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on Technology and Industrial Dynamics |
| By: | Hoda Mohamed (Friedrich Schiller University Jena) |
| Abstract: | How the use of industrial robots affects value capture in fragmented global production networks, represented by global value chains (GVCs), remains an open question. I focus on the automotive industry - the largest consumer of industrial robots and one of the most traded manufacturing industries - to examine how robot adoption affects value capture through backward and forward GVC participation. In addition, I assess how automation shapes an industry’s position within the value chain, using upstreamness as a proxy. Using data from OECD TiVa, OECD ICIO, and IFR for 56 countries and 14 manufacturing industries from 1997 to 2017, I apply OLS, OLS-IV, and Poisson pseudo maximum likelihood fixed effects models to analyze the impact of automation on GVC integration. My findings reveal that robot adoption significantly increases forward GVC participation, particularly among factory economies, while also driving higher upstreamness. These results indicate that robots enable industries to capture more value in GVCs while maintaining their upstream positions in GVCs, which are symbolized by forward linkages and trade in intermediate goods. |
| Keywords: | robots, global value chains, automotive, trade in value-added |
| JEL: | F14 O14 L62 |
| Date: | 2025–03–31 |
| URL: | https://d.repec.org/n?u=RePEc:jrp:jrpwrp:2025-0005 |
| By: | Mahdi Ghodsi (The Vienna Institute for International Economic Studies, wiiw); Sandra M. Leitner (The Vienna Institute for International Economic Studies, wiiw); Maryna Tverdostup (The Vienna Institute for International Economic Studies, wiiw) |
| Abstract: | Labour shortages in Europe have led firms to adopt two key strategies automation and the employment of migrants. This study empirically examines the relationship between robot adoption and immigrant labour (differentiated by region of origin and education level) in Austrian firms using a novel dataset linking firm-level survey data on robotics adoption from Austria’s Information and Communication Technologies (IKTU ) surveys (waves 2018, 2020 and 2022) with registry-based employment records. Employing Poisson pseudo-maximum likelihood (PPML) estimations, we analyse firm-level employment decisions while controlling for firm characteristics, industry and region. Our findings show that firms adopting robots tend to employ more workers overall, particularly those with low and medium education levels. Notably, robot-adopting firms employ a higher share of low-educated migrants who are not from the European Economic Area (EEA), suggesting complementarity rather than substitution. However, automation appears to reduce the employment of highly educated migrant workers relative to natives. Distinguishing between industrial and service robots, we find that service robots have a stronger association with employment growth than industrial robots. The impact of robot adoption also differs by sector and is most pronounced in manufacturing, whereas its effects vary in the private service sectors. Our findings suggest that while automation can alleviate labour shortages, it may reinforce labour market segmentation. For EU policy makers, targeted interventions are needed to support the transition of migrant workers into higher-skilled occupations and to ensure that the benefits of automation are equitably distributed. Given the EU-wide relevance of automation and migration dynamics, these results provide insights that are also applicable beyond Austria. |
| Keywords: | Migration, automation, employment, firm- and worker-level analysis |
| JEL: | D22 J23 J24 J61 O33 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:wii:wpaper:262 |
| By: | Fontanelli, Luca; Guerini, Mattia; Miniaci, Raffaele; Secchi, Angelo |
| Abstract: | While artificial intelligence (AI) adoption holds the potential to enhance business operations through improved forecasting and automation, its relation with average productivity growth remain highly heterogeneous across firms. This paper shifts the focus and investigates the impact of predictive artificial intelligence (AI) on the volatility of firms’ productivity growth rates. Using firm-level data from the 2019 French ICT survey, we provide robust evidence that AI use is associated with increased volatility. This relationship persists across multiple robustness checks, including analyses addressing causality concerns. To propose a possible mechanisms underlying this effect, we compare firms that purchase AI from external providers (“AI buyers”) and those that develop AI in-house (“AI developers”). Our results show that heightened volatility is concentrated among AI buyers, whereas firms that develop AI internally experience no such effect. Finally, we find that AI-induced volatility among “AI buyers” is mitigated in firms with a higher share of ICT engineers and technicians, suggesting that AI’s successful integration requires complementary human capital. |
| Keywords: | Dairy Farming, Production Economics, Research and Development/Tech Change/Emerging Technologies, Resource/Energy Economics and Policy |
| Date: | 2025–04–07 |
| URL: | https://d.repec.org/n?u=RePEc:ags:feemwp:355806 |
| By: | Lorena M. D’Agostino (University of Milano-Bicocca); Rosina Moreno (AQR-IREA, University of Barcelona); Damián Tojeiro-Rivero (ESADE-University Ramon Llull) |
| Abstract: | Taking the long-established evidence on knowledge spillovers that states that part of the new created knowledge spills over to other firms mostly located in the physical proximity, we aim at providing evidence on the role of green knowledge spillovers on firms’ innovation. We posit that in addition to internal factors, firm innovation is determined by external regional factors, among which we specifically focus on the spillovers generated by environmental EU-funded research at the regional level. The results indicate that the presence of partners engaged in EU-environmental projects in a region has a positive and significant effect on process innovation. |
| Keywords: | innovation; environment; EU-funded research; Framework Programme; region; firm JEL classification: R11; O31; O44 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:aqr:wpaper:202409 |
| By: | Vivarelli, Marco; Piva, Mariacristina; Tani, Massimiliano |
| Abstract: | Labor mobility is considered a powerful channel to acquire external knowledge and trigger complementarities in the innovation and R&D investment strategies; however, the extant literature has focused on either scientists’ mobility or migration of high-skilled workers, while virtually no attention has been devoted to the possible role of short-term business visits. Using a unique and novel database originating a country/sector unbalanced panel over the period 1998-2019 (for a total of 8, 316 longitudinal observations), this paper aims to fill this gap by testing the impact of BVs on R&D investment. Results from GMM-SYS estimates show that short-term mobility positively and significantly affects R&D investments; moreover, our findings indicate - as expected - that the beneficial impact of BVs is particularly significant in less innovative countries and in less innovative industries. These outcomes justify some form of support for BVs within the portfolio of the effective innovation policies, both at the national and local level. |
| JEL: | O31 O32 O15 J61 |
| Date: | 2025–04–03 |
| URL: | https://d.repec.org/n?u=RePEc:unm:unumer:2025010 |
| By: | Rossana Mastrandrea (Department of Management, University of Turin, Torino, Italy); Fabio Montobbio (Dipartimento di Politica Economica, DISCE, Università Cattolica del Sacro Cuore, Milano, Italy – ICRIOS, Bocconi University, Milano, Italy – BRICK, Collegio Carlo Alberto, Torino, Italy); Gabriele Pellegrino (Dipartimento di Politica Economica, DISCE, Università Cattolica del Sacro Cuore, Milano, Italy); Massimo Riccaboni (IMT School for Advanced Studies, Lucca, Italy – IUSS, Pavia, Italy); Valerio Sterzi (Bordeaux School of Economics (BSE), University of Bordeaux, CNRS, UMR 6060, Bordeaux, France) |
| Abstract: | This study examines the roles of public and private sector actors in the development of mRNA vaccines, a breakthrough innovation in modern medicine. Using a dataset of 151 core patent fam- ilies and 2, 416 antecedent (cited) patents, we analyze the structure and dynamics of the mRNA vaccine knowledge network through network theory. Our findings highlight the central role of biotechnology firms, such as Moderna and BioNTech, alongside the crucial contributions of univer- sities and public research organizations (PROs) in providing foundational knowledge. We develop a novel credit allocation framework, showing that universities, PROs, government and research cen- ters account for at least 27% of the external technological knowledge base behind mRNA vaccine breakthroughs—representing a minimum threshold of their overall contribution. Our study offers new insights into pharmaceutical and biotechnology innovation dynamics, emphasizing how Mod- erna and BioNTech’s mRNA technologies have benefited from academic institutions, with notable differences in their institutional knowledge sources. |
| Keywords: | breakthrough innovation, innovation networks, patent analysis, mRNA vaccines, COVID- 19 |
| JEL: | I10 I18 L65 O31 O34 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:ctc:serie5:dipe0047 |
| By: | Jesús Fernández-Villaverde; Yang Yu; Francesco Zanetti |
| Abstract: | Defensive hiring of researchers by incumbent firms with monopsony power reduces creative destruction. This mechanism helps explain the simultaneous rise in R&D spending and decline in TFP growth in the US economy over recent decades. We develop a simple model highlighting the critical role of the inelastic supply of research labor in enabling this effect. Empirical evidence confirms that the research labor supply in the US is indeed inelastic and supports other model predictions: incumbent R&D spending is negatively correlated with creative destruction and sectoral TFP growth while extending incumbents’ lifespan. All these effects are amplified when ideas are harder to find. An extended version of the model quantifies these mechanisms’ implications for productivity, innovation, and policy. |
| Date: | 2025–03–11 |
| URL: | https://d.repec.org/n?u=RePEc:oxf:wpaper:1072 |
| By: | Silva Neira, Ignacio; Rodríguez González, Carlos; Pédussel Wu, Jennifer |
| Abstract: | Globalization has significantly influenced economic policy in Latin America. After the debt crisis of the 1980s, capital controls were removed leading to a substantial increase in Foreign Direct Investment (FDI) to the region. Chile, in particular, has extensively promoted free international integration, with the import of technology through FDI playing a major role in its economic development. During the 1990s, Chile experienced a period of rapid GDP growth, increased exports, and higher productivity. However, its productive dynamism has since stalled, trapping the country in an income plateau. Insights from evolutionary economics provide a framework for understanding this phenomenon, where neoclassical theory falls short. This study seeks to provide empirical evidence on whether FDI has promoted or hindered the innovative performance of domestic firms in Chile. Using firm-level data, the research employs the well-known CDM model to address selection bias in innovation efforts. The econometric analysis measures the impact of foreign competition on local innovation, specifically examining how foreign ownership and competition within economic sectors influence innovation outputs in local firms. The findings indicate that firms facing higher levels of foreign competition are less likely to implement new processes or products. These results offer valuable policy implications, highlighting the nuanced effects of FDI on host economies. The impact of FDI varies depending on the type of investment, the economic sector, and the technology introduced. Consequently, strategies aimed at leveraging FDI for economic catch-up must account for these variances and focus on fostering local innovation and technological advancement. |
| Keywords: | Foreign Direct Investment, CDM Model, Innovation, Technology transfer |
| JEL: | F21 O33 L25 O54 D22 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:ipewps:313642 |
| By: | Juliana Oliveira-Cunha; Bruno Serra-Lorenzo; Anna Valero |
| Abstract: | In this policy brief, we present new data from a survey of 373 UK firms conducted in May 2024 in partnership with the Confederation of British Industry (CBI). This is a follow-up to our two earlier surveys which revealed that firms adopted more new digital technologies in response to the Covid-19 pandemic. The surveys showed that such innovative activity had persisted, but that innovation patterns were uneven - with larger and more digitised businesses being more likely to adopt new technologies since the pandemic. Since then, UK businesses and consumers have faced significant challenges, including the cost-of-living and energy crises, while continuing to adapt to changes brought about by Brexit. This survey wave provides an updated view on business innovation through crises and change in the early 2020s. |
| Keywords: | Covid-19, Technological change, Brexit |
| Date: | 2025–04–02 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepsps:50 |
| By: | Alessia Matano (AQR-IREA, University of Barcelona and Università di Roma “La Sapienza”); Paolo Naticchioni (Roma Tre University and IZA) |
| 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: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:aqr:wpaper:202501 |
| By: | Arsène Perrot (Gran Sasso Science Institute); Fabiano Compagnucci (Gran Sasso Science Institute); Paolo Veneri (Gran Sasso Science Institute) |
| Abstract: | This paper assesses the impact of local exposure to robots on the physical health of workers and the broader population’s mental health across Italian provinces. The empirical analysis relies on data from the International Federation of Robotics to build a measure of robot penetration at the provincial level, combined with provincial-level data on workplace accidents and mental health issues provided by Italian agencies for work insurance and statistics, respectively. Our results, derived from a set of linear and non-linear models and instrumental variable approaches, highlight that robotisation has reduced the number of accidents in the workplace. At the same time, robotisation is associated with an increase in mental disorders in the local population. The effects are strongly heterogeneous across places, with large metropolitan areas experiencing a relatively greater reduction in accidents and lower prevalence of mental health issues compared to other provinces, potentially exacerbating long-standing regional well-being disparities. |
| Keywords: | Automation; Robotisation; Workers’ health; Mental health; Regional disparities |
| JEL: | I10 J01 R10 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:ahy:wpaper:wp63 |