recherche Scientifique - Università di Corsica Pasquale Paoli [Université de Corse Pascal Paoli], LEDi - Laboratoire d'Economie de Dijon [Dijon] - UBE - Université Bourgogne Europe) |
| Abstract: | In this article, we re-examine the innovation process through the CDM model. Compared to the existing literature, this study offers several contributions. First, it relies on an unusually large dataset of 509, 033 firms from nine European countries – Bulgaria, the Czech Republic, Estonia, Spain, Hungary, Lithuania, Portugal, Romania, and Slovakia – over the period 1998–2016. This extensive dataset allows us to explore cross-country heterogeneity, as well as potential temporal trends across multiple survey waves. Second, the paper provides a systematic and detailed review of the vast CDM literature, offering a structured synthesis of prior findings and highlighting the main areas where results diverge across studies. Third, methodologically, we compare three alternative estimation strategies, which enables us to evaluate the robustness of our findings and to identify potential sources of heterogeneity in estimated relationships. Across all specifications, we find that R&D investment has a positive effect on the share of new products in sales, which subsequently enhances firm performance. Promoting innovation can have a substantial impact on performance. However, the magnitudes of these effects vary depending on the country, the estimation method, and the treatment of potential biases. In some countries, innovation generates stronger positive spillover effects on firm performance, while others are more effective at transforming R&D into innovation but face challenges in converting this innovation into productivity gains. This implies, on the one hand, that public policies must be context-specific, and on the other hand, that the choice of estimation method and the treatment of potential biases can significantly affect the robustness and validity of the results. |
| Keywords: | Innovation process, CDM model, Methodological comparison |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05536446 |
| By: | Nuriye Melisa Bilgin; Ester Faia; Gianmarco Ottaviano |
| Abstract: | We examine how upstream firms' technology adoption affects the performance and adoption decisions of downstream partners. Using business-to-business data with administrative records on advanced technology adoption, we find gains in productivity, performance, adoption probabilities of firms connected to the adopter, relatively to those that are not. Identification combines staggered event studies, balanced panels of pre-existing relationships, and recentering methods to address expected exposure within the network. Gains vary along firm size, centrality, technology quality, but do not systematically increase with input exposure, suggesting that knowledge spillovers may induce organizational adjustments. Adoption by competitors is associated with short-run negative effects. |
| Keywords: | technology diffusion, adoption and propagation, firm networks, firm productivity, imported inputs |
| Date: | 2026–03–11 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2157 |
| By: | Robert J. R. Eliott; Gavin D. J. Harper; Viet Nguyen-Tien |
| Abstract: | Electric vehicles (EVs) are central to decarbonising road transport, a sector responsible for 23% of global energy-related emissions, and their adoption carries both economic and societal implications. This paper provides an economic review of EV transitions, synthesizing theory, stylized facts, and frontier empirical findings. We document three key observations: EV adoption has historically occurred in waves that stalled and revived; contemporary adoption is highly heterogeneous across countries; and the transition reshapes automotive sector activities and supply chains, increasing reliance on geographically concentrated critical minerals and generating Environmental, Social and Governance (ESG) and political economy challenges. We then analyze the economic drivers of adoption, including total cost of ownership, network externalities, and complementary technologies such as charging infrastructure, grid integration, and digital innovations. Supply-side constraints, resource scarcity, and innovation dynamics are examined, highlighting how the EV platform interacts with broader technological and industrial systems. The analysis emphasizes the systemic, path-dependent, and platform nature of EV transitions and outlines policy-relevant insights for managing adoption, supply chains, and innovation. Finally, we identify avenues for future research, including the economics of end-of-life and used EVs, resilient supply chains, and the role of complementary technologies in accelerating low-carbon transitions. |
| Keywords: | Electric vehicles, critical materials, supply chains |
| Date: | 2026–03–17 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2164 |