Is GenAI causing the relative decline in early-career hiring? Our latest research finds that these effects may be conflated with another important driver: the rise of WFH arrangements (1/N) 
The decline, which has been widely documented, has seen a large fall in the share of new hires going to early-career / junior workers. We find a near 10pp decline in junior-share of new hires in US, UK, Canada, Australia
This has been shown to be concentrated in routine-cognitive white collar occupations. The challenge we highlight is that GenAI exposure is super strongly correlated with WFH exposure, posing a challenge for empirical analysis.
We show that the effect of GenAI exposure is strong before accounting for WFH, using two different outcomes at firm-, region-, and occupation-levels.
BUT when we control for WFH exposure, this effect all but disappears in our baseline results. This is NOT the case with WFH exposure, which is a robust predictor of the fall in junior-share of hiring with or without AI
In the paper, we do a whole bunch of extensions and robustness exercises. For example, we find that even a dummy variable capturing WFH is enough to render our main GenAI effect insignificant.
But why WFH? We also propose a stylised model to explain the mechanism: WFH makes supervision, monitoring, and on-the-job learning harder, all of which hit junior-workers more. Firms less willing to invest in junior talent when these frictions rise.
We hope this adds a new dimension to the important conversation about the fall in junior-hiring, perhaps some good news relative to the AI-jobpocalypse story - org. frictions from WFH feel much more manageable than technology-induced displacement.
Huge thanks to my coauthor @ymschindler , and loads of other comments and feedback on this paper from @LSEnews @cage_warwick @CEP_LSE .
• • •
Missing some Tweet in this thread? You can try to
force a refresh
