Digitale Arbeitswelt – Chancen und Herausforderungen für Beschäftigte und Arbeitsmarkt
Der digitale Wandel der Arbeitswelt gilt als eine der großen Herausforderungen für Wirtschaft und Gesellschaft. Wie arbeiten wir in Zukunft? Welche Auswirkungen hat die Digitalisierung und die Nutzung Künstlicher Intelligenz auf Beschäftigung und Arbeitsmarkt? Welche Qualifikationen werden künftig benötigt? Wie verändern sich Tätigkeiten und Berufe? Welche arbeits- und sozialrechtlichen Konsequenzen ergeben sich daraus?
Dieses Themendossier dokumentiert Forschungsergebnisse zum Thema in den verschiedenen Wirtschaftsbereichen und Regionen.
Im Filter „Autorenschaft“ können Sie auf IAB-(Mit-)Autorenschaft eingrenzen.
- Gesamtbetrachtungen/Positionen
- Arbeitsformen, Arbeitszeit und Gesundheit
- Qualifikationsanforderungen und Berufe
- Arbeitsplatz- und Beschäftigungseffekte
- Wirtschaftsbereiche
- Arbeits- und sozialrechtliche Aspekte / digitale soziale Sicherung
- Deutschland
- Andere Länder/ internationaler Vergleich
- Besondere Personengruppen
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Literaturhinweis
Winners and losers when firms robotize: wage effects across occupations and education (2026)
Zitatform
Barth, Erling, Marianne Røed, Pål Schøne & Janis Umblijs (2026): Winners and losers when firms robotize: wage effects across occupations and education. In: The Scandinavian Journal of Economics, Jg. 128, H. 1, S. 3-32. DOI:10.1111/sjoe.12593
Abstract
"This paper analyses the impact of robots on workers' wages in the manufacturing sector, with a particular focus on relative wages for workers with different levels of education and in different occupations. Using high-quality matched employer–employee register data with firm-level information on the introduction of industrial robots, we identify the effects of robotization on relative wages within firms. Skilled blue-collar workers with a vocational degree experience a decline in wages when firms introduce robots, while there are only small effects for the other groups of workers. These results suggest that robots are substitutes for tasks undertaken by skilled blue-collar workers in manufacturing, and furthermore that the adoption of robots contributes to a polarization of the labor market and a hollowing out of the wage distribution, rather than to skill-biased technical change." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation Experiments and Inequality (2026)
Zitatform
Benzell, Seth Gordon & Kyle R. Myers (2026): Automation Experiments and Inequality. (NBER working paper / National Bureau of Economic Research 34668), Cambridge, Mass, 26 S., App. DOI:10.3386/w34668
Abstract
"Many experiments study the productivity effects of automation technologies such as generative algorithms. A key test in these experiments relates to inequality: does the technology increase output more for high- or low-skill workers? However, the theoretical content of this empirical test has been unclear. Here, we formalize a theory that describes the experimental effect of automation technologies on worker-level output and, therefore, inequality. Worker-level output depends on a task-level production function, and workers are heterogeneous in their task-level skills. Workers perform a task themselves or delegate it to the automation technology. The inequality effect of improved automation depends on the interaction of two factors: (i) the correlation in task-level skills across workers, and (ii) workers' skills relative to the technology's effective skill. In many cases we study, the inequality effect is non-monotonic --- as technologies improve, inequality decreases then increases. The model and descriptive statistics of skill correlations generally suggest that the diversity of automation technologies will play an important role in the evolution of inequality." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Digital divide and income inequality: causal evidence from Italian provinces (2026)
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Bergantino, Angela Stefania, Giulio Fusco, Mario Intini & Gianluca Monturano (2026): Digital divide and income inequality: causal evidence from Italian provinces. In: The Annals of Regional Science, Jg. 75, H. 1. DOI:10.1007/s00168-025-01440-z
Abstract
"The digital economy can function either as a catalyst to stimulate economic growth or else as a driver of socioeconomic inequality when its benefits are unevenly distributed. This study investigates the effect of rural digital connectivity on income inequality in Italy. Utilizing NUTS 3 panel data spanning 2014–2022, we conduct a counterfactual Difference-in-Differences approach with continuous treatment intensity to estimate the impact of introducing rural broadband coverage at speeds of 30 and 100 Mbps on multiple measures of income distribution, including the Gini, Theil, and Atkinson indices. The empirical framework incorporates a comprehensive set of socioeconomic controls, as well as provincial and time fixed effects, to account for unobserved heterogeneity and regional path dependencies. Our findings indicate that broadband expansion is significantly associated with increasing inequality, suggesting that access alone does not guarantee inclusive outcomes, particularly in localities characterized by structural fragility and limited human capital. Additional heterogeneity and spatial analyses demonstrate that these inequality effects are more evident in southern provinces and localities with a higher concentration of inner areas, where the digital divide remains more pronounced. These findings accentuate the dual role of digitalization and highlight the necessity of coordinated policy interventions that combine infrastructure investment with digital skills development, institutional capacity-building, and spatially integrated governance strategies." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Retirement decisions in the age of COVID-19 pandemic: are older employees in digital occupations working longer? (2026)
Zitatform
Gallo, Giovanni & Amparo Nagore García (2026): Retirement decisions in the age of COVID-19 pandemic: are older employees in digital occupations working longer? In: Review of Economics of the Household, S. 1-34. DOI:10.1007/s11150-025-09827-9
Abstract
"This paper investigates the retirement response to the pandemic and to the resulting acceleration in the adoption of new technologies. Using the European Union Statistics of Income and Living Conditions datasets and leveraging the natural experiment of many workers being forced to work from home in Europe during the lockdown, we compare the retirement response of older workers in digital occupations (i.e. more exposed to the accelerated adoption of new technologies) versus non-digital occupations to detect any differences in retirement behaviour, which we interpret as digitalization effects. In addition, we analyze changes in retirement decisions by gender and geographic area. We find that retirement rates increased during COVID-19 in Europe, especially in Mediterranean countries and among women. This trend may be linked to gender occupational segregation. In Mediterranean countries, digitalization increases female retirement, likely due to challenges in balancing digital work and family responsibilities while working from home. In Eastern countries, and to a lesser extent in Northern countries, digitalization leads to postponing retirement among women, likely due to greater gender equality in unpaid work. In contrast, the retirement age for men is less affected by the pandemic with no significant differences between digital and non-digital occupations. This may exacerbate the existing gender gap in labor force participation and pension outcomes." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))
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Literaturhinweis
Automation and the risk of labor market exclusion across Europe (2026)
Zitatform
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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Literaturhinweis
Good Jobs or Bad Jobs? Immigrant Workers in the Gig Economy (2026)
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Liu, Cathy Yang & Rory Renzy (2026): Good Jobs or Bad Jobs? Immigrant Workers in the Gig Economy. In: International migration review, Jg. 60, H. 1, S. 114-138. DOI:10.1177/01979183241309585
Abstract
"New work arrangements enabled by online platforms, or gig work, saw substantive growth during the COVID-19 pandemic. Various estimates have suggested the wide participation of workers in the gig economy, with minority and immigrant workers well represented. The quality of work is a multi-dimensional concept that goes beyond earnings. One framework of good jobs and bad jobs centers on control over work schedule, content and duration, stability, safety, benefits and insurance, as well as career advancement opportunities. Using a newly released national survey focused on entrepreneurs and workers in the United States, we find that about 18.5 percent immigrant workers and 21.1 percent native-born workers participated in the gig economy as their primary or secondary job. In terms of job quality, immigrant gig workers work shorter hours and have significantly less fringe benefits than non-gig workers as well as U.S.-born gig workers, reflecting a double disadvantage. However, they tend to have higher entrepreneurial aspirations, suggesting the transient nature of gig arrangements and potential for career advancements. This paper provides a comprehensive analysis of the characteristics and implication of immigrants’ engagement with the gig economy and offers policy and theoretical discussions." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Improving the effects of industrial robot adoption on employment, total factor productivity, and real wages in 52 world economies and OECD members (2026)
Zitatform
Matsuki, Takashi (2026): Improving the effects of industrial robot adoption on employment, total factor productivity, and real wages in 52 world economies and OECD members. In: Review of world economics, S. 1-32. DOI:10.1007/s10290-025-00626-z
Abstract
"This study investigates the effects of industrial robot adoption in the production process on unemployment rate, employment ratio in manufacturing, and total factor productivity (TFP) growth in 52 countries, and real wage growth in 31 and 20 OECD member countries for 2007–2019. The operating stock of robots per employee significantly impacts these variables; robot adoption lowers the unemployment rate and raises TFP and real wage growth. However, it reduces the employment ratio in manufacturing. In addition, the slight but significant positive contribution of robot adoption is observed only in the 90-percentile (top 10-percentile) of the real wage distribution. Interestingly, workers in the bottom and top tails (10- and 90-percentiles) of the wage distribution asymmetrically benefit from robotization. The industry ratio of value-added improves the labor market by reducing the unemployment rate and raising the employment ratio in manufacturing, TFP growth, and real wage growth. The information and communication technology (ICT) development also positively contributes to the employment ratio in Asia’s manufacturing, TFP growth, and real wage growth." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
How local labour market skill relatedness and size moderate the impacts of automation (2026)
Zitatform
Njekwa Ryberg, Peter (2026): How local labour market skill relatedness and size moderate the impacts of automation. In: Regional Studies, Jg. 60, H. 1. DOI:10.1080/00343404.2025.2598031
Abstract
"This paper examines how local labour market skill relatedness and size moderate the impacts of automation on occupations across Swedish local labour markets. Using administrative data and a spatially explicit risk of automation measure that accounts for regional differences in occupational task contents, it finds a negative association between automation and employment growth and wage income growth for non-metropolitan occupations between 2011 and 2021. Skill relatedness and labour market size mitigate these negative relationships. In contrast, no negative associations are found for metropolitan occupations. Due to their higher shares of non-automatable tasks, they are more resilient to adverse automation effects." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Human-centred digital transitions and skill mismatches in European workplaces (2026)
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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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Literaturhinweis
Where Have All the (Boomer) Routine Workers Gone? (2026)
Scotese, Carol A.;Zitatform
Scotese, Carol A. (2026): Where Have All the (Boomer) Routine Workers Gone? In: The B.E. Journal of Economic Analysis and Policy, S. 1-44. DOI:10.1515/bejeap-2024-0396
Abstract
"This paper examines the employment outcomes of a cohort of non-college educated individuals who exit employment from occupations most exposed to automation risk. The analysis employs a novel set of granular task measures estimated from the detailed job attributes in the Occupational Information Network (O*NET). The granularity enables a rich characterization of non-routine work and task mobility choices for those without a college degree. The data yield multiple types of interpersonal, decision-making, cognitive, and technical tasks. Employing the granular tasks to analyze the employment outcomes for non-college educated workers who transition out of routine work, this study finds (1) the granular measures detect abstract tasks performed intensively in a range of skill contexts, (2) when exiting routine intensive work, non-college propensity to enter abstract work is just under 65 %, and (3) approximately one-quarter of those entries are into tasks yielding average wage gains for those making that transition." (Author's abstract, IAB-Doku, © De Gruyter) ((en))
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Literaturhinweis
AI Skills Improve Job Prospects: Causal Evidence from a Hiring Experiment (2026)
Zitatform
Stephany, Fabian, Ole Teutloff & Angelo Leone (2026): AI Skills Improve Job Prospects: Causal Evidence from a Hiring Experiment. (arXiv papers), 46 S. DOI:10.48550/arXiv.2601.13286
Abstract
"The growing adoption of artificial intelligence (AI) technologies has heightened interest in the labour market value of AI-related skills, yet causal evidence on their role in hiring decisions remains scarce. This study examines whether AI skills serve as a positive hiring signal and whether they can offset conventional disadvantages such as older age or lower formal education. We conduct an experimental survey with 1,700 recruiters from the United Kingdom and the United States. Using a paired conjoint design, recruiters evaluated hypothetical candidates represented by synthetically designed résumés. Across three occupations – graphic designer, officeassistant, and software engineer –, AI skills significantly increase interview invitation probabilities by approximately 8 to 15 percentage points. AI skills also partially or fully offset disadvantages related to age and lower education, with effects strongest for office assistants, where formal AI certification plays an additional compensatory role. Effects are weaker for graphic designers, consistent with more skeptical recruiter attitudes toward AI in creative work. Finally, recruiters’ own background and AI usage significantly moderate these effects. Overall, the findings demonstrate that AI skills function as a powerful hiring signal and can mitigate traditional labour market disadvantages, with implications for workers’ skill acquisition strategies and firms’ recruitment practices." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation and Polarization (2025)
Zitatform
Acemoglu, Daron & Jonas Löbbing (2025): Automation and Polarization. In: Journal of Political Economy. 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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Literaturhinweis
The Impact of Aging and AI on Japan's Labor Market: Challenges and Opportunities (2025)
Asao, Kohei; Seitani, Haruki; Stepanyan, Ara; Xu, TengTeng;Zitatform
Asao, Kohei, Haruki Seitani, Ara Stepanyan & TengTeng Xu (2025): The Impact of Aging and AI on Japan's Labor Market: Challenges and Opportunities. (IMF working papers / International Monetary Fund 2025,184), Washington, DC, 17 S.
Abstract
"This paper explores the complex roles of demographic changes and technological innovation in shaping Japan's labor market. We use regression analysis to assess the impact of population aging on labor productivity and shortages. Our findings indicate that the aging workforce contributes to labor shortages and potentially weighs on labor productivity. We also investigate occupational level data to identify the complementarity and substitutability of AI in occupational tasks as well as skill transferability. Our research reveals that Japanese workers face lower exposure to AI compared to their counterparts in other advanced economies, thereby constraining AI's potential to mitigate labor shortages. Furthermore, the disparities in skill requirements across occupations with different AI exposures highlight the importance of facilitating labor mobility from displaced jobs to those in demand." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
On automation, labor reallocation and welfare (2025)
Zitatform
Auray, Stéphane & Aurélien Eyquem (2025): On automation, labor reallocation and welfare. In: Journal of Economic Dynamics and Control, Jg. 177. DOI:10.1016/j.jedc.2025.105129
Abstract
"We develop an open-economy model of endogenous automation with heterogeneous firms and labor-market reallocation to quantify the contribution of various trends to the adoption of robots in the U.S. economy. The decline in the relative price of robots is the major trend leading to automation, but interacts with other trends that either hinder (rising entry costs, rising markups) or slightly foster (rising labor productivity, declining trade costs) the adoption of robots. Taken alone, the decline in the relative price of robots produces moderate welfare gains in the long run, but less than labor productivity growth. We then exploit our model to show that a decline in the relative price of robots (i) generates small positive cross-country automation spillovers and (ii) produces inefficient labor-market reallocation since a small subsidy on robots combined with a training subsidy can generate small welfare gains. Our main conclusion is that automation can not be simply modeled as an exogenous decline in the price of robots, and must be analyzed in a broader framework taking into account trends affecting firms, such as the decline in business dynamism and the rise in markups." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V.) ((en))
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Literaturhinweis
Expertise (2025)
Autor, David; Thompson, Neil;Zitatform
Autor, David & Neil Thompson (2025): Expertise. In: Journal of the European Economic Association, Jg. 23, H. 4, S. 1203-1271. DOI:10.1093/jeea/jvaf023
Abstract
"When job tasks are automated, does this augment or diminish the value of labor in the tasks that remain? We argue the answer depends on whether removing tasks raises or reduces the expertise required for remaining non-automated tasks. Since the same task may be relatively expert in one occupation and inexpert in another, automation can simultaneously replace experts in some occupations while augmenting expertise in others. We propose a conceptual model of occupational task bundling that predicts that changing occupational expertise requirements have countervailing wage and employment effects: automation that decreases expertise requirements reduces wages but permits the entry of less expert workers; automation that raises requirements raises wages but reduces the set of qualified workers. We develop a novel, content-agnostic method for measuring job task expertise, and we use it to quantify changes in occupational expertise demands over four decades attributable to job task removal and addition. We document that automation has raised wages and reduced employment in occupations where it eliminated inexpert tasks, but lowered wages and increased employment in occupations where it eliminated expert tasks. These effects are distinct from—and in the case of employment,opposite to—the effects of changing task quantities. The expertise framework resolves the puzzle of why routine task automation has lowered employment but often raised wages in routine task-intensive occupations. It provides a general tool for analyzing how task automation and new task creation reshape the scarcity value of human expertise within and across occupations." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Intersecting Shocks: The Combined Labor Market Impacts of Automation and Immigration (2025)
Bennett, Patrick; Johnsen, Julian Vedeler;Zitatform
Bennett, Patrick & Julian Vedeler Johnsen (2025): Intersecting Shocks: The Combined Labor Market Impacts of Automation and Immigration. (CESifo working paper 12217), München, 41 S.
Abstract
"We study how the labor market shocks of automation and immigration interact to shape workers' outcomes. Using matched employer –employee data from Norwegian administrative registers, we combine animmigration shock triggered by the European Union's 2004 enlargement with an automation shock based on the adoption of industrial robots across Europe. Although these shocks largely occur in separate industries, we show that automation reduces earnings not only in manufacturing but also in construction, where tasks overlap with robot-exposed sectors. Importantly, workers jointly exposed to automation and immigration suffer earnings losses greater than those facing either shock in isolation. These losses are driven by downward occupational mobility into low-wage services and re-sorting into lower-premium firms. Even within the Norwegian welfare system, the ability of social insurance to offset these long-run earnings declines is limited. Our findings underscore the importance of analyzing labor market shocks jointly, rather than in isolation, to fully understand their distributional consequences." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Remote work, skill upgrading, and wage inequality post-COVID (2025)
Zitatform
Bennett, Jeremy (2025): Remote work, skill upgrading, and wage inequality post-COVID. In: Economics of Innovation and New Technology, S. 1-24. DOI:10.1080/10438599.2025.2602133
Abstract
"This paper examines how the widespread shift to remote work during the COVID-19 pandemic reshaped skill development and wage inequality across occupations in the United States. Using a difference-in-differences framework and data from the Current Population Survey (CPS), American Time Use Survey (ATUS), and O*NET, we compare outcomes for remote-capable and non-remote occupations before and after the pandemic. Results show that remote-capable jobs experienced significantly higher wage growth – approximately 4–5 percent – relative to non-remote jobs, even after accounting for worker and occupational characteristics. These occupations also displayed greater gains in educational attainment and digital skill engagement, while non-remote occupations faced disruptions in access to training. The findings align with human-capital and task-based theories, suggesting that remote work intensified skill-biased technological inequality. Policy implications include the need for targeted workforce training, equitable digital infrastructure investment, and institutional support for workers in less adaptable roles. The study contributes to understanding how technological and organizational change reshape human capital formation and wage structures in the post-pandemic labor market." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The dynamics of automation adoption: Firm-level heterogeneity and aggregate employment effects (2025)
Zitatform
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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Literaturhinweis
Re‐Skilling in the Age of Skill Shortage: Adult Education Rather Than Active Labor Market Policy (2025)
Zitatform
Bonoli, Giuliano, Patrick Emmenegger & Alina Felder-Stindt (2025): Re‐Skilling in the Age of Skill Shortage: Adult Education Rather Than Active Labor Market Policy. In: Regulation and governance, S. 1-13. DOI:10.1111/rego.70065
Abstract
"European economies face the task of providing the necessary skills for the “twin transition ” in a period of skill shortage. As a result, we may expect countries to reorient their labor market policy towards re-skilling. We look for evidence of a reorientation in two relevant policy fields: active labor market policy (ALMP) and adult education (AE). We explore general trends in both fields based on quantitative indicators and compare recent policy developments in four countries with strong ALMP and AE sectors: Denmark, France, Germany, and Sweden. We do not observe clear evidence of a general movement away from activation and towards re-skilling in ALMP. However, in AE, we identify several re-skilling initiatives that address skill shortages. Relying on insights from queuing theories of hiring and training, we argue that due to changes in the population targeted by ALMP, the locus of re-skilling policy is increasingly moving towards AE." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation and segmentation: Downgrading employment quality among the former “insiders” of Western European labour markets (2025)
Zitatform
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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Literaturhinweis
Technological innovations and workers’ job insecurity: the moderating role of human resource strategies (2025)
Zitatform
Caselli, Mauro, Andrea Fracasso, Arianna Marcolin & Sergio Scicchitano (2025): Technological innovations and workers’ job insecurity: the moderating role of human resource strategies. In: Journal of industrial and business economics, Jg. 52, H. 1, S. 153-176. DOI:10.1007/s40812-024-00329-w
Abstract
"In this paper, we empirically assess the impact of firms’ technological innovations on the workers’ perceived probability of job loss. We take advantage of a unique dataset based on a large and representative cross-sectional survey covering several characteristics of Italian workers and their firms. We find that a firm ’s technological adoption reduces job insecurity among its surviving workers, and the effect is stronger when the innovation makes tasks simpler and their execution more precise. We also find that the relationship between technological innovation and job insecurity is moderated by human resource strategies, such as training programs, labor-saving automation and dismissal plans adopted after the introduction of the innovation. Thus, workers’ perceptions of job insecurity vary significantly across innovative firms, and firms’ human resource strategies act as arelevant moderating factors." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment (2025)
Zitatform
Caselli, Mauro, Andrea Fracasso, Sergio Scicchitano, Silvio Traverso & Enrico Tundis (2025): What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment. In: Research Policy, Jg. 54, H. 1. DOI:10.1016/j.respol.2024.105135
Abstract
"This work investigates the impact that changes in the local exposure to robots had on changes in Italian employment over the period 2011–2018. It contributes to the debate by providing novel and granular evidence on the impact of robot adoption on new activity-based groups of occupations and by focusing on the overlap between the functional similarities of robot applications and occupations. This framework, consistently centered on workers ’ and robots’ activities, reveals highly heterogeneous effects of robotization, ranging from positive to negative across different groups of occupations, thereby supporting a nuanced and granular reading of this debated phenomenon. In particular, the local share of robot operators increases where the increase in robot adoption is larger, while the local share of workers using intensively their torso decreases." (Author's abstract, IAB-Doku, © 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.) ((en))
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Literaturhinweis
AI and the global productivity divide: Fuel for the fast or a lift for the laggards? (2025)
Zitatform
Chaar, Tania, Francesco Filippucci, Cecilia Jona-Lasinio & Giuseppe Nicoletti (2025): AI and the global productivity divide. Fuel for the fast or a lift for the laggards? (OECD Artificial Intelligence Papers 51), Paris, 42 S. DOI:10.1787/c315ea90-en
Abstract
"Artificial Intelligence (AI) has the potential to be an important driver of productivity growth over the next decade, even if with significant cross-country heterogeneity. This paper examines the potential of AI to foster productivity growth in Low-Income Countries (LICs) and Lower-Middle-Income Countries (LMICs). LICs and LMICs risk benefiting less from AI due to low incidence of knowledge-intensive services, where gains from AI mostly occur. Additionally, barriers to AI adoption include inadequate digital infrastructure, low levels of education and skills in the workforce, limited access to financing for high AI adoption costs, and underdeveloped regulatory frameworks. At the same time, LICs and LMICs may benefit from factors such as a young workforce and international spillovers through knowledge transfers. Overall, structural weaknesses in LICs and LMICs risk outweighing these potential advantages. This underscores the need for policies that enhance capabilities for AI adoption in LICs and LMICs and help seizing long-run opportunities from the global AI economy." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
How welfare states influence online platform work in Europe (2025)
Zitatform
Chueri, Juliana & Petter Törnberg (2025): How welfare states influence online platform work in Europe. In: Journal of European Social Policy, S. 1-17. DOI:10.1177/09589287251357463
Abstract
"Digital labor platforms are reshaping global labor markets by enabling the transnational contracting of service workers. While the dominant perspective emphasizes market forces, predicting that lower-wage countries will dominate the supply side, this view overlooks the institutional context in which platform labor emerges. This paper advances the argument that national welfare institutions are key to shaping participation in the platform economy. We provide the first large-scale cross-national comparative analysis of platform labor, combining micro-level data from one of the world’s largest remote work platforms with country-level indicators from 26 European countries. In line with market expectations, we find that lower-wage countries supply most low-skilled labor, while higher-wage countries show a more balanced distribution between low- and high-skilled workers. Crucially, however, our analysis reveals that greater welfare state generosity is associated with lower levels of platform participation, especially in low-skilled occupations. We argue that platform labor cannot be understood solely as a function of technological change or wage differentials. It is also an expression of structural constraints: where social protections are weak, people are more likely to turn to precarious forms of online work." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Equalising the effects of automation? The role of task overlap for job finding (2025)
Zitatform
Dabed, Diego, Sabrina Genz & Emilie Rademakers (2025): Equalising the effects of automation? The role of task overlap for job finding. In: Labour Economics, Jg. 96. DOI:10.1016/j.labeco.2025.102766
Abstract
"This paper investigates whether task overlap can equalise the distributional effects of automation for unemployed job seekers displaced from routine jobs. Using a language model, we establish a novel job-to-job task similarity measure. Exploiting the resulting job network to define job markets flexibly, we find that only the most similar jobs affect job finding. Since automation-exposed jobs overlap with other highly exposed jobs, task-based reallocation provides little relief for affected job seekers. We show that this is not true for more recent software exposure, for which task overlap lowers the inequality in job finding." (Author's abstract, IAB-Doku, © 2025 The Authors. Published byElsevier B.V.) ((en))
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Literaturhinweis
Macroeconomic and Labor Market Drivers of AI Adoption in Europe: A Machine Learning and Panel Data Approach (2025)
Zitatform
Drago, Carlo, Alberto Costantiello, Marco Savorgnan & Angelo Leogrande (2025): Macroeconomic and Labor Market Drivers of AI Adoption in Europe: A Machine Learning and Panel Data Approach. In: Economies, Jg. 13, H. 8. DOI:10.3390/economies13080226
Abstract
"This article investigates the macroeconomic and labor market conditions that shape the adoption of artificial intelligence (AI) technologies among large firms in Europe. Based on panel data econometrics and supervised machine learning techniques, we estimate how public health spending, access to credit, export activity, gross capital formation, inflation, openness to trade, and labor market structure influence the share of firms that adopt at least one AI technology. The research covers all 28 EU members between 2018 and 2023. We employ a set of robustness checks using a combination of fixed-effects, random-effects, and dynamic panel data specifications supported by Clustering and supervised learning techniques. We find that AI adoption is linked to higher GDP per capita, healthcare spending, inflation, and openness to trade but lower levels of credit, exports, and capital formation. Labor markets with higher proportions of salaried work, service occupations, and self-employment are linked to AI diffusion, while unemployment and vulnerable work are detractors. Cluster analysis identifies groups of EU members with similar adoption patterns that are usually underpinned by stronger economic and institutional fundamentals. The results collectively suggest that AI diffusion is shaped not only by technological preparedness and capabilities to invest but by inclusive macroeconomic conditions and equitable labor institutions. Targeted policy measures can accelerate the equitable adoption of AI technologies within the European industrial economy." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Narrowing the digital divide: Economic and social convergence in Europe’s digital transformation (2025)
Duff, Cían; Soldi, Rossella; Hyland, Marie; Cavallini, Simona; Peruffo, Eleonora; Krieg, Marielena;Zitatform
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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Literaturhinweis
Industrial robots and employment change in manufacturing: A decomposition analysis (2025)
Zitatform
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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Literaturhinweis
Cross-country skills-technology policy debates through large language models (2025)
Einhoff, Jan; López Trejos, Isabella; Paunov, Caroline;Zitatform
Einhoff, Jan, Isabella López Trejos & Caroline Paunov (2025): Cross-country skills-technology policy debates through large language models. (OECD science, technology and industry working papers 2025,20), Paris, 43 S. DOI:10.1787/d5f669be-en
Abstract
"Language models, this paper conducts a cross-country comparative innovation policy analysis of skills-technology policy debates across seven OECD member countries (Austria, Canada, Finland, Germany, Korea, Sweden, and the United Kingdom). Results highlight the dominance of STEM (science, technology, engineering and mathematics) and digital skills in these policy debates, the relative neglect of green skills, and the emphasis on soft skills across all technology fields. The analysis also identifies common policy instruments, which include collaborative platforms and direct financial support. Overall, the paper shows how large language models can help policy analysts identify patterns and gaps in extensive policy texts that nonetheless critically demands expert oversight and careful interpretation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The digital skill premium: Evidence from job vacancy data (2025)
Garcia-Lazaro, Aida ; Mendez-Astudillo, Jorge ; Newnes, Linda ; Larkin, Charles ; Lattanzio, Susan ;Zitatform
Garcia-Lazaro, Aida, Jorge Mendez-Astudillo, Susan Lattanzio, Charles Larkin & Linda Newnes (2025): The digital skill premium: Evidence from job vacancy data. In: Economics Letters, Jg. 250. DOI:10.1016/j.econlet.2025.112294
Abstract
"This paper examines the relationship between digital skills demand and posted wages in the UK using novel vacancy data. Digital skills — classified into basic, intermediate, and advanced using an XGBoost model — are linked to significant wage premiums. Within occupations, they are associated with 5.8% higher wages, with advanced and intermediate skills increasing wages by up to 8.9% when listed in job postings. Each additional digital skill increases wages by 1%, rising to 1.6% for advanced and intermediate skills. Artificial intelligence (AI) and cybersecurity skills yield particularly high returns, increasing wages by 8.6%–9.7% when listed and by 4.8%–5.4% per additional skill." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Contextualizing inequalities in the gig economy: evidence from online cleaning platforms in five European cities (2025)
Zitatform
Giuliani, Giovanni Amerigo & Rebecca Paraciani (2025): Contextualizing inequalities in the gig economy: evidence from online cleaning platforms in five European cities. In: The international journal of sociology and social policy, S. 1-20. DOI:10.1108/ijssp-12-2024-0619
Abstract
"Purpose: This paper explores the impact of national contexts on the profile of workers in the gig economy, with a specific focus on online cleaning platforms. The study aims to understand how national contexts influence the gender and ethnic composition of workers on domestic cleaning platforms, examining the intersectional effects of gender and ethnicity in platform-based work. Design/methodology/approach: Focusing on the case of the Yoopies platform operating in five Western European cities – Berlin, Copenhagen, Paris, Rome and Stockholm – this exploratory research is based on an original dataset that combines platform-based data directly collected from Yoopies with national-level data provided by Eurostat. Hypotheses were tested using simple correlation analysis to assess cross-country differences. Findings: The study shows that national contexts play an important role in shaping the gender and ethnic composition of workers on online cleaning platforms. Specifically, it identifies how structural features of the offline labor market influence the gendering and racialization of these platforms, highlighting variations across countries. The research also finds evidence of intersectional effects, where gender and ethnicity intersect to shape the profile of platform workers. Originality/value: This paper contributes to the growing literature on domestic work in the digital platform economy by providing a comparative perspective on cross-country differences in the composition of the platform workforce. It highlights the importance of national offline labor market characteristics in contributing to shaping platform-mediated work and provides new insights into the intersectionality of gender, ethnicity, and work in the gig economy. The findings contribute to both platform economy research and labor market studies, offering implications for policy and future research on the dynamics of digital work." (Author's abstract, IAB-Doku, © Emerald Group) ((en))
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Literaturhinweis
A technological construction of society: Comparing GPT-4 and human respondents for occupational evaluation in the UK (2025)
Zitatform
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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Literaturhinweis
Generative AI and jobs: a refined global index of occupational exposure (2025)
Gmyrek, Pawel ; Troszyński, Marek; Berg, Janine ; Kamiński, Karol; Nafradi, Balint ; Konopczyński, Filip; Rosłaniec, Konrad; Ładna, Agnieszka;Zitatform
Gmyrek, Pawel, Janine Berg, Karol Kamiński, Filip Konopczyński, Agnieszka Ładna, Balint Nafradi, Konrad Rosłaniec & Marek Troszyński (2025): Generative AI and jobs. A refined global index of occupational exposure. (ILO working paper / International Labour Organization 140), Geneva, 72 S. DOI:10.54394/hetp0387
Abstract
"This study updates the ILO’s 2023 Global Index of Occupational Exposure to Generative AI (GenAI), incorporating recent advances in the technology and increasing user familiarity with GenAI tools. Using a representative sample from the 29,753 tasks in the Polish occupational classification system and a survey of 1,640 people employed in each 1-digit ISCO-08 groups, we collect 52,558 data points regarding perceive potential of automation for 2,861 tasks. We then compare this input with a survey and several rounds of Delphi-style discussions among a smaller group of international experts. Based on this process, we create a repository of knowledge about task automation that goes beyond national specificities and use it to develop an AI assistant able to predict scores for tasks in the technical documentation of ISCO-08. Our 2025 scores are presented in a revised framework of four progressively increasing exposure gradients, with a new set of global estimates of employment shares exposed to GenAI. Clerical occupations continue to have the highest exposure levels. Additionally, some strongly digitized occupations have increased exposure, highlighting the expanding abilities of GenAI regarding specialized tasks in professional and technical roles. Globally, one in four workers are in an occupation with some GenAI exposure. 3.3% of global employment falls into the highest exposure category, albeit with significant differences between female (4.7%) and male employment (2.4%). These differences increase with countries’ income (9.6% female vs 3.5% male in Gradient 4in HICs), and so does the overall exposure (11% of total employment in LICs vs 34% in HICs). As most occupations consist of tasks that require human input, transformation of jobs is the most likely impact of GenAI. Linking our refined index with national micro data enables precise projections of such transformations, offering a foundation for social dialogue and targeted policy responses to manage the transition." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Governing the Digital Transition: The Moderating Effect of Unemployment Benefits on Technology‐Induced Employment Outcomes (2025)
Zitatform
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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Literaturhinweis
Does the Technological Transformation of Firms Go Along With More Employee Control Over Working Time? Empirical Findings From an EU-Wide Combined Dataset (2025)
Zitatform
Greenan, Nathalie & Silvia Napolitano (2025): Does the Technological Transformation of Firms Go Along With More Employee Control Over Working Time? Empirical Findings From an EU-Wide Combined Dataset. In: Review of Political Economy, Jg. 37, H. 2, S. 500-522. DOI:10.1080/09538259.2024.2445096
Abstract
"We investigate the links between the technological transformation of firms and employee control over working time. We conduct EU-wide analysis at the meso-level by relating information from the European Company Survey 2019 (Eurofound and Cedefop) with the Labour Force Survey ad hoc module 2019 (Eurostat). This dataset allows analysing the technological transformation of firms as a relationship between three types of investments (in R&D, digital technologies and learning capacity of the organisation) that spur innovation outputs. We then study the consequences of the technological transformation on the spread of unfavourable working time arrangements, distinguishing between individual and organisation-oriented arrangements. Our model considers the direct effects of investments in Digital technologies adoption and use and Learning capacity of the organisation and the mediating role of firms' innovation strategies. Results indicate that the Learning capacity of the organisation is directly associated with more individual-oriented working time flexibility, but entails higher organisation-oriented working time flexibility. The effect of Digital technologies adoption and use depends instead on firms' innovation strategy: product innovation leads to more employee control over working time, while marketing innovation has the opposite outcome. Process and organisational innovations yield mixed consequences buffering employees from organisation-oriented working time flexibility in more time-constrained work environments." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Diverging paths: AI exposure and employment across European regions (2025)
Zitatform
Guarascio, Dario, Jelena Reljic & Roman Stöllinger (2025): Diverging paths: AI exposure and employment across European regions. In: Structural Change and Economic Dynamics, Jg. 73, S. 11-24. DOI:10.1016/j.strueco.2024.12.010
Abstract
"This study explores exposure to artificial intelligence (AI) technologies and employment patterns in Europe. First, we provide a thorough mapping of European regions focusing on the structural factors—such as sectoral specialisation, R&D capacity, productivity and workforce skills—that may shape diffusion as well as economic and employment effects of AI. To capture these differences, we conduct a cluster analysis which group EU regions in four distinct clusters: high-tech service and capital centres, advanced manufacturing core, southern and eastern periphery. We then discuss potential employment implications of AI in these regions, arguing that while regions with strong innovation systems may experience employment gains as AI complements existing capabilities and production systems, others are likely to face structural barriers that could eventually exacerbate regional disparities in the EU, with peripheral areas losing further ground." (Author's abstract, IAB-Doku, © 2024 The Author(s). Published by Elsevier B.V.) ((en))
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Literaturhinweis
Robots vs. Workers: Evidence From a Meta‐Analysis (2025)
Zitatform
Guarascio, Dario, Alessandro Piccirillo & Jelena Reljic (2025): Robots vs. Workers: Evidence From a Meta‐Analysis. In: Journal of Economic Surveys, Jg. 39, H. 5, S. 2254-2271. DOI:10.1111/joes.12699
Abstract
"This study conducts a meta-analysis to assess the effects of robotization on employment and wages, synthesizing the evidence from 33 studies (644 estimates) on employment and a subset of 19 studies (195 estimates) on wages. The results challenge the alarmist narrative about the risk of widespread technological unemployment, suggesting that the overall relationship between robotization and employment or wages is minimal. However, the effects are far from uniform, with adverse outcomes observed in specific contexts, such as the United States, manufacturing sectors, and middle-skilled occupations. The analysis also identifies a publication bias favoring negative wage effects, though correcting for this bias confirms the negligible impact of robotization." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Generative AI's Impact on Student Achievement and Implications for Worker Productivity (2025)
Zitatform
Hausman, Naomi, Oren Rigbi & Sarit Weisburd (2025): Generative AI's Impact on Student Achievement and Implications for Worker Productivity. (CESifo working paper 11843), München, 39 S.
Abstract
"Student use of Artificial Intelligence (AI) in higher education is reshaping learning and redefining the skills of future workers. Using student-course data from a top Israeli university, we examine the impact of generative AI tools on academic performance. Comparisons across more and less AI-compatible courses before and after ChatGPT's introduction show that AI availability raises grades, especially for lower-performing students, and compresses the grade distribution, eroding the signal value of grades for employers. Evidence suggests gains in AI-specific human capital but possible losses in traditional human capital, highlighting benefits and costs AI may impose on future workforce productivity." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Large Language Models, Small Labor Market Effects (2025)
Zitatform
Humlum, Anders & Emilie Vestergaard (2025): Large Language Models, Small Labor Market Effects. (BFI Working Papers / University of Chicago, Becker Friedman Institute for Research in Economics 2025,56), Chicago, 64 S. DOI:10.2139/ssrn.5219933
Abstract
"We examine the labor market effects of AI chatbots using two large-scale adoption surveys (late 2023 and 2024) covering 11 exposed occupations (25,000 workers, 7,000 workplaces), linked to matched employer-employee data in Denmark. AI chatbots are now widespread —most employers encourage their use, many deploy in-house models, andtraining initiatives are common. These firm-led investments boost adoption, narrow demographic gaps in take-up, enhance workplace utility, and create new job tasks. Yet, despite substantial investments, economic impacts remain minimal. Using difference-in-differences and employer policies as quasi-experimental variation, we estimate precise zeros: AI chatbots have had no significant impact on earnings or recorded hours in any occupation, with confidence intervals ruling out effects larger than 1%. Modest productivity gains (average time savings of 3%), combined with weak wage pass-through, help explain these limited labor market effects. Our findings challenge narratives of imminent labor market transformation due to Generative AI." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Robots & AI exposure and wage inequality: a within occupation approach (2025)
Zitatform
Jaccoud, Florencia (2025): Robots & AI exposure and wage inequality: a within occupation approach. In: Eurasian business review, Jg. 15, H. 4, S. 1035-1090. DOI:10.1007/s40821-025-00306-w
Abstract
"This paper examines the linkages between occupational exposure to recent automation technologies and inequality across 19 European countries. Using data from the European Union Structure of Earnings Survey (EU-SES), a fixed-effects model is employed to assess the association between occupational exposure to artificial intelligence (AI) and to industrial robots–two distinct forms of automation–and within-occupation wage inequality. The analysis reveals that occupations with higher exposure to robots tend to have lower wage inequality, particularly among workers in the lower half of the wage distribution. In contrast, occupations more exposed to AI exhibit greater wage dispersion, especially at the top of the wage distribution. We argue that this disparity arises from differences in how each technology complements individual worker abilities: robot-related tasks often complement routine physical activities, while AI-related tasks tend to amplify the productivity of high-skilled, cognitively intensive work." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Demographic change, secular stagnation, and inequality: automation as a blessing? (2025)
Zitatform
Jacobs, Arthur & Freddy Heylen (2025): Demographic change, secular stagnation, and inequality: automation as a blessing? In: Journal of demographic economics, Jg. 91, H. 4, S. 508-548. DOI:10.1017/dem.2024.10
Abstract
"We study whether the increased adoption of available automation technologies allows economies to avoid the negative effect of aging on per capita output. We develop a quantitative theory in which firms choose to which extent they automate in response to a declining workforce and rising old-age dependency. An important element in our model is the integration of two capital types: automation capital that acts as a substitute to human labor, and traditional capital that is a complement to labor. Empirically, our model's predictions largely match data regarding automation (robotization) density across OECD countries. Simulating the model, we find that aging-induced automation only partially compensates the negative growth effect of aging in the absence of technical progress in automation technology. One reason is that automated tasks are no perfect substitutes for non-automated tasks. A second reason is that automation raises the interest rate and thus inhibits positive behavioral reactions to aging (later retirement and investment in human capital). Moreover, increased automation generates a falling net labor share of income and rising welfare inequality. We evaluate alternative policy responses to cope with this inequality." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Robots, AI, and unemployment (2025)
Zitatform
Kudoh, Noritaka & Hiroaki Miyamoto (2025): Robots, AI, and unemployment. In: Journal of Economic Dynamics and Control, Jg. 174. DOI:10.1016/j.jedc.2025.105069
Abstract
"Do robots and artificial intelligence (AI) cause joblessness? We develop a dynamic general equilibrium model with search-matching frictions. In our model, robots substitute routine human tasks, and AI substitutes abstract human tasks. We find a cutoff level for the elasticity of substitution between routine labor input and robots, above which an increase in robot productivity leads to increased unemployment. We examine a scenario in which AI-driven automation of abstract tasks transforms high-skilled workers into unskilled ones. A substantial productivity gain through AI is required to offset the output loss associated with this labor displacement." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V.) ((en))
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Literaturhinweis
Upgrading jobs for all: How welfare states shape differences in life satisfaction between the winners and losers of structural change (2025)
Zitatform
Küstermann, Leon (2025): Upgrading jobs for all: How welfare states shape differences in life satisfaction between the winners and losers of structural change. In: Socio-economic review, Jg. 23, H. 4, S. 1895-1921. DOI:10.1093/ser/mwaf029
Abstract
"Structural economic change transforms occupational structures in a way that has benefited college-educated knowledge economy workers while creating risks for workers in routine and interpersonal service jobs. However, looking beyond economic outcomes, it is striking that differences in life satisfaction between these occupational groups in some European countries are much smaller than in others. To explain this pattern, I analyze data from the European Social Survey and the European Working Conditions Survey for twenty-five countries. I show that these life satisfaction differences are smaller in countries where jobs in “losing” occupations are designed similarly to jobs in “winning” occupations. Further, I demonstrate that both social investment and social protection reduce this life satisfaction gap by equalizing job satisfaction and job design between occupational groups. Hence, my results support the argument that welfare states achieve inclusive outcomes in the context of structural economic change through their interactions with workplaces." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Digitalisation of jobs and gender-age segregation in digital tasks: Cross-country evidence based on ESJS2 data (2025)
Leitner, Sebastian; Zilian, Stella Sophie;Zitatform
Leitner, Sebastian & Stella Sophie Zilian (2025): Digitalisation of jobs and gender-age segregation in digital tasks: Cross-country evidence based on ESJS2 data. (WIIW working paper 269), Wien, 37 S.
Abstract
"This paper addresses the disproportional effects of digitalisation across age by investigating (i) within-job age segregation in tasks by digital intensity; (ii) within-job age disparities in digital upskilling; (iii) age inequalities in wage returns to digital job tasks; and (iv) the role of gender in this age segregation and inequalities. The analysis is based on data of Cedefop's second wave of the European Skills and Jobs Survey (ESJS2), conducted in 2021. First results of the analysis show that even when controlling for occupation-industry job pairs apart from using other explanatory variables, age segregation and gender gaps are prevalent in the case of digital skill intensity of tasks performed in the jobs of employees, though not in the case of digital upskilling via training measures. Applying the same appropriate controls, we also find that higher within-job digital skill intensity is associated with higher hourly wages. Gender wage gaps are sizable across all skill intensity categories in addition to widening in older age groups." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Do robots decrease humans’ wages? (2025)
Zitatform
Logchies, Thomas, Tom Coupé & W. Robert Reed (2025): Do robots decrease humans’ wages? In: Applied Economics Letters, S. 1-5. DOI:10.1080/13504851.2025.2466748
Abstract
"While there are studies that show a positive or negative impact of robots on wages, a meta-analysis of 2,586 estimates from 52 studies in this paper finds that when one looks at the literature as a whole, there is no clear evidence of a sizable impact of robots on wages." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Impact of robots and artificial intelligence on labor and skill demand: evidence from the UK (2025)
Zitatform
Lábaj, Martin, Tomáš Oleš & Gabriel Procházka (2025): Impact of robots and artificial intelligence on labor and skill demand: evidence from the UK. In: Eurasian business review, Jg. 15, H. 4, S. 953-1001. DOI:10.1007/s40821-025-00314-w
Abstract
"Over the past four decades, automation technologies have replaced routine tasks performed by medium-skilled workers, and contributed to increased labor market polarization. With the advent of artificial intelligence, this dynamic may have shifted, extending task substitution to non-routine tasks performed by high-skilled workers. Using textual analysis and descriptions of technology found in patent texts, we construct novel occupational exposures to robot and artificial intelligence technologies. These occupational exposures are then used to analyze changes in labor and skill demand over the last decade in the United Kingdom. We find that the middle part of the income distribution is primarily exposed to robot technology, while exposure to artificial intelligence increases monotonically across income percentiles. Second, we find that exposure to robots is strongest among high school dropouts and declines monotonically with education, while artificial intelligence automation has a limited impact on the same workers, with a pronounced exposure among college graduates. Third, our findings suggest asymmetric effects of automation technologies across skill groups. Robot automation reduces demand for low-skilled workers, while AI technology shifts demand away from high-skilled workers, with the direct effects consistently negative despite the presence of several compensating mechanisms. Fourth, despite significant effects on wage bill, we find no robust relationship between automation exposure and changes in the employment-to-population ratio. Finally, a joint estimation of the effects of robot and AI automation shows that robot automation is positively associated with an increase in demand for skilled workers, while AI automation is weakly associated with a decrease in demand for skilled workers." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
AI innovation and the labor share in European regions (2025)
Zitatform
Minniti, Antonio, Klaus Prettner & Francesco Venturini (2025): AI innovation and the labor share in European regions. In: European Economic Review, Jg. 177. DOI:10.1016/j.euroecorev.2025.105043
Abstract
"This paper examines how the development of Artificial Intelligence (AI) affects the distribution of income between capital and labor, and how these shifts contribute to regional income inequality. To investigate this issue, we analyze data from European regions dating back to 2000. We find that for every doubling of regional AI innovation, the labor share declines by 0.5% to 1.6%, potentially reducing it by 0.09 to 0.31 percentage points from an average of 52%, solely due to AI. This new technology has a particularly negative impact on high- and medium-skill workers, primarily through wage compression, while for low-skill workers, employment expansion induced by AI mildly offsets the associated wage decline. The effect of AI is not driven by other factors influencing regional development in Europe or by the concentration of the AI market." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Just another cog in the machine? A worker‐level view of robotization and tasks (2025)
Zitatform
Nikolova, Milena, Anthony Lepinteur & Femke Cnossen (2025): Just another cog in the machine? A worker‐level view of robotization and tasks. In: Economica, Jg. 92, H. 368, S. 1101-1148. DOI:10.1111/ecca.70006
Abstract
"Technological change has led to a decline in the share of routine and physical jobs, and a rise in the share of abstract and social ones at the economy level. However, much less is known about how these trends unfold at the individual level. Do workers' tasks become more or less routine and physical? Do workers shift towards more social and abstract activities? This paper is the first to explore these questions in the context of robotization. We use survey data from 20 European countries to develop worker-level indices of physical, routine, abstract and social tasks, which we link to industry-level robotization exposure. Using instrumental variable techniques, we find that robotization reduces physically demanding tasks but increases routine tasks, while also limiting opportunities for cognitively challenging work and human interaction. This study provides a worker-centric perspective on the relationship between technology and task composition, revealing insights that aggregate analyses miss." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Artificial intelligence, automation and employment dynamics: empirical evidence from G7 economies (2025)
Zitatform
Okur, Fatih & Enes Özdemir (2025): Artificial intelligence, automation and employment dynamics: empirical evidence from G7 economies. In: Journal of Economic Studies, S. 1-17. DOI:10.1108/jes-06-2025-0414
Abstract
"Purpose: This study examines how the rapid adoption of artificial intelligence (AI) and automation affects employment dynamics across G7 economies. While previous research has often focused on either AI or robotics in isolation, their combined and long-term effects on employment remain poorly understood. Addressing this gap is crucial for policymakers seeking to balance technological progress with labor market stability. Design/methodology/approach: Using a balanced panel dataset covering 2010–2024 for the G7 countries, thestudy investigates the relationships between AI investment (proxied by information and communication technology (ICT) investment), robot density (ROBOT), wages, productivity (PRD) and education spending (EDU), and their impact on employment. The analysis employs panel unit root and cross-sectional dependence tests, a panel autoregressive distributed lag (ARDL) framework estimated via the pooled mean group (PMG) estimator, and robustness checks using Driscoll–Kraay fixed effects, common correlatedeffects (CCE) estimators, country-specific regressions and Dumitrescu –Hurlin panel causality tests. Findings: The results reveal that AI investment has a significant negative effect on employment in the long run, whereas ROBOT shows a positive but context-dependent relationship. Wage levels are negatively associated with employment, while PRD shows only a modest positive influence. Education expenditure exhibits mixed behavior – positive in the short run but negative in the long run – suggesting potential misalignment with evolving labor market needs. Causality tests confirm a unidirectional link from AI investment to employment, underscoring its structural role in labor market change. Research limitations/implications: This study is limited by data availability, particularly the lack of detailed sectoral or occupational breakdowns across countries. As a result, it cannot fully capture the distributional effects of AI and automation across different worker groups. The use of proxies, such as ICT investment for AI, may not reflect the full scope of AI deployment. Despite these limitations, the findings highlight important macro-level dynamics and suggest that technological investments significantly shape employment trends. Future research should utilize micro-level data to explore sector-specific impacts, wage effects and labor force transitions in response to digital transformation. Practical implications: The findings suggest that without targeted policy interventions, increased AI investment may displace workers in the long run. Policymakers should prioritize reskilling, adapt education systems to evolving technological needs, and differentiate strategies across sectors and worker skill levels. Social implications: This study highlights the potential for AI and automation to reshape labor markets, with implications for income distribution, job security and social cohesion. The displacement of routine jobs may disproportionately affect low-skilled and vulnerable workers, increasing the risk of inequality and social exclusion. To prevent deepening divides, social policies must focus on equitable access to education, digital literacy and lifelong learning. Supporting workforce adaptability through inclusive training programs and social safety nets is essential. The results underscore the urgent need for collaborative efforts between governments, educational institutions and industries to ensure a socially sustainable digital transformation. Originality/value: This study is among the first to jointly analyze AI and robotics within a dynamic panel framework, offering new cross-country evidence on their heterogeneous employment effects in advanced economies. By integrating multiple estimation strategies and country-specific perspectives, the paper contributes to a more nuanced understanding of how technological transformation reshapes labor markets and highlights the institutional conditions that mediate these effects." (Author's abstract, IAB-Doku, © EmeraldGroup) ((en))
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Literaturhinweis
Benign effects of technological change on the labour share: evidence from European regions (2025)
Zitatform
Pialli, Guido (2025): Benign effects of technological change on the labour share: evidence from European regions. In: Cambridge Journal of Economics, Jg. 49, H. 4, S. 795-824. DOI:10.1093/cje/beaf021
Abstract
"The labor share across European regions has shown significant variation since the late 1990s. This paper explores the role of technological change in explaining this regional variation. Specifically, this paper proposes and tests the hypothesis that the recent shift in technological change is labor-intensive, driven by a localized, bottom-up process that exploits the skills and learning processes of the workforce. The empirical analysis, using data from 171 European regions over the period 1999–2015, supports the theoretical framework, showing that technological change has a positive and economically significant impact on the labor share." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Occupational Autonomy and Wage Divergence: Evidence From European Survey Data (2025)
Zitatform
Rabensteiner, Thomas & Alexander Guschanski (2025): Occupational Autonomy and Wage Divergence: Evidence From European Survey Data. In: BJIR, Jg. 63, H. 4, S. 696-713. DOI:10.1111/bjir.70003
Abstract
"Wages across occupations in Western Europe have diverged, resulting in increased wage inequality. However, existing theories such as routine-biased technological change (RBTC) or task offshoring fail to explain this trend. We propose a new explanation based on occupational autonomy. Autonomy measures workers' control and influence over their work process based on the tasks required in an occupation. Analysing individual-level data from the EU Survey of Income and Living Conditions, we reveal a rising autonomy wage premium, that is, higher wage growth for occupations with higher autonomy, which accurately predicts the observed occupational wage divergence. We also find that the autonomy premium increases more rapidly in countries and industries with greater employee monitoring and outsourcing, as well as in countries with declining minimum wages. These findings imply that low-autonomy occupations have been disadvantaged by recent socioeconomic trends that have altered power relations in the workplace. Notably, our analysis does not support previous explanations for occupational wage trends based on RBTC or task offshoring." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
European regional employment and exposure to labour-saving technical change: results from a direct text similarity measure (2025)
Zitatform
Riccio, Federico, Jacopo Staccioli & Maria Enrica Virgillito (2025): European regional employment and exposure to labour-saving technical change: results from a direct text similarity measure. (LEM working paper series / Laboratory of Economics and Management 2025/19), Pisa, 34 S. DOI:10.57838/sssa/02jp-b197
Abstract
"Does labor-saving technological change pose a threat to European employment, and if so, to what extent? This study investigates the degree of employment exposure to labor-saving technological change across NUTS-2 regions in Europe. We construct a cross-walked metric between the SOC and ISCO classification systems to adapt the direct measure of occupational exposure developed by Montobbio et al. (2024) for the US economy and apply it to the European context. This methodology enables us to generate detailed insights into the exposure of European occupations by leveraging the similarity rankings between technological classifications in the USPTO (CPCs) and task descriptions. To evaluate the transmission from occupational exposure to employment outcomes, we utilise data from the European Structure of Earnings Survey (EU-SES), thereby constructing exposure indices at both sectoral and regional levels. Finally, we examine the industrial and geographical diffusion of labor-saving technological change in recent years and provide robust econometric evidence indicating that low-wage regions, as well as deindustrialising areas heavily integrated into global value chains, are disproportionately vulnerable to the threat of substitution." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Sociotechnical imaginaries of social inequality in the design and use of AI recruitment technology (2025)
Zitatform
Sartori, Laura & Clementine Collett (2025): Sociotechnical imaginaries of social inequality in the design and use of AI recruitment technology. In: European Societies, Jg. 27, H. 3, S. 409-432. DOI:10.1162/euso_a_00035
Abstract
"Through interviewing 12 companies in Italy which either design (vendors) or use (clients) AI recruitment technology systems, we explore how these companies perceive their systems to interact with issues of social inequality and how these perceptions, in practice, carry societal impacts. Three sociotechnical imaginaries (Jasanoff and Kim, 2015) were consistently embedded within these companies’ visions of this intersection: the third eye, the river, and the car bonnet. Through critically analyzing these imaginaries, we find that they exhibit an overriding desire for productivity and talent capture from clients, and a consequential de-prioritization of addressing social inequality and scrutinizing the ways it could be reproduced from both vendors and clients. It demonstrates that the current ‘desired’ futures, shown by the sociotechnical imaginaries which vendors and clients share for AI-tec-tech are really leading us towards an ‘undesirable’ future of hiring which continues to perpetuate social inequality. This study contributes one of the first pieces of empirical work to simultaneously assess the perceptions of AI-rec-tech vendors ’ and clients’ surrounding social inequality, to shed light on the priorities for design and the motivations for usage, and to reflect upon how this impacts society. This is a significant and original contribution to the evolving body of literature on AI-rec-tech in sociology, critical data studies, and communications." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Artificial Intelligence and Technological Unemployment (2025)
Zitatform
Wang, Ping & Tsz-Nga Wong (2025): Artificial Intelligence and Technological Unemployment. (NBER working paper / National Bureau of Economic Research 33867), Cambridge, Mass, 53 S.
Abstract
"How large is the impact of artificial intelligence (AI) on labor productivity and unemployment? This paper introduces a labor-search model of technological unemployment, conceptualizing the generative aspect of AI as a learning-by-using technology. AI capability improves through machine learning from workers and in turn enhances their labor productivity, but eventually displaces workers if wage renegotiation fails. Three distinct equilibria emerge: no AI, some AI with higher unemployment, or unbounded AI with sustained endogenous growth and little impact on employment. By calibrating to the U.S. data, our model predicts more than threefold improvements in productivity in some-AI steady state, alongside a long-run employment loss of 23%, with half this loss occurring over the initial five-year transition. Plausible change in parameter values could lead to global and local indeterminacy. The mechanism highlights the considerable uncertainty of AI's impacts in the presence of labor-market frictions. In the unbounded-AI equilibrium, technological unemployment would not occur. We further show that equilibria are inefficient despite adherence to the Hosios condition. By improving job-finding rate and labor productivity, the optimal subsidy to jobs facing the replacement risk of AI can generate a welfare gain from 26.6% in the short run to over 50% in the long run." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Education pathways to mitigate automation anxiety: skill development as key for job satisfaction in the age of machines replacing human (2025)
Zitatform
Yuan, Bocong, Jiannan Li & Hairong Zhao (2025): Education pathways to mitigate automation anxiety: skill development as key for job satisfaction in the age of machines replacing human. In: International Journal of Manpower, Jg. 46, H. 9, S. 1676-1698. DOI:10.1108/ijm-02-2024-0093
Abstract
"Purpose: The application of intelligent machine in the workplace has led to increasing concern about technically induced unemployment. This study is to investigate the mechanism of how such risk affects the job satisfaction. Design/methodology/approach: We use the secondary data from SHARE (wave 8) and a longitudinal survey to examine the influence mechanism of how intelligent machine job substitution risk affects job satisfaction. Findings: Results show that intelligent machine job substitution risk has a negative impact on job satisfaction. Besides, skill development opportunity mediates the negative relation between intelligent machine job substitution risk and job satisfaction. Further, work support buffers the negative relation between intelligent machine job substitution risk and skill development opportunity, while enhancing the positive relation between skill development opportunity and job satisfaction. Originality/value: This study is the first to examine the mediation role of skill development opportunity in the relation between the intelligent machine job substitution risk and job satisfaction. Also, this study is the first to explore the role of work support in the above relation. This study enriches relevant research regarding the intelligent machine application in workplace and provides important insights for organization management." (Author's abstract, IAB-Doku, © Emerald Group) ((en))
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Literaturhinweis
The AI Redemption: How technology is rewriting the rules of cross-industry labor mobility (2025)
Zhang, Su; Wang, Xiaolin; Wang, Huijuan; Xia, Yan;Zitatform
Zhang, Su, Xiaolin Wang, Yan Xia & Huijuan Wang (2025): The AI Redemption: How technology is rewriting the rules of cross-industry labor mobility. In: International Review of Economics and Finance, Jg. 103. DOI:10.1016/j.iref.2025.104575
Abstract
"This study considers the evolution and iteration of digital technology, conducting both theoretical and empirical research on the effects of information technology and artificial intelligence technology on cross-industry labor mobility. Theoretically, we construct a general equilibrium model that includes labor and digital technology to analyze the intrinsic mechanisms by which digital technology affects cross-industry labor mobility. Empirically, using the probit model and the instrumental variable approach, we find robust evidence of a significant positive effect of digital technology on cross-industry labor mobility through the pooled four-wave data from the China Family Panel Studies (CFPS) from 2014 to 2020. The findings indicate that digital technology significantly promotes cross-industry labor mobility. Mechanism analysis reveals that information technology, represented by computers, drives low-skilled labor towards non-skill-intensive industries through substitution and productivity effects, while artificial intelligence technology promotes the flow of both low-skilled and high-skilled labor towards skill-intensive industries through “de-skilling” and “re-skilling”. The impact of digital technology on cross-industry labor mobility varies significantly across different genders, the type of hukou, age, and employment types. Further mechanism analysis suggests that digital technology facilitates higher wage gains by promoting cross-industry labor mobility." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier Inc.) ((en))
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Literaturhinweis
Effects of digital innovation on income inequality among different workforces: evidence from Chinese industries (2025)
Zhou, Yongguang; Xie, Weihong; Li, Qun; Li, Jingwu;Zitatform
Zhou, Yongguang, Weihong Xie, Jingwu Li & Qun Li (2025): Effects of digital innovation on income inequality among different workforces: evidence from Chinese industries. In: Applied Economics, Jg. 57, H. 22, S. 2809-2821. DOI:10.1080/00036846.2024.2331424
Abstract
"To understand the impact of digital innovation on the workforce and its role in achieving common prosperity, this paper uses data from Chinese A-share listed companies during 2006–2021 to investigate the effects of digital innovation on income inequality among different industry-level groups. We find that digital innovation significantly reduces income inequality among employees across industries, but it does not significantly impact income inequality within management groups. Through mechanistic analysis, we find that digital innovation decreases income inequality among ordinary employees whose incomes are closely linked to company performance and thereby for the entire workforce by narrowing the income gap across industries. However, as digital innovation does not significantly influence evaluation systems (e.g. educational degrees) for management income, it does not contribute to reducing income inequality among managerial levels. These findings provide valuable insights to develop policies for common prosperity." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Digital labour and welfare regimes: The impact of the institutional context on the prevalence of platform work (2025)
Zitatform
Zwysen, Wouter & Bianca Luna Fabris (2025): Digital labour and welfare regimes: The impact of the institutional context on the prevalence of platform work. In: Competition and Change, S. 1-21. DOI:10.1177/10245294251349484
Abstract
"Platform work is on the rise across Europe, but not similarly across countries as shown from the as yet limited cross-national research. This study sets out to analyze how structural differences in the organization of the economy and welfare state shape individual’s engagement with platform work and particularly (1) the take-up of platform work; and (2) the extent to which the more economically vulnerable are overrepresented. In a context where the labour market is more regulated, workers are more protected, and there is a more generous safety net, there is less need to engage in generally precarious platform work. This study makes use of two comparable cross-national datasets on engagement in platform work across Europe. We find indications that platform work is generally less likely in countries where there is greater social spending and redistribution, higher passive labour market policy spending, and lower labour market dualization. Such factors, namely, social security and the regulation of the labour market, particularly protect more vulnerable workers." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
New technology and workers’ perceived impact on job quality: Does labor organization matter? (2025)
Zitatform
ten Berge, Jannes & Fabian Dekker (2025): New technology and workers’ perceived impact on job quality: Does labor organization matter? In: Economic and Industrial Democracy, Jg. 46, H. 2, S. 619-654. DOI:10.1177/0143831x241265911
Abstract
"There is an emerging literature focusing on the impact of technological change on work quality. This study contributes to the literature by examining (1) workers’ expectations regarding the effect of technological change on perceived job insecurity, as well as physical and psychological job demands, and (2) how these expectations are shaped by the degree of labor organization within countries. The article uses cross-national data for 25 OECD countries. It is found that labor organization decreases perceived levels of job insecurity related to technological change, but also lowers workers’ expectations of technology improving the quality of their work. These findings may indicate that in environments where technological change is less strongly moderated by organized labor, workers put greater emphasis on technology as a driver of (short-term) work changes. Alternatively, these findings may signal a lack of ‘worker power’ of organized labor to enforce technologies that improve the quality of employment." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
OECD Skills Outlook 2025: Building the Skills of the 21st Century for All (2025)
Zitatform
(2025): OECD Skills Outlook 2025. Building the Skills of the 21st Century for All. (OECD skills outlook), Paris, 261 S. DOI:10.1787/26163cd3-en
Abstract
"The OECD Skills Outlook 2025 examines how countries can build the 21st-century skills needed to sustain growth and social progress. It explores how differences in background, education and opportunity shape who develops, uses and benefits from key skills such as literacy, numeracy and adaptive problem solving. Differential access to skills development limits the potential of many, thereby constraining economic performance. Socio-economic background strongly influences who builds skills that are valued in the labour market, whereas differences between men and women appear mainly in how skills are used and rewarded. As skill demands evolve faster than policy cycles, investing in lifelong learning and using timely labour-market intelligence are crucial to help people adapt, strengthen productivity and ensure that no one is left behind in a changing world." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Learning from Ricardo and Thompson: Machinery and Labor in the Early Industrial Revolution, and in the Age of AI (2024)
Zitatform
Acemoglu, Daron & Simon Johnson (2024): Learning from Ricardo and Thompson: Machinery and Labor in the Early Industrial Revolution, and in the Age of AI. (NBER working paper / National Bureau of Economic Research 32416), Cambridge, Mass, 45 S. DOI:10.3386/w32416
Abstract
"David Ricardo initially believed machinery would help workers but revised his opinion, likely based on the impact of automation in the textile industry. Despite cotton textiles becoming one of the largest sectors in the British economy, real wages for cotton weavers did not rise for decades. As E.P. Thompson emphasized, automation forced workers into unhealthy factories with close surveillance and little autonomy. Automation can increase wages, but only when accompanied by new tasks that raise the marginal productivity of labor and/or when there is sufficient additional hiring in complementary sectors. Wages are unlikely to rise when workers cannot push for their share of productivity growth. Today, artificial intelligence may boost average productivity, but it also may replace many workers while degrading job quality for those who remain employed. As in Ricardo's time, the impact of automation on workers today is more complex than an automatic linkage from higher productivity to better wages." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation and Rent Dissipation: Implications for Wages, Inequality, and Productivity (2024)
Zitatform
Acemoglu, Daron & Pascual Restrepo (2024): Automation and Rent Dissipation: Implications for Wages, Inequality, and Productivity. (NBER working paper / National Bureau of Economic Research 32536), Cambridge, Mass, 79 S. DOI:10.3386/w32536
Abstract
"This paper studies the effects of automation in economies with labor market distortions that generate worker rents—wages above opportunity cost—in some jobs. We show that automation targets high-rent tasks, dissipating rents and amplifying wage losses from automation. It also reduces within-group wage dispersion for exposed groups. Automation-driven rent dissipation is inefficient and reduces (and could even negate) the productivity gains from automation. Using data for the US from 1980 to 2016, we find evidence of sizable rent dissipation and reduced within-group wage dispersion due to automation. Using these estimates and accounting for equilibrium effects, we estimate that automation accounts for 52% of the increase in between-group inequality in the US since 1980, with rent dissipation being responsible for a fifth of this contribution. We also estimate that inefficient rent dissipation offset 60–90% of the productivity gains from automation since 1980." (Author'sabstract, IAB-Doku) ((en))
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Literaturhinweis
A Relational Work Perspective on the Gig Economy: Doing Creative Work on Digital Labour Platforms (2024)
Zitatform
Alacovska, Ana, Eliane Bucher & Christian Fieseler (2024): A Relational Work Perspective on the Gig Economy: Doing Creative Work on Digital Labour Platforms. In: Work, Employment and Society, Jg. 38, H. 1, S. 161-179. DOI:10.1177/09500170221103146
Abstract
"Based on interviews with 49 visual artists, graphic designers and illustrators working on two leading global digital labour platforms, this article examines how creative workers perform relational work as a means of attenuating labour commodification, precarity, and algorithmic normativity. The article argues that creative work on online labour platforms, rather than being entirely controlled by depersonalised, anonymised and algorithm-driven labour market forces, is also infused in relational infrastructures whose upkeep, solidity and durability depends on the emotional efforts undertaken by workers to match economic transactions and their media of exchange to meaningful client relations. By applying a relational work perspective from economic sociology to the study of platform-mediated gig work, the article elucidates the micro-foundations of creative work in the digital gig economy, including how labour inequalities are produced and reproduced within and around micro-level interpersonal interactions." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The impact of ICT and robots on labour market outcomes of demographic groups in Europe (2024)
Zitatform
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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Literaturhinweis
Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech (2024)
Zitatform
Avery, Mallory, Andreas Leibbrandt & Joseph Vecci (2024): Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech. (CESifo working paper 10996), München, 70 S.
Abstract
"The use of Artificial Intelligence (AI) in recruitment is rapidly increasing and drastically changing how people apply to jobs and how applications are reviewed. In this paper, we use two field experiments to study how AI recruitment tools can impact gender diversity in the male-dominated technology sector, both overall and separately for labor supply and demand. We find that the use of AI in recruitment changes the gender distribution of potential hires, in some cases more than doubling the fraction of top applicants that are women. This change is generated by better outcomes for women in both supply and demand. On the supply side, we observe that the use of AI reduces the gender gap in application completion rates. Complementary survey evidence suggests that anticipated bias is a driver of increased female application completion when assessed by AI instead of human evaluators. On the demand side, we find that providing evaluators with applicants' AI scores closes the gender gap in assessments that otherwise disadvantage female applicants. Finally, we show that the AI tool would have to be substantially biased against women to result in a lower level of gender diversity than found without AI." (Author's abstract, IAB-Doku) ((en))
Ähnliche Treffer
auch erschienen als: Monash Economics Working Papers, 2023-09 -
Literaturhinweis
Labour Market Engineers: Reconceptualising Labour Market Intermediaries with the Rise of the Gig Economy in the United States (2024)
Zitatform
Baber, Ashley (2024): Labour Market Engineers: Reconceptualising Labour Market Intermediaries with the Rise of the Gig Economy in the United States. In: Work, Employment and Society, Jg. 38, H. 3, S. 723-743. DOI:10.1177/09500170221150087
Abstract
"Gig work – accessing job opportunities through an app – has brought renewed attention to precarious non-standard labour arrangements. Scholars have begun to consider the intermediary role that platforms such as Uber, Lyft and Doordash play in exploiting and controlling workers. Yet, literature on labour market intermediaries has muddied conceptions of their role, impact and outcomes for workers by lumping a variety of institutions under the same umbrella term. Drawing from previous theoretical and empirical works throughout the temporary help and gig industries, this article proposes a reconceptualisation of labour market intermediaries as labour market engineers highlighting four mutually reinforcing features. This sociological reconceptualisation updates the understanding of for-profit labour market intermediaries by demonstrating the market making behaviours of firms of on-demand labour in the US context. Likewise, this reconceptualisation notes how gig firms have adapted and expanded these features in ways that increase precarity for workers." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
New Technologies, Migration and Labour Market Adjustment: An Intra-European Perspective (2024)
Zitatform
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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Literaturhinweis
Which Migrant Jobs are Linked with the Adoption of Novel Technologies, Robotization, and Digitalization? (2024)
Zitatform
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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Literaturhinweis
Robots and firms' labour search: The role of temporary work agencies (2024)
Beneito, Pilar; Wilemme, Guillaume; Vicente-Chirivella, Oscar; Garcia-Vega, Maria;Zitatform
Beneito, Pilar, Maria Garcia-Vega, Oscar Vicente-Chirivella & Guillaume Wilemme (2024): Robots and firms' labour search: The role of temporary work agencies. (Research paper / Nottingham Centre for Research on Globalisation and Economic Policy 2024,02), Nottingham, 55 S.
Abstract
"We study the impact of industrial robots on the use of labor intermediaries or temporary work agencies (TWAs) and firm productivity. We develop a theoretical framework where new technologies increase the need for quality match workers. TWAs help firms to search for workers who better match their technologies. The model predicts that using robots increases TWA use, which increases robots' productivity. We test the model implications with panel data of Spanish firms from 1997 to 2016 with information on robot adoption and TWA use. Using staggered difference-in-difference (DiD) estimations, we estimate the causal effects of robot adoption on TWAs. We find robot adopters increase the probability of TWA use compared to non-adopters. We also find that firms that combine robots with TWAs achieve higher productivity than those who adopt robots without TWAs." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The impact of AI on the workforce: Tasks versus jobs? (2024)
Bonney, Kathryn; Foster, Lucia; Haltiwanger, John ; Buffington, Catherine ; Kroff, Zachary; Goldschlag, Nathan ; Breaux, Cory; Dinlersoz, Emin; Savage, Keith;Zitatform
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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Literaturhinweis
Spatial and Occupational Mobility of Workers Due to Automation (2024)
Zitatform
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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Literaturhinweis
Unveiling the automation—wage inequality nexus within and across regions (2024)
Zitatform
Capello, Roberta, Simona Ciappei & Camilla Lenzi (2024): Unveiling the automation—wage inequality nexus within and across regions. In: The Annals of Regional Science, Jg. 73, H. 4, S. 1729-1756. DOI:10.1007/s00168-024-01317-7
Abstract
"Since the1800s, automation technologies have been interpreted as a source of displacement effects, largely conceptualised and empirically proved in a vast literature. This paper claims that, despite their non-manufacturing nature, metropolitan regions are not exempted by the negative effects of automation on wage inequalities across workers’ groups. The paper empirically proves this statement by analysing the effects on jobs and wage differentials among groups of workers associated with the diffusion of robot technologies in Italian NUTS3 regions in the period 2012–2019. Results show that automation technologies in the form of robotisation do displace jobs, harming particularly low-skilled workers in non-metropolitan manufacturing regions, where inter-group wage inequalities increase. However, through the creation of high-skilled jobs, also cities experience a rise of inter-group workers inequalities. These results call for appropriate policies to cope with the changing occupational profiles requested by the labour market." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Digital Technologies and Firms' Employment and Training (2024)
Zitatform
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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Literaturhinweis
Unemployment and the direction of technical change (2024)
Zitatform
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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Literaturhinweis
Intellectualization and substitution elasticity of capital on the labour force in logistics enterprises: evidence from China and the United States (2024)
Zitatform
Chen, Xi, Xiang Wen Cai, Xu Ding, Le Song & Cheng Chen (2024): Intellectualization and substitution elasticity of capital on the labour force in logistics enterprises: evidence from China and the United States. In: Applied Economics Letters, Jg. 31, H. 5, S. 395-400. DOI:10.1080/13504851.2022.2136615
Abstract
"This paper addresses the substitution elasticity of capital on the labor force in the context of the development of intellectualization. Given the substitution of capital for labor, China's benchmark listed logistics companies are compared with an American company to discuss the evolution of capital - labor substitution. A large-scale intellectualization process began in 2017, and based on a variable elasticity of substitution, this paper creates an econometric model of substitution elasticity between capital and labor and its evolution between 2017 and 2021. The American logistics company UPS maintains a relatively high level of substitution elasticity, and Chinese logistics companies are quickly catching up. The substitution elasticity of capital on labor in Chinese enterprises trends upward year after year. In 2021, the capital - labor substitution elasticity of logistics enterprises in both countries showed considerable growth. The calculation model of substitution elasticity presented in this paper can be extended to different regions and industries to measure intelligent development levels and the relationship between capital and the labor force." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Digital technologies, labor market flows and training: Evidence from Italian employer-employee data (2024)
Zitatform
Cirillo, Valeria, Andrea Mina & Andrea Ricci (2024): Digital technologies, labor market flows and training: Evidence from Italian employer-employee data. In: Technological forecasting & social change, Jg. 209. DOI:10.1016/j.techfore.2024.123735
Abstract
"New technologies can shape the production process by affecting the way in which inputs are embedded in the organization, their quality, and their use. Using an original employer-employee dataset that merges firm-level data on digital technology adoption and other characteristics of production with employee-level data on worker entry and exit rates from the administrative archive of the Italian Ministry of Labor, this paper explores the effects of new digital technologies on labor flows in the Italian economy. Using a Difference-in-Difference approach, we show that digital technologies lead to an increase in the firm-level hiring rate – particularly for young workers - and reduce the firm-level separation rate. We also find that digital technologies are positively associated with workplace training, proxied by the share of trained employees and the amount of training costs per employee. Furthermore, we explore the heterogeneity of effects related to different technologies (robots, cybersecurity and IoT). Our results are confirmed through several robustness checks." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
Wishing for More: Technological Change, the Rise of Involuntary Part-Time Employment and the Role of Active Labour Market Policies (2024)
Zitatform
Doorn, Lars Van & Olaf van Vliet (2024): Wishing for More: Technological Change, the Rise of Involuntary Part-Time Employment and the Role of Active Labour Market Policies. In: Journal of Social Policy, Jg. 53, H. 3, S. 751-771. DOI:10.1017/S0047279422000629
Abstract
"Technological change has squeezed the demand for middle-skill jobs, which typically involve routine-intense tasks. This squeeze has coincided with an increase in the number of part-time working individuals who wish to work more hours. We argue that these two trends are linked. Due to the decline of middle-skill employment, medium-educated workers shift into low-skill employment, increasing the supply of labor for jobs in this segment of the labor market. This pushes those dependent on these jobs to accept part-time jobs, even if these involve fewer hours than they prefer. To empirically assess this claim, we analyze involuntary part-time employment across 16 European countries between 1999 and 2010. Our analysis confirms that a decline in middle-skill employment is associated with an increase in involuntary part-time employment at the bottom end of the labor market. This finding implies that the automation of routine-intense labour worsens employment possibilities in this segment of the labor market. However, we show that training and job creation schemes mitigate this effect. These programs cushion competition either by providing medium-educated workers with the necessary skills to shift into high-skill jobs or by increasing employment possibilities. Thus, governments have the tools to support workers facing challenges in the knowledge economy." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Migrant Women in the UK’s Digital Economy: The Elimination of Labour Market Barriers in the Digital Labour Market (2024)
Erinc Oztas, Miray;Zitatform
Erinc Oztas, Miray (2024): Migrant Women in the UK’s Digital Economy: The Elimination of Labour Market Barriers in the Digital Labour Market. In: Social Sciences, Jg. 13, H. 9. DOI:10.3390/socsci13090494
Abstract
"This research paper delves into the complexities migrant women face within the UK labor market, with a specific focus on the digital economy’s role as both a barrier and a conduit for employment opportunities. Migrant women in the UK encounter dual barriers to labour market entry: systemic challenges rooted in migration and gender biases, and the digital divide that exacerbates access and inclusion issues within the burgeoning digital economy. Through an exploratory descriptive analysis, this study explores how digitalism—defined as the integration of digital technologies into economic and societal practices—circumvents traditional labor market entry barriers such as languages barriers. By setting out the grounds for a potential hypothesis and further research in the era of AI, this paper underlines how through the implementation of AI tools, traditional barriers such as language barriers are eliminated in the digital labour market." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The effects of automation in the apparel and automotive sectors and their gender dimensions (2024)
Fana, Marta ; Tejani, Sheeba; Kucera, David; Esquivel, Valeria ; Bárcia De Mattos, Fernanda; Anzolin, Guendalina;Zitatform
Fana, Marta, Fernanda Bárcia De Mattos, Valeria Esquivel, Guendalina Anzolin, David Kucera & Sheeba Tejani (2024): The effects of automation in the apparel and automotive sectors and their gender dimensions. (JRC science for policy report 136639), Brüssel, 66 S.
Abstract
"This report is the final output of a research project investigating the effects of automation on employment in the automotive, apparel and footwear industries in five countries, namely Germany, Indonesia, Mexico, Romania, and Spain. The main objective of this project has been to improve our understanding of how ongoing processes of technological upgrading, particularly automation, impact women's and men's employment and work in these industries. Our findings suggest that, in the short term, close to the introduction of new automation technology, the impact on employment takes the form of reassignment of workers directly involved in automated processes to other positions, tasks, and occupations. This study also explored the impact of automation in terms of work organization and working conditions. Across the case studies, it emerged that the adoption of automation technologies has reduced heavy and repetitive tasks and improved health and safety for workers directly concerned by automation. Another interesting and related common finding is the reduction of workers' autonomy who are now subject to more standardization of tasks together with an ongoing process of deskilling of operators. Finally, in the apparel and footwear sector, we did not find evidence of defeminisation at the establishment level as well as the automotive factories remains highly male-dominated. Cultural norms and stereotypes which influence not only the jobs women and men apply to and get hired for, but also which training and education they engage in, contribute to this gender segregation in both sectors." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Job Satisfaction and the Digital Transformation of the Public Sector: The Mediating Role of Job Autonomy (2024)
Zitatform
Fleischer, Julia & Camilla Wanckel (2024): Job Satisfaction and the Digital Transformation of the Public Sector: The Mediating Role of Job Autonomy. In: Review of Public Personnel Administration, Jg. 44, H. 3, S. 431-452. DOI:10.1177/0734371X221148403
Abstract
"Worldwide, governments have introduced novel information and communication technologies (ICTs) for policy formulation and service delivery, radically changing the working environment of government employees. Following the debate on work stress and particularly on technostress, we argue that the use of ICTs triggers “digital overload” that decreases government employees’ job satisfaction via inhibiting their job autonomy. Contrary to prior research, we consider job autonomy as a consequence rather than a determinant of digital overload, because ICT-use accelerates work routines and interruptions and eventually diminishes employees’ freedom to decide how to work. Based on novel survey data from government employees in Germany, Italy, and Norway, our structural equation modeling (SEM) confirms a significant negative effect of digital overload on job autonomy. More importantly, job autonomy partially mediates the negative relationship between digital overload and job satisfaction, pointing to the importance of studying the micro-foundations of ICT-use in the public sector." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Assessing the impact of new technologies on wages and labour income shares (2024)
Zitatform
Ghodsi, Mahdi, Robert Stehrer & Antea Barišić (2024): Assessing the impact of new technologies on wages and labour income shares. In: Technological forecasting & social change, Jg. 209. DOI:10.1016/j.techfore.2024.123782
Abstract
"This paper advances the literature on the impacts of new technologies on labor markets, focusing on wage and labor income shares. Using a dataset from 32 countries and 38 industries, we analyze the effects of new technologies – proxied by patents, information and communication technology (ICT) capital usage, and robot intensity – on average wages and labour income shares over time. Our results indicate a positive correlation between patents and wage levels along with a minor negative impact on labor income shares, suggesting that technology rents are not fully passed on to labor. Robot intensity is positively associated with labor income shares, while ICT capital has an insignificant effect. These effects persist over time and are reinforced by global value chain (GVC) linkages. Our conclusions align with recent research indicating that new technologies have a generally limited impact on wages and labour income shares." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
Will robot replace workers? Assessing the impact of robots on employment and wages with meta-analysis (2024)
Zitatform
Guarascio, Dario, Alessandro Piccirillo & Jelena Reljic (2024): Will robot replace workers? Assessing the impact of robots on employment and wages with meta-analysis. (GLO discussion paper / Global Labor Organization 1395), Essen, 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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Literaturhinweis
Will robot replace workers? Assessing the impact of robots on employment and wages with meta-analysis (2024)
Zitatform
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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Literaturhinweis
Job computerization, occupational employment and wages: A comparative study of the United States, Germany, and Japan (2024)
Zitatform
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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Literaturhinweis
Does robotization improve the skill structure? The role of job displacement and structural transformation (2024)
Zitatform
Hu, Shengming, Kai Lin, Bei Liu & Hui Wang (2024): Does robotization improve the skill structure? The role of job displacement and structural transformation. In: Applied Economics, Jg. 56, H. 28, S. 3415-3430. DOI:10.1080/00036846.2023.2206623
Abstract
"The literature generally focuses on the impact of robots or artificial intelligence on the employment and wages, but ignores the effect of robotization on the skill structure and its underlying mechanisms and lacks empirical evidence from developing countries. We theoretically develop a task model by introducing the skill structure and empirically investigate the effect of robotization on the skill structure based on Chinese provincial panel data from 2006 to 2018. Results show that: (1) the development of robotization in China is conducive to improving the skill structure, and the baseline conclusion still holds even though adopting multiple indexes of skill structure and controlling the endogeneity bias. (2) Robotization generates not only job displacement effect by displacing unskilled workers with robots but also structural transformation effect by increasing the proportion of technology-intensive industries, which can improve the skill structure. (3) In coastal provinces with strong Internet foundation, information transmission capacity and labour protection intensity, high labour cost and ageing rate, robotization plays a stronger role in improving the skill structure. Moreover, robotization can induce the employment polarization. These conclusions can help avoid technical unemployment and promote the upgrading of the skill structure in China." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation and Offshoring on Wage Inequality in Japan (2024)
Kikuchi, Shinnosuke; Kikuchi, Shinnosuke;Zitatform
Kikuchi, Shinnosuke (2024): Automation and Offshoring on Wage Inequality in Japan. (RIETI discussion paper 24046), Tokyo, 24 S.
Abstract
"I examine the effect of task displacement from automation technology and offshoring on wage inequality using data for Japan since 1980. First, I do not find evidence that task displacement from automation increases wage inequality, which contrasts with the finding for the US. Second, I find that the rise in offshoring has distributional consequences and is progressive after the mid-1990s. The surge in offshoring is concentrated in industries where ex-ante low-wage workers work and disproportionally increases their wages. This increase in wages is due to the increases in monthly payroll, decreases in hours worked, decreases in employment rate, and decreases in the share of offshorable occupations." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Is the wage premium on using computers at work gender-specific? (2024)
Zitatform
Kristal, Tali, Efrat Herzberg-Druker & Adena White (2024): Is the wage premium on using computers at work gender-specific? In: Research in Social Stratification and Mobility, Jg. 89. DOI:10.1016/j.rssm.2024.100890
Abstract
"Past research on the relationship between computers and wages has revealed two stylized facts. First, workers who use a computer at work earn higher wages than similar workers who do not (termed as ‘the computer wage premium’). Second, women are more likely to use a computer at work than are men. Given the recognized computer wage premium and women’s advantage in computer use at work, we ask: Is the wage premium on using computers at work gender- or non-gender-specific? Given gendered processes operating at both the occupational and within-occupation levels, we expect that returns to computer usage are gender-bias. This contrasts the skill-biased technological change (SBTC) theory assumption that the theorized pathways through which computers boost earnings are non-gender-specific productivity-enhancing mechanisms. Analyzing occupational data on computer use at work from O*NET attached to the 1979–2016 Current Population Surveys (CPS) and individual-level data from the 2012 Survey of Adult Skills (PIAAC), we find that the computer wage premium is biased in favor of men at the occupation level. We conclude by suggesting that computer-based technologies relate to reproducing old forms of gender pay inequality due to gendered processes that operate mainly at the structural level (i.e., occupations) rather than at the individual level." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
Automation, Bargaining Power, and Labor Market Fluctuations (2024)
Zitatform
Leduc, Sylvain & Zheng Liu (2024): Automation, Bargaining Power, and Labor Market Fluctuations. In: American Economic Journal. Macroeconomics, Jg. 16, H. 4, S. 311-349. DOI:10.1257/mac.20220181
Abstract
"We argue that the threat of automation weakens workers’ bargaining power in wage negotiations, dampening wage adjustments and amplifying unemployment fluctuations. We make this argument based on a business cycle model with labor market search frictions, generalized to incorporate automation decisions. In the model, procyclical automation threats create endogenous real wage rigidity that amplifies labor market fluctuations. The automation mechanism is consistent with empirical evidence. It is also quantitatively important for explaining the large volatilities of unemployment and vacancies relative to that of real wages, a puzzling observation through the lens of standard business cycle models." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Reshoring, Automation, and Labor Markets Under Trade Uncertainty (2024)
Zitatform
Leduc, Sylvain & Zheng Liu (2024): Reshoring, Automation, and Labor Markets Under Trade Uncertainty. (Working papers series / Federal Reserve Bank of San Francisco 2024-16), San Francisco, Calif., 42 S. DOI:10.24148/wp2024-16
Abstract
"We study the implications of trade uncertainty for reshoring, automation, and U.S. labor markets. Rising trade uncertainty creates incentive for firms to reduce exposures to foreign suppliers by moving production and distribution processes to domestic producers. However, we argue that reshoring does not necessarily bring jobs back to the home country or boost domestic wages, especially when firms have access to labor-substituting technologies such as automation. Automation improves labor productivity and facilitates reshoring, but it can also displace jobs. Furthermore, automation poses a threat that weakens the bargaining power of low-skilled workers in wage negotiations, depressing their wages and raising the skill premium and wage inequality. The model predictions are in line with industry-level empirical evidence." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Embracing artificial intelligence in the labour market: the case of statistics (2024)
Zitatform
Liu, Jin, Kaizhe Chen & Wenjing Lyu (2024): Embracing artificial intelligence in the labour market: the case of statistics. In: Humanities and Social Sciences Communications, Jg. 11. DOI:10.1057/s41599-024-03557-6
Abstract
"In an era marked by rapid advancements in artificial intelligence (AI), the dynamics of the labor market are undergoing significant transformation. A common concern amidst these changes is the potential obsolescence of traditional disciplines due to AI-driven productivity enhancements. This study delves into the evolving role and resilience of these disciplines within the AI-influenced labor market. Focusing on statistics as a representative field, we investigate its integration with AI and its interplay with other disciplines. Analyzing 279.87 million online job postings in the United States from 2010 to 2022, we observed a remarkable 31-fold increase in the demand for AI-specialized statistical talent, diversifying into 932 distinct AI-related job roles. Additionally, our research identified four major interdisciplinary clusters, encompassing 190 disciplines with a statistical focus. The findings also highlight a growing emphasis on specific hard skills within these AI roles and the differences in demand for AI talent in statistics across economic sectors and regions. Contrary to the pessimistic view of traditional disciplines’ survival in the AI age, our study suggests a more optimistic outlook. We recommend that professionals and organizations proactively adapt to AI advancements. Governments and academic institutions should collaborate to foster interdisciplinary skill development and evaluation for AI talents, thereby enhancing the employability of individuals from traditional disciplines and contributing to broader economic growth." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The effects of automation on workers’ wages (2024)
Zitatform
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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Literaturhinweis
Coverage for platform workers and the self-employed in case of unemployment in Switzerland: Access to protection and ways of improvement (2024)
Zitatform
Magoga-Sabatier, Sabrine (2024): Coverage for platform workers and the self-employed in case of unemployment in Switzerland: Access to protection and ways of improvement. In: European Journal of Social Security, Jg. 26, H. 2, S. 198-213. DOI:10.1177/13882627241256003
Abstract
"Whether they are self-employed, atypical employees, or self-employed using an umbrella company, there is still almost no social protection against unemployment or partial loss of activity in Switzerland for platform workers. The same can be said for the self-employed in general. This contribution shows that platform workers, irrespective of their exact legal status, and the self-employed in general, risk sanctions for taking on unsuitable work, for being insufficiently available for decent work or unable to prove a loss of income. However hard they try, they cannot even contribute to a voluntary unemployment insurance scheme. We show that the Swiss social protection scheme, a product of years of federal direct democracy, is hardly able to adapt to the fast-moving platform work environment, thus increasing the risks of precariousness and the burden on the cantons' social assistance for the next generation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Robots, meaning, and self-determination (2024)
Zitatform
Nikolova, Milena, Femke Cnossen & Boris Nikolaev (2024): Robots, meaning, and self-determination. In: Research Policy, Jg. 53, H. 5. DOI:10.1016/j.respol.2024.104987
Abstract
"This paper is the first to examine the impact of robotization on work meaningfulness, autonomy, competence, and relatedness, which are essential to motivation and well-being at work. Using surveys of workers and robotization data for 14 industries in 20 European countries spanning 2005–2021, we find a consistent negative impact of robotization on perceived work meaningfulness and autonomy. Using instrumental variables, we find that doubling robotization leads to a 0.9 % decrease in work meaningfulness and a 1 % decline in autonomy. To put this in perspective, if the robotization levels of the top 5 industry were to match those of the leading industry in terms of robot adoption in 2020 (equivalent to a 7.5-fold increase), it would result in a decline of 6.8 % in work meaningfulness and 7.5 % in autonomy. The link between robotization, competence, and relatedness is also negative but less robust. We also examine how tasks, skills, and socio-demographic characteristics moderate the main relationships. We find that workers with routine tasks experience an even greater negative effect of robotization in terms of declines in their autonomy, competence, and relatedness. However, we also discover that utilizing computers as tools for independent work can help workers maintain a sense of autonomy, competence, and relatedness in industries and job roles that adopt robots. Our results highlight that by deteriorating work meaningfulness and self-determination, robotization can impact work life above and beyond its consequences for employment and wages." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
Robotization and returns to tasks (2024)
Parmentier, Lucas;Zitatform
Parmentier, Lucas (2024): Robotization and returns to tasks. In: Economics Bulletin, Jg. 44, H. 4, S. 1545-1551.
Abstract
"I provide new evidence of the impacts of robotization on the returns to tasks in US labor markets between 1990 and 2007. I find that the adoption of one robot per thousand workers increases the changes in the returns to abstract and routine tasks by 0.049 and 0.066 percentage points, respectively, relative to manual tasks. These magnitudes imply that the adoption of one robot per thousand workers has substantial effects on wages since it increases wages by 1.70% due to the positive impact of robotization on the returns to abstract tasks, and by 3.76% due to the positive effects on the returns to routine tasks. The results are robust to various specifications." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The impact of a decade of digital transformation on employment, wages, and inequality in the EU: A “conveyor belt” hypothesis (2024)
Richiardi, Matteo ; Neysan, Khabirpour; Caterina, Astarita; Ekkehard, Ernst; Leonie, Westhoff; Lorenzo, Pelizzari; Clare, Fenwick;Zitatform
Richiardi, Matteo, Westhoff Leonie, Astarita Caterina, Ernst Ekkehard, Fenwick Clare, Khabirpour Neysan & Pelizzari Lorenzo (2024): The impact of a decade of digital transformation on employment, wages, and inequality in the EU: A “conveyor belt” hypothesis. (CeMPA working paper series / Centre for Microsimulation and Policy Analysis (CeMPA) 5/24), Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research 54 S.
Abstract
"We study the effects of digital transformation in the EU on individual employment outcomes, wage growth, and income inequality, during the decade 2010-2019. Our results allow us to formulate a “conveyor belt” hypothesis, whereas digital skills are important for finding a job, but less so for retaining it. 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 earning 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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Literaturhinweis
The job demands-resources model as a theoretical lens for the bright and dark side of digitization (2024)
Zitatform
Scholze, Alexander & Achim Hecker (2024): The job demands-resources model as a theoretical lens for the bright and dark side of digitization. In: Computers in Human Behavior, Jg. 155. DOI:10.1016/j.chb.2024.108177
Abstract
"With digitization continuing to reshape work environments, organizations must confront the challenges of comprehending its “bright side” and “dark side” effects. A growing imperative exists to comprehend how digitization affects employee well-being and to create sustainable health-centric workplaces. The established Job Demands-Resources model offers a pertinent theoretical framework for gaining fresh insights into alterations in job demands and resources caused by digitization. This study extends the Job Demands-Resources model to include digital job demands and resources by utilizing a sample of 898 white-collar employees. Partial Least Squares Structural Equation Modeling was employed to investigate digitization's interrelationships and dependencies within an organizational context. The results confirm that the Job Demands-Resources model offers a holistic approach to investigating the concrete effects of the “dark side" and “bright side" of digitization in a concrete work scenario and to classify them in a theoretically structured way. This study offers starting points for the future design of workplaces and strategies for organizations to harness the positive aspects of digitization while concurrently mitigating the psychological stress on employees." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Neue Technologien und Löhne: Erste Analysen basierend auf österreichischen Mikrodaten (2024)
Zitatform
Stehrer, Robert (2024): Neue Technologien und Löhne. Erste Analysen basierend auf österreichischen Mikrodaten. (WIIW Forschungsarbeiten in deutscher Sprache 27), Wien, 40 S.
Abstract
"In diesem Bericht wird der Effekt der Verwendung neuer Technologien – von Robotern, 3D-Druck, Big Data und anderer softwarebasierter Anwendungen – auf Löhne und Lohnstrukturen untersucht. Die Untersuchung beruht auf der IKTU-Erhebung und weiteren detaillierten Daten auf Firmen- und Personenebene. Als Methode werden Mincer-Regressionen in einer Querschnittsanalyse geschätzt, in denen für Personen- und Firmenmerkmale kontrolliert wird. Für Letztere wird insbesondere eine Variable verwendet, die anzeigt, ob die Firma neue Technologien (z. B. Roboter) verwendet oder nicht. Die Resultate zeigen, dass die Auswirkungen der neuen Technologien auf Löhne durchaus differenziert betrachtet werden müssen. Die Effekte sind jedoch in allen Fällen gering bzw. insignifikant. Interessanterweise gibt es in so gut wie allen Fällen – mit Ausnahme der Verwendung von Chatservices –- einen positiven Effekt auf die Löhne der Frauen. Über die Bildungsgruppen hinweg zeigen sich leichte Polarisierungsmuster, wobei jedoch die Personen mit mittlerer Qualifikation im Durchschnitt eher positiv betroffen sind." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Neue Technologien, Firmenperformance und Beschäftigung: Erste Analysen basierend auf österreichischen Firmendaten (2024)
Zitatform
Stehrer, Robert (2024): Neue Technologien, Firmenperformance und Beschäftigung. Erste Analysen basierend auf österreichischen Firmendaten. (WIIW Forschungsarbeiten in deutscher Sprache 26), Wien, 34 S.
Abstract
"Dieser Bericht untersucht basierend auf Firmendaten für Österreich – der IKTU-Erhebung und den LSE-Daten – den Zusammenhang von neuen Technologien mit der Firmenperformance und Beschäftigungsstrukturen. Neue Technologien – untersucht werden der Einsatz von Robotern, 3D-Druck, Big-Data-Analysen, Verwendung von Cloud- und Chat-Services, CRM-Software oder automatisierter Datenaustausch, Verwendung sozialer Medien sowie auch die Beschäftigung von IKT-Spezialisten und -Spezialistinnen bzw. die Durchführung von IKT-Schulungen – korrelieren stark positiv mit der Größe der Firmen gemessen am Umsatz, der Beschäftigung und den Investitionen. Firmen, die neue Technologien verwenden, sind auch durchschnittlich produktiver und zahlen durchschnittlich etwas höhere Löhne. Letzteres gilt jedoch nicht, wenn man auch für die Größe kontrolliert. Es zeigen sich keine signifikanten Wachstumseffekte in Bezug auf diese Variablen, und somit finden sich auch keine signifikanten Beschäftigungseffekte, die – wie oftmals befürchtet – von der Anwendung der neuen Technologien ausgehen. Auch hinsichtlich der Beschäftigungsstrukturen (unter Kontrolle von Firmengröße) – untersucht wurden der Anteil von Frauen, geringfügig bzw. Teilzeitbeschäftigten und der Anteil der Lehrlinge – finden sich kaum signifikante bzw. robuste Resultate dahingehend, dass sich Firmen, die neue Technologien anwenden, von denen unterscheiden, die das nicht tun. Auch hier gibt es keinerlei Hinweise darauf, dass sich die Beschäftigungsanteile bei den beiden Typen der Firmen unterschiedlich stark verändern. Diese Resultate können und sollen auf Basis der hier verwendeten und weiterer Daten als Grundlage für weitere Untersuchungen dienen (z. B. für detailliertere Beschäftigungsstrukturen), um mögliche Auswirkungen der „digitalen Revolution“ auf Beschäftigung auf Firmenebene besser abschätzen zu können." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Skill Supply, Technology Diffusion and the Labor Market (2024)
Zitatform
Stepanok, Ignat & Mewael F. Tesfaselassie (2024): Skill Supply, Technology Diffusion and the Labor Market. In: German Economic Review, Jg. 25, H. 2, S. 101-125., 2024-05-28. DOI:10.1515/ger-2023-0098
Abstract
"We analyze the short and long-run effects of an increase in the skill supply on skill-specific wages and unemployment in a model with endogenous, nonlinear diffusion of a general purpose technology (GPT) and labor market frictions. We calibrate and simulate the model using the trend rise in relative skill supply in the U.S. over two decades starting in the early 1970s. The transitional dynamics of the model show (i) an initial slump and long-run rise in the relative wage of high-skill labor and (ii) a long-run rise in the relative level of unemployment of low-skill versus high-skill labor. An increase in the number of skilled individuals reduces hiring costs and increases the incentive for firms to engage in the costly adoption of a new GPT. Stronger labor market rigidity and higher worker bargaining power are shown to have similar effects on relative wages and unemployment: changes in relative wages are more pronounced, whereas the response of relative unemployment is muted. The exact opposite effects are found in the case of a higher degree of substitution between products." (Author's abstract, IAB-Doku; © De Gruyter) ((en))
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Literaturhinweis
Multidimensional heterogeneity and matching in a frictional labor market - An application to polarization (2024)
Zitatform
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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