Individualism and the Formation of Human Capital
Katharina Hartinger, Sven Resnjanskij, Jens Ruhose, Simon Wiederhold
Journal of the European Economic Association,
forthcoming
Abstract
There is an ongoing debate about the economic effects of individualism. We establish that individualism leads to better educational and labor market outcomes. Using data from the largest international adult skill assessment, we identify the effects of individualism by exploiting variation between migrants at the origin country, origin language, and person level. Migrants from more individualistic cultures have higher cognitive skills and larger skill gains over time. They also invest more in their skills over the life-cycle, as they acquire more years of schooling and are more likely to participate in adult education activities. In fact, individualism is more important in explaining adult skill formation than any other cultural trait that has been emphasized in previous literature. In the labor market, more individualistic migrants earn higher wages and are less often unemployed. We show that our results cannot be explained by selective migration or omitted origin-country variables.
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Firm Training, Automation, and Wages: International Worker-Level Evidence
Oliver Falck, Yuchen Guo, Christina Langer, Valentin Lindlacher, Simon Wiederhold
Research Policy,
Vol. 55 (3),
2026
Abstract
Firm 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 firm training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without firm training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that training reduces workers’ automation risk by 3.8 percentage points, equivalent to 8% of the average automation risk. The training-induced reduction in automation risk accounts for 15% of the wage returns to firm training. Firm training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Training is similarly effective across gender, age, and education groups, suggesting widely shared benefits rather than gains concentrated in specific demographic segments.
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Training
Comprehensive Training Programs: CompNet and MDI Welcome to our Training Programs, designed to empower participants with the knowledge and skills needed for productivity analysis…
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Micro-data Infrastructure (MDI) Training The MDI Training is a three-session program designed to equip researchers (NPBs) with the skills to effectively work with cross-country…
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Training
Comprehensive Training Programs: CompNet and MDI Welcome to our Training Programs, designed to empower participants with the knowledge and skills needed for productivity analysis…
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Research Articles
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IWH-DPE in a Nutshell
IWH-DPE in a Nutshell The IWH Doctoral Programme in Economics (IWH-DPE) is the unit that organises the education of doctoral students at the IWH in close cooperation with partner…
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Research Clusters
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Firm Training, Automation, and Wages: International Worker-Level Evidence
Oliver Falck, Yuchen Guo, Christina Langer, Valentin Lindlacher, Simon Wiederhold
Abstract
Firm 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 firm training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without firm training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that training reduces workers’ automation risk by 3.8 percentage points, equivalent to 8% of the average automation risk. The training-induced reduction in automation risk accounts for 15% of the wage returns to firm training. Firm training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Training is similarly effective across gender, age, and education groups, suggesting widely shared benefits rather than gains concentrated in specific demographic segments.
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East Germany
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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