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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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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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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, S. 1-27. 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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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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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), 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.

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Zenk, Johanna (2024): Demografie, Digitalisierung, Dekarbonisierung. Die zukünftigen Arbeitsmarktentwicklungen inmitten der Transformation. In: Zur Debatte, Jg. 54, H. 2, S. 18-21., 2024-05-27.

Abstract

Der deutsche Arbeitsmarkt steht inmitten einer Vielzahl von Transformationen. Der Vortrag basiert auf den Ergebnissen des Projekts Qualifikation und Beruf in der Zukunft. Darin geht es um die zukünftige Entwicklung auf dem Arbeitsmarkt. Ziel ist es, die mittel- und langfristigen Veränderungen der Arbeitswelt und des Bildungswesens abzubilden. Anhand derer kann frühzeitig erkannt werden, wo es Passungsprobleme zwischen Arbeitskräftebedarf und Arbeitskräfteangebot geben kann. Im Hinblick auf die zukünftige Arbeitsmarktentwicklung befasst sich die Autorin vor allem mit den drei Megatrends demografischer Wandel, Digitalisierung und Dekarbonisierung, beziehungsweise ökologische Transformation. (IAB)

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Acemoglu, Daron & Simon Johnson (2023): Rebalancing AI. In: Finance and development H. December, S. 26-29.

Abstract

"Optimistic forecasts regarding the growth implications of AI abound. AI adoption could boost productivity growth by 1.5 percentage points per year over a 10-year period and raise global GDP by 7 percent ($7 trillion in additional output), according to Goldman Sachs. Industry insiders offer even more excited estimates, including a supposed 10 percent chance of an “explosive growth” scenario, with global output rising more than 30 percent a year. All this techno-optimism draws on the “productivity bandwagon”: a deep-rooted belief that technological change— including automation—drives higher productivity, which raises net wages and generates shared prosperity. Such optimism is at odds with the historical record and seems particularly inappropriate for the current path of “just let AI happen,” which focuses primarily on automation (replacing people). We must recognize that there is no singular, inevitable path of development for new technology. And, assuming that the goal is to sustainably improve economic outcomes for more people, what policies would put AI development on the right path, with greater focus on enhancing what all workers can do?" (Text excerpt, IAB-Doku) ((en))

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Acemoglu, Daron, Hans R. A. Koster & Ceren Ozgen (2023): Robots and Workers: Evidence from the Netherlands. (NBER working paper / National Bureau of Economic Research 31009), Cambridge, Mass, 60 S.

Abstract

"We estimate the effects of robot adoption on firm-level and worker-level outcomes in the Netherlands using a large employer-employee panel dataset spanning 2009-2020. Our firm-level results confirm previous findings, with positive effects on value added and hours worked for robot-adopting firms and negative outcomes on competitors in the same industry. Our worker-level results show that directly-affected workers (e.g., blue-collar workers performing routine or replaceable tasks) face lower earnings and employment rates, while other workers indirectly gain from robot adoption. We also find that the negative effects from competitors' robot adoption load on directly-affected workers, while other workers benefit from this industry-level robot adoption. Overall, our results highlight the uneven effects of automation on the workforce." (Author's abstract, IAB-Doku) ((en))

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Agrawal, Ajay K., Joshua S. Gans & Avi Goldfarb (2023): The Turing Transformation: Artificial Intelligence, Intelligence Augmentation, and Skill Premiums. (NBER working paper / National Bureau of Economic Research 31767), Cambridge, Mass, 12 S.

Abstract

"We ask whether a technical objective of using human performance of tasks as a benchmark for AI performance will result in the negative outcomes highlighted in prior work in terms of jobs and inequality. Instead, we argue that task automation, especially when driven by AI advances, can enhance job prospects and potentially widen the scope for employment of many workers. The neglected mechanism we highlight is the potential for changes in the skill premium where AI automation of tasks exogenously improves the value of the skills of many workers, expands the pool of available workers to perform other tasks, and, in the process, increases labor income and potentially reduces inequality. We label this possibility the “Turing Transformation.” As such, we argue that AI researchers and policymakers should not focus on the technical aspects of AI applications and whether they are directed at automating human-performed tasks or not and, instead, focus on the outcomes of AI research. In so doing, our goal is not to diminish human-centric AI research as a laudable goal. Instead, we want to note that AI research that uses a human-task template with a goal to automate that task can often augment human performance of other tasks and whole jobs. The distributional effects of technology depend more on which workers have tasks that get automated than on the fact of automation per se." (Author's abstract, IAB-Doku) ((en))

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Bock-Schappelwein, Julia & Andrea Egger (2023): Arbeitsmarkt und Beruf 2030. Rückschlüsse für Österreich. (AMS-Report / Arbeitsmarktservice Österreich 173), Wien, 110 S.

Abstract

"Demographie, Digitalisierung und Ökologisierung werden die Arbeitswelt in den kommenden Jahren maßgeblich beeinflussen. Mit Hilfe von Literaturanalysen wird im Rahmen dieser mit Jahresmitte 2023 abgeschlossenen Studie im Auftrag der Abt. Arbeitsmarktforschung und Berufsinformation des AMS Österreich von den beiden Autorinnen Julia Bock-Schappelwein (WIFO) und Andrea Egger (abif) nach Berufsfeldern gesucht, in denen sich diese Herausforderungen deutlich abzeichnen und möglicherweise gegenseitig verstärken. Ziel ist es, besonders betroffene Berufsfelder zu identifizieren und damit verbundene Anpassungs- bzw. Qualifizierungsbedarfe aufzuzeigen." (Autorenreferat, IAB-Doku)

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Bogusz, Honorata, Anna Matysiak & Michaela Kreyenfeld (2023): Structural Labour Market Change, Cognitive Work, and Fertility in Germany. (Working papers / Faculty of Economic Sciences, University of Warsaw 2023-08), Warsaw, 44 S.

Abstract

"Technological change and globalisation have been transforming the structure of labour demand in favour of workers performing cognitive tasks. Even though past research has found that labour force participation is an important determinant of fertility behaviour, few studies have addressed the fertility effects of the long-term structural changes of labour market. To fill this gap, we measure the cognitive task content of work at the occupation level using data from the Employment Survey of the German Federal Institute for Vocational Education and Training (BiBB). We link this contextual information with employment and fertility histories of women and men from the German Socio-Economic Panel 1984-2018 (GSOEP). With event history models, we find that fertility transitions of men working in occupations characterised by high cognitive task intensity are accelerated. We also observe elevated birth risks among women in occupations requiring cognitive labour. However, this pattern is more ambiguous, as we find that non-working women also experience elevated birth rates." (Author's abstract, IAB-Doku) ((en))

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Brynjolfsson, Erik & Gabriel Unger (2023): The macroeconomics of artificial intelligence. In: Finance and development H. December, S. 20-25.

Abstract

"Economists have a poor track record of predicting the future. And Silicon Valley repeatedly cycles through hope and disappointment over the next big technology. So a healthy skepticism toward any pronouncements about how artificial intelligence will change the economy is justified. Nonetheless, there are good reasons to take seriously the growing potential of AI—systems that exhibit intelligent behavior, such as learning, reasoning, and problem-solving —to transform the economy, especially given the astonishing technica ladvances of the past year. AI may affect society in a number of areas besides the economy—including national security, politics, and culture. But in this article, we focus on the implications of AI on three broad areas of macroeconomic interest: productivity growth, the labor market, and industrial concentration. AI does not have a predetermined future. It can develop in very different directions. The particular future that emerges will be a consequence of many things, including technological and policy decisions made today. For each area, we present a fork in the road: two paths that lead to very different futures for AI and the economy. In each case, the bad future is the path of least resistance. Getting to the better future will require good policy—including • Creative policy experiments • A set of positive goals for what society wants from AI, not just negative outcomes to be avoided • Understanding that the technological possibilities of AI are deeply uncertain and rapidly evolving and that society must be flexible in evolving with them." (Author's abstract, IAB-Doku) ((en))

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Bughin, Jacques (2023): Does artificial intelligence kill employment growth: the missing link of corporate AI posture. In: Frontiers in artificial intelligence, Jg. 6. DOI:10.3389/frai.2023.1239466

Abstract

"Introduction An intense debate has been on-going about how artificial intelligence (AI) technology investments have an impact on employment. The debate has often focused on the potential of AI for human task automation, omitting the strategic incentive for firms to cooperate with their workers as to exploit AI technologies for the most relevant benefit of new product and service innovation. Method We calibrate an empirical probit regression model of how changes in employment relate to AI diffusion, based on formalizing a game-theoretical model of a firm exploiting the twin role of AI innovation and AI automation for both absolute and competitive advantage. Results The theoretical game-theory prediction is that employment following AI technology adoption is not negative, and ultimately depends on how AI leads to new success in innovation, competition which defines the competitive reward of innovation and profit sharing between workers and firms. Our estimation, is based on a global survey of 3,000 large companies across 10 countries, demonstrates that a firm employment growth depends on two strategic postures, that is, the firm relative maturity of AI adoption as well as its relative bias toward AI-based product innovation. Discussion The contribution of this research is to highlight the twin role of firm and workers in shaping how technology will affect employment. AI in particular marries the potential of task automation with even more potential for expansion." (Author's abstract, IAB-Doku) ((en))

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Carbonero, Francesco, Enzo Weber & Christian J. Offermanns (2023): The Fall of the Labor Income Share: the Role of Technological Change and Hiring Frictions. In: Review of Economic Dynamics, Jg. 49, S. 251-268., 2022-01-09. DOI:10.1016/j.red.2022.09.001

Abstract

"Die Veränderungen in der funktionalen Einkommensverteilung erhalten in der Forschung viel Aufmerksamkeit. Wir dokumentieren einen durchschnittlichen Rückgang des labour share (Anteil des Faktors Arbeit an der Einkommensverteilung) von 8 Prozentpunkten für acht europäische Länder und die USA zwischen 1980 und 2007. Wir untersuchen theoretisch und empirisch zwei Mechanismen: Substitution zwischen Informations- und Kommunikationstechnologie (IKT) und Arbeit sowie Friktionen bei Beschäftigungsanpassungen. Wir finden, dass Substitution zwischen IKT und Arbeit wesentlich den Rückgang des labour share erklären kann. Wenn Arbeitsmarktfriktionen berücksichtigt werden, übernehmen diese allerdings einen Teil der Erklärungskraft. Insbesondere spielen Einstellungskosten in Europa eine größere Rolle als in den USA. Schließlich wird die Subsitutionselastizität zwischen IKT und Arbeit als Funktion institutioneller und struktureller Variablen modelliert und festgestellt, dass sie mit dem Anteil von Routine-Berufen positiv und mit dem Anteil hochqualifizierter Arbeiter negativ korreliert." (Autorenreferat, IAB-Doku)

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Cardi, Olivier & Romain Restout (2023): Why Hours Worked Decline Less after Technology Shocks? (Economics working paper series / The Department of Economics, Lancaster University Management School 2023,07), Lancaster, 187 S.

Abstract

"The contractionary effect of aggregate technology shocks on hours worked has shrunk over time in OECD countries. Our estimates suggest that this finding can be attributed to the increasing share of the variance of technology improvements driven by asymmetric technology shocks across sectors. While technology improvements uniformly distributed across sectors are found empirically to give rise to a dramatic decline in total hours worked, asymmetric technology shocks do the opposite. By depreciating non-traded prices, symmetric technology shocks generate a contractionary effect on non-traded labor and thus on total hours. In contrast, by appreciating non-traded prices, technological change concentrated toward traded industries puts upward pressure on wages which has a strong expansionary effect on total hours worked. A two-sector open economy model with frictions into the movements of inputs can reproduce the time-increasing response of both total and sectoral hours worked we estimate empirically once we allow for factor-biased technological change and we let the share of asymmetric technology shocks increase over time. A model with endogenous technology decisions reveals that two-third of the progression of asymmetric technology shocks is driven by greater exposition of traded industries to the international stock of knowledge." (Author's abstract, IAB-Doku) ((en))