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
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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))
-
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), 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))
-
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))
-
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))
-
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))
Aspekt auswählen:
Aspekt zurücksetzen
- 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