Training, Automation, and Wages: International Worker-level Evidence
Oliver Falck, Yuchen Guo, Christina Langer, Valentin Lindlacher, Simon Wiederhold
IWH Discussion Papers,
No. 27,
2024
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.
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Robots, Occupations, and Worker Age: A Production-unit Analysis of Employment
Liuchun Deng, Steffen Müller, Verena Plümpe, Jens Stegmaier
European Economic Review,
November
2024
Abstract
We analyse the impact of robot adoption on employment composition using novel micro data on robot use in German manufacturing plants linked with social security records and data on job tasks. Our task-based model predicts more favourable employment effects for the least routine-task intensive occupations and for young workers, with the latter being better at adapting to change. An event-study analysis of robot adoption confirms both predictions. We do not find adverse employment effects for any occupational or age group, but churning among low-skilled workers rises sharply. We conclude that the displacement effect of robots is occupation biased but age neutral, whereas the reinstatement effect is age biased and benefits young workers most.
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From Shares to Machines: How Common Ownership Drives Automation
Joseph Emmens, Dennis Hutschenreiter, Stefano Manfredonia, Felix Noth, Tommaso Santini
IWH Discussion Papers,
No. 23,
2024
Abstract
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Robot Adoption at German Plants
Liuchun Deng, Verena Plümpe, Jens Stegmaier
Jahrbücher für Nationalökonomie und Statistik,
No. 3,
2024
Abstract
Using a newly collected dataset at the plant level from 2014 to 2018, we provide the first microscopic portrait of robotization in Germany and study the correlates of robot adoption. Our descriptive analysis uncovers five stylized facts: (1) Robot use is relatively rare. (2) The distribution of robots is highly skewed. (3) New robot adopters contribute substantially to the recent robotization. (4) Robot users are exceptional. (5) Heterogeneity in robot types matters. Our regression results further suggest plant size, high-skilled labor share, exporter status, and labor shortage to be strongly associated with the future probability of robot adoption.
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Labor Market Polarization and Student Debt
Sanket Korgaonkar, Elena Loutskina, Constantine Yannelis
SSRN Working Paper,
2024
Abstract
This paper uses a new empirical design to explore how labor market polarization affects individuals’ incentive to pursue education funded on the margin by student debt. We argue that the labor market polarization–where automation replaces mid-skill and mid-education-level job–changes the marginal benefits of education and training and sharpens incentives to incur student debt. We advance a new measure of labor market polarizations that allows to capture the heterogeneity of this phenomena across geographies and time. Using this measure, we find that U.S. CBSAs that experience deeper labor market polarization see an increase in student debt balances and in the number of people pursuing student debt. On average, the decline in middle-skill jobs and wages has little effect on individuals’ ability to pay down existing student debt. The effects are most pronounced in ZIP codes with lower average credit scores, lower incomes, and higher share of the minority population.
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Three Research Clusters Research Cluster "Economic Dynamics and Stability" Research Questions This cluster focuses on empirical analyses of macroeconomic dynamics and stability.…
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Department Profiles
Research Profiles of the IWH Departments All doctoral students are allocated to one of the four research departments (Financial Markets – Laws, Regulations and Factor Markets –…
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Robots, Occupations, and Worker Age: A Production-unit Analysis of Employment
Liuchun Deng, Steffen Müller, Verena Plümpe, Jens Stegmaier
IWH Discussion Papers,
No. 5,
2023
Abstract
We analyse the impact of robot adoption on employment composition using novel micro data on robot use in German manufacturing plants linked with social security records and data on job tasks. Our task-based model predicts more favourable employment effects for the least routine-task intensive occupations and for young workers, with the latter being better at adapting to change. An event-study analysis of robot adoption confirms both predictions. We do not find adverse employment effects for any occupational or age group, but churning among low-skilled workers rises sharply. We conclude that the displacement effect of robots is occupation biased but age neutral, whereas the reinstatement effect is age biased and benefits young workers most.
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