There is concern that the risky behaviors of teenagers, such as truancy, negatively influence the behaviors of others through their social networks. We use administrative data to construct social networks based on students who are truant together. We simulate these networks to document that certain students systematically coordinate their absences. We validate them by showing that a parent information intervention on student absences has spillover effects from treated students onto their peers. Excluding these effects understates the intervention’s cost-effectiveness by 43%. We show that there is potential to use networks to target interventions more efficiently given a budget constraint.

Low-income families often live in low-upward-mobility neighborhoods. We study why by using a randomized trial with housing voucher recipients that provided information, financial support, and customized search assistance to move to high-opportunity neighborhoods. The treatment increased the fraction moving to high-upward-mobility areas from 15 to 53 percent. A second trial reveals this treatment effect is driven primarily by customized search assistance. Qualitative interviews show that the intervention relaxed bandwidth constraints and addressed family-specific needs. Our findings imply many low-income families do not have strong preferences to stay in low-opportunity areas and that barriers in housing search significantly increase residential segregation by income.