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on Technology and Industrial Dynamics |
| By: | Flavio Calvino; Luca Fontanelli |
| Abstract: | In this work we characterise French firms using artificial intelligence (AI) and explore the link between AI use and productivity. We distinguish AI users that source AI from external providers (AI buyers) from those developing their own AI systems (AI developers). AI buyers tend to be larger than other firms, but this relation is explained by ICT-related variables. Conversely, AI developers are larger and younger beyond ICT. Other digital technologies, digital skills and infrastructure play a key role for AI use, with AI developers leveraging more specialised ICT human capital than AI buyers. Overall, AI users tend to be more productive, however this is related to the self-selection of more productive and digital-intensive firms into AI use. This is not the case for AI developers, for which the positive link between AI use and productivity remains evident beyond selection. |
| Keywords: | technology diffusion, artificial intelligence, digitalisation, productivity |
| JEL: | D20 J24 O14 O33 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11466 |
| By: | Leogrande, Angelo; Drago, Carlo; Mallardi, Giulio; Costantiello, Alberto; Magaletti, Nicola |
| Abstract: | This article focuses on the propensity to patent across Italian regions, considering data from ISTAT-BES between 2004 and 2019 to contribute to analyzing regional gaps and determinants of innovative performances. Results show how the North-South gap in innovative performance has persisted over time, confirming the relevance of research intensity, digital infrastructure, and cultural employment on patenting activity. These relations have been analyzed using the panel data econometric model. It allows singling out crucial positive drivers like R&D investment or strongly negative factors, such as limited mobility of graduates. More precisely, given the novelty of approaches applied in the used model, the following contributions are represented: first, the fine grain of regional differentiation, from which the sub-national innovation system will be observed. It also puts forward a set of actionable policy recommendations that would contribute to more substantial inclusive innovation, particularly emphasizing less-performing regions. By focusing on such dynamics, this study will indirectly address how regional characteristics and policies shape innovation and technological competitiveness in Italy. Therefore, it contributes to the debate on regional systems of innovation and their possible role in economic development in Europe since the economic, institutional, and technological conditions are differentiated between various areas in Italy. |
| Keywords: | Innovation, Innovation and Invention, Management of Technological Innovation and R&D, Technological Change, Intellectual Property and Intellectual Capital |
| JEL: | O30 O31 O32 O33 O34 O35 O38 |
| Date: | 2024–12–23 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:123081 |
| By: | Domenico Delli Gatti; Roberta Terranova; Enrico Maria Turco |
| Abstract: | Can standard measures of industrial policy such as R&D subsidies or financial support for machine replacement be effective tools to reverse the current pattern of increasing market power and declining business dynamism? To answer this question we explore the effects of various industrial policy instruments in a macroeconomic agent-based model calibrated to reproduce the decline in US business dynamism over the last half-century. Our results indicate that R&D subsidies alone are insufficient to address the underlying causes of declining dynamism. They become effective, however, when combined in a policy mix with knowledge diffusion policies, particularly those favoring advanced technology adoption by small firms. In this case, industrial policy fosters growth by closing the productivity gap between leaders and laggards, and thereby curbing market power. These findings suggests a two-pronged approach to the design of industrial policy, integrating firm-level subsidies with knowledge diffusion measures and therefore ensuring that innovation and competition policies advance together. |
| Keywords: | macroeconomic dynamics, innovation, knowledge diffusion, market power, industrial policy, agent-based model |
| JEL: | C63 E32 L10 L52 O31 O33 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11544 |
| By: | Lewandowski, Piotr (Institute for Structural Research (IBS)); Szymczak, Wojciech (Institute for Structural Research (IBS)) |
| Abstract: | We study the effect of the adoption of automation technologies – industrial robots, and software and databases – on the incidence of atypical employment in 13 EU countries between 2006 and 2018. We find that industrial robots significantly increase atypical employment share, mostly through involuntary part-time and involuntary fixed-term work. We find no robust effect of software and databases. We also show that the higher trade union density mitigates the robots' impact on atypical employment, while employment protection legislation appears to play no role. Using historical decompositions, we attribute about 1-2 percentage points of atypical employment shares to rising robot exposure. |
| Keywords: | robots, automation, atypical employment, trade unions |
| JEL: | J23 J51 O33 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17544 |
| By: | Hege, Ulrich; Li, Kai; Zhang, Yifei |
| Abstract: | We study the effect of climate-related innovation on carbon emissions by analyzing supply chain networks. We find that climate innovation reduces carbon emissions at customer firms, driven by product innovations. The effect is economically significant, dominated by the most emission-intensive customer firms, gradually increases over a five-year horizon, and is significant for Scope 1 and Scope 2 emissions. We then look at the diffusion of climate innovation to new customers. We find that customers ex-hibit a strong preference for suppliers with new climate patents, that climate patents allow suppliers to attract new customers, especially customers with high environmental ratings or a large carbon footprint, and that these new customers subsequently also reduce their emissions. We use the quasi-random assignment of patent examiners and the exogenous technological obsolescence of climate patents as instruments to suggest a causal interpretation of the main findings. |
| Keywords: | climate innovation; supply chains; new customer firms; business stealing; carbon emissions; environmental scores; patent examiner leniency; technology obsoles-cence. |
| JEL: | L14 O31 O33 Q54 Q55 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130108 |
| By: | Bridget Kauma; Giordano Mion |
| Abstract: | We propose a new data resource that attempts to overcome limitations of standard firm-level datasets for the UK (like the ARD/ABS) by building on administrative data covering the population of UK firms with at least one employee. We also construct a similar dataset for France and use both datasets to: 1) Provide some highlights of the data and an overall picture of the evolution of aggregate UK and French productivity and markups: 2) Analyse the spatial distribution of productivity in both countries at a fine level of detail – 228 Travel to Work Areas (TTWAs) for the UK and 297 Zones d‘emploi (ZEs) for France – while focusing on the role of economic density. Our findings suggest that differences in firm productivity across regions are magnified in the aggregate by an increasing productivity return of density along the productivity distribution. |
| Keywords: | firm-level dataset, merging, BSD, FAME, VAT, FICUS, FARE, productivity, markups, UK, France, regional disparities, density |
| JEL: | R12 D24 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11543 |
| By: | Esther Ann Bøler; Katinka Holtsmark; Karen Helene Ulltveit-Moe; Katinka Kristine Holtsmark |
| Abstract: | We analyze how a major negative shock to the producers of fossil fuels may lead to a shift from dirty to clean R&D along the supply chain. First, we develop a theoretical framework of directed technical change, showing that adjustment costs in R&D activity can lead fossil energy sector suppliers to shift their R&D activity towards clean innovation more than other firms, as a consequence of a negative oil price shock. Second, we investigate the impact of a major drop in the oil price in 2014 on clean R&D. Relying on rich firm level trade data, we propose a novel method of identifying firms’ exposure to the price shock. We find that more exposed firms increased their clean R&D investments more than less exposed firms. Our findings contribute to the understanding of the drivers of clean technological change, which is vital to assess the effectiveness of different climate policy measures, including carbon pricing. |
| Keywords: | clean innovation, supply chains, carbon pricing |
| JEL: | D25 F18 O31 Q55 Q58 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11550 |
| By: | César Andrés Manuel; Arias Omar; Fukuzawa Daisuke; Trung Le Duong |
| Abstract: | The evidence on the final effect of industrial automation on employment is still inconclusive. We argue that automation leads to employment creation when there are greater trade opportunities because productivity growth lead to scale effects that outweigh displacement effects, in line with the traditional argument of trade gains based on comparative advantages but augmented by automation. On the import side, industrial automation increases the demand for raw materials and standardized intermediate inputs. On the export side, an increased production at lower cost benefits from greater access to the world market. Exploiting cross-country variation in population aging combined with global industry trends in robot adoption, we find that industries experiencing greater automation exhibit higher increments in their (backward and forward) participation in GVCs, output and employment, than less exposed industries; and no differential effects on the average wage or labor’s share of value added. Interestingly, our estimates suggest that greater integration into GVCs is associated with both increased robot adoption and employment gains from automation. Finally, we find that growing robot adoption in industry’s export destinations is related to increased robot adoption in the domestic market, which supports a demand-driven explanation for automation. |
| JEL: | F14 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:aep:anales:4717 |
| By: | Antonin Bergeaud (HEC Paris, CEP-LSE, CEPR); Max Deter (University of Potsdam); Maria Greve (Utrecht University); Michael Wyrwich (Groningen University) |
| Abstract: | We investigate the causal relationship between inventor migration and regional innovation in the context of the large-scale migration shock from East to West Germany between World War II and the construction of the Berlin Wall in 1961. Leveraging a newly constructed, century-spanning dataset on German patents and inventors, along with an innovative identification strategy based on surname proximity, we trace the trajectories of East German inventors and quantify their impact on innovation in West Germany. Our findings demonstrate a significant and persistent boost to patenting activities in regions with higher inflows of East German inventors, predominantly driven by advancements in chemistry and physics. We further validate the robustness of our identification strategy against alternative plausible mechanisms. We show in particular that the effect is stronger than the one caused by the migration of other high skilled workers and scientists. |
| Keywords: | patents, migration, Germany, Iron Curtain, innovation |
| JEL: | H10 N44 P20 D31 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:pot:cepadp:84 |
| By: | Qiu, Xincheng (Peking University); Yoshida, Masahiro (Waseda University) |
| Abstract: | We study the impact of climate change on the labor share. Using a newly constructed dataset combining US county-level labor shares with climate variables, we find that extreme temperatures reduce labor share. This adverse effect is more pronounced in industries with higher outdoor exposure and automation potential. We also show that extreme temperatures accelerate the adoption of industrial robots. Overall, climate change accounts for 14% of the decline in labor share during 2001–2019. In the last century, however, the opposing effects of decreased cold days and increased hot days offset each other, consistent with the well-documented constancy of labor share. |
| Keywords: | climate change, labor share, automation |
| JEL: | E25 Q54 O33 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17485 |
| By: | Fabrizio Leone |
| Abstract: | The diffusion of automation technology raises questions about the future of work, leading to calls for policy interventions. The ongoing debate centers on the decisions made by technology adopters. In this paper, I study supply-side adjustments and their role in shaping policy outcomes. I focus on the global market for industrial robots, a leading type of automation technology, where a few multinational enterprises (MNEs) dominate sales. To evaluate how these MNEs respond to policy changes, I collect new data on their characteristics and global sales networks. I then develop and estimate a multi-country general equilibrium model featuring oligopolistic multinational robot sellers. Using this model, I find that MNEs' market entry and pricing responses transmit internationally and amplify the aggregate and distributional effects of policies targeting robots. |
| Keywords: | multinational enterprises, market power, automation |
| JEL: | F10 F16 F23 L13 O33 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11537 |
| By: | Avendano, Rolando (Asian Development Bank); Tani, Massimiliano (University of New South Wales); Tolin, Lovely C. (Asian Development Bank) |
| Abstract: | In this paper, we examine whether, and if so how, an economy's deliberate policy choices of regional cooperation and integration influence underlying determinants of economic growth. Building on models of growth and innovation, we analyze the role of regional integration on labor productivity and firms' probability to innovate using data from a panel of 170 economies and 60, 000 firms over a period of two decades. Our results suggest that regionalism, as captured by metrics of regional cooperation and integration, can positively contribute to labor productivity and innovation, in addition to known factors of production. |
| Keywords: | regional integration, productivity, innovation, Asia |
| JEL: | F02 F15 O4 O30 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17495 |
| By: | Falck, Oliver (Ifo Institute for Economic Research); Guo, Yuchen (ifo Institute, University of Munich); Langer, Christina (Stanford University); Lindlacher, Valentin (Dresden University of Technology); Wiederhold, Simon (IWH Halle) |
| Abstract: | Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90, 000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether job training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without job training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that job training reduces workers' automation risk by 4.7 percentage points, equivalent to 10 percent of the average automation risk. The training-induced reduction in automation risk accounts for one-fifth of the wage returns to job training. Job training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Women tend to benefit more from training than men, with the advantage becoming particularly pronounced at older ages. |
| Keywords: | job training, human capital, automation, technological change, entropy balancing |
| JEL: | J24 J31 J61 O33 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17503 |
| By: | Dupuy, Arnaud (University of Luxembourg); Raux, Morgan (University of Luxembourg); Signorelli, Sara (CREST) |
| Abstract: | The recent digital revolution has significantly broadened the scope of IT-related tasks in most occupations in the labor market. In this paper, we document these changes, we propose a novel conceptual framework for thinking about the effect of technological change that incorporates the changing task distance between occupations, and we investigate its impact on worker mobility using a gravity equation approach. Our results reveal that the evolution of skill distance between jobs significantly affected mobility patterns, disproportionately favoring workers with preexisting knowledge of digital tools. Finally, we micro-found our gravity equation through a matching model to evaluate mobility in counterfactual scenarios without technological change. |
| Keywords: | occupation mobility, technological change, search and matching |
| JEL: | J23 J24 J62 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17535 |
| By: | Thiemo Fetzer; Peter John Lambert; Bennet Feld; Prashant Garg |
| Abstract: | This paper leverages generative AI to build a network structure over 5, 000 product nodes, where directed edges represent input-output relationships in production. We layout a two-step ‘build-prune’ approach using an ensemble of prompt-tuned generative AI classifications. The ’build’ step provides an initial distribution of edge-predictions, the ‘prune’ step then re-evaluates all edges. With our AI-generated Production Network (AIPNET) in toe, we document a host of shifts in the network position of products and countries during the 21st century. Finally, we study production network spillovers using the natural experiment presented by the 2017 blockade of Qatar. We find strong evidence of such spill-overs, suggestive of on-shoring of critical production. This descriptive and causal evidence demonstrates some of the many research possibilities opened up by our granular measurement of product linkages, including studies of on-shoring, industrial policy, and other recent shifts in global trade. |
| Keywords: | supply-chain network analysis, large language models, on-shoring, industrial policy, trade wars, econometrics-of-LLMs |
| JEL: | F14 F23 L16 F52 O25 N74 C81 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11497 |
| By: | Manuel Hoffmann; Sam Boysel; Frank Nagle; Sida Peng; Kevin Xu |
| Abstract: | Recent advances in artificial intelligence (AI) technology demonstrate considerable potential to complement human capital intensive activities. While an emerging literature documents wide-ranging productivity effects of AI, relatively little attention has been paid to how AI might change the nature of work itself. How do individuals, especially those in the knowledge economy, adjust how they work when they start using AI? Using the setting of open source software, we study individual level effects that AI has on task allocation. We exploit a natural experiment arising from the deployment of GitHub Copilot, a generative AI code completion tool for software developers. Leveraging millions of work activities over a two year period, we use a program eligibility threshold to investigate the impact of AI technology on the task allocation of software developers within a quasi-experimental regression discontinuity design. We find that having access to Copilot induces such individuals to shift task allocation towards their core work of coding activities and away from non-core project management activities. We identify two underlying mechanisms driving this shift - an increase in autonomous rather than collaborative work, and an increase in exploration activities rather than exploitation. The main effects are greater for individuals with relatively lower ability. Overall, our estimates point towards a large potential for AI to transform work processes and to potentially flatten organizational hierarchies in the knowledge economy. |
| Keywords: | generative artificial intelligence, digital work, open source software, knowledge economy |
| JEL: | H40 O30 J00 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11479 |