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Barth, Erling, Marianne Røed, Pål Schøne & Janis Umblijs (2025): Winners and losers when firms robotize: wage effects across occupations and education. In: The Scandinavian Journal of Economics, S. 1-30. 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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Diebold, Céline (2025): Using Google search data to examine factory automation and its effect on employment. In: Economic analysis and policy, Jg. 86, S. 1301-1328. DOI:10.1016/j.eap.2025.03.042

Abstract

"This paper revisits the link between robot adoption and employment across more than 100 European regions over a period of five years. A simple model is provided arguing that interest in robots precedes the actual deployment of robots. Thus, a novel instrument is introduced: interest in automation revealed by Google searches. This allows for a tentatively causal interpretation of the results. A small, yet significant positive aggregate effect is identified, along with heterogeneous effects across sex and educational attainment. The local effect on aggregate employment tends to be roughly twice as large as the spillover effect on neighbouring regions." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V. on behalf of The Economic Society of Australia (Queensland) Inc.) ((en))

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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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Mak, Eric & Aloysius Siow (2025): Occupational Choice, Matching, and Earnings Inequality. In: Journal of Political Economy, Jg. 133, H. 1, S. 355-383. DOI:10.1086/732530

Abstract

"We combine classic occupational choice (Roy, 1951) and frictionless matching (Sattinger, 1979) to explain earnings by occupation and firm in a way that is consistent with the double assignment. In our model, within-firm inequality is globally non-zero whenever there is asymmetry in the revenue function or the occupational skill distribution across occupations. Occupational earnings overlap each other, and unlike the Roy Model, the distributions of potential earnings are endogenous. In line with recent empirical findings on earning decomposition, skill-biased technical change (SBTC)increases within-firm inequality mostly among high-wage firms and not among low-wagefirms." (Author's abstract, IAB-Doku) ((en))

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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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Rabensteiner, Thomas & Alexander Guschanski (2025): Occupational Autonomy and Wage Divergence: Evidence From European Survey Data. In: BJIR, S. 1-18. 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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Richiardi, Matteo Guido, Leonie Westhoff, Caterina Astarita, Ekkehard Ernst, Clare Fenwick, Neysan Khabirpour & Lorenzo Pelizzari (2025): The impact of a decade of digital transformation on employment, wages, and inequality in the EU: a “conveyor belt” hypothesis. In: Socio-economic review, S. 1-27. DOI:10.1093/ser/mwaf011

Abstract

"We study the effects of digital transformation in the European Union on individual employment outcomes, wage growth, and income inequality, during the decade 2010–9. Our results allow us to formulate a ‘conveyor-belt’ hypothesis suggesting that employment confers a competitive advantage in navigating the digital transition due to the accumulation of pertinent skills in the workplace. Because digital skills are acquired with the changing demands of the job, their initial endowment matters less for the employed than for the non-employed. Furthermore, the ability of out-of-work individuals with higher digital skills to jump back on the labour market is reduced for those with higher education, suggesting a faster depreciation of their digital skills. A similar effect, although of limited size, is found for earning growth: out-of-work individuals with higher digital skills are not only more likely to find a job, but experience higher earnings growth, compared to their peers with lower digital skills. Our results point to a vulnerability of workers ‘left behind’ from the digital transformation and the labour market. The overall effects on inequality are, however, limited." (Author's abstract, IAB-Doku) ((en))

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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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Afonso, Óscar & Rosa Forte (2024): Routine and non-routine sectors, tasks automation and wage polarization. In: Applied Economics, Jg. 56, H. 55, S. 7262-7285. DOI:10.1080/00036846.2023.2280461

Abstract

"Recent and detailed data point to a polarization of wages with regard to the distribution of skills, particularly in developed countries over the past three decades, requiring the literature to address modelling approaches focused on automating different types of tasks. In the DTC literature, the technological-knowledge bias leads to an increase in the wage of skilled workers relative to unskilled workers. Motivated by this literature, this paper considers three types of workers (skilled, medium-skilled and unskilled) but retain the economic mechanisms that produce the results. Thus, wage inequality continues to result from the technological-knowledge bias, which, in the face of automation dynamics, reveals that medium-skilled workers are the relatively most penalized, generating wage polarization. Furthermore, as in the directed technical change literature, the relative supply of skilled workers continues to affect the skill premium." (Author's abstract, IAB-Doku) ((en))

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Albinowski, Maciej & Piotr Lewandowski (2024): The impact of ICT and robots on labour market outcomes of demographic groups in Europe. In: Labour Economics, Jg. 87. DOI:10.1016/j.labeco.2023.102481

Abstract

"We study the age- and gender-specific labour market effects of two key modern technologies, Information and Communication Technologies (ICT) and robots. Our sample includes 14 European countries between 2010 and 2018. We use the variation in technology adoption between industries and apply the instrumental variables strategy proposed by Acemoglu and Restrepo (2020) to identify the causal effects of technology adoption. We find that exposure to ICT and robots increased the shares of young and prime-aged women in employment and in the wage bills of particular sectors. However, it reduced the shares of older women and prime-aged men. We do not detect significant effects of technology adoption on the relative wages of most demographic groups. Between 2010 and 2018, the growth in ICT capital played a larger role than robot adoption in the changes in the withinsector labor market outcomes of demographic groups." (Author's abstract, IAB-Doku, ©2024 Elsevier) ((en))

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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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Brzozowski, Michał & Joanna Siwińska-Gorzelak (2024): Did robots make wages less responsive to unemployment? In: Technological forecasting & social change, Jg. 209. DOI:10.1016/j.techfore.2024.123769

Abstract

"Over recent years, there has been a notable change in the relationship that ties wage dynamics and unemployment, bearing significant implications for the formulation and implementation of monetary policies. Previous studies have identified a range of factors that potentially underlie this phenomenon but neglected the impact of robotisation. This paper seeks to address this gap by using data for 33 advanced economies and presenting compelling and robust empirical evidence of the moderating effect of robotisation on the relationship between unemployment and wage inflation." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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Burzyński, Michał (2024): Spatial and Occupational Mobility of Workers Due to Automation. (LISER working papers), Esch-sur-Alzette, 52 S.

Abstract

"Automation of labor tasks is one of the most dynamic aspects of recent technological progress. This paper aims at improving our understanding of the way that automation affects labor markets, analyzing the example of European countries. The quantitative theoretical methodology proposed in this paper allows to focus on automation-induced migration of workers, occupation switching and income inequality. The key findings include that automation in the first two decades of the 21st century had a significant impact on job upgrading of native workers and generated gains in many local labor markets. Even though net migration of workers was attenuated due to convergence in incomes across European regions, mobility at occupation levels had a sizeable impact on transmitting welfare effects of automation." (Author's abstract, IAB-Doku) ((en))

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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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Dauth, Wolfgang & Michael Moritz; Katharina Grienberger, Florian Lehmer, Steffen Müller, Bernd Fitzenberger, Verena Plümpe, Oliver Falck, Anja Bauer, Anja Sonnenburg, Markus Janser, Christian Schneemann, André Diegmann, Britta Matthes & Anna Solms (sonst. bet. Pers.) (2024): Wie bewältigen Regionen die digitale und ökologische Transformation von Wirtschaft und Arbeitsmarkt? (Podium). In: IAB-Forum H. 06.05.2024. DOI:10.48720/IAB.FOO.20240506.01

Abstract

"Was bedeuten die absehbaren Transformationsprozesse der kommenden Jahrzehnte auf regionaler Ebene und wie können sie gemeistert werden? Antworten auf diese Fragen gab der IWH/IAB-Workshop zur Arbeitsmarktpolitik, der in diesem Jahr erstmals am IAB in Nürnberg stattfand." (Autorenreferat, IAB-Doku)

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Falck, Oliver, Yuchen Guo, Christina Langer, Valentin Lindlacher & Simon Wiederhold (2024): Training, Automation, and Wages: International Worker-Level Evidence. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 17503), Bonn, 72 S.

Abstract

"Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether job training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without job training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that job training reduces workers' automation risk by 4.7 percentage points, equivalent to 10 percent of the average automation risk. The training-induced reduction in automation risk accounts for one-fifth of the wage returns to job training. Job training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Women tend to benefit more from training than men, with the advantage becoming particularly pronounced at older ages." (Author's abstract, IAB-Doku) ((en))

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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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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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Guo, Yuchen Mo, Oliver Falck, Christina Langer, Valentin Lindlacher & Simon Wiederhold (2024): Training, Automation, and Wages: Worker-Level Evidence. (Beiträge zur Jahrestagung des Vereins für Socialpolitik 2024: Upcoming Labor Market Challenges 302366), Berlin, 47 S.

Abstract

"This paper investigates the impact of job training on workers’ susceptibility to automation. Using rich individual-level data from the Programme for the International Assessment of Adult Competencies (PIAAC) across 37 industrialized countries, we construct a unique individual-level measure of automation risk based on the tasks performed at work. We uncover substantial variation in automation risk within detailed occupations, which would have been overlooked by previous occupation-level automation measures. To estimate the effect of training on workers’ automation risk, we include tested numeracy skills as a proxy for unobserved ability that are unique to our data, and apply entropy balancing to account for selection bias. We find that job training is an important factor in explaining workers’ susceptibility to automation, even within narrowly defined occupations. Our results show that workers who participate in job training witness a 4.7 percentage point reduction in their automation risk compared to observationally equivalent workers without training. Additionally, workers participating in training earn approximately 8 percent higher wages compared to their counterparts without training. While training is effective in reducing automation risk and increasing wages in all sample countries, there is a substantial heterogeneity in the magnitude of training effects. Moreover, training benefits both younger and older workers equally, and is more effective for women. Our findings thus underscore the crucial role of training in enabling the workforce to adapt and thrive amidst evolving technological changes." (Author's abstract, IAB-Doku) ((en))

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Heluo, Yuxi & Oliver Fabel (2024): Job computerization, occupational employment and wages: A comparative study of the United States, Germany, and Japan. In: Technological forecasting & social change, Jg. 209. DOI:10.1016/j.techfore.2024.123772

Abstract

"This study adds to the growing literature on wage and employment responses to the risk of job computerization. Specifically, it revisits the original occupational perspective and inquires into the nature of the adjustments of occupational wages and employment, i.e., the potential benefits and costs associated with professional careers in such occupations. The investigation further aims at identifying whether these adjustment processes are universal - as suggested by the global availability of the respective technology - or reflect country-specific peculiarities. To this end, it conducts a comparative analysis with data from the United States, Germany, and Japan, three G7 lead countries which share the commitment to fostering technological progress, but which are also characterized by distinctly different labor market institutions and approaches to industrial policies. Generally consistent with the country-specific employment institutions and common corporate strategies, transmission channels - as reflected by the relationship between adjustments of occupational employment and wages - differ between countries. In all three countries, though, higher risks of computerization are associated with relative wage losses in occupations which require low levels of formal education or training." (Author's abstract, IAB-Doku, © 2024 Elsevier) ((en))

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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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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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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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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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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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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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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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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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Brall, Franziska & Ramona Schmid (2023): Automation, Robots and Wage Inequality in Germany. A decomposition Analysis. In: Labour, Jg. 37, H. 1, S. 33-95. DOI:10.1111/labr.12236

Abstract

"We conduct a decomposition analysis based on recentred influence function (RIF) regressions to disentangle the relative importance of automation and robotization for wage inequality in the manufacturing sector in Germany between 1996 and 2017. Our measure of automation threat combines occupation-specific scores of automation risk with sector-specific robot densities. We find that besides changes in the composition of individual characteristics, structural shifts among different automation threat groups are a non-negligible factor associated with wage inequality between 1996 and 2017. Moreover, the increase in wage dispersion among the different automation threat groups has contributed significantly to higher wage inequality in the 1990s and 2000s." (Author's abstract, IAB-Doku, © Wiley) ((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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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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Hutter, Christian & Enzo Weber (2023): Labour market effects of wage inequality and skill-biased technical change. In: Applied Economics, Jg. 55, H. 27, S. 3063-3084., 2022-07-22. DOI:10.1080/00036846.2022.2108751

Abstract

"Ziel dieser Arbeit ist es, die Beziehung zwischen Ungleichheit und der Arbeitsmarktentwicklung in Deutschland seit 1975 näher zu beleuchten. Die wichtigsten Theorien sowie auch die empirische Evidenz sind sich zu diesem Thema nicht einig. Unser strukturelles Vektorfehlerkorrekturmodell modelliert explizit den qualifikationsverzerrenden technologischen Fortschritt als Quelle von Ungleichheit. Mithilfe von nicht-rekursiven Langfristrestriktionen werden die Effekte von Ungleichheitsschocks, qualifikationsverzerrenden (und -neutralen) Technologieschocks auf Arbeitsvolumen, reale Lohnkosten und Produktivität identifiziert. Deskriptive Evidenz zeigt, dass der jahrzehntelange Anstieg der Lohnungleichheit im Jahr 2010 gestoppt wurde und sich sogar umkehrte. Dafür ist hauptsächlich die sinkende Ungleichheit in der unteren Hälfte der Lohnverteilung verantwortlich. Die Impuls-Antwort-Analysen verdeutlichen, dass qualifikationsverzerrende Technologieschocks sich negativ auf das Arbeitsvolumen auswirken, die Lohnungleichheit, Lohnkosten und Produktivität allerdings erhöhen. Ungleichheitsschocks haben ebenfalls einen negativen Effekt auf das Arbeitsvolumen, reduzieren zusätzlich aber die Produktivität." (Autorenreferat, IAB-Doku)

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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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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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Shimizu, Ryosuke & Shohei Momoda (2023): Does automation technology increase wage? In: Journal of macroeconomics, Jg. 77. DOI:10.1016/j.jmacro.2023.103541

Abstract

"This paper examines the relationship between automation technology and wages. In the model, producers either choose automation or non-automation technology, whichever is more profitable. Furthermore, when producers introduce automation technology, they must pay fixed costs, which differ between industries. The main results of this paper indicate that the increased productivity of automation technology promotes automation, decreases labor income share, and also decreases wages when the level of automation diffusion is sufficiently high." (Author's abstract, IAB-Doku, © 2023 Elsevier) ((en))

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Wicht, Alexandra, Nora Müller, Reinhard Pollak & Silke Anger (2023): Gendered wage effects of changes in job tasks: Evidence from Germany. (SocArXiv papers), 26 S. DOI:10.31235/osf.io/5dcgw

Abstract

"While previous research showed that technological progress and digitization change job Tasks within occupations and that these occupation-level changes in job tasks affect the wage structure and personal wages, little is known about whether individual changes in job Tasks affect personal earnings. Following the task-biased technological change approach, we analyze whether individuals who take on more non-routine job tasks with a low Automation risk (complex and autonomous tasks) are rewarded with higher wages. Accounting for the strong gender segregation of the German labor market, we separately analyze men and women and, due to the rigid German labor market, additionally account for job changes as a potential moderator. We use three-wave panel data covering a period of nine years from the German National Educational Panel Study. Our results from fixed-effects regressions Show that there is substantial heterogeneity in the relationship between changes in non-routine Job tasks and wages by gender and between those who have or have not changed jobs, which is masked when looking at average wage differentials by non-routine job tasks. While both genders benefit from increased task complexity in job changes, the impact is more pronounced for females, helping to slightly narrow the still persistent gender wage gap. However, when taking on more autonomous tasks in job changes, males experience significant benefits, further contributing to the widening of the gender wage gap. In essence, our findings underscore gender-specific monetary returns to increasing non-routine tasks, particularly highlighting the ability of male job changers to monetarize their newly assigned tasks." (Author's abstract, IAB-Doku) ((en))

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Willcox, Michael & Brittany Feor (2023): Structural Changes in Canadian Employment from 1997 to 2022. (JRC working papers series on labour, education and technology 2023,08), Sevilla, 33 S.

Abstract

"This paper uses the European Jobs Monitor (2017) jobs' approach to examine the structural changes in employment and wages in Canada between 1997 and 2022. Changes in employment and real wages reveals a long-term pattern of upgrading, particularly after the 2008 financial crisis. There is variation in these patterns within the 25-year period including a shift towards higher quality jobs after the financial crisis and evidence of wage polarisation between 2020 and 2022. Employment and wage trends by sector, sex and age were explored. Employment shifted away from manufacturing towards the healthcare and social assistance, professional, scientific, and technical services, and construction sectors since the late 1990s which accelerated after the global financial crisis. The wage gap and difference in employment shares between men and women has narrowed over time, despite recent widening following the pandemic. Canada's aging population has resulted in a growing share of mature workers in the labour market and in core-age workers becoming more concentrated in mid-to-high wage jobs." (Author's abstract, IAB-Doku) ((en))

Abstract

"This study is made of two parts: part A and part B. Part A of the study analyses - through 27 country fiches - the extent to which each EU Member State is prepared for ensuring a socially fair digital transformation in the coming years, based on both its current situation and future prospects. In this analysis, key areas of focus include the labor market, digital skills of the population, social protection as well as cross-cutting dimensions, such as the digitalization level of businesses and the quality of digital infrastructures. Part B of the study reviews - through 30 case studies - some of the main actual and potential uses of digital technologies (including AI) by a country’s public sector for improving the design and the delivery of social benefits and active labor market policies, as well as for complementing the monitoring of poverty and income inequality (the case studies analysed are mainly in Member States but also in a few third countries)." (Author's abstract, IAB-Doku) ((en))

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Acemoglu, Daron, David Autor, Jonathon Hazell & Pascual Restrepo (2022): Artificial Intelligence and Jobs: Evidence from Online Vacancies. In: Journal of labor economics, Jg. 40, H. S1, S. S293-S340. DOI:10.1086/718327

Abstract

"We study the impact of artificial intelligence (AI) on labor markets using establishment-level data on the near universe of online vacancies in the United States from 2010 onward. There is rapid growth in AI-related vacancies over 2010–18 that is driven by establishments whose workers engage in tasks compatible with AI’s current capabilities. As these AI-exposed establishments adopt AI, they simultaneously reduce hiring in non-AI positions and change the skill requirements of remaining postings. While visible at the establishment level, the aggregate impacts of AI-labor substitution on employment and wage growth in more exposed occupations and industries is currently too small to be detectable." (Author's abstract, IAB-Doku) ((en))

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Acemoglu, Daron & Pascual Restrepo (2022): Tasks, Automation, and the Rise in U.S. Wage Inequality. In: Econometrica, Jg. 90, H. 5, S. 1973-2016. DOI:10.3982/ECTA19815

Abstract

"We document that between 50% and 70% of changes in the U.S. wage structure over the last four decades are accounted for by relative wage declines of worker groups specialized in routine tasks in industries experiencing rapid automation. We develop a conceptual framework where tasks across industries are allocated to different types of labor and capital. Automation technologies expand the set of tasks performed by capital, displacing certain worker groups from jobs for which they have comparative advantage. This framework yields a simple equation linking wage changes of a demographic group to the task displacement it experiences. We report robust evidence in favor of this relationship and show that regression models incorporating task displacement explain much of the changes in education wage differentials between 1980 and 2016. The negative relationship between wage changes and task displacement is unaffected when we control for changes in market power, deunionization, and other forms of capital deepening and technology unrelated to automation. We also propose a methodology for evaluating the full general equilibrium effects of automation, which incorporate induced changes in industry composition and ripple effects due to task reallocation across different groups. Our quantitative evaluation explains how major changes in wage inequality can go hand‐in‐hand with modest productivity gains." (Author's abstract, IAB-Doku) ((en))

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Arntz, Melanie, Boris Ivanov & Laura Pohlan (2022): Regional Structural Change and the Effects of Job Loss. (ZEW discussion paper 22-019), Mannheim, 55 S.

Abstract

"In vielen Ländern sind routine-intensive Berufe rückläufig, aber wie wirkt sich dies auf die individuelle Karriere aus, wenn der Rückgang dieser Berufe im lokalen Arbeitsmarkt besonders stark ausfällt? Diese Studie zeigt basierend auf administrativen Daten aus Deutschland und einem mit Matching kombinierten Differenz-von-Differenzen-Ansatz, dass die individuellen Kosten eines Arbeitsplatzverlustes stark von der Tätigkeitsorientierung des regionalen Strukturwandels abhängen. Personen aus manuellen routine-intensiven Berufen haben nach einer Entlassung wesentlich höhere und lang anhaltende Beschäftigungs- und Lohnverluste in Regionen, in denen der Rückgang dieser Berufe am stärksten ausgeprägt ist. Regionale und berufliche Mobilität dienen teilweise als Anpassungsmechanismen, sie sind jedoch mit hohen Kosten verbunden, da diese Wechsel auch Verluste bei unternehmensspezifischen Lohnaufschlägen mit sich bringen. Beschäftigte, die nicht entlassen werden, bleiben hingegen weitgehend vom Strukturwandel verschont." (Autorenreferat, IAB-Doku)

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Bachmann, Ronald & Myrielle Gonschor (2022): Technological Progress, Occupational Structure and Gender Gaps in the German Labour Market. (IZA discussion paper 15419), Bonn, 39 S.

Abstract

"We analyze if technological progress and the corresponding change in the occupational structure have improved the relative position of women in the labour market. We show that the share of women rises most strongly in non-routine cognitive and manual occupations, but declines in routine occupations. While the share of women also rises relatively strongly in high-paying occupations, womens' individual-level wages lag behind which implies within-occupation gender wage gaps. A decomposition exercise shows that composition effects with respect to both individual and job characteristics can explain the rise of female shares in the top tier of the labour market to an extent. However, the unexplained part of the decomposition is sizeable, indicating that developments such as technological progress are relevant." (Author's abstract, IAB-Doku) ((en))

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Bachmann, Ronald, Gökay Demir, Colin Green & Arne Uhlendorff (2022): The Role of Within-Occupation Task Changes in Wage Development. (Ruhr economic papers 975), Essen, 41 S. DOI:10.4419/96973140

Abstract

"Wir untersuchen, wie Veränderungen der Aufgabeninhalte im Laufe der Zeit die berufliche Lohnentwicklung beeinflussen. Anhand von Umfragedaten aus Deutschland dokumentieren wir eine erhebliche Heterogenität bei der Veränderung von Aufgabeninhalten innerhalb eines Berufes. Kombiniert man diese Erkenntnisse mit administrativen Daten zu individuellen Beschäftigungsergebnissen über einen Zeitraum von 25 Jahren, so stellt man fest, dass es eine erhebliche Heterogenität in Bezug auf Lohneinbußen bei ursprünglich routineintensiven Tätigkeiten gibt. Während Berufe, die (relativ) routineintensiv bleiben, erhebliche Lohneinbußen mit sich bringen, bleiben die Löhne in Berufen mit abnehmender Routineintensität stabil oder steigen sogar. Diese Ergebnisse lassen sich nicht durch Kompositions- oder Kohorteneffekte erklärt werden." (Autorenreferat, IAB-Doku)

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Berg, Janine, Francis Green, Laura Nurski & David Spencer (2022): Risks to job quality from digital Technologies: are industrial relations in Europe ready for the challenge? (Working paper / Bruegel 2022,16), Brussels, 31 S.

Abstract

"We examine the job quality effects of new digital technologies in Europe, using the framework of seven job quality ‘domains’: pay, working time quality, prospects, skills and discretion, work intensity, social environment and physical environment. The theoretical effects from new technology are ambivalent for all domains. Data on robot shocks matched to the European Working Conditions Surveys for 2010 and 2015 is used to generate empirical estimates, which show significant aggregate negative effects in three domains, and a positive effect in one. Some negative effects are enhanced where there is below-median collective bargaining. In light of these analyses, and in order to think through the challenge of regulating the development and implementation of all forms of digital technologies, we review regulations in several European countries. Drawing on the principles of human-centred design, we advance the general hypothesis that worker participation is important for securing good job quality outcomes, at both the innovation and adoption stages. We also consider the application to the regulation of job quality of national and supra-national data protection legislation. In these ways, the paper extends the debate about the future of work beyond employment and pay, to a consideration of job quality more broadly." (Author's abstract, IAB-Doku) ((en))

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Cords, Dario & Klaus Prettner (2022): Technological unemployment revisited: automation in a search and matching framework. In: Oxford economic papers, Jg. 74, H. 1, S. 115-135. DOI:10.1093/oep/gpab022

Abstract

"Will automation raise unemployment and what is the role of education in this context? To answer these questions, we propose a search and matching model of the labour market with two skill types and with industrial robots. In line with evidence to date, robots are better substitutes for low-skilled workers than for high-skilled workers. We show that robot adoption leads to rising unemployment and falling wages of low-skilled workers and falling unemployment and rising wages of high-skilled workers. In a calibration to Austrian and German data, we find that robot adoption destroys fewer low-skilled jobs than the number of high-skilled jobs it creates. For Australia and the USA, the reverse holds true. Allowing for endogenous skill acquisition of workers implies positive employment effects of automation in all four countries. Thus, the firm creation mechanism in the search and matching model and skill acquisition are alleviating the adverse effects of automation." (Author's abstract, IAB-Doku) ((en))

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Gries, Thomas & Wim Naudé (2022): Modelling artificial intelligence in economics. In: Journal for labour market research, Jg. 56. DOI:10.1186/s12651-022-00319-2

Abstract

"We provide a partial equilibrium model wherein AI provides abilities combined with human skills to provide an aggregate intermediate service good. We use the model to find that the extent of automation through AI will be greater if (a) the economy is relatively abundant in sophisticated programs and machine abilities compared to human skills; (b) the economy hosts a relatively large number of AI-providing firms and experts; and (c) the task-specific productivity of AI services is relatively high compared to the task-specific productivity of general labor and labor skills. We also illustrate that the contribution of AI to aggregate productive labor service depends not only on the amount of AI services available but on the endogenous number of automated tasks, the relative productivity of standard and IT-related labor, and the substitutability of tasks. These determinants also affect the income distribution between the two kinds of labor. We derive several empirical implications and identify possible future extensions." (Author's abstract, IAB-Doku, © Springer) ((en))

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(2022): Atlas der digitalen Arbeit. Daten und Fakten über die Beschäftigung der Zukunft. Berlin ; Düsseldorf, 54 S.

Abstract

"Der Atlas der digitalen Arbeit blickt auf viele verschiedene Branchen: Auto, Chemie und Pharma, aber auch die Pflege und die öffentliche Hand. Es geht um grundlegende Fragen: Wie weit sind smarte Computer und Roboter in diesen Bereichen auf dem Vormarsch? Welche Folgen hat das für die Beschäftigten? Wie viel verdienen Menschen in digitalen Berufen? Was verändert sich in der Berufsausbildung? Macht Homeoffice glücklich? Profitieren Frauen und Männer gleichermaßen von den Vorteilen der digitalen Arbeitswelt? Der neue Atlas der digitalen Arbeit, den die Hans-Böckler-Stiftung und der Deutsche Gewerkschaftsbund (DGB) herausgeben, bildet zahlreiche Aspekte der Arbeitswelt von heute ab und bringt Entwicklungstrends auf den Punkt. Mit kurzen Texten und prägnanten, aktuellen Infografiken, gestaltet von der renommierten Berliner Atlasmanufaktur. Eine solide Grundlage, um über die Arbeit der Zukunft zu diskutieren." (Autorenreferat, IAB-Doku)

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Hornuf, Lars & Daniel Vrankar (2022): Hourly Wages in Crowdworking: A Meta-Analysis. (CESifo working paper 9540), München, 38 S.

Abstract

"In the past decade, crowdworking on online labor market platforms has become the main source of income for a growing number of people worldwide. This development has led to increasing political and scientific interest in the wages that people can earn on such platforms. In this article, we extend the literature based on a single platform, region, or category of crowdworking by conducting a meta-analysis of the prevalent hourly wages. After a systematic and rigorous literature search, we consider 20 primary empirical studies, including 104 wages and 76,282 data points from 22 platforms, eight different countries, and a time span of 12 years. We find that, on average, microwork results in an hourly wage of less than $6. This wage is significantly lower than the mean wage of online freelancers, which is roughly three times higher. We find that hourly wages accounting for unpaid work, such as searching for tasks and communicating with requesters, tend to be significantly lower than wages not considering unpaid work. Legislators and researchers evaluating wages in crowdworking should be aware of this bias when assessing hourly wages, given that the majority of the literature does not account for the effect of unpaid work time on crowdworking wages. To foster the comparability of different research results, we suggest that scholars consider a wage malus to account for unpaid work. Finally, we find that hourly wages collected through surveys tend to be lower than wages collected via browser plugins or other technical data collection methods." (Author's abstract, IAB-Doku) ((en))

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Korinek, Anton & Megan Juelfs (2022): Preparing for the (Non-Existent?) Future of Work. (NBER working paper 30172), Cambridge, Mass, 42 S. DOI:10.3386/w30172

Abstract

"This paper considers the labor market and distributional implications of a scenario of ever-more-intelligent autonomous machines that substitute for human labor and drive down wages. We lay out three concerns arising from such a scenario and evaluate recent predictions and objections to these concerns. Then we analyze how a utilitarian social planner would allocate work and income if these concerns start to materialize. As the income produced by autonomous machines rises and the value of labor declines, a utilitarian planner finds it optimal to phase out work, beginning with workers who have low labor productivity and job satisfaction, since they have comparative advantage in enjoying leisure. This is in stark contrast to welfare systems that force individuals with low labor productivity to work. If there are significant wage declines, avoiding mass misery will require other ways of distributing income than labor markets, whether via sufficiently well-distributed capital ownership or via benefits. Recipients could still engage in work for its own sake if they enjoy work amenities such as structure, purpose and meaning. If work gives rise to positive externalities such as social connections or political stability, or if individuals undervalue the benefits of work because of internalities, then a social planner would incentivize work. However, in the long run, the planner might be able to achieve a higher level of social welfare by adopting alternative ways of providing these benefits." (Author's abstract, IAB-Doku) ((en))

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Ocampo, Sergio (2022): A Task-Based Theory of Occupations with Multidimensional Heterogeneity. (Centre for Human Capital and Productivity (CHCP) working paper series 2022-02), London, Ontario, 64 S.

Abstract

"I develop an assignment model of occupations with multidimensional heterogeneity in production tasks and worker skills. Tasks are distributed continuously in the skill space, whereas workers have a discrete distribution with a finite number of types. Occupations arise endogenously as bundles of tasks optimally assigned to a type of worker. The model allows us to study how occupations respond to changes in the economic environment, making it useful for analyzing the implications of automation, skill-biased technical change, offshoring, and worker training. Using the model, I characterize how wages, the marginal product of workers, the substitutability between worker types, and the labor share depend on the assignment of tasks to workers. I introduce automation as the choice of the optimal size and location of a mass of identical robots in the task space. Automation displaces workers by replacing them in the performance of tasks, generating a cascading effect on other workers as the boundaries of occupations are redrawn." (Author's abstract, IAB-Doku) ((en))