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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Joint Economic Forecast Spring 2025 Geopolitical turn intensifies crisis – structural reforms even more urgent April 10, 2025 The German economy will continue to tread water in…
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Unions as Insurance: Workplace Unionization and Workers' Outcomes During COVID-19
Nils Braakmann, Boris Hirsch
Industrial Relations: A Journal of Economy and Society,
No. 2,
2024
Abstract
We investigate to what extent workplace unionization protects workers from external shocks by preventing involuntary job separations. Using the COVID-19 pandemic as a plausibly exogenous shock hitting the whole economy, we compare workers who worked in unionized and non-unionized workplaces directly before the pandemic in a difference-in-differences framework. We find that unionized workers were substantially more likely to remain working for their pre-COVID employer and to be in employment. This greater employment stability was not traded off against lower working hours or labor income.
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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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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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Uncovered Workers in Plants Covered by Collective Bargaining: Who Are They and How Do They Fare?
Boris Hirsch, Philipp Lentge, Claus Schnabel
British Journal of Industrial Relations,
No. 4,
2022
Abstract
Abstract In Germany, employers used to pay union members and non-members in a plant the same union wage in order to prevent workers from joining unions. Using recent administrative data, we investigate which workers in firms covered by collective bargaining agreements still individually benefit from these union agreements, which workers are not covered anymore and what this means for their wages. We show that about 9 per cent of workers in plants with collective agreements do not enjoy individual coverage (and thus the union wage) anymore. Econometric analyses with unconditional quantile regressions and firm-fixed-effects estimations demonstrate that not being individually covered by a collective agreement has serious wage implications for most workers. Low-wage non-union workers and those at low hierarchy levels particularly suffer since employers abstain from extending union wages to them in order to pay lower wages. This jeopardizes unions' goal of protecting all disadvantaged workers.
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