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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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

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

Abstract

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