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on Technology and Industrial Dynamics |
| By: | Jaccoud, Florencia (RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn) |
| Abstract: | This paper examines the linkages between occupational exposure to recent automation technologies and inequality across 19 European countries. Using data from the European Union Structure of Earnings Survey (EU-SES), a fixed-effects model is employed to assess the association between occupational exposure to artificial intelligence (AI) and to industrial robots - two distinct forms of automation -and within occupation wage inequality. The analysis reveals that occupations with higher exposure to robots tend to have lower wage inequality, particularly among workers in the lower half of the wage distribution. In contrast, occupations more exposed to AI exhibit greater wage dispersion, especially at the top of the wage distribution. We argue that this disparity arises from differences in how each technology complements individual worker abilities: robot-related tasks often complement routine physical activities, while AI-related tasks tend to amplify the productivity of high-skilled, cognitively intensive work. |
| JEL: | J31 J24 O15 O33 |
| Date: | 2025–04–22 |
| URL: | https://d.repec.org/n?u=RePEc:unm:unumer:2025013 |
| By: | Ribeiro, Marcos; Prettner, Klaus |
| Abstract: | How do new technologies affect economic growth and the skill premium? To answer this question, we analyze the impact of industrial robots and artificial intelligence (AI) on the wage differential between low-skill and high-skill workers across 52 countries using counterfactual simulations. In so doing, we extend the nested CES production function framework of Bloom et al. (2025) to account for cross-country income heterogeneity. Confirming prior findings, we show that the use of industrial robots tends to increase wage inequality, while the use of AI tends to reduce it. Our contribution lies in documenting substantial heterogeneity across income groups: the inequality-increasing effect of robots and the inequality-reducing effects of AI are particularly strong in high-income countries, while they are less pronounced among middle- and lower-middle income countries. In addition, we show that both technologies boost economic growth. In terms of policy recommendations, our findings suggest that investments in education and skill-upgrading can simultaneously raise average incomes and mitigate the negative effects of automation on wage inequality. |
| Keywords: | Automation Industrial Robots AI Skill premium |
| JEL: | J31 O33 |
| Date: | 2025–04–28 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:124633 |
| By: | Patrick Llerena; Corentin Lobet; André Lorentz |
| Abstract: | We propose a disaggregated representation of production using an agent-based fund-flow model that emphasizes inefficiencies, such as factor idleness and production instability, and allows us to explore their emergence through simulations. The model incorporates productivity dynamics (learning and depreciation) and is extended with time-saving process innovations. Specifically, we assume workers possess inherent creativity that flourishes during idle periods. The firm, rather than laying off idle workers, is assumed to harness this potential by involving them in the innovation process. Results show that a firm’s organizational and managerial decisions, the temporal structure of the production system, the degree of workers’ learning and forgetting, and the pace of innovation are critical factors influencing production efficiency in both the short and long term. The coevolution of production and innovation processes emerges in our model through the two-sided effects of idleness: the loss of skills through forgetting and the deflection of time from the production of goods to the production of ideas giving birth to idleness-driven innovations. In doing so, it allows us to question the status of labour as an adjustment variable in a productive organisation. The paper concludes by discussing potential solutions to this issue and suggesting avenues for future research. |
| Keywords: | Production Theory; Firm Theory; Agent-based model; Idleness; Innovation; Fund-flow. |
| JEL: | D21 D24 D83 J24 L25 O31 O33 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ulp:sbbeta:2024-45 |
| By: | David Marguerit |
| Abstract: | Artificial intelligence (AI) is reshaping the labor market by changing the task content of occupations. This study investigates the impact of AI development on the emergence of new work, employment, and wages in the United States from 2015 to 2022. I develop innovative methods to measure occupational and industry exposure to AI technologies that substitute labor (automation AI ) or enhance workers' output (augmentation AI), and to identify new work (i.e., new job titles). To address endogeneity, I use instrumental variable estimators, leveraging AI development in countries with limited economic ties to the United States. The findings indicate that automation AI negatively impacts new work, employment, and wages in low-skilled occupations, while augmentation AI fosters the emergence of new work and raises wages for high-skilled occupations. These results suggest that AI may contribute to rising wage inequality. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2503.19159 |
| By: | Xincheng Qiu (Guanghua School of Management, Peking University); Masahiro Yoshida (Department of Political Science and Economics, Waseda University, Tokyo) |
| 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: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:wap:wpaper:2507 |
| By: | Agnolin, Paolo (Bocconi University); Anelli, Massimo (Bocconi University); Colantone, Italo (Bocconi University); Stanig, Piero (Bocconi University) |
| Abstract: | Labor unions play a crucial role in liberal democracies by influencing labor market and political dynamics, organizing workers’ demands and linking them to parties. However, their importance has progressively diminished in the last decades. We suggest that technological change—and industrial robotization in particular—has contributed to weakening the role of unions. We produce novel granular data on union density at the sub-national and industry level for 15 countries of western Europe over 2002-2018. Employing these data, we estimate the impact of industrial robot adoption on unionization rates. We find that regions more exposed to automation experience a decrease in union density. The decline in unionization occurs via a compositional effect, i.e., a reallocation of employment away from traditionally unionized industries towards less unionized ones. On the other hand, there is no clear evidence of a systematic reduction in union density within industries more exposed to automation. |
| Keywords: | robots, automation, labor unions, Europe, regions |
| JEL: | J5 J2 O3 P0 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17864 |
| By: | Arthur Jacobs (Ghent University) |
| Abstract: | I evaluate the link between automation and the rise in top income concentration when inequality matters for macro. The novel mechanism is that automation redistributes income towards high-wealth households who save more, which lowers the interest rate and incites firms to automate more. To operationalize this, I build a tractable heterogeneous-agent model (1) with wealth in the utility function as a luxury good, and (2) a firm-side choice on automation. I find that introducing realistic savings rate heterogeneity largely eliminates the need for ad hoc technology shifts. Rather, automation is the outcome of increased top income concentration, not just its driver. |
| Keywords: | automation, wealth inequality, capitalist spirit, task-based production, heterogeneous-agent |
| JEL: | E25 J23 O33 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:nbb:reswpp:202505-475 |
| By: | Minetti, Raoul; Murro, Pierluigi; Peruzzi, Valentina |
| Abstract: | We investigate the influence of firms' global status on the allocation of credit during a financial crisis. Using data on 15, 000 businesses from seven European countries, we find that firms participating in global value chains were 25% less likely to be rationed by banks during the 2009 Great Recession. We next match information on the geography of firms' value chains with data on banks' branch and subsidiary networks. We find that banks especially insulated from credit rationing firms with supply chain relationships in the countries where banks have the largest presence. The results reveal that banks aimed at reducing spillovers on their lending and consulting activities with global chains rather than leveraging their knowledge of internationally traded products. |
| Keywords: | Banks; global value chains; financial crises; spillovers. |
| JEL: | D22 F10 G20 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:124369 |
| By: | Bracco, Jessica; Brambilla, Irene; Cerimelo, Manuela; César, Andrés; Falcone, Guillermo |
| Abstract: | This paper studies concentration and market power in Chile and Colombia and the role that globalization and automation have had in shaping these two phenomena. Using panels of firm surveys, we compute firm-level markups and industry-level concentration measures. Applying a difference in differences methodology that relies on variation across industries in exposure to robotization technology, import competition from China and tariff declines in US markets due to the signature of free trade agreements, we study the causal effects of these shocks on market power and concentration. We find that, while robotization technology has reduced markups on average, it has increased markups and total factor productivity of top industry firms; that the pro-competitive effect of Chinese imports has indeed led to a decrease in market power of domestic firms; and that increased export opportunities due to free trade agreements have led to an increase in market power, with interesting heterogeneities across the two countries. |
| Keywords: | Mark-ups;Market concentration;trade agreements;Robotization |
| JEL: | L11 F14 F61 O33 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:14099 |
| By: | Hanming Fang (University of Pennsylvania and NBER); Ming Li (Chinese University of Hong Kong); Guangli Lu (Chinese University of Hong Kong) |
| Abstract: | We decode China’s industrial policies from 2000 to 2022 by employing large language models (LLMs) to extract and analyze rich information from a comprehensive dataset of 3 million documents issued by central, provincial, and municipal governments. Through careful prompt engineering, multistage extraction and refinement, and rigorous verification, we use LLMs to classify the industrial policy documents and extract structured information on policy objectives, targeted industries, policy tones (supportive or regulatory/suppressive), policy tools, implementation mechanisms, and intergovernmental relationships, etc. Combining these newly constructed industrial policy data with micro-level firm data, we document four sets of facts about China’s industrial policy that explore the following questions: What are the economic and political foundations of the targeted industries? What policy tools are deployed? How do policy tools vary across different levels of government and regions, as well as over the phases of an industry’s development? What are the impacts of these policies on firm behavior, including entry, production, and productivity growth? We also explore the political economy of industrial policy, focusing on top-down transmission mechanisms, policy persistence, and policy diffusion across regions. Finally, we document spatial inefficiencies and industry-wide overcapacity as potential downsides of industrial policies. |
| Keywords: | Large Language Models; Industrial Policy; Policy Diffusion; Revealed Comparative Advantage; Overcapacity |
| JEL: | L52 O25 C55 |
| Date: | 2025–05–12 |
| URL: | https://d.repec.org/n?u=RePEc:pen:papers:25-012 |
| By: | Kuai, Wenjing (Hunan University); Elliott, Robert J. R. (University of Birmingham); Okubo, Toshihiro (Keio University); Ozgen, Ceren (University of Birmingham) |
| Abstract: | To address climate change concerns, Japan is accelerating the greening of its economy. In this paper we analyze the characteristics of the workers that are contributing to the green transition and estimate the so-called green wage premium. Using propriety data from a recent worker-level survey for Japan, we provide a continuous measure of the degree to which a job can be considered green and document how green jobs are different from non-green jobs by sector, occupation and different demographics. Our structural model estimates of a green wage premium show that the hourly wage of green workers is 7.3% higher on average than non-green work- ers. A 10% increase in the green intensity of a job is shown to increase average hourly wages by 0.8%. Decomposition results suggest that the explainable part of the wage premium is largely due to task differences, gender disparities (in lower percentiles), and occupation. The unexplained part of the green wage premium are found mainly in high-paying green jobs where certain characteristics appear to be better rewarded, possibly driven by supply and demand imbalances. |
| Keywords: | Japan, wage gap, employment, green jobs, green transition, climate change |
| JEL: | Q50 Q52 J24 J31 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17878 |
| By: | Eric A. Hanushek; Simon Janssen; Jacob D. Light; Lisa Simon |
| Abstract: | We analyze the full distribution of displaced workers’ earnings losses using a new method that combines matching and synthetic control group approaches at the individual level. We find that the distribution of earnings losses is highly skewed. Average losses, as estimated by conventional event studies, are driven by a small number of workers who suffer catastrophic losses, while most recover quickly. Observable worker characteristics explain only a small fraction of the variance in earnings losses. Instead, we find substantial heterogeneity in earnings losses even among workers displaced by the same firm who have identical observed characteristics such as education, age, and gender. Workers with minimal earnings losses adjust quickly by switching industries, occupations, and especially regions, while comparable workers with catastrophic losses adjust slowly, even though they are forced to make comparable numbers of switches in the long run. |
| Keywords: | displacement losses, synthetic control groups, distributions of treatment effects. |
| JEL: | J24 J64 O30 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11865 |