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Professor Dr Oliver Falck

Professor Dr Oliver Falck
Current Position

since 3/14

Research Professor

Halle Institute for Economic Research (IWH) – Member of the Leibniz Association

since 10/11

Professor of Economics, esp. Empirical Innovation Economics

University of Munich

Research Interests
  • innovation
  • growth and economic development

Oliver Falck joined the institute as a Research Professor in March 2014. His research focuses on innovation and growth as well as entrepreneurship.

Oliver Falck holds the position of Professor of Economics, especially Empirical Innovation Economics at the LMU Munich and he is the Director of the ifo Center for Industrial Organisation and New Technologies. Apart from that, he is also the Programme Director of CESifo Research Network.

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Professor Dr Oliver Falck
Professor Dr Oliver Falck
- Department Structural Change and Productivity
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Publications

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Returns to ICT Skills

Oliver Falck Alexandra Heimisch-Roecker Simon Wiederhold

in: Research Policy, No. 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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Working Papers

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Training, Automation, and Wages: International Worker-level Evidence

Oliver Falck Yuchen Guo Christina Langer Valentin Lindlacher Simon Wiederhold

in: IWH Discussion Papers, No. 27, 2024

Abstract

<p>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.</p>

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