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Professor Dr. Oliver Falck

Professor Dr. Oliver Falck
Aktuelle Position

seit 3/14

Forschungsprofessor

Leibniz-Institut für Wirtschaftsforschung Halle (IWH)

seit 10/11

Professor für Volkswirtschaftslehre, insb. Empirische Innovationsökonomik

Ludwig-Maximilians-Universität München

Forschungsschwerpunkte
  • Innovation
  • Wachstum und wirtschaftliche Entwicklung

Oliver Falck ist seit März 2014 Forschungsprofessor am IWH. Er erforscht Innovation und Wachstum sowie Unternehmertum.

Oliver Falck ist der Inhaber des ifo-Stiftungslehrstuhls für Volkswirtschaftslehre, insbesondere Empirische Innovationsökonomik an der Ludwig-Maximilians-Universität München. Zugleich leitet er am ifo Institut das Zentrum für Industrieökonomik und neue Technologien, an dem auch das ifo-LMU Economics & Business Data Center (EBDC) angesiedelt ist. Darüber hinaus ist Oliver Falck Programmdirektor des CESifo Forschungsnetzwerks.

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Professor Dr. Oliver Falck
Professor Dr. Oliver Falck
- Abteilung Strukturwandel und Produktivität
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Publikationen

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Returns to ICT Skills

Oliver Falck Alexandra Heimisch-Roecker Simon Wiederhold

in: Research Policy, Vol. 50 (7), 2021

Abstract

How important is mastering information and communication technology (ICT) on modern labor markets? We answer this question with unique data on ICT skills tested in 19 countries. Our two instrumental-variable models exploit technologically induced variation in broadband Internet availability that gives rise to variation in ICT skills across countries and German municipalities. We find statistically and economically significant returns to ICT skills. For instance, an increase in ICT skills similar to the gap between an average-performing and a top-performing country raises earnings by about 8 percent. One mechanism driving positive returns is selection into occupations with high abstract task content.

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Arbeitspapiere

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Firm Training, Automation, and Wages: International Worker-Level Evidence

Oliver Falck Yuchen Guo Christina Langer Valentin Lindlacher Simon Wiederhold

in: IWH Discussion Papers, Nr. 27, 2024

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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