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Acemoglu, Daron & Jonas Löbbing (2026): Automation and Polarization. In: Journal of Political Economy, Jg. 134, H. 3, S. 1017-1072. DOI:10.1086/739330

Abstract

"We develop an assignment model of automation. Each of a continuum of tasks of variable complexity is assigned to either capital or one of a continuum of labor skills. We characterize conditions for interiorautomation, whereby tasks of intermediate complexity are performed by capital. Interior automation arises when the most skilled workers have a comparative advantage in the most complex tasks relative to capital, and when the wages of the least skilled workers are sufficiently low relative to both their own productivity and the effective cost of capital in low-complexity tasks. Minimum wages and other sourcesof higher wages at the bottom make interior automation less likely. Starting with interior automation, a reduction in the cost of capital (or an increase in capital productivity) causes employment and wage polarization. Specifically, further automation pushes workers into tasks at the lower and upper ends ofthe task distribution. It also monotonically increases the skill premium above a threshold and reduces the skill premium below this threshold. Moreover, automation tends to reduce the real wage of Workers with comparative advantage profiles close to that of capital. We show that large enough increases in capital productivity ultimately induce a transition to low-skill automation and qualitatively alter the effects of automation—thereafter inducing monotone increases in skill premia rather than wage polarization." (Author's abstract, IAB-Doku) ((en))

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Casas, P., E. Fernández-Macías, F. Martínez-Plumed, E. Gómez, I. González-Vázquez & S. Salotti (2026): Revisiting the occupational impact of AI in the generative AI era. (JRC working papers series on labour, education and technology 2026,02), Sevilla, 71 S.

Abstract

"Generative AI is reshaping what artificial intelligence can do in the workplace, calling into question pre-GenAI assessments of which workers and tasks are most exposed. In this paper we trace the evolution of AI exposure in the European labour market from 2008 to 2024 by linking 352 AI benchmarks to 14 cognitive abilities, 108 work tasks and 127 ISCO-3 occupations, weighting benchmarks by their research intensity in the AI literature and thus deriving AI exposure by cognitive ability. Bundling work tasks into occupations based on intensity indicators, we explore occupational exposure to AI. We find that the cognitive abilities most exposed to the recent surge of AI research are ideas-related, such as attention and search, comprehension and expression and logical reasoning. Because the associated information processing and problem-solving tasks are the most transversal across occupations, we find an exponential increase in AI exposure across all occupational categories of workers, even though comparatively high-skilled occupations are more exposed than elementary occupations. This points at a substantial and transversal labour market impact of AI." (Author's abstract, IAB-Doku) ((en))

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Lamperti, Fabio & Davide Castellani (2026): Automation and the risk of labor market exclusion across Europe. In: Structural Change and Economic Dynamics, Jg. 77, S. 62-76. DOI:10.1016/j.strueco.2025.12.014

Abstract

"Labor market exclusion represents a major concern in several European economies, particularly affecting highly exposed demographic groups. This paper examines the potential effect of automation technologies on the risk of being locked into protracted unemployment or inactivity, using Labour Force Survey data for the European Union 27 countries and the United Kingdom, between 2009 and 2019. Our study employs repeated cross-sections of individual-level data to compute probabilities of exclusion outcomes due to automation adoption, controlling for several individual, macroeconomic, and region-specific characteristics, and for potential selection mechanisms. Findings highlight that, on average, the adoption of new automation technologies is associated with a higher probability of being inactive. This is consistent with the view that automation may exacerbate job insecurity, psychological discouragement, and detachment from job-seeking. This relationship is heterogeneous across demographic groups, with younger individuals being relatively more affected." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))

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Pouliakas, Konstantinos & Giulia Santangelo (2026): Human-centred digital transitions and skill mismatches in European workplaces. (CEDEFOP working paper series / European Centre for the Development of Vocational Training 2026,01), Luxembourg, 163 S. DOI:10.2801/9894877

Abstract

"New digital and artificial intelligence technologies are fast reshaping skill requirements in the EU labour market, fostering skill mismatches. There are marked concerns about the potentially adverse consequences of automation and AI on employment, as well as the lagging competitiveness of EU economies as individuals’ upskilling or reskilling is failing to adapt. To deepen understanding of how digitalisation is affecting the nature of work and skill mismatches in EU labour markets, Cedefop carried out the second wave of the European skills and jobs survey in 2021. In this special edition of Cedefop’s working paper series, ten original, short contributions have been drafted in which researchers explore in depth, for the first time, the ESJS2 microdata. The publication presents a wealth of focused and robust empirical analyses, covering a wide range of different issues on how the digital transition is affecting jobs, skills and training in Europe." (Author's abstract, IAB-Doku) ((en))

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Alasalmi, Juho (2025): Artificial Intelligence in the European Labour Markets. (DIFIS-Impuls 2026,1), Duisburg ; Bremen, 4 S.

Abstract

"This review surveys the emerging evidence regarding the effects of artificial intelligence technologies in the labour market and on labour market inequality through the lens of the theoretical framework of task-based production and the literature in the field of economics on technological change. The evidence analysed concerns the time period after the early 2010s, with an emphasis on the effects of generative AI after 2022. The focus is on research studying European labour markets. After outlining the context of routine- and skill-biased technological change and job polarisation, the existing evidence regarding AI adoption in production and its effects on productivity and employment is reviewed. The review concludes with a discussion on labour market policy that mediates the effects of AI on the distribution of productivity gains and the direction of technological change and a consideration of the effect of technological change on attitudes toward labour market policy and democracy itself." (Author's abstract, IAB-Doku) ((en))

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Bertermann, Alexander, Wolfgang Dauth, Jens Suedekum & Ludger Wößmann (2025): Training or Retiring? How Labor Markets Adjust to Trade and Technology Shocks. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 18247), Bonn, 47 S.

Abstract

"How do firms and workers adjust to trade and technology shocks? We analyze two mechanisms that have received little attention: training that upgrades skills and early retirement that shifts adjustment costs to public pension systems. We combine novel data on training participation and early retirement in German local labor markets with established measures of exposure to trade competition and robot adoption. Results indicate that negative trade shocks reduce Training - particularly in manufacturing - while robot exposure increases Training - particularly in indirectly affected services. Both shocks raise early retirement among manufacturing workers. Structural change thus induces both productivity-enhancing and productivity-reducing responses, challenging simple narratives of labor market adaptation and highlighting the scope for policy to promote adjustment mechanisms conducive to aggregate productivity." (Author's abstract, IAB-Doku) ((en))

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Bisio, Laura, Angelo Cuzzola, Marco Grazzi & Daniele Moschella (2025): The dynamics of automation adoption: Firm-level heterogeneity and aggregate employment effects. In: European Economic Review, Jg. 173. DOI:10.1016/j.euroecorev.2024.104943

Abstract

"We investigate the impact of investment in automation-related goods on adopting and non-adopting firms in the Italian economy during 2011–2019. We integrate datasets on trade activities, firms’, and workers’ characteristics for the population of Italian importing firms and estimate the effects on adopters ’ outcomes within a difference-in-differences design exploiting import lumpiness in product categories linked to automation technologies (including robots). We find a positive average adoption effect on the adopters’ employment: firms are, on average, around 3% larger in terms of employment after an automation spike. Crucially, the employment effect is heterogeneous across firms: a positive effect is predominant among small firms, which are around 5% larger five years after the spike; on the contrary, a negative displacement effect is predominant among medium and large firms, with an employment contraction at five years of around -4%. This result can shed light on one potential reason behind the mixed results in the literature, i.e. different size distribution of the samples used. We complete the framework with a 5-digit sector-level analysis showing that adopting automation technologies has an overall weak negative effect on aggregate employment, and with an analysis of the competition effects of automation, showing that non-adopters suffer a loss in sales and employment." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))

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Buzzelli, Gregorio (2025): Automation and segmentation: Downgrading employment quality among the former “insiders” of Western European labour markets. In: International Journal of Social Welfare, Jg. 34, H. 2. DOI:10.1111/ijsw.70011

Abstract

"The literature on labor market segmentation traditionally looks at servitisation as the main structural driver behind the rise of employment precariousness, overlooking another crucial engine of the knowledge-economy transition: the Information and Communication Technologies (ICT) revolution. This paper proposes a task-based approach to complement the skill-biased framework usually applied to labor market segmentation, investigating the correlation between occupational exposure to the risk of automation and low-quality employment. The empirical analysis, based on 14 countries sampled from ESS (2002–2018), shows a strong correlation between technological replaceability and low income across all of Western Europe, especially after the Great Recession, while its association with atypical employment is mainly driven by fixed-term contracts in Central and Southern Europe and by part-time arrangements in Anglo-Saxon and Scandinavian countries. Overall, a “recalibrated” dualisation emerges in Western European labor markets, characterized by the diffusion of low labor earnings and atypical contracts among mid-skill routine workers, besides the low-skill service precariat." (Author's abstract, IAB-Doku) ((en))

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Cardi, Olivier & Romain Restout (2025): Why hours worked decline less after technology shocks? In: Journal of International Economics, Jg. 157. DOI:10.1016/j.jinteco.2025.104095

Abstract

"The contractionary effect of technology shocks on hours gradually vanishes over time in OECD countries. To rationalize the decline in hours and its disappearance, we use a VAR-based decomposition of technology shocks into symmetric and asymmetric technology improvements. While hours decline dramatically when technology improves at the same rate across sectors, hours significantly increase when technology improvements occur at different rates. Because they are primarily driven by symmetric technology improvements, permanent technology shocks drive down total hours. Such a decline progressively vanishes due to the growing importance of asymmetric technology shocks. To reach these two conclusions, we simulate a two-sector model which can reproduce the contractionary effect on hours once the economy is internationally open and we allow for production factors’ mobility costs, factor-biased technological change, and home bias. To account for the vanishing decline in hours, we have to let the share of asymmetric technology shocks increase over time." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))

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Diebold, Céline (2025): Using Google search data to examine factory automation and its effect on employment. In: Economic analysis and policy, Jg. 86, S. 1301-1328. DOI:10.1016/j.eap.2025.03.042

Abstract

"This paper revisits the link between robot adoption and employment across more than 100 European regions over a period of five years. A simple model is provided arguing that interest in robots precedes the actual deployment of robots. Thus, a novel instrument is introduced: interest in automation revealed by Google searches. This allows for a tentatively causal interpretation of the results. A small, yet significant positive aggregate effect is identified, along with heterogeneous effects across sex and educational attainment. The local effect on aggregate employment tends to be roughly twice as large as the spillover effect on neighbouring regions." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V. on behalf of The Economic Society of Australia (Queensland) Inc.) ((en))

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Dorville, Yann, Francesco Filippucci & Luca Marcolin (2025): How do structural trends affect labour market shortages and mismatch? (OECD productivity working papers 38), Paris, 63 S. DOI:10.1787/acfb5c31-en

Abstract

"This paper examines how AI and digital technology diffusion, the green transition, globalisation and population ageing jointly affect labour market tightness across 26 OECD countries and 34 sectors. It finds that digitalisation and decarbonisation increase tightness, while ageing does so only over time. Import competition and labour-substituting AI diffusion, conversely, reduce shortages." (Author's abstract, IAB-Doku) ((en))

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Duff, Cían, Marie Hyland, Marielena Krieg, Eleonora Peruffo, Simona Cavallini & Rossella Soldi (2025): Narrowing the digital divide. Economic and social convergence in Europe’s digital transformation. (Eurofound research report / European Foundation for the Improvement of Living and Working Conditions), Dublin, 822 S. DOI:10.2806/1764165

Abstract

"Digitalization has been on the EU policy agenda since 2000. While great strides have been made in this area over the past two decades, the digital transformation is not yet complete. This report seeks to deepen our understanding of the evolution towards a digital Europe. By applying the lens of convergence, the report assesses the progress of Member States towards the EU ’s policy targets, where Member States are growing together and wheredigital gaps are expanding. It also considers the gaps in the progress of digitalization between socioeconomic groups and regions. According to almost all indicators analysed, historically lower-performing Member States have been catching up with the digital leaders. However, at a more granular level, digitalization of businesses has been uneven and significant inequalities persist between regions and socioeconomic groups. The report shines a light on the role of digitalization in the EU’s economic convergence and considers the progress in and benefits of digitalisation for the private sector. The findings show that access is still an issue for vulnerable groups, in particular low-income households, older individuals and those with lower levels of education. Importantly, these are the groups that are more reliant on public services, and they may struggle to access e-government. While progress is being made, some groups remain at risk of being left behind in the digital transition. Considering this, the report highlights a range of policy approaches being deployed across Europe that aim to narrow the digital divide." (Author's abstract, IAB-Doku) ((en))

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Eder, Andreas, Wolfgang Koller & Bernhard Mahlberg (2025): Industrial robots and employment change in manufacturing: A decomposition analysis. In: Structural Change and Economic Dynamics, Jg. 74, S. 591-602. DOI:10.1016/j.strueco.2025.05.014

Abstract

"This paper examines the contribution of industrial robots to employment change in manufacturing in a sample of 17 European countries and the USA over the period 2004 to 2019. We combine index decomposition analysis (IDA) and production-theoretical decomposition analysis (PDA). First, we use IDA to decompose employment change in the manufacturing industry into changes in (aggregate) manufacturing output, changes in the sectoral structure of the manufacturing industry, and changes in labor intensity (the inverse of labor productivity) which is a composite index of labour intensity change within each of the nine sub-sectors of total manufacturing. Second, we use PDA to further decompose labor intensity change to isolate the contribution of technical efficiency change, technological change, human capital change, change in non-robot capital intensity and change in robot capital intensity to employment change. In almost all of the countries considered, labour intensity is falling in entire manufacturing, exerting a dampening effect on employment. Robotization contributes to this development by reducing labor intensities and employment in all countries and sub-sectors, though to varying degrees. Manufacturing output, in turn, grows in all countries except Greece, Spain and Italy, which increases employment and counteracts or in some countries even more than offsets the dampening effect of declining labor intensities. The structural change within manufacturing has an almost neutral effect in many countries." (Author's abstract, IAB-Doku, © 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.) ((en))

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Gmyrek, Pawel, Christoph Lutz & Gemma Newlands (2025): A technological construction of society: Comparing GPT-4 and human respondents for occupational evaluation in the UK. In: BJIR, Jg. 63, H. 1, S. 180-208. DOI:10.1111/bjir.12840

Abstract

"Despite initial research about the biases and perceptions of large language models (LLMs), we lack evidence on how LLMs evaluate occupations, especially in comparison to human evaluators. In this paper, we present a systematic comparison of occupational evaluations by GPT-4 with those from an in-depth, high-quality and recent human respondents survey in the UK. Covering the full ISCO-08 occupational landscape, with 580 occupations and two distinct metrics (prestige and social value), our findings indicate that GPT-4 and human scores are highly correlated across all ISCO-08 major groups. At the same time, GPT-4 substantially under- or overestimates the occupational prestige and social value of many occupations, particularly for emerging digital and stigmatized or illicit occupations. Our analyses show both the potential and risk of using LLM-generated data for sociological and occupational research. We also discuss the policy implications of our findings for the integration of LLM tools into the world of work." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Golboyz, Mark (2025): Governing the Digital Transition: The Moderating Effect of Unemployment Benefits on Technology‐Induced Employment Outcomes. In: Social Inclusion, Jg. 13. DOI:10.17645/si.10114

Abstract

"The digital transition shapes work in numerous ways. For instance, by affecting employment structures. To ensure that the digital transition results in better employment opportunities in terms of socio-economic status, labor markets have to be guided appropriately. The European Pillar of Social Rights can be the political framework to foster access to employment and tackle inequalities that result from the digital transition. Current research primarily examines scenarios of occupational upgrading and employment polarisation. In the empirical literature, there is no consensus on which of these developments prevail. Findings vary between countries and across different study periods. Accordingly, this article provides a theoretical explanation for the conditions under which occupational upgrading and employment polarization become more likely. Further, this article examines how the use of information and communication technology (ICT) capital in the production of goods and services affects the socio-economic status of individuals and, more importantly, whether unemployment benefits moderate this effect. Methodologically, the article uses multilevel maximum likelihood regression models with an empirical focus on 12 European countries and 19 industries. The analysis is based on data from the European Labour Force Survey (EU-LFS), the European Union Level Analysis of Capital, Labour, Energy, Materials, and Service Inputs (EU-KLEMS) research project, and the Comparative Welfare Entitlements Project (CWEP). The results of the article indicate that generous unemployment benefits are associated with occupational upgrading. This implies that educational and vocational labor market policies need to be developed to prevent the under-skilled from being left behind and to enable these groups to benefit from the digital transition. Consequently, it is not only the extent to which work involves routine tasks or the skills of workers that determine how technological change affects employment, but also social rights shape employment through unemployment benefits." (Author's abstract, IAB-Doku) ((en))

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Müller, Steffen & Verena Plümpe (2025): Wie Roboter die betriebliche Beschäftigungsstruktur verändern. In: Wirtschaft im Wandel, Jg. 31, H. 1, S. 10-13. DOI:10.18717/wwfyns-ep75

Abstract

"Der Einsatz von Robotern verändert die Arbeitswelt grundlegend – doch welche spezifischen Effekte hat dies auf die Beschäftigungsstruktur? Unsere Analyse untersucht die Folgen des Robotereinsatzes anhand neuartiger Mikrodaten aus deutschen Industriebetrieben. Diese Daten verknüpfen Informationen zum Robotereinsatz mit Sozialversicherungsdaten und detaillierten Angaben zu Arbeitsaufgaben. Auf Basis eines theoretischen Modells leiten wir insbesondere positive Beschäftigungseffekte für Berufe mit wenig repetitiven, programmierbaren Aufgaben ab, sowie für jüngere Arbeitskräfte, weil diese sich besser an technologische Veränderungen anpassen können. Die empirische, mikroökonomische Analyse des Robotereinsatzes auf Betriebsebene bestätigt diese Vorhersagen: Die Beschäftigung steigt für Techniker, Ingenieure und Manager und junge Beschäftigte, während sie bei geringqualifizierten Routineberufen sowie bei Älteren stagniert. Zudem steigt die Fluktuation bei geringqualifizierten Arbeitskräften signifikant an. Unsere Ergebnisse verdeutlichen, dass der Verdrängungseffekt von Robotern berufsabhängig ist, während junge Arbeitskräfte neue Tätigkeiten übernehmen." (Autorenreferat, IAB-Doku)

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Neumann, Uwe (2025): Digital transformation, employment change and the adaptation of regions in Germany. In: Structural Change and Economic Dynamics, Jg. 73, S. 37-50. DOI:10.1016/j.strueco.2024.12.014

Abstract

"Digital change is often said to lead to large-scale job losses. Using data from administrative sources in Germany, this study examines the extent to which adaptation to digital change has affected regional employment growth and disparities over the past decade. The analysis confirms previous research according to which increases in productivity coincide with regional job growth rather than decline. Incorporating various indicators of digitalisation and automation into a model of industry-specific regional job growth shows that local labour markets with very different characteristics – regions with strong manufacturing clusters on the one hand and large cities on the other – have achieved employment growth despite high automation exposure. While the study highlights regional differentials with respect to the adaptation to technological change, less prosperous regions may face a much greater challenge in realising job creation potentials. The results argue against policy efforts aimed at “protecting” jobs from digitalisation and automation." (Author's abstract, IAB-Doku, © 2025 The Author. Published by Elsevier B.V.) ((en))

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Parent-Thirion, Agnes, Nora Wukovits-Votzi & Jessye Muller (2025): Future-oriented occupations in the EU. Main features, employment conditions, and job strain. 51 S. DOI:10.2767/2953537

Abstract

"The way we work is changing due to developments associated with the digital and green transition as well as demographic change, as a driver of current and future labour shortages. As these transitions impact job content, tasks and processes, they will change how people work, the skills needed to carry out jobs, employment conditions, and, ultimately, dimensions of their job quality. These transition-related changes in occupations are of high relevance for workers, job applicants, and students training to join these occupations, as well as stakeholders, and policy makers, at the sectoral, national, and European levels. While their impacts are separately treated in this analysis, the green and digital transitions can further exacerbate labour shortages given the skill profiles required by related occupations." (Text excerpt, IAB-Doku) ((en))

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Richiardi, Matteo Guido, Leonie Westhoff, Caterina Astarita, Ekkehard Ernst, Clare Fenwick, Neysan Khabirpour & Lorenzo Pelizzari (2025): The impact of a decade of digital transformation on employment, wages, and inequality in the EU: a “conveyor belt” hypothesis. In: Socio-economic review, Jg. 23, H. 3, S. 1225-1251. DOI:10.1093/ser/mwaf011

Abstract

"We study the effects of digital transformation in the European Union on individual employment outcomes, wage growth, and income inequality, during the decade 2010–9. Our results allow us to formulate a ‘conveyor-belt’ hypothesis suggesting that employment confers a competitive advantage in navigating the digital transition due to the accumulation of pertinent skills in the workplace. Because digital skills are acquired with the changing demands of the job, their initial endowment matters less for the employed than for the non-employed. Furthermore, the ability of out-of-work individuals with higher digital skills to jump back on the labour market is reduced for those with higher education, suggesting a faster depreciation of their digital skills. A similar effect, although of limited size, is found for earning growth: out-of-work individuals with higher digital skills are not only more likely to find a job, but experience higher earnings growth, compared to their peers with lower digital skills. Our results point to a vulnerability of workers ‘left behind’ from the digital transformation and the labour market. The overall effects on inequality are, however, limited." (Author's abstract, IAB-Doku) ((en))

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Weber, Enzo & Gerd Zika (2025): Wegen KI könnten 800.00 Arbeitsplätze wegfallen und neu entstehen. Gastbeitrag. In: Frankfurter Allgemeine Zeitung H. 19.11.2025 Frankfurt am Main.

Abstract

"Wie wird KI die Arbeitswelt verändern? Eine neue Studie wagt eine Prognose. Die zentrale Botschaft: Die Zahl der Arbeitsplätze bleibt weitgehend stabil, doch die Umwälzungen dahinter werden gewaltig sein." (Autorenreferat, IAB-Doku, © Frankfurter Allgemeine Zeitung)

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Wohlrabe, Klaus (2025): Mehr KI, weniger Jobs? Was Unternehmen in Deutschland erwarten. In: ifo Schnelldienst digital, Jg. 6, H. 8, S. 1-12.

Abstract

"Die Nutzung von Künstlicher Intelligenz (KI) in der deutschen Wirtschaft nimmt weiter zu – insbesondere in größeren Unternehmen. Auf Basis von Sonderfragen im Rahmen der monatlichen Konjunkturumfragen wird gezeigt: Derzeit fallen die direkten Beschäftigungseffekte von KI noch gering aus. Für die kommenden fünf Jahre wird jedoch deutlich häufiger ein Einfluss auf die Beschäftigtenzahl erwartet – vor allem in Form eines Stellenabbaus. Die Einschätzungen unterscheiden sich je nach Branche teils erheblich. Trotz zunehmender Praxiserfahrung bleibt eine deutliche Unsicherheit über die langfristigen Arbeitsmarktauswirkungen bestehen. Die Ergebnisse liefern einen ersten Einblick in die beschäftigungspolitischen Erwartungen von Unternehmen in Deutschland mit Blick auf KI." (Autorenreferat, IAB-Doku)

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Zeng, Shihong, Zeyuan Yang & Zhibin Zhang (2025): Servitization and employment effects in manufacturing: international experiences under digital technology conditions. In: Applied Economics, S. 1-18. DOI:10.1080/00036846.2025.2526854

Abstract

"This study examines the impact of manufacturing servitization on employment in 43 countries between 2000 and 2020, considering the role of digital technology. Using data from the World Input-Output Tables and the International Labour Organization, we explore how servitization affects employment in manufacturing and productive services. Our findings show that servitization leads to a substitution effect on manufacturing employment and a creation effect on productive service employment. The adoption of digital technology amplifies the substitution effect while weakening the creation effect. We further conduct heterogeneity analysis based on factor demand, factor input, level of industrialization, and level of economic development. We find that the substitution effect is most significant in low-tech manufacturing, while the creation effect is strongest in high-tech manufacturing. Regarding factor input, the creation effect is concentrated in low- to mid-tech productive service sectors. The substitution effect is more pronounced in less industrialized and developed countries, while the creation effect is more evident in highly industrialized and developing countries.The study identifies two key mechanisms through which servitization influences employment, namely improving information technology levels and reducing institutional distance. These findings contribute to the understanding of employment transitions in the digital economy and provide valuable insights for policymaking." (Author's abstract, IAB-Doku) ((en))

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Zika, Gerd, Theresa-Marie Hassemer, Markus Hummel, Bennet Krebs, Tobias Maier, Anke Mönnig, Christian Schneemann, Enzo Weber & Johanna Zenk (2025): Künstliche Intelligenz: Potenzielle Effekte für den deutschen Arbeitsmarkt. (IAB-Forschungsbericht 23/2025), Nürnberg, 58 S. DOI:10.48720/IAB.FB.2523

Abstract

"Die fortschreitende Entwicklung und Integration von Künstlicher Intelligenz (KI) prägt zunehmend die globalen Märkte und Arbeitsweisen und hat auch in Deutschland einen immer größeren Einfluss. Deshalb wird mit der vorliegenden Szenarioanalyse für einen Zeitraum von 15 Jahren untersucht, welchen Einfluss KI auf die Entwicklung von Wirtschaft und Arbeitsmarkt in Deutschland entfalten könnte. Um Aussagen über potenzielle Effekte eines KI-Szenarios treffen zu können, müssen entsprechende Annahmen getroffen werden. Anschließend wird das KI-Szenario mit einem Referenz-Szenario verglichen. Im KI-Szenario wird unterstellt, dass die notwendige Infrastruktur für die KI-Entwicklung und -Integration vorhanden ausgebaut wird. Insbesondere muss ausreichend Rechenkapazität in Rechenzentren verfügbar sein. Zudem wird KI je nach Branche unterschiedlich stark zum Einsatz kommen. So müssen von den Betrieben der jeweiligen Branchen unterschiedlich hohe Vorlaufinvestitionen getätigt werden. Dabei ist zu erwarten, dass die Wirkung des KI-Einsatzes je nach Branche unterschiedlich ausfallen wird. In manchen Branchen können Materialeinsparungen, in anderen Produktivitätssteigerungen oder neue Absatzmöglichkeiten realisiert werden. In vielen Branchen dürften diese Effekte auch in Kombination auftreten. Schließlich entwickeln auch andere Länder KI und wenden diese an. Für das KI-Szenario wird deshalb angenommen, dass die Wirkungen im Ausland insgesamt ähnlich ausfallen werden wie in Deutschland, mit den entsprechenden Effekten auf deutsche Importpreise. Den Berechnungen zufolge lässt sich durch KI insbesondere mittel- und langfristig eine deutlich höhere Wertschöpfung bei nahezu gleichem Arbeitseinsatz erzielen als im Referenz-Szenario. Unter den getroffenen Annahmen kann das jährliche Wirtschaftswachstum um durchschnittlich 0,8 Prozentpunkte höher liegen als im Referenz-Szenario. Kumuliert über die nächsten 15 Jahre könnten so 4,5 Billionen Euro an zusätzlicher Wertschöpfung erwirtschaftet werden. Die Zahl an Arbeitsplätzen liegt im KI-Szenario nach 15 Jahren insgesamt auf einem ähnlichen Niveau wie im Referenz-Szenario. Dennoch zeigen sich deutliche Verschiebungen am Arbeitsmarkt. So gibt es Wirtschaftsbereiche, in denen der Arbeitskräftebedarf steigt, während in anderen Bereichen Arbeitsplätze verloren gehen. Zu Beginn der verstärkten KI-Entwicklung und -Integration ist zunächst mit einem insgesamt höheren Arbeitskräftebedarf zu rechnen, um beispielsweise die benötigte Infrastruktur bereitzustellen, Daten zu erschließen oder Modelle zu entwickeln. Mittelfristig kommt es zu einem etwas geringeren Arbeitskräftebedarf aufgrund zunehmender Effizienzgewinne. Gegen Ende des Projektionszeitraums besteht jedoch Potenzial, diese Arbeitsplatzverluste wieder auszugleichen. Dabei zieht insbesondere die Entwicklung neuer Geschäftsmodelle einen höheren Arbeitskräftebedarf nach sich. Insgesamt gleichen sich die gegenläufigen Effekte auf die Beschäftigung weitgehend aus. Im KI-Szenario führt der Einsatz von KI unterm Strich also nicht ausschließlich zu positiven oder negativen Effekten auf dem Arbeitsmarkt. Vielmehr kommt es in einigen Bereichen zu Verschiebungen. Bei den IT- und Informationsdienstleistern liegt die Zahl der Erwerbstätigen nach 15 Jahren beispielsweise um rund 110.000 Personen höher als im Referenz-Szenario. Hingegen liegt die Zahl der Erwerbstätigen bei den Unternehmensdienstleistern im KI-Szenario zum gleichen Zeitpunkt um rund 120.000 Personen niedriger. Eine KI-induzierte Absenkung der Erwerbstätigenzahlen ist jedoch nicht zwingend mit einer Verschlechterung der Arbeitsmarktlage verbunden. Vielmehr könnten knappe Personalressourcen langfristig effizienter eingesetzt werden, wodurch Potenzial besteht, etwaige Arbeitskräfteengpässe in anderen Bereichen zu reduzieren. Gleichzeitig ist zu erwarten, dass ein verstärkter KI-Einsatz die Anforderungen an die Beschäftigten verändern wird. So dürften insbesondere hochqualifizierte Tätigkeiten stärker von KI-Anwendungen betroffen sein als von Entwicklungen im Bereich klassischer nicht-lernender Software." (Autorenreferat, IAB-Doku)

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Albinowski, Maciej & Piotr Lewandowski (2024): The impact of ICT and robots on labour market outcomes of demographic groups in Europe. In: Labour Economics, Jg. 87. DOI:10.1016/j.labeco.2023.102481

Abstract

"We study the age- and gender-specific labour market effects of two key modern technologies, Information and Communication Technologies (ICT) and robots. Our sample includes 14 European countries between 2010 and 2018. We use the variation in technology adoption between industries and apply the instrumental variables strategy proposed by Acemoglu and Restrepo (2020) to identify the causal effects of technology adoption. We find that exposure to ICT and robots increased the shares of young and prime-aged women in employment and in the wage bills of particular sectors. However, it reduced the shares of older women and prime-aged men. We do not detect significant effects of technology adoption on the relative wages of most demographic groups. Between 2010 and 2018, the growth in ICT capital played a larger role than robot adoption in the changes in the withinsector labor market outcomes of demographic groups." (Author's abstract, IAB-Doku, ©2024 Elsevier) ((en))

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Arntz, Melanie, Sabrina Genz, Terry Gregory, Florian Lehmer & Ulrich Zierahn-Weilage (2024): De-Routinization in the Fourth Industrial Revolution - Firm-Level Evidence. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 16740), Bonn, 65 S.

Abstract

"This paper examines the extent to which aggregate-level de-routinization can be attributed to firm-level technology adoption during the most recent technological expansion. We use administrative data and a novel firm survey to distinguish frontier technologies from older technologies. We find that adopters of frontier technologies contribute substantially to deroutinization. However, this is driven only by a subset of these firms: large adopters replace routine jobs and less routine-intensive adopters experience faster growth. These scale and composition effects reflect firms' readiness to adopt and implement frontier technologies. Our results suggest that an acceleration of technology adoption would be associated with faster de-routinization and an increase in between-firm heterogeneity." (Author's abstract, IAB-Doku) ((en))

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Bachmann, Ronald, Myrielle Gonschor, Piotr Lewandowski & Karol Madoń (2024): The impact of Robots on Labour market transitions in Europe. In: Structural Change and Economic Dynamics, Jg. 70, S. 422-441. DOI:10.1016/j.strueco.2024.05.005

Abstract

"Dieses Papier untersucht die Auswirkungen von Robotern auf Arbeitsmarkttransitionen in 16 europäischen Ländern. Generell reduzieren Roboter Übergänge von der Beschäftigung in die Arbeitslosigkeit und erhöhen die Wahrscheinlichkeit, einen neuen Job zu finden. Arbeitskosten sind eine wichtige Erklärung für die beobachteten Unterschiede zwischen Ländern: In Ländern mit niedrigeren Arbeitskosten zeigt sich ein stärkerer Effekt auf Einstellungen und Trennungen. Diese Auswirkungen sind bei Arbeitskräften in Berufen mit manuellen oder kognitiven Routineaufgaben besonders ausgeprägt, bei Berufen mit nicht-routine kognitiven Aufgaben hingegen vernachlässigbar. Für junge und ältere Arbeitskräfte in Ländern mit niedrigeren Arbeitskosten wirken sich Roboter positiv auf Übergänge aus. Unsere Ergebnisse deuten darauf hin, dass die Einführung von Robotern in den meisten europäischen Ländern zu einem Anstieg der Beschäftigung und einem Rückgang der Arbeitslosigkeit geführt hat, vor allem durch einen Rückgang der Übergänge in die Arbeitslosigkeit." (Autorenreferat, IAB-Doku)

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Barišić, Antea, Mahdi Ghodsi & Robert Stehrer (2024): Which Migrant Jobs are Linked with the Adoption of Novel Technologies, Robotization, and Digitalization? (WIIW working paper 241), Wien, 66 S.

Abstract

"In recent decades, the development of novel technologies has intenzified due to globalization, prompting countries to enhance competitiveness through innovation. These technologies have significantly improved global welfare, particularly in sectors like healthcare, where they have facilitated tasks and boosted productivity, for example playing a crucial role in combating the COVID-19 pandemic. However, certain technologies, such as robots, can negatively impact employment by replacing workers and tasks. Additionally, the emergence of artificial intelligence as digital assets not only replaces specific tasks but also introduces complexities that may displace employees who are unable to adapt. While the existing literature extensively explores the heterogeneous effects of these technologies on labor markets, studies of their impact on migrant workers remain scarce. This paper presents pioneering evidence on the effects of various novel technologies on migrant employment in the European Union. The analysis covers 18 EU member states from 2005 to 2019 focusing on the impact of novel innovations, robot adoption, three types of digital assets, and total factor productivity, on migrant employment. The key findings reveal that innovations measured by the number of granted patents increase both the number and proportion of migrant workers relative to the overall workforce. While robots do replace jobs, their impact on native workers surpasses that of migrant workers, resulting in a higher share of migrant workers following robot adoption. Total factor productivity positively influences migrant workers, while the effects of digital assets are heterogeneous. Moreover, the impacts of these technologies on migrant workers vary significantly across different occupation types and educational levels." (Author's abstract, IAB-Doku) ((en))

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Barišić, Antea, Mahdi Ghodsi, Michael Landesmann, Alireza Sabouniha & Robert Stehrer (2024): New Technologies, Migration and Labour Market Adjustment: An Intra-European Perspective. (WIIW policy notes and reports 77), Wien, 26 S.

Abstract

"In this note, we study the relationship between the use of new technologies (e.g. robots and various ICT assets), labor demand and migration patterns. The adoption of new technologies might change the demand for labor in various ways, which in turn will have an impact on skill composition and wage levels of different types of workers. We report the main results from a study that first analyses the impact of robot adoption on wages by sector and skills. Second, we study the impact of robot adoption in manufacturing industries on the attraction of migrants while controlling for other factors in the labor demand function. This is followed by an analysis of push and pull factors of bilateral migration that focuses on the impact of relative automation gaps across countries. Finally, using the OeNB Euro Survey, we examine determinants of the intention to migrate and the role of income differentials between the countries of origin and destination." (Author's abstract, IAB-Doku) ((en))

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Bonfiglioli, Alessandra, Rosario Crinò, Harald Fadinger & Gino Gancia (2024): Robot Imports and Firm-Level Outcomes. In: The Economic Journal, Jg. 134, H. 664, S. 3428-3444. DOI:10.1093/ej/ueae055

Abstract

"We use French data over the 1994-2013 period to study how imports of industrial robots affect firm-level outcomes. Guided by a simple model, we develop a novel empirical strategy to identify the causal effects of robot adoption. Our results suggest that, while demand shocks generate a positive correlation between robot imports and employment at the firm level, exogenous exposure to automation leads to job losses. We also find that robot exposure increases labor productivity and some evidence that it may raise the relative demand for high-skill professions." (Author's abstract, IAB-Doku) ((en))

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Bonney, Kathryn, Cory Breaux, Catherine Buffington, Emin Dinlersoz, Lucia Foster, Nathan Goldschlag, John Haltiwanger, Zachary Kroff & Keith Savage (2024): The impact of AI on the workforce: Tasks versus jobs? In: Economics Letters, Jg. 244. DOI:10.1016/j.econlet.2024.111971

Abstract

"Will the adoption of AI by businesses substitute for worker tasks or jobs? This is a core question for which relatively scarce evidence exists—especially in the wake of recent advances in generative AI. Using a new large-scale business survey by the U.S. Census Bureau, we find that AI use is having a much greater impact on worker tasks than on employment levels at the firm level. About 27% of firms using AI report replacing worker tasks, but only about 5% experience employment change due to AI use. These rates are expected to increase to nearly 35% and 12%, respectively, in the near future." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Burzyński, Michał (2024): Spatial and Occupational Mobility of Workers Due to Automation. (LISER working papers 2024-04), Esch-sur-Alzette, 52 S.

Abstract

"Automation of labor tasks is one of the most dynamic aspects of recent technological progress. This paper aims at improving our understanding of the way that automation affects labor markets, analyzing the example of European countries. The quantitative theoretical methodology proposed in this paper allows to focus on automation-induced migration of workers, occupation switching and income inequality. The key findings include that automation in the first two decades of the 21st century had a significant impact on job upgrading of native workers and generated gains in many local labor markets. Even though net migration of workers was attenuated due to convergence in incomes across European regions, mobility at occupation levels had a sizeable impact on transmitting welfare effects of automation." (Author's abstract, IAB-Doku) ((en))

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Caselli, Mauro, Edwin Fourrier-Nicolai, Andrea Fracasso & Sergio Scicchitano (2024): Digital Technologies and Firms' Employment and Training. (CESifo working paper 11056), München, 63 S.

Abstract

"This study examines the causal influence of digital technologies, specifically operational (ODT) and information digital technologies (IDT), on firms' employment structure using Italian firm-level data. It employs a unique empirical approach, constructing instrumental variables based on predetermined employment composition and global technological progress, proxied by patents. Findings indicate that IDT investment positively affects employment, favoring a skilled, IT-competent workforce, as supported by firms' training and recruitment plans. Conversely, ODT investment does not significantly alter total employment but skews the workforce towards temporary contracts. The study contributes methodologically by distinguishing between ODT and IDT and highlighting nuanced employment dynamics within firms." (Author's abstract, IAB-Doku) ((en))

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Casey, Gregory (2024): Unemployment and the direction of technical change. In: European Economic Review, Jg. 168. DOI:10.1016/j.euroecorev.2024.104802

Abstract

"I construct and analyze a growth model in which technical change can increase unemployment. I first analyze the forces that deliver a constant steady state unemployment rate in this setting. Labor-saving technical change increases unemployment, which lowers wages and creates incentives for future investment in labor-using technologies. In the long run, this interaction generates a balanced growth path that is observationally equivalent to that of the standard neoclassical growth model, except that it also incorporates a positive steady state level of unemployment and a falling relative price of investment. I also study the effects of a permanent increase in the ability of R&D to improve labor-saving technologies. In the long run, this change leads to faster growth in output per worker and wages, but it also yields higher unemployment and a lower labor share of income. In the short run, this change exacerbates existing inefficiencies and slows economic growth." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Damelang, Andreas & Michael Otto (2024): Who is Replaced by Robots? Robotization and the Risk of Unemployment for Different Types of Workers. In: Work and occupations, Jg. 51, H. 2, S. 181-206. DOI:10.1177/07308884231162953

Abstract

"We study the effects of robotization on unemployment risk for different types of workers. We examine the extent to which robotization increases inequality at the skill level and at the occupational level using two theoretical frameworks: skill-biased technological change and task-biased technological change. Empirically, we combine worker-level data with information on actual investments in industrial robots. Zooming in on the German manufacturing industry, our multivariate results show that robotization affects different types of workers differently. We do not observe an increase in unemployment risk for low- and medium-skilled, but we find a considerably lower unemployment risk among high-skilled workers. Moreover, the unemployment risk is significantly higher in occupations with highly substitutable tasks, but only in industries that invest largely in robots." (Author's abstract, IAB-Doku, © SAGE) ((en))

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Gathmann, Christina, Christian Kagerl, Laura Pohlan & Duncan Roth (2024): The pandemic push: Digital technologies and workforce adjustments. In: Labour Economics, 2024-04-05. DOI:10.1016/j.labeco.2024.102541

Abstract

"Using a novel firm survey matched to administrative employee records, we demonstrate that the COVID-19 pandemic was a push factor for the diffusion of digital technologies in Germany. Two out of three firms invested in digital technologies. Three quarters of those investing firms invested because of the pandemic, particularly in hardware and software to enable decentralized communication, management, and coordination. These investments also fostered additional firm-sponsored training, underscoring the complementarity between investments in digital technologies and training. We then show that the investments helped firms insure their workers against the economic downturn. Firms with additional digital investments retained more of their employees on regular working hours and relied less on short-time work. Low- and medium-skilled, as well as young workers, benefited the most from the insurance effect of digital investments." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Guarascio, Dario, Alessandro Piccirillo & Jelena Reljic (2024): Will robot replace workers? Assessing the impact of robots on employment and wages with meta-analysis. (LEM working paper series / Laboratory of Economics and Management 2024,03), Pisa, 31 S.

Abstract

"This study conducts a meta-analysis to assess the effects of robotization on employment and wages, compiling data from 33 studies with 644 estimates on employment and a subset of 19 studies with 195 estimates on wages. We identify a publication bias towards negative outcomes, especially concerning wages. After correcting for this bias, the actual impact appears minimal. Thus, concerns about the disruptive effects of robots on employment and the risk of widespread technological unemployment may be exaggerated or not yet empirically supported. While this does not preclude that robots will be capable of gaining greater disruptive potential in the future or that they are not already disruptive in specific contexts, the evidence to date suggests their aggregate effect is negligible." (Author's abstract, IAB-Doku) ((en))

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Güven, Barış (2024): Has labor-saving technology accelerated? Evidence from industry-level data. In: Structural Change and Economic Dynamics, Jg. 70, S. 442-456. DOI:10.1016/j.strueco.2024.05.008

Abstract

"What role has labor-saving technological change played in the recent past in charting out the trajectory of employment? Have we already transitioned into a new technological regime where production technologies are more invasive upon labor’s terrain? In this study, I provide empirical evidence to answer these questions. Using industry-level data from 12 advanced economies for 1970–2007, I show that capital goods did not become more effective in labor-saving after 1980 or 1990. Similarly, the strength of the relationship between employment and output did not decline after 1980 or 1990. While many recent econometric studies have estimated the number of workers displaced due to industrial robots with which the media and public are highly preoccupied, there is nothing new in the fact that production technologies are labor-saving and displace workers. The importance of demand side factors and structural change (mainly deindustrialization) in determining employment patterns is often neglected, leading to a misleading assessment of the impact of labor-saving technologies on employment." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Heluo, Yuxi & Oliver Fabel (2024): Job computerization, occupational employment and wages: A comparative study of the United States, Germany, and Japan. In: Technological forecasting & social change, Jg. 209. DOI:10.1016/j.techfore.2024.123772

Abstract

"This study adds to the growing literature on wage and employment responses to the risk of job computerization. Specifically, it revisits the original occupational perspective and inquires into the nature of the adjustments of occupational wages and employment, i.e., the potential benefits and costs associated with professional careers in such occupations. The investigation further aims at identifying whether these adjustment processes are universal - as suggested by the global availability of the respective technology - or reflect country-specific peculiarities. To this end, it conducts a comparative analysis with data from the United States, Germany, and Japan, three G7 lead countries which share the commitment to fostering technological progress, but which are also characterized by distinctly different labor market institutions and approaches to industrial policies. Generally consistent with the country-specific employment institutions and common corporate strategies, transmission channels - as reflected by the relationship between adjustments of occupational employment and wages - differ between countries. In all three countries, though, higher risks of computerization are associated with relative wage losses in occupations which require low levels of formal education or training." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Jestl, Stefan (2024): Industrial robots, and information and communication technology: the employment effects in EU labour markets. In: Regional Studies, Jg. 58, H. 11, S. 1981-1998. DOI:10.1080/00343404.2023.2292259

Abstract

"This paper explores the effects of industrial robots and information and communication technology (ICT) on regional employment in European Union countries. The empirical analysis relies on a harmonized comprehensive regional dataset that combines business statistics and national and regional accounts data. This rich dataset enables us to provide detailed insights into the employment effects of automation and computerisation in EU regions for the period 2001–16. The results suggest relatively weak effects on regional total employment dynamics. However, industrial robots show negative employment effects in local manufacturing industries and positive employment effects in local non-manufacturing industries. While the negative effect is concentrated in particular local manufacturing industries, the positive effect has operated in local service industries. Information technology investments show positive employment effects in local manufacturing industries and some individual local service industries, while communication technology investments are shown to be irrelevant for employment dynamics. In contrast, software and database investments have had a predominantly negative association with local employment." (Author's abstract, IAB-Doku) ((en))

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Lühr, Thomas & Tobias Kämpf (2024): KI und der Wandel von Angestelltenarbeit. Zum „blinden Fleck“ der aktuellen Automatisierungsdebatte. In: WSI-Mitteilungen, Jg. 77, H. 2, S. 98-106. DOI:10.5771/0342-300X-2024-2-98

Abstract

"Der Beitrag analysiert den Wandel von Angestelltenarbeit vor dem Hintergrund der digitalen Transformation. Ausgangspunkt ist ein Automatisierungsschub, der durch erweiterte Möglichkeiten der Nutzung Künstlicher Intelligenz (KI) geprägt ist. Auf der Grundlage empirischer Befunde werden die qualitativen Veränderungstendenzen von Arbeit in den Blick genommen, und zwar sowohl aus der Anwenderperspektive der Sachbearbeiter*innen als auch aus der Sicht der hochqualifizierten Entwickler*innen und Implementoren neuer KI-Lösungen. Insgesamt wird ein Strukturwandel von Angestelltenarbeit konstatiert, der nicht nur das Risiko von Jobverlusten, sondern auch Potenziale für eine Aufwertung und Höherqualifizierung hervorbringt und sich im Angestelltenbewusstsein manifestiert. In arbeitspolitischer Perspektive eröffnen sich Anknüpfungspunkte für eine Vorwärtsstrategie im Sinne eines nachhaltigen Umbaus von Beschäftigung." (Autorenreferat, IAB-Doku)

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Lükemann, Laura (2024): Flexibility potentials of digital work communication – mothers’ labour market involvement in comparative perspective. In: Community, work & family, Jg. 27, H. 5, S. 627-648. DOI:10.1080/13668803.2024.2418560

Abstract

"Digital work communication offers increased flexibility in timing and location, helping employees, particularly mothers, balance work and private life. This flexibility can enhance mothers' ability to increase their contracted hours in paid employment, especially given the impact of childbirth on their careers. Drawing on boundary management theory, this study posits that digital communication with supervisors enables mothers to better manage work tasks alongside personal obligations, potentially allowing them to work longer hours. However, the actual use of this flexibility is influenced by a country's level of de-familialisation, which refers to family policies that reduce care dependency. Analyzing data from the European Social Survey involving 3,179 mothers across 25 countries, the study found that mothers generally worked longer hours when they utilized digital communication more frequently. Comparisons across countries showed that this relationship was stronger in nations with robust de-familialisation policies. The findings suggest that the potential of digital work communication to enhance work involvement is particularly leveraged in countries that promote de-familialisation, allowing mothers to navigate their professional and personal responsibilities more effectively." (Author's abstract, IAB-Doku) ((en))

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Madoń, Karol (2024): The effects of automation on workers’ wages. (IBS working paper / Instytut Badan Strukturalnych 2024,06), Warszawa, 35 S.

Abstract

"This study examines the impact of automation on workers’ wages across 20 European countries between 2010–2018. Overall, it identifies a net positive effect of robot adoption on average wages at the sectoral level, especially pronounced among routine manual and nonroutine manual occupations. Importantly, these effects differ between countries- workers in Eastern European countries benefit twice as much from automation as their Western European counterparts. In Western European countries, higher average wages are associated with a decreasing share of routine workers. Results are robust to the exclusion of different capital measures, a battery of fixed effects, a change of instrument and an alternative measure of wages." (Author's abstract, IAB-Doku) ((en))

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Montobbio, Fabio, Jacopo Staccioli, Maria Enrica Virgillito & Marco Vivarelli (2024): The empirics of technology, employment and occupations: Lessons learned and challenges ahead. In: Journal of Economic Surveys, Jg. 38, H. 5, S. 1622-1655. DOI:10.1111/joes.12601

Abstract

"This paper is a critical review of the empirical literature resulting from recent years of debate and analysis regarding technology and employment and the future of work as threatened by technology, outlining both lessons learned and challenges ahead. We distinguish three waves of studies and relate their heterogeneous findings to the choice of technological proxies, the level of aggregation, the adopted research methodology and to the relative focus on robots, automation and AI. The challenges ahead include the need for awareness of possible ex‐ante biases associated with the adopted proxiesfor innovation; the recognition of the trade‐off between microeconometric precision and a more holistic macroeconomic approach; the need for granular analysis of the reallocation and transformation of occupations and tasks brought about by different types of new technologies; the call for a closer focus on impacts on labor quality, in terms of types of jobs and working conditions." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Nurski, Laura & Nina Ruer (2024): Exposure to generative artificial intelligence in the European labour market. (Working paper / Bruegel 2024,06), Brüssel, 33 S.

Abstract

"We apply two sets of generative artificial intelligence (GenAI) occupational exposure scores – one task-based, one ability-based – to the European Labour Force Survey. While using different methodologies, our findings reveal consistent demographic patterns across the two approaches: jobs held by women, highly educated and younger workers are more exposed to GenAI technology in Europe. We also review the literature on the recent productivity impact of GenAI. Within the same occupations, less-experienced or less-skilled workers consistently get the largest productivity gains from GenAI support. We argue that a task-based analysis is more fruitful than an ability-based one, both for guiding GenAI adoption in organisations and their workplaces, and for assessing the employment and job quality impact on workers. Finally, we provide policy recommendations that can help workers (ie the labor supply) adjust to technological disruption, such as providing training and social safety nets. But we go further by also suggesting policy interventions that could redirect future labor demand towards better jobs, by promoting job redesign and organisational agility. Monitoring GenAI’s employment effects and researching the ‘jagged technological frontier’ is necessary to further build our understanding of the employment impact of this transformational technology." (Author's abstract, IAB-Doku) ((en))

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Peede, Lennert & Michael Stops (2024): Artificial intelligence technologies, skills demand and employment: evidence from linked job ads data. (IAB-Discussion Paper 15/2024), Nürnberg, 62 S. DOI:10.48720/IAB.DP.2415

Abstract

"Wir untersuchen, wie künstliche Intelligenz (KI) die Arbeitsnachfrage auf der Betriebsebene beeinflusst. Um die Aktivitäten in der Entwicklung, Implementierung oder Nutzung von KI-Technologien zu messen, verwenden wir den Anteil derjenigen Stellenausschreibungen, die einen Bezug zu KI haben. Niedrige KI-Stellenanteile insgesamt zeigen, dass wir eine frühe Phase der KI-Einführung untersuchen. Auf der Betriebsebene hängt der KI-Stellenanteil mit einem relativ geringen Rückgang derjenigen Kompetenzanforderungen zusammen, die nicht mit KI-Technologien in Verbindung stehen. Darüber hinaus finden wir keine Auswirkungen auf die Gesamtbeschäftigung in den Betrieben, aber ein leicht höheres Beschäftigungswachstum in Jobs mit hoch komplexen Tätigkeiten." (Autorenreferat, IAB-Doku)

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Rujin, Svetlana (2024): Labor market institutions and technology-induced labor adjustment along the extensive and intensive margins. In: Journal of macroeconomics, Jg. 79. DOI:10.1016/j.jmacro.2023.103571

Abstract

"What is the composition of total hours response to a technology shock in countries with different labor market institutions in terms of extensive and intensive margin movements? To answer this question, I identify technology shocks using structural vector autoregressions (SVARs) and decompose the responses of hours into adjustments along the extensive and intensive margins. I compare the adjustments along the two margins between groups of countries with strict and flexible labor market institutions. I find that both margins play a large role in accommodating technology shocks, with adjustments along the intensive margin being more important. Furthermore, countries with flexible labor market institutions display a larger drop in employment, whereas the results for the intensive margin are mixed. Finally, the cross-country differences in fluctuations along the two margins can be linked to the strictness of institutions that target quantity and price adjustments in the labor market." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Sharfaei, Shahab (2024): Robots and employment: A review. In: International Labour Review, Jg. 163, H. 2, S. 271-293. DOI:10.1111/ilr.12417

Abstract

"Rapid advances in robotics signal a scientific breakthrough that could have major implications for the world economy and the field of economics. This article reviews recent literature on this topic to examine the evidence from two perspectives. First, I critically review the theoretical literature on the effects of robot adoption on employment and analyse the capacity of different theories to describe these influences. Second, I evaluate the current empirical evidence regarding the impact of robot technology on the economy in terms of employment and reshoring. This exercise highlights the limitations in the literature and points to avenues for future research." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Tan, Joanne (2024): Multidimensional heterogeneity and matching in a frictional labor market - An application to polarization. In: Labour Economics, Jg. 90. DOI:10.1016/j.labeco.2024.102604

Abstract

"This paper examines the role that changes in production technology, namely computerization, have played on labor market inequality in the US from the late 1980s to the 2010s. It also demonstrates that such technological change is consistent with the timing of labor market polarization in the US, including the end of the decline in 50∕10 wage percentile ratio and the slowdown of employment growth in high-wage jobs from the 2000s. The paper does so using a model with two key ingredients: 1) directed search and 2) two-sided multidimensional heterogeneity. Calibration results show that the complementarity between a workers’ cognitive skills and the cognitive task intensity of jobs increased while that between manual skill and tasks did not. The full model can fully account for the rise and fall of the 90∕50 and 50∕10 wage percentile ratios respectively. It also generates 72.6 percent of the rise in employment share of high-paying jobs relative to middling jobs and 69 percent of the fall in employment share of middling jobs relative to low-paying jobs. The paper suggests that the end of the decline in the 50∕10 wage ratio may be due to rank-switching between workers across the wage distribution from the 2000s, while the slowdown of employment growth in high-wage jobs may result from the trade-off between the returns to applying for high-wage jobs and the likelihood of being hired." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Traverso, Silvio, Massimiliano Vatiero & Enrico Zaninotto (2024): Automation and flexible labor contracts: Firm-level evidence from Italy. (GLO discussion paper / Global Labor Organization 1425), Essen, 33 S.

Abstract

"This study examines the association between investments in automation technologies and employment outcomes at the firm level, utilizing a panel dataset of about 10,450 Italian firms. Focusing on the proliferation of non-standard, flexible labor contracts introduced by labor market reforms in the 2000s, we identify a positive relationship between automation investments and the adoption of flexible labor arrangements. With the aid of a conceptual framework, we interpret these findings as evidence of complementarity between flexible capital, represented by automation technologies, and flexible labor, manifested through non-standard contractual arrangements. This complementarity is crucial for enhancing operational flexibility, a critical determinant of firm performance in the modern market environment. However, while this adaptability is beneficial for firms, it raises concerns about job security, the potential for lower wages among workers, and the reduction of workers' incentives to invest in human capital. In terms of policy implications, our analysis underscores the need for measures that safeguard workers' interests without compromising the efficiency gains from automation." (Author's abstract, IAB-Doku) ((en))

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Walwei, Ulrich (2024): Substituierungspotenziale sind nicht gleichbedeutend mit Arbeitsplatzverlusten. In: Goinger Kreis (Hrsg.) (2024): Liebeserklärung an die Arbeit. Was Arbeit ausmacht, wie sie uns bereichert und wie wir sie wertschätzen müssen, getr. Sz.