Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Identifying policy-relevant treatment effects from randomized experiments requires the absence of spillovers between participants and nonparticipants (SUTVA) or variation in observed treatment levels. We find that SUTVA is violated for a Danish activation program for unemployed workers. Using a difference-in-differences model, we show that nonparticipants in the experiment regions find jobs more slowly after the introduction of the program than workers in other regions. We estimate an equilibrium search model to identify the policy-relevant treatment effect. A large-scale rollout of the program is shown to decrease welfare, while a standard partial microeconometric cost-benefit analysis concludes the opposite.