There is growing evidence that the labour market for young workers is challenging. Graduates are finding it more difficult to get jobs after graduation. Several research papers have noted that generative AI may be to blame (see this post, for example), with one research paper referring to the changes in the labour market as seniority-biased technological change (see this post).
But the challenge with trying to attribute changes in the labour market to the rise of generative AI is that there are other contemporaneous changes affecting the labour market as well. One of those changes is the rise of working from home (as I noted in yesterday's post). Working from home may reduce the prospects for junior workers in part because it costs more to supervise and monitor them when they are working from home. Junior workers also benefit from on-the-job learning when they work with other people, and that on-the-job learning is less effective when they work from home. Combining those two effects, working from home reduces the incentive for employers to hire junior workers.
This new working paper by Peter Lambert (University of Warwick) and Yannick Schindler (Ellison Institute of Technology, Oxford) tries to disentangle the effects of generative AI and working from home on employment of younger workers. They use data from Revelio Labs that is made up of monthly matched employer-employee records collected from résumés (predominantly from LinkedIn) to construct a measure of the junior share of all new hires. They also use data from Lightcast on the near-universe of online job postings across thousands of online job sites and other websites. They use the Lightcast data to construct a measure of the share of job postings that require three or fewer years of experience. Their data from both sources covers the period from 2017 to 2025, and includes four countries: the US, the UK, Canada, and Australia.
Lambert and Schindler then use that data, along with measures of 'exposure to generative AI' and 'exposure to working from home' at the occupation level, in a difference-in-differences strategy. That means that they essentially compare the change in the share of junior job hires (or job postings) between occupations that are more or less exposed to generative AI (or working from home). Their main results are neatly summarised in Figure 3 from the paper:
Panel (a) shows that the junior share of new hires decreases significantly in jobs that are more exposed to working from home, from 2023 onwards (the black line). When they also control for exposure to generative AI (the red line), the effect of working from home barely changes. In contrast, Panel (b) shows that the junior share of new hires also decreases significantly in jobs that are more exposed to generative AI, from 2023 onwards (the black line). However, when they also control for exposure to working from home (the blue line), the effect of generative AI becomes much smaller and statistically insignificant. The results are similar for the share of job postings requiring three or fewer years' experience, as shown in Panels (c) and (d) of the figure.
The size of the effects are quite large too. A one-standard-deviation increase in exposure to working from home reduces the junior share of new hires by about two percentage points, and the share of job postings requiring three or fewer years' experience by 1.5 percentage points.
Lambert and Schindler conclude that, based on their results, working from home is a better predictor of the decline in junior hiring than generative AI. Given potential benefits of working from home, they are reluctant to recommend policies against working from home, instead noting that:
...micro-level adjustments may be required to help firms adapt their organizational practices, so as to enjoy the benefits of WFH [work from home] arrangements while simultaneously managing the development of early-career talent.
Seen alongside the negative mental health impacts of working from home (as noted in yesterday's post), this should give us further pause for thought. However, it is worth noting that even if working from home is a better predictor of reductions in junior hiring than generative AI within their model, that doesn't let generative AI off the hook entirely. Since both trends are happening at the same time, reducing working from home might not eliminate the negative impacts on junior hiring, but instead make generative AI appear more important as an explanation. Lambert and Schindler note early in their paper that it is often the same occupations (white-collar occupations) that are most exposed to both working from home and generative AI. Given that, perhaps Lambert and Schindler's recommendation for micro-level changes in organisational practice may be the best mitigation strategy available to us.
[HT: Marginal Revolution]
Read more:
- ChatGPT and the labour market
- More on ChatGPT and the labour market
- The impact of generative AI on contact centre work
- Some good news for human accountants in the face of generative AI
- Good news, bad news, and students' views about the impact of ChatGPT on their labour market outcomes
- Swiss workers are worried about the risk of automation
- Generative AI and entry-level employment
- Generative AI and seniority-biased technological change
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