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
Wages, Skills, and Skill-Biased Technical Change: The Canonical Model Revisited (2023)
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Bowlus, Audra, Lance Lochner, Chris Robinson & Eda Suleymanoglu (2023): Wages, Skills, and Skill-Biased Technical Change. The Canonical Model Revisited. In: The Journal of Human Resources, Jg. 58, H. 6, S. 1783-1819. DOI:10.3368/jhr.0617-8889r1
Abstract
"While influential, the canonical supply–demand model of the wage returns to skill has faced challenges, including theoretically wrong-signed elasticities of substitution, counterintuitive paths for skill-biased technical change (SBTC), and an inability to account for observed deviations in college premia for younger versus older workers. We show that using improved estimates of skill prices and supplies that account for variation in skills across cohorts helps to explain the college premium differences between younger versus older workers and produces better out-of-sample predictions, positive elasticities of substitution between high- and low-skill workers, and a more modest role for SBTC. We further show that accounting for recession-induced jumps and trend adjustments in SBTC and linking SBTC to direct measures of information technology investment expenditures yield an improved fit, no puzzling slowdown in SBTC during the early 1990s, and a higher elasticity of substitution between high- and low-skill workers than previous ad hoc assumptions." (Author's abstract, IAB-Doku, © the Board of Regents of the University of Wisconsin System) ((en))
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Literaturhinweis
Does artificial intelligence kill employment growth: the missing link of corporate AI posture (2023)
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Bughin, Jacques (2023): Does artificial intelligence kill employment growth: the missing link of corporate AI posture. In: Frontiers in artificial intelligence, Jg. 6. DOI:10.3389/frai.2023.1239466
Abstract
"Introduction An intense debate has been on-going about how artificial intelligence (AI) technology investments have an impact on employment. The debate has often focused on the potential of AI for human task automation, omitting the strategic incentive for firms to cooperate with their workers as to exploit AI technologies for the most relevant benefit of new product and service innovation. Method We calibrate an empirical probit regression model of how changes in employment relate to AI diffusion, based on formalizing a game-theoretical model of a firm exploiting the twin role of AI innovation and AI automation for both absolute and competitive advantage. Results The theoretical game-theory prediction is that employment following AI technology adoption is not negative, and ultimately depends on how AI leads to new success in innovation, competition which defines the competitive reward of innovation and profit sharing between workers and firms. Our estimation, is based on a global survey of 3,000 large companies across 10 countries, demonstrates that a firm employment growth depends on two strategic postures, that is, the firm relative maturity of AI adoption as well as its relative bias toward AI-based product innovation. Discussion The contribution of this research is to highlight the twin role of firm and workers in shaping how technology will affect employment. AI in particular marries the potential of task automation with even more potential for expansion." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The Fall of the Labor Income Share: the Role of Technological Change and Hiring Frictions (2023)
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Carbonero, Francesco, Enzo Weber & Christian J. Offermanns (2023): The Fall of the Labor Income Share: the Role of Technological Change and Hiring Frictions. In: Review of Economic Dynamics, Jg. 49, S. 251-268., 2022-01-09. DOI:10.1016/j.red.2022.09.001
Abstract
"Die Veränderungen in der funktionalen Einkommensverteilung erhalten in der Forschung viel Aufmerksamkeit. Wir dokumentieren einen durchschnittlichen Rückgang des labour share (Anteil des Faktors Arbeit an der Einkommensverteilung) von 8 Prozentpunkten für acht europäische Länder und die USA zwischen 1980 und 2007. Wir untersuchen theoretisch und empirisch zwei Mechanismen: Substitution zwischen Informations- und Kommunikationstechnologie (IKT) und Arbeit sowie Friktionen bei Beschäftigungsanpassungen. Wir finden, dass Substitution zwischen IKT und Arbeit wesentlich den Rückgang des labour share erklären kann. Wenn Arbeitsmarktfriktionen berücksichtigt werden, übernehmen diese allerdings einen Teil der Erklärungskraft. Insbesondere spielen Einstellungskosten in Europa eine größere Rolle als in den USA. Schließlich wird die Subsitutionselastizität zwischen IKT und Arbeit als Funktion institutioneller und struktureller Variablen modelliert und festgestellt, dass sie mit dem Anteil von Routine-Berufen positiv und mit dem Anteil hochqualifizierter Arbeiter negativ korreliert." (Autorenreferat, IAB-Doku)
Ähnliche Treffer
frühere (möglw. abweichende) Version: IAB-Discussion Paper 28/2017 -
Literaturhinweis
Occupational Exposure to Capital-Embodied Technical Change (2023)
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Caunedo, Julieta, David Jaume & Elisa Keller (2023): Occupational Exposure to Capital-Embodied Technical Change. In: The American economic review, Jg. 113, H. 6, S. 1642-1685. DOI:10.1257/aer.20211478
Abstract
"We study differences in exposure to factor-biased technical change among occupations by providing the first measures of capital-embodied technical change (CETC) and of the elasticity of substitution between capital and labor at the occupational level. We document sizable occupational heterogeneity in both measures, but quantitatively, it is the heterogeneity in factor substitutability that fuels workers' exposure to CETC. In a general equilibrium model of worker sorting across occupations, CETC accounts for almost all of the observed labor reallocation in the US between 1984 and 2015. Absent occupational heterogeneity in factor substitutability, CETC accounts for only 17 percent of it." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Innovation and the Labor Market: Theory, Evidence and Challenges (2023)
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Corrocher, Nicoletta, Daniele Moschella, Jacopo Staccioli & Marco Vivarelli (2023): Innovation and the Labor Market: Theory, Evidence and Challenges. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 16199), Bonn, 32 S.
Abstract
"This paper deals with the complex relationship between innovation and the labor market, analyzing the impact of new technological advancements on overall employment, skills and wages. After a critical review of the extant literature and the available empirical studies, novel evidence is presented on the distribution of labor-saving automation (namely robotics and AI), based on natural language processing of US patents. This mapping shows that both upstream high-tech providers and downstream users of new technologies—such as Boeing and Amazon—lead the underlying innovative effort." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
AI technologies and employment: micro evidence from the supply side (2023)
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Damioli, Giacomo, Vincent Van Roy, Daniel Vertesy & Marco Vivarelli (2023): AI technologies and employment: micro evidence from the supply side. In: Applied Economics Letters, Jg. 30, H. 6, S. 816-821. DOI:10.1080/13504851.2021.2024129
Abstract
"In this work we investigate the possible job-creation impact of artificial intelligence (AI) technologies, focusing on the supply side, where the development of these technologies can be conceived as product innovations in upstream sectors. The empirical analysis is based on a worldwide longitudinal sample (obtained by merging the EPO PATSTAT and BvD-ORBIS databases) of more than 3,500 front-runner companies that patented AI-related inventions over the period 2000–2016. Based on system GMM estimates of dynamic panel models, our results show a positive and significant impact of AI patent families on employment, supporting the labour-friendly nature of AI product innovation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The employment impact of AI technologies among AI innovators (2023)
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Damioli, Giacomo, Vincent Van Roy, Daniel Vertesy & Marco Vivarelli (2023): The employment impact of AI technologies among AI innovators. (MSI discussion paper / KU Leuwen 2306), KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven 36 S.
Abstract
"This study supports the labour-friendly nature of product innovation among developers of artificial intelligence (AI) technologies. GMM-SYS estimates on a worldwide longitudinal dataset covering 3,500 companies that patented inventions related to AI technologies over the period 2000-2016 show a positive and significant impact of AI patent families on employment. The effect is small in magnitude and limited to service sectors and younger firms, which are front-runners of the AI revolution. We also detect some evidence of increasing returns suggesting that innovative companies more focused on AI technologies are those obtaining larger impacts in terms of job creation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Migration and Migrant Labour in the Gig Economy: An Intervention (2023)
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Doorn, Niels van, Fabian Ferrari & Mark Graham (2023): Migration and Migrant Labour in the Gig Economy: An Intervention. In: Work, Employment and Society, Jg. 37, H. 4, S. 1099-1111. DOI:10.1177/09500170221096581
Abstract
"In urban gig economies around the world, platform labour is predominantly migrant labour, yet research on the intersection of the gig economy and labour migration remains scant. Our experience with two action research projects, spanning six cities on four continents, has taught us how platform work impacts the structural vulnerability of migrant workers. This leads us to two claims that should recalibrate the gig economy research agenda. First, we argue that platform labour simultaneously degrades working conditions while offering migrants much-needed opportunities to improve their livelihoods. Second, we contend that the reclassification of gig workers as employees is by itself not sufficient to counter the precarisation of migrant gig work. Instead, we need ambitious policies at the intersection of immigration, social welfare, and employment regulation that push back against the digitally mediated commodification of migrant labour worldwide." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation and the employment elasticity of fiscal policy (2023)
Ebeke, Christian H.; Eklou, Kodjovi M.;Zitatform
Ebeke, Christian H. & Kodjovi M. Eklou (2023): Automation and the employment elasticity of fiscal policy. In: Journal of macroeconomics, Jg. 75. DOI:10.1016/j.jmacro.2023.103502
Abstract
"This paper investigates whether automation (the use of industrial robots in production) makes fiscal policy less powerful for stimulating job creation. It posits that a fiscal stimulus will lead to fewer new jobs if the supplementary demand that it creates can be met by using more robots in production processes. Using data for 18 European countries over recent decades, including data on the use of industrial robots, our results show three main findings. First, the pace of automation for the average country in the sample has halved the sensitivity of employment to fiscal stimulus. Second, manufacturing industry employment reacts less to fiscal stimulus in the presence of rapid automation as the average substituability between labor and machines is relatively higher. Third, low-skill jobs as well as women employment are less sensitive to fiscal stimulus in the presence of rapid robot use. We conclude that the effectiveness of fiscal policy in expanding job creation faces an important challenge in a world undergoing structural changes such as the rapid pace of automation." (Author's abstract, IAB-Doku, © 2023 Elsevier) ((en))
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Literaturhinweis
Routinization of work processes, de-routinization of job structures (2023)
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Fernández-Macías, Enrique, Martina Bisello, Eleonora Peruffo & Riccardo Rinaldi (2023): Routinization of work processes, de-routinization of job structures. In: Socio-economic review, Jg. 21, H. 3, S. 1773-1794. DOI:10.1093/ser/mwac044
Abstract
"This article investigates changes in routine tasks and computer use in European jobs in the period 1995–2015, putting them in the context of the debates on the future of work and the impact of automation. Digital technologies not only affect employment shifts but also shape work organization. A shift-share analysis combining European Working Conditions Survey and European Labour Force Survey data assesses to what extent recent changes in tasks are the result of changes in the structure of employment (shifts in employment across jobs) or changes in the content of work itself (transformation in the task contents and methods within jobs). The results suggest contrasting trends between observed changes in tasks measures within jobs and compositional shifts in employment for routine tasks indexes. Employment structures are de-routinizing while work itself is becoming more routine. These results seem also related to the increased use of computers at work during the same period." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The Evolution of Platform Gig Work, 2012-2021 (2023)
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Garin, Andrew, Emilie Jackson, Dmitri K. Koustas & Alicia Miller (2023): The Evolution of Platform Gig Work, 2012-2021. (NBER working paper / National Bureau of Economic Research 31273), Cambridge, Mass, 72 S.
Abstract
"We document the dynamics of tax-based measures of work mediated by online platforms from 2012 through 2021. We present a measurement framework to account for high reporting thresholds on some information returns using returns from states with lower reporting thresholds to provide a more complete estimate of total platform work. Updating data through 2021 allows us to provide the most comprehensive estimates of the COVID-19 pandemic on tax filing behavior. We find that the number of workers receiving information returns not subject to the 1099-K gap increased dramatically during the pandemic, with least 5 million individuals receiving information returns from platform gig work by 2021, nearly all from transportation platforms. We present evidence that the availability of expanded unemployment insurance benefits resulted in many individuals who were platform workers in 2019 not reporting any self-employment income in 2020-2021. At the same time, other services done by platform gig workers increased dramatically by at least 3.1 million people between 2019 and 2021. Interestingly, the broader 1099-contract economy follows a different trend, declining during this period, suggesting the challenges for tax administration are largely concentrated among platform gig workers, at least through 2021." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The puzzle of changes in employment and wages in routine task-intensive occupations (2023)
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Ghosh, Pallab & Zexuan Liu (2023): The puzzle of changes in employment and wages in routine task-intensive occupations. In: Empirical economics, Jg. 65, H. 4, S. 1965-1980. DOI:10.1007/s00181-023-02394-x
Abstract
"Autor and Dorn (Am Econ Rev 103(5):1553–1597, 2013) provide an explanation of the polarization of US employment and wages for the period 1980–2005. Using the 1980 Census and 2005 American Community Survey data, this study replicates the estimation results of Autor and Dorn (2013) for employment polarization in all major occupation groups and qualitatively matches the wage polarization results. Also, we investigate the puzzle of why employment and wages changed in opposite directions only in clerical and administrative support occupations in 1980–2005." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))
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Literaturhinweis
Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs (2023)
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González Ehlinger, Eugenia & Fabian Stephany (2023): Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs. (CESifo working paper 10817), München, 37 S.
Abstract
"For emerging professions, such as jobs in the field of Artificial Intelligence (AI) or sustainability (green), labor supply does not meet industry demand. In this scenario of labor shortages, our work aims to understand whether employers have started focusing on individual skills rather than on formal qualifications in their recruiting. By analyzing a large time series dataset of around one million online job vacancies between 2019 and 2022 from the UK and drawing on diverse literature on technological change and labor market signalling, we provide evidence that employers have started so-called “skill-based hiring” for AI and green roles, as more flexible hiring practices allow them to increase the available talent pool. In our observation period the demand for AI roles grew twice as much as average labor demand. At the same time, the mention of university education for AI roles declined by 23%, while AI roles advertise five times as many skills as job postings on average. Our analysis also shows that university degrees no longer show an educational premium for AI roles, while for green positions the educational premium persists. In contrast, AI skills have a wage premium of 16%, similar to having a PhD (17%). Our work recommends making use of alternative skill building formats such as apprenticeships, on-the-job training, MOOCs, vocational education and training, micro-certificates, and online bootcamps to use human capital to its full potential and to tackle talent shortages." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Faire Arbeit in der österreichischen Plattformökonomie? (2023)
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Griesser, Markus, Martin Gruber-Risak, Benjamin Herr, Leonhard Plank & Laura Vogel (2023): Faire Arbeit in der österreichischen Plattformökonomie? (Materialien zu Wirtschaft und Gesellschaft 242), Wien, 94 S.
Abstract
"Die vorliegende Studie liefert eine branchenübergreifende Darstellung der ortsgebundenen Plattformarbeit in Österreich anhand einer Untersuchung von sechs Unternehmen aus vier unterschiedlichen Branchen (Essenslieferung, Lebensmittellieferung, Personentransport, Reinigungsarbeit). Sie entstand im Kontext des internationalen Fairwork-Netzwerks, das im Sinne der Aktionsforschung zur Verbesserung der Arbeitsbedingungen im Bereich der Plattformökonomie beitragen möchte. Dabei werden Unternehmen entlang von fünf Prinzipien (faire Bezahlung, faire Arbeitsbedingungen, faire Verträge, faire Management-Prozesse, faire Mitbestimmung) auf Basis eines multimethodischen Designs bewertet. Die Ergebnisse der Studie unterstreichen die große Heterogenität von ortsgebundener Plattformarbeit und verdeutlichen, dass die Auswirkungen für Beschäftigte stark von den gewählten Geschäftsmodellen der Unternehmen abhängen. Dabei schneiden jene Plattformen am besten ab, die geschäftliche Risiken und Verantwortung nicht einseitig auf Beschäftigte abschieben." (Autorenreferat, IAB-Doku)
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Literaturhinweis
The skill-specific impact of past and projected occupational decline (2023)
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Hensvik, Lena & Oskar Nordström Skans (2023): The skill-specific impact of past and projected occupational decline. In: Labour Economics, Jg. 81. DOI:10.1016/j.labeco.2023.102326
Abstract
"Using population-wide data on a vector of cognitive abilities and productive non-cognitive traits among Swedish male workers, we show that occupational employment growth has been monotonically skill-biased in terms of these intellectual skills, despite a simultaneous (polarizing) decline in middle-wage jobs. Employees in growing low-wage occupations have more of these skills than employees in other low-wage occupations. Conversely, employees in declining, routine-task intensive, mid-wage occupations have comparably little of these skills. Employees in occupations that have grown relative to other occupations with similar wages have more intellectual skills overall but are particularly well-endowed with the non-cognitive trait “Social Maturity” and cognitive abilities in the “Technical” and “Verbal” domains. Projections from the US Bureau of Labor Statistics about future occupational labor demand do not indicate that the relationship between employment growth and skills is about to change in the near future." (Author's abstract, IAB-Doku, © 2023 Elsevier) ((en))
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Literaturhinweis
Robots, Natives and Immigrants in US local labor markets (2023)
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Javed, Mohsin (2023): Robots, Natives and Immigrants in US local labor markets. In: Labour Economics, Jg. 85. DOI:10.1016/j.labeco.2023.102456
Abstract
"I analyze the impact of industrial robots on the employment of natives and immigrants in US local labor markets between 1990 and 2014. The proposed mechanism, through which robot adoption affects the employment of natives and immigrants differentially, is based on two facts: first, robots tend to displace workers based on the task content of occupations, and second, natives and immigrants in the US differ in their task specialization. Therefore, robots should affect their employment unequally. Exploiting plausibly exogenous variation in robot exposure across US local labor markets over time, I test this mechanism and find that the effect on immigrants is roughly 1.76 times greater than that observed for natives. Specifically, I find that one more robot per thousand workers reduces the employment-to-population ratio of natives and immigrants by 0.38 and 0.67 percentage points, respectively. I attribute these results to the fact that immigrants specialize in jobs or tasks at risk of being automated." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
Robots and Wages: A Meta-Analysis (2023)
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Jurkat, Anne, Rainer Klump & Florian Schneider (2023): Robots and Wages: A Meta-Analysis. (EconStor Preprints 274156), Kiel, 72 S.
Abstract
"The empirical evidence on how industrial robots affect employment and wages is very mixed. Our meta-study helps to uncover the potentially true effect of industrial robots on labor market outcomes and to identify drivers of the heterogeneous empirical results. By means of a systematic literature research, we collected 53 papers containing 2143 estimations for the impact of robot adoption on wages. We observe only limited evidence for a publication bias in favor of negative results. The genuine overall effect of industrial robots on wages is close to zero and both statistically and economically insignificant. With regard to the drivers of heterogeneity, we find that more positive results are obtained if primary estimations a) include more countries in their sample, b) control for ICT capital, demographic developments, or tenure, c) focus on employees that remain employed in the same sector, d) consider only non-manufacturing industries, e) are specified in long differences, and f) come from a peer-reviewed journal article. More negative effects, in turn, are reported for primary estimations that are i) weighted, ii) aggregated at country level, iii) control for trade exposure, iv) and consider only manufacturing industries. We also find some evidence for skill-biased technological change. The magnitude of that effect is albeit small and less robust than one might expect in view of skill-biased technological change. We find little evidence for data dependence." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Measuring the technological bias of robot adoption and its implications for the aggregate labor share (2023)
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Koch, Michael & Ilya Manuylov (2023): Measuring the technological bias of robot adoption and its implications for the aggregate labor share. In: Research Policy, Jg. 52, H. 9. DOI:10.1016/j.respol.2023.104848
Abstract
"This paper investigates the technological bias of robot adoption using a rich panel data set of Spanish manufacturing firms over a 25-year period. We apply the production function estimation when productivity is multidimensional to the case of an automating technology, to reveal the Hicks-neutral and labor-augmenting technological change brought about by robot adoption within firms. Our results indicate a causal effect of robots on Hicks-neutral and labor-augmenting components of productivity. The biased technological change turns out to be an important determinant of the decline in the aggregate share of labor in the Spanish manufacturing sector." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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Literaturhinweis
Technology and Labor Displacement: Evidence from Linking Patents with Worker-Level Data (2023)
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Kogan, Leonid, Dimitris Papanikolaou, Lawrence D. W. Schmidt & Bryan Seegmiller (2023): Technology and Labor Displacement: Evidence from Linking Patents with Worker-Level Data. (NBER working paper / National Bureau of Economic Research 31846), Cambridge, Mass, 93 S.
Abstract
"We develop measures of labor-saving and labor-augmenting technology exposure using textual analysis of patents and job tasks. Using US administrative data, we show that both measures negatively predict earnings growth of individual incumbent workers. While labor-saving technologies predict earnings declines and higher likelihood of job loss for all workers, labor-augmenting technologies primarily predict losses for older or highly-paid workers. However, we find positive effects of labor-augmenting technologies on occupation-level employment and wage bills. A model featuring labor-saving and labor-augmenting technologies with vintage-specific human capital quantitatively matches these patterns. We extend our analysis to predict the effect of AI on earnings." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Trade Unions and the Process of Technological Change (2023)
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Kostøl, Fredrik B. & Elin Svarstad (2023): Trade Unions and the Process of Technological Change. In: Labour Economics, Jg. 84. DOI:10.1016/j.labeco.2023.102386
Abstract
"We investigate how trade unions influence the process of technological change at the workplace level. Using matched employer-employee data, comprising all Norwegian workplaces and working individuals in the period 2000-2014, we exploit exogeneous changes in the tax rules for union members to identify how changes in unionization rates affect the structural composition of occupations within workplaces. Making a distinction between routine and non-routine workers, based on their estimated probabilities of being replaced by automation technologies, we show how labor unions contribute to raising the relative wage of routine workers over non-routine workers. As routine workers on average have lower earnings than non-routine workers, unions thereby contribute to compress wages at the workplace level. The direct implication of this policy is shown to reduce the relative demand for routine workers over non-routine workers in unionized establishments. However, our results also suggest that unions influence the relative demand for routine workers, conditional on relative wages. Our findings thus give some support to bargaining theories where unions force firms off their demand curves." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))
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