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on Technology and Industrial Dynamics |
| By: | Mahmut Zeki Akarsu (College of Economics and International Trade, Pusan National University, Busan, Korea); Cassidy Hruz (Vanderbilt Law School, Vanderbilt University); Zeynep Yom (Department of Economics, Villanova School of Business, Villanova University) |
| Abstract: | This paper examines how firms adjust their innovative activities during recessions and whether they learn from past downturns. Using COMPUSTAT data linked with patent and citation information, we analyze U.S. firms across four major recessions and test whether R&D expansion in one recession predicts R&D investment in the next. Exploiting recessions as exogenous shocks to the economy for identification, we find that firms performing above the median during the 2001 recession invested substantially more in R&D during the Great Recession. These learning effects are stronger for small firms, firms with high bond ratings, and those in high-technology or high-opportunity sectors, and weaker in concentrated industries. Earlier recessions also have a persistent, though gradually diminishing, effect on later downturns. Instrumental-variables and propensity-score-matching analyses confirm that these patterns reflect a learning mechanism consistent with creative accumulation. |
| Keywords: | R&D, innovation, patents, business cycles, COMPUSTAT |
| JEL: | E32 G30 O32 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:vil:papers:62 |
| By: | Storm, Eduard (Institute for Advanced Studies (IHS) and RWI – Leibniz Institute for Economic Research); Gonschor, Myrielle (Kienbaum Consultants); Schmidt, Marc Justin (TU Dortmund, RTG 2484) |
| Abstract: | We study how artificial intelligence (AI) affects workers’ earnings and employment stability, combining German job vacancy data with administrative records from 2017–2023. Identification comes from changes in workers’ exposure to local AI skill demand over time, instrumented with national demand trends. We find no meaningful displacement or productivity effects on average, but notable skill heterogeneity: expert workers with deep domain knowledge gain while non-experts often lose, with returns shaped by occupational task structures. We also document AI-driven reinstatement effects toward analytic and interactive tasks that raise earnings. Overall, our results imply distributional concerns but also job-augmenting potential of early AI technologies. |
| Keywords: | AI, Online Job Vacancies, Skill Demand, Worker-level Analysis, Employment, Earnings, Expertise |
| JEL: | D22 J23 J24 J31 O33 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:ihs:ihswps:number61 |
| By: | Juan S. Mora-Sanguinetti; Cristina Peñasco; Rok Spruk |
| Abstract: | This paper analyses the effect 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 2008 – 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 results 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: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:bfr:banfra:1016 |
| By: | Massimiliano Mazzanti (Università degli studi di Ferrara); Alessandro Montanaro (Università degli studi di Ferrara); Fabiola Onofrio (Università degli studi di Ferrara); Emy Zecca (Università degli studi di Ferrara) |
| Abstract: | This work investigates sustainability-oriented innovation among Italian small and medium-sized enterprises (SMEs) within the broader context of the European twin transition toward sustainability and digitalization. Based on survey data from 740 manufacturing firms, it analyses the diffusion of research and development activities, digital technologies, and circular economy practices across firm sizes and regions. The results reveal a persistent dualism: medium and large firms, mostly located in northern regions, show higher levels of innovation and digital adoption, while smaller firms remain limited by financial and structural constraints. Circular innovation largely focuses on efficiency measures, whereas advanced strategies such as eco-design remain rare. Digitalization acts as both a driver and an enabler of sustainable transformation but progresses unevenly across territories. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:srt:wpaper:1225 |
| By: | Ruth Appel; Peter McCrory; Alex Tamkin; Miles McCain; Tyler Neylon; Michael Stern |
| Abstract: | In this report, we document patterns of Claude usage over time, in 150+ countries, across US states, and among businesses deploying Claude through the API. Based on a privacy-preserving analysis of 1 million conversations on Claude.ai and 1 million API transcripts, we have four key findings: (1) Users increasingly entrust Claude with more autonomy, with directive task delegation rising from 27% to 39% in the past eight months. (2) Claude usage is geographically concentrated with high income countries overrepresented in global usage relative to their working age population. (3) Local economic considerations shape patterns of use both in terms of topic and in mode of collaboration with Claude. (4) API customers use Claude to automate tasks with greater specialization among use cases most amenable to programmatic access. To enable researchers and policymakers to further study the impact of AI on the economy, we additionally open-source the underlying data for this report. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.15080 |
| By: | Niklas Engbom; Hannes Malmberg; Tommaso Porzio; Federico Rossi; Todd Schoellman |
| Abstract: | Chandler (1977) shows that large firms require hierarchies of white-collar workers to coordinate complex production. We document that this insight continues to hold globally today, and we show that low education levels in developing countries limit the supply of white-collar workers and constrain firm size. We extend the occupational choice model of Lucas (1978) to allow entrepreneurs to reorganize their firms by allocating administrative tasks to hired professionals, which brings the firm closer to constant returns to scale. We calibrate the model to be consistent with cross-sectional microdata and validate it using quasi-experimental and experimental evidence on the effects of educational expansions and management training interventions. Skills explain two-thirds of the reorganization of production into large firms with economic development, while structural transformation and reductions in barriers are needed to explain the remaining shift. |
| JEL: | E0 O0 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34483 |
| By: | Qiulin Ke; Fangchen Zhang |
| Abstract: | Empirical studies provide evidence that commercial real estate with BREME, LEED, ECP, or Energy Star certifications command sale and rent premiums. However, there is a regional gap in green building distribution, often influenced by property market returns and underlying economic conditions in these areas. This paper empirically investigates the factors driving the transformation of green buildings across regions in England and Wales, focusing on regional economic development, green jobs provision, deprivation and commercial real estate market dynamics. We use the building locations of EPC ratings that meet the UK government minimum standards (i.e. EPC rating A-C) to explore the spatial clustering of green building practices in commercial buildings in England and Wale and explore the factors that cause the spatial difference of green buildings. |
| Keywords: | Green Building; social economic development; Spatial Distribution; UK |
| JEL: | R3 |
| Date: | 2025–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:arz:wpaper:eres2025_234 |
| By: | Leonardo Bursztyn; Alex Imas; Rafael Jiménez-Durán; Aaron Leonard; Christopher Roth |
| Abstract: | Anxiety about falling behind can drive people to embrace emerging technologies with uncertain consequences. We study how social forces shape demand for AI-based learning tools early in the education pipeline. In incentivized experiments with parents—key gatekeepers for children’s AI adoption—we elicit their demand for unrestricted AI tools for teenagers’ education. Parental demand rises with the share of other teenagers using the technology, with social forces increasing willingness to pay for AI by more than 60%. Providing information about potentially adverse effects of unstructured AI use negatively shifts beliefs about the merits of AI, but does not change individual demand. Instead, this information increases parents’ preference for banning AI in schools. Follow-up experiments show that social information has little effect on beliefs about AI quality, perceived skill priorities, or support for bans, suggesting that effects operate through social pressure rather than social learning. Our evidence highlights social pressure driving individual technology adoption despite widespread support for restricting its use. |
| JEL: | D83 D91 I20 O33 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34488 |
| By: | Andrés Erosa; Luisa Fuster; Gueorgui Kambourov; Richard Rogerson |
| Abstract: | Two robust empirical facts are that mean wages and cross-sectional wage dispersion both increase over the life cycle. We study how these two changes vary across occupations and document a strong positive correlation: occupations with high mean wage growth over the life cycle also exhibit greater increases in cross-sectional wage dispersion. We develop a novel dynamic Roy model that features both static and dynamic comparative advantage and show that it can account for the variation in life cycle wage distributions across high and low wage occupations. Dynamic comparative advantage reflects individual heterogeneity in occupation specific learning abilities and is the dominant force that shapes occupation choice in our model. We highlight several important implications of dynamic comparative advantage and show that our model captures the data better than a benchmark model that features persistent shocks. |
| JEL: | E24 J24 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34481 |
| By: | Byrne, Stephen (Central Bank of Ireland); Goodhead, Robert (Central Bank of Ireland) |
| Abstract: | This paper decomposes the sources of capital misallocation at the country and industry level in Europe. Using a comprehensive dataset of European firms from 19 countries, we find that the majority of the observed misallocation stems from persistent firm-specific distortions, with a smaller role for adjustment costs and uncertainty. We document substantial differences in the sources of misallocation across industries. Our analysis reveals strong correlations between these permanent distortions and industry-level variation in both financial factors, and factors relating to productivity. Understanding the factors driving capital misallocation is important for policymakers seeking to address productivity constraints and stimulate growth in the long run. |
| JEL: | E0 O11 O4 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:cbi:wpaper:11/rt/25 |