We conduct a randomized evaluation of two job-search support programs for urban youth in Ethiopia. One group of treated respondents receives a subsidy to cover the transport costs of job search. Another group participates in a job application workshop where their skills are certified and they...

We evaluate the impacts of a randomized job-fair intervention in which jobseekers and employers can meet at low cost. The intervention generates few hires, but it lowers participants' expectations and causes both firms and workers to invest more in search as predicted by a theoretical model;...

We study how active labor market policies affect the exchange of information and support among jobseekers. Leveraging a unique social network survey in Ethiopia, we find that a randomized job-search assistance intervention reduces information sharing and support between treated jobseekers and...

We introduce a novel methodology for adaptive targeted experiments. Our Tempered Thompson Algorithm balances the goals of maximizing the precision of treatment effect estimates and maximizing the welfare of experimental participants. A hierarchical Bayesian model allows us to adaptively target...