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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Training, Automation, and Wages: International Worker-level Evidence
Oliver Falck, Yuchen Guo, Christina Langer, Valentin Lindlacher, Simon Wiederhold
CESifo Working Papers,
No. 11533,
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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The Nasty Gap 30 years after unification: Why East Germany is still 20% poorer than the West Dossier In a nutshell The East German economic convergence process is hardly…
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Our Projects 07.2022 ‐ 12.2026 Evaluation of the InvKG and the federal STARK programme On behalf of the Federal Ministry of Economics and Climate Protection, the IWH and the RWI…
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Population and labour market Inhabitants are all people (Germans and foreigners) with permanent residence in federal territory (or in a Land). That does not include members of…
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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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Elderly Left Behind? How Older Workers Can Participate in the Modern Labor Market
Oliver Falck, Valentin Lindlacher, Simon Wiederhold
EconPol Forum,
No. 5,
2022
Abstract
In her 2021 State of the Union address, European Commission’s President Ursula von der Leyen announced that “[the EU] will invest in 5G and fiber. But equally important is the investment in digital skills.” Indeed, the EU Recovery and Resilience Facility, which runs until 2026, has earmarked substantial funds to tackle the digital divide, in acknowledgment of the fact that the EU is not only missing ICT specialists but also that many Europeans do not have sufficient digital skills to thrive in today’s society and labor market. Many observers argue that older workers in particular lack digital skills, suffering more often from computer anxiety and showing lower computer self-efficacy (Czaja et al. 2006). This lack of skills hampers their employability and productivity in a technologically fast-changing world.
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