At risk or responsive: Rethinking unemployment policy
Sebastian Ernst,  Andreas I Mueller, and Johannes Spinnewijn

Public services increasingly use predictive algorithms to direct scarce support towards those most at risk. But are these also the people who benefit most from intervention? This column explains how to navigate this trade-off and shows why it matters in practice. Job search counselling gets people into work faster, but has little effect on those at greatest risk of long-term unemployment. Combining predictions of risk and responsiveness can make scarce support substantially more effective, while highlighting the need for different support for those hardest to help.

You can read the full paper here.