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on Technology and Industrial Dynamics |
| By: | Caldarola, Bernardo (Mt Economic Research Inst on Innov/Techn, RS: GSBE other - not theme-related research); Fontanelli, Luca |
| Abstract: | Recent empirical evidence finds positive associations between digitalisation and industry concentration. However, ICT may not be all alike. We investigate the effect of the purchase of cloud services on the long run size growth rate of French firms. Our findings suggest that cloud services positively impact firm growth rates, with smaller firms experiencing more significant benefits compared to larger firms. This evidence suggests that the diffusion of cloud technologies may help mitigate concentration in the era of the digital transition by favouring the digitalisation and growth of smaller firms, especially when the cloud services provided are more advanced. |
| JEL: | L20 L25 O33 |
| Date: | 2024–09–24 |
| URL: | https://d.repec.org/n?u=RePEc:unm:unumer:2024026 |
| By: | Park , Donghyun (Asian Development Bank); Shin, Kwanho (Korea University) |
| Abstract: | We examine the implications of robots and artificial intelligence (AI) for employment and productivity, using a rich firm-level database from the Survey of Business Activities provided by Statistics Korea. While previous studies have explored the effects of robots and AI separately, we investigate their effects jointly within a unified framework. We deploy propensity score matching to control for firm characteristics, enabling a potential causal interpretation of the differential impacts of robots and AI. We find that the patterns of adopting robots and AI differ significantly across industries. Additionally, although the overall share of firms adopting robots is larger, AI adoption is more concentrated among bigger firms. Our main finding is that, while adopting robots and adopting AI both increase employment, only adopting AI improves labor productivity. However, such productivity gains are accompanied by a decrease in the labor share of income, suggesting a potential shift in value distribution favoring capital income. Furthermore, we find that the immediate impact of adopting both robots and AI is an increase in temporary but not permanent employment. Finally, there is no evidence that firms adopting both robots and AI improve their labor productivity, potentially reflecting a lack of synergy. |
| Keywords: | artificial intelligence; robots; employment; productivity |
| JEL: | D22 J21 J24 O33 O40 |
| Date: | 2025–02–07 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:0769 |
| By: | Marius Faber; Kemal Kilic; Gleb Kozliakov; Dalia Marin |
| Abstract: | The world economy has become more and more globalized as firms have organized production along global value chains. But more recently, globalization has stalled. This paper shows that higher uncertainty, in combination with better automation technologies, has likely contributed to that trend reversal. We show that plausibly exogenous exposure to uncertainty in developing countries leads to reshoring to high-income countries, but only if industrial robots have made this economically feasible. In contrast, we find no strong evidence of nearshoring or diversification. We address concerns about reverse causality by showing that results hold when using two alternative identification strategies. In a narrative approach, we use only locally generated spikes in uncertainty, for which the narrative around the events suggest that they are plausibly exogenous. In a small open economy approach, we restrict the sample to small developed countries that are unlikely to cause uncertainty in the developing world. Moreover, we show that results are robust to the main threats to identification related to shift-share instruments. |
| Keywords: | Global value chains, Uncertainty, Automation, Reshoring, Shift-share design |
| JEL: | F14 F15 F16 J23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:snb:snbwpa:2025-02 |
| By: | Dirk Czarnitzki; Robin Lepers; Maikel Pellens |
| Abstract: | The circular economy represents a systematic shift in production and consumption, aimed at extending the life cycle of products and materials while minimizing resource use and waste. Achieving the goals of the circular economy presents firms with the challenge of innovating new products, technologies, and business models, however. This paper explores the role of artificial intelligence as an enabler of circular economy innovations. Through an empirical analysis of the German Community Innovation Survey, we show that firms investing in artificial intelligence are more likely to introduce circular economy innovations than those that do not. Additionally, the results indicate that the use of artificial intelligence enhances firms’ abilities to lower production externalities (for instance, reducing pollution) through these innovations. The findings of this paper underscore artificial intelligence’s potential to accelerate the transition to the circular economy. |
| Keywords: | Circular economy, Innovation, Artificial intelligence |
| Date: | 2025–01–23 |
| URL: | https://d.repec.org/n?u=RePEc:ete:ecoomp:758339 |
| By: | Cowan, Robin (RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn); Jonard, Nicolas; Samson, Ruth |
| Abstract: | Many scholars observed changes in the intellectual property rights systems in the 1980s and 1990s throughout the world. Patent systems in particular seemed to be expanding their scope, and the legal system seemed to be changing its attitudes towards intellectual property rights. At the same time, and probably in response, firms started to change their patenting behaviour by treating patents as tools of competition and bargaining rather than as a means to protect the fruits of intellectual labour. In this paper we present a simulation model that can be used to discuss that shift. Firms search for new technologies and patent what they find. But different firms have different strategies: one is to protect an invention; a second is to protect a technology space; the third is to attack others' technology spaces. In the literature the latter two have been described as different types of blocking. We examine different IPR regimes, characterized by who is able to infringe whose patent rights . This is an extreme case of who is able to extract rents from a given configuration of patent rights. |
| JEL: | O31 O34 C60 L50 |
| Date: | 2024–04–24 |
| URL: | https://d.repec.org/n?u=RePEc:unm:unumer:2024008 |
| By: | Lema, Rasmus (RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn); Perez, Carlota |
| Abstract: | Green is now emerging, albeit not fast enough, as a new direction shaping innovation, investment and lifestyles. Indeed, the requirements of the green transformation give rise to the emergence of entirely new technologies, and it changes the parameters of competitiveness across industry, agriculture and services. These changes have profound implications for latecomer development, both positive and negative. The identification of strategies for seizing opportunities and overcoming challenges in the green economy is a central concern for policy makers and business managers alike. We argue that the theoretical framework of techno-economic paradigms shifts is particularly useful for understanding the dynamics of large-scale transformation and its associated institutional change. To fully grasp the nature of the green transformation, it is necessary to take a step back and locate it in relation to the history of technological revolutions and their regular patterns of diffusion. In this respect, we argue that the ongoing debate about the green transformation and latecomer development must consider two key conditions. First, it must recognize that the green transformation is primarily a direction-driven phenomenon, shaped by aspirational, political, and institutional changes, rather than a technology-driven phenomenon per se. Second, it must acknowledge the potential of information and communication technology (ICT) not only to accelerate and deepen the green transition itself but also to foster latecomer development within it. |
| JEL: | O44 Q55 O38 O33 |
| Date: | 2024–02–05 |
| URL: | https://d.repec.org/n?u=RePEc:unm:unumer:2024001 |
| By: | Marco De Simone; Dario Guarascio; Jelena Reljic |
| Abstract: | This paper examines the impact of robotisation on workplace safety in EU manufacturing sectors between 2011 and 2019. To address endogeneity concerns, we employ an instrumental variable approach and find that robot adoption reduces both injuries and fatalities. Specifically, a 10 per cent increase in robot adoption is associated with a 0.066 per cent reduction in fatalities and a 1.96 per cent decrease in injuries. Our findings highlight the context-dependent nature of these effects. The safety benefits of robotisation materialise only in high-tech sectors and in countries where industrial relations provide strong worker protections. In contrast, in traditional industries and countries with weaker institutional frameworks, these benefits remain largely unrealised. The results are robust to several sensitivity tests. |
| Keywords: | EU, robotisation; technology; workplace safety; injuries; fatalities; industrial relations |
| JEL: | J01 J08 J28 J50 J81 L60 O33 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:sap:wpaper:wp255 |
| By: | Andrew B. BERNARD; Andreas MOXNES; SAITO Yukiko |
| Abstract: | This paper examines the importance of economic integration on the production of innovation. During the late 1980s and-90s, Shikoku and Honshu, Japan’s largest and fourth largest islands, were connected for the first time by three different bridges. This greatly reduced travel times compared to previous modes of transport such as ferry. We examine the impact of bridge connections on team formation and the production of knowledge, as measured by patent data. Using the geolocation of inventors before the opening of the bridges, we find that inventors located close to the bridges increased knowledge production more than inventors located farther away from the bridges. The treated inventors matched to more productive inventors at greater distances. Inventors on Shikoku were more likely to change their innovation teams and add co-inventors from Honshu while dismissing collaborators from Shikoku. The results are robust to instrumenting for the location of the bridges using the minimum bridge span distances between Shikoku and Honshu. We present a parsimonious economic framework that is largely consistent with the empirical evidence. Our results suggest that economic integration can have sizable effects on idea creation and innovation. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:25009 |
| By: | Venkat Ram Reddy Ganuthula; Kirshna Kumar Balaraman |
| Abstract: | This paper examines labor market polarization through a comparative analysis of skill-based employment and wage distributions in India and the United States during 2018-2023, with particular attention to differential automation risks and AI preparedness. Using detailed occupation-level data, automation risk metrics, and a series of statistical tests including wage premium analysis, employment share tests, and wage-employment regressions, we document significant structural differences in labor markets between developing and developed economies. Our analysis yields four key findings. First, we find statistically significant differences in employment distribution patterns, with India showing disproportionate concentration in low-skill employment compared to the US, particularly in occupations with high automation risk. Second, regression analysis reveals that wage premiums differ systematically between the two countries, with significantly larger skill-based wage gaps in India. Third, we find robust evidence of a negative relationship between employment size and wages, suggesting stronger labor supply effects in developing economies. Fourth, analysis of occupation-specific automation risk reveals that developing economies face a "double vulnerability" - concentration of employment in both low-skill occupations and jobs with higher automation potential, complicated by lower AI preparedness scores. These findings provide novel empirical evidence on how development stages influence labor market polarization patterns and carry important implications for skill development and technology adoption policies in developing economies. Our results suggest that traditional approaches to labor market development may need significant modification to account for the differential impacts of AI across development stages. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2501.15809 |
| By: | Gabor Katay (European Commission, Directorate†General for Economic and Financial Affairs); Palma Filep-Mosberger (Magyar Nemzeti Bank (Central Bank of Hungary)); Francesco Tucci (Sapienza Università di Roma) |
| Abstract: | The paper evaluates the impact of the European Commission’s Seventh Framework Programme (FP7) grants on profit†oriented firms’ post†treatment performance. Using a quasi†experimental design and a dataset covering applicants from 46 countries, we find that FP7 grants increase firms’ sales and labour productivity by about 18%. However, there is no significant impact on employment levels, pointing to potential growth barriers that prevent firms from scaling production despite improved productivity. The effectiveness of these grants varies significantly based on factors such as financial constraints, project risk profiles, market structure, and the innovation environment. Smaller, less productive firms with tighter financial constraints in technologyintensive sectors operating in concentrated markets and favourable innovation environments, particularly those undertaking longer and riskier projects, tend to benefit more. |
| Keywords: | EU funds for research and innovation; firm productivity; regression†discontinuity design. |
| JEL: | C31 G28 H57 O31 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:mnb:wpaper:2025/1 |
| By: | Michael R. Douglas; Sergiy Verstyuk |
| Abstract: | We study long-run progress in artificial intelligence in a quantitative way. Many measures, including traditional ones such as patents and publications, machine learning benchmarks, and a new Aggregate State of the Art in ML (or ASOTA) Index we have constructed from these, show exponential growth at roughly constant rates over long periods. Production of patents and publications doubles every ten years, by contrast with the growth of computing resources driven by Moore's Law, roughly a doubling every two years. We argue that the input of AI researchers is also crucial and its contribution can be objectively estimated. Consequently, we give a simple argument that explains the 5:1 relation between these two rates. We then discuss the application of this argument to different output measures and compare our analyses with predictions based on machine learning scaling laws proposed in existing literature. Our quantitative framework facilitates understanding, predicting, and modulating the development of these important technologies. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2501.17894 |