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on Technology and Industrial Dynamics |
| By: | Anna Matysiak (Interdisciplinary Centre for Labour Market and Family Dynamics, Faculty of Economic Sciences, University of Warsaw); Linus Andersson (Swedish Institute for Social Research, Stockholm University); Wojciech Hardy (Interdisciplinary Centre for Labour Market and Family Dynamics, Faculty of Economic Sciences, University of Warsaw) |
| Abstract: | This study examines whether long-term structural labour market change, driven by industrial robotization, has influenced family formation and union stability in Sweden. Linking Swedish population register data (1994–2017) with sector-level measures of robot penetration, we analyse transitions into first marriage, first, second, and third births, and divorce. We distinguish between current exposure to robotization among employed workers and residual exposure among individuals who exited employment in robotizing sectors. Event-history models are complemented by an instrumental-variable approach that exploits cross-national variation in robot adoption to strengthen causal interpretation. On average, we find only weak associations between robotization and family transitions. However, substantial heterogeneity emerges by educational attainment. Among low- and medium-educated women and men, higher exposure to automation is linked to lower birth risks, weaker marriage formation, and higher divorce risks. In contrast, highly educated individuals experience neutral or positive associations between automation and family formation, alongside greater union stability. We conclude that the aggregate contribution of structural labour market change caused by industrial automation to Sweden’s post-recession fertility decline appears limited, automation contributes to widening educational disparities in family trajectories and reinforces cumulative disadvantage across labour market and family domains. |
| Keywords: | labour market, technology, industrial robots, family, fertility |
| JEL: | J31 J13 O33 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:war:wpaper:2026-5 |
| By: | Kateryna Tkach (Gran Sasso Science Institute); Alberto Marzucchi (Gran Sasso Science Institute); Ugo Rizzo (Department of Mathematics and Computer Science, University of Ferrara); Michela Borghesi (Department of Economics and Management, University of Ferrara) |
| Abstract: | We contribute to the literature on the green, digital and twin transitions by providing novel evidence on their implications for industrial dynamics. In particular, we investigate whether the local supply of skills in the green, digital and twin domains is related to firm entry and exit at the NUTS3 level in Italy. We exploit a recently created dataset on the near-universe of Italian university programme descriptions to capture the skills provided through higher education. We find that the supply of green, digital and twin skills enhances opportunities for firm entry. We rule out the possibility that this effect simply reflects the supply of high-skilled labour in general. The supply of green skills may induce higher industrial renewal, being it also correlated with higher exit rates. |
| Keywords: | skill supply; university graduates; industrial dynamics; local economic performance |
| JEL: | O33 Q55 J24 R11 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:srt:wpaper:0726 |
| By: | Christian Gschwendt; Martina Viarengo; Thea S. Zoellner |
| Abstract: | The economic impact of technological change will critically depend on how future workers invest in their human capital. Yet, little is known about how future workers themselves evaluate and choose their educational and occupational paths in light of emerging technologies. This paper examines how adolescents currently at the school-to-work transition stage value working with generative artificial intelligence (GenAI) in their future occupations, and how automation risk and opportunities for continuing education shape these preferences. We field a discrete-choice experiment among a nationally representative sample of over 7, 000 Swiss adolescents aged around 15. We find that adolescents generally exhibit an aversion to collaborating with GenAI at work, with females consistently more averse than males. However, preferences are nuanced: adolescents welcome greater GenAI collaboration, provided that GenAI usage levels remain moderate and that it is not accompanied by increases in job-automation risk. Finally, continuing education opportunities in occupations improve attitudes towards working with GenAI across genders. Our results challenge simple narratives of technology acceptance or rejection, revealing that adolescents' willingness to work with GenAI depends on how it is implemented — its intensity, associated displacement risks, and accompanying skill development - rather than the technology itself. Our findings suggest that the way future workers value GenAI collaboration in their career choices critically depends on its intensity and on the interplay with automation risk and AI-related educational opportunities. |
| Keywords: | occupational choice, gender gaps, GenAI, choice experiment, continuing education, automation risk |
| JEL: | I24 J24 O33 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:iso:educat:0251 |
| By: | Imen Bouhlel (ESSEC Business School, France); Nathalie Lazaric (Université Côte d'Azur, CNRS, GREDEG, France); Paolo Zeppini (Université Côte d'Azur, CNRS, GREDEG, France) |
| Abstract: | Climate change calls for a transition to a more sustainable economy. Incumbent technologies pose a barrier to the diffusion of innovative solutions. Furthermore, the benefits of novel sustainable practices, such as recycling, can be offset by the adoption of obsolete polluting technologies. Understanding the mechanism of competitive diffusion is crucial for designing policies that favour promising but underdeveloped technologies. We propose an agent-based model where adoption occurs in a social network by word-of-mouth, in a percolation framework. We study how learning affects competitive diffusion and find that small differences in technologies' costs lead to large differences in their diffusion sizes. In addition, increasing the number of early adopters can back-fire and hinder overall diffusion. We calibrate the model to data on plastic waste recycling, where alternative solutions such as mechanical and physical/chemical technologies compete for a new market. Green public procurement, tax exemption and R&D boost are implemented for triggering sustainable transitions. The direction of technical change is discussed, as well as the role of policymakers in creating a shift in the plastic value chain. |
| Keywords: | Agent-based modeling; Learning curves; Mission-oriented policies; Networks; Percolation |
| JEL: | O33 Q55 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:gre:wpaper:2026-04 |
| By: | Loren Brandt; Feitao Jiang; Yao Luo; Yingjun Su |
| Abstract: | This paper examines how the geographic distribution of supply and demand shapes market power in the Chinese steel industry. Drawing on novel data, we develop and estimate an equilibrium model that accommodates spatial demand variations and rich firm heterogeneity—encompassing differences in location, product quality, production coefficients, and cost efficiencies. Using this framework, we simulate the impact of shifts in downstream demand and evaluate the welfare implications of mergers under various market frictions—an issue central to China’s industrial policy. We show that consolidation design is central to welfare outcomes: mergers led by more efficient firms and confined within regions generate substantially larger gains than nationally coordinated consolidation centered on large incumbents. The realized 2018–2024 merger wave achieved only a fraction of attainable welfare improvements. Our simulation results also suggest that as the geographic locus of demand evolves, the effects of industrial reorganization hinge critically on how supply adjusts across regions. |
| Keywords: | Spatial Differentiation, Capacity Misalignment, Market Power, Merger Analysis, Sales Aggregation |
| JEL: | G34 L13 L61 R12 |
| Date: | 2026–02–25 |
| URL: | https://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-820 |
| By: | Jan LukÅ¡iÄ; Jörg Peschner; Giuseppe Piroli |
| Abstract: | We find that patents registered by multinational enterprises (MNEs) in tax havens help avoid taxes in the EU but fail to increase the total factor productivity (TFP) of EU-located group members. We conclude that many of those patents' prime purpose is not to make technology available and then diffuse it smoothly within the group. It is rather to avoid taxes in the EU by shifting profits to low-tax offshore entities. We suggest that implementing a comprehensive system of withholding taxes on outbound royalty payments could reduce profit-shifting associated with patents, thereby fostering more innovative and efficient uses of intellectual property. |
| Keywords: | Multinational enterprises, taxes, TFP, innovation. |
| JEL: | D24 F38 H21 H25 O32 |
| Date: | 2026–01–04 |
| URL: | https://d.repec.org/n?u=RePEc:eei:rpaper:eeri_rp_2026_04 |
| By: | Emin Dinlersoz; Timothy Dunne; John C. Haltiwanger; Veronika Penciakova |
| Abstract: | The business entry literature typically observes firms only at the first hire. We provide a new perspective using linked administrative microdata tracking the universe of U.S. business applications and their transition into employer firms. We model entry as a two-stage process: pursuit of a business idea (proxied by a business application) and implementation (transition). Results show these margins are distinct and associate differently with local conditions. While both margins matter, high-startup locations are characterized by high application intensity, whereas low-startup locations exhibit low transition rates, suggesting geographic disparities in entry arise from different dynamics at each stage of the entrepreneurial process. |
| JEL: | L26 M13 R12 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34881 |
| By: | Nicolas Crouzet; Pulak Ghosh; Apoorv Gupta; Filippo Mezzanotti |
| Abstract: | We show that the age composition of the population can shape the speed at which businesses adopt new technologies, using evidence from mobile payments in India. Consumers' propensity to use new payment technologies declines with age, creating stronger incentives for businesses serving younger customers to accept these technologies. We document this pattern in the rollout of a mobile payment option by a major fintech company. A model where consumer attitudes toward technology vary by age implies that business adoption is inefficiently low, with the young bearing disproportionate welfare losses from network externalities. Jointly subsidizing transaction and adoption costs restores efficiency. |
| JEL: | G23 J11 O33 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34885 |
| By: | Arvanitopoulos, Theodoros; Bulian, Simon; Wilson, Charlie; Jordan, Andrew J; Tosun, Jale; Vasilakos, Nicholas |
| Abstract: | The corpus of national climate policies continues to grow - but to what effect? Using data on 3, 917 policy instruments across 43 OECD countries and major emerging economies from 2000-2022, we show that national climate policy portfolios specializing in instrument types and sectors are associated with faster reductions in fossil CO2 emission intensity. Supported by exemplar country case studies, we also provide quantitative evidence that the effectiveness of climate policy is amplified by long-term emission reduction targets and the presence of dedicated governmental bodies including ministries and intergovernmental organisations. The cumulative effect of all climate policy portfolios over our study period amounts to 3.1 GtCO2 fewer emissions in 2022 relative to a no-policy counterfactual - substantially less than what's needed to stay on track for the Paris Agreement goals. |
| JEL: | N0 |
| Date: | 2026–01–23 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:137198 |