Excited to be spending the month of April at Stanford University, hosted by Rick Hanushek at @hooverinstitution.bsky.social. Many thanks for the warm hospitality and the opportunity to engage with such a vibrant academic community.

If you’re around campus, drop me a line—always happy to chat!

[8] Heterogeneity I: Training is effective across nearly all countries, indicating strong external validity. Women tend to benefit more than men, with the gender advantage growing at older ages. This suggests that training may reduce gender disparities in rapidly changing labor markets.

[6] Mechanisms I: Training allows workers to shift toward low-automation tasks like negotiation, advising, or complex problem-solving. Interestingly, training also raises engagement in high-automation tasks (e.g., manual dexterity), but the effect is much smaller.

[4] Leveraging within-occupation, within-industry variation and controlling for cognitive skills & many background characteristics, we find that job training reduces automation risk by 4.7 pp (-10%). This reduction explains 1/5 of the positive wage effect of training.

[3] There is substantial variation in automation risk within occupations. Even occupations at opposite ends of the occupation-level automation risk spectrum show notable overlap in individual-level risk. This highlights the importance of going beyond existing occupation-level measures.

🚨NEW PAPER ALERT🚨
Does job training reduce workers’ automation risk? And does its effectiveness vary by country, gender, or training type? We study these questions in a new WP (w/ Oliver Falck, Mo Guo @christinalanger.bsky.social & @lindlacher.bsky.social). #EconSky

CESifo WP: bit.ly/3D4CDS5

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Very happy to have surpassed the 1000 follower mark. I know it's not a lot for others here, but I am super proud of it! Btw, I never had that many at the other place...