Publications

Behaviorally informed “nudges” are widely used in government outreach but are often seen as too modest to address poverty at scale. In four field experiments over 2 y (n = 542,804 low-income households), we test whether more proactive communication, varying message framing, and more precise targeting can boost take-up of tax-based benefits in California above and beyond traditional light-touch approaches. Our interventions focused on extremely vulnerable households, most with no prior-year earnings, who were at risk of missing out on two crucial benefits: the 2021 expanded Child Tax Credit and pandemic-relief Economic Impact Payments. Light-touch outreach consistently increased take-up of these benefits by 0.14 to 2 percentage points—a 150% to over 500% relative increase—regardless of message, sample, timing, or modality. These light-touch approaches resulted in over $4 million disbursed, with a highly cost-effective return of $50 to over $8,000 per $1 spent. However, higher-touch proactive outreach, varying messaging, and more precise targeting yielded minimal additional benefits, with proactive outreach even showing negative returns. These findings demonstrate that light-touch outreach can effectively shift behavior among very vulnerable households in contexts with reduced compliance burdens, but also underscore an urgent need to rethink the role of higher-touch strategies in closing take-up gaps in social safety net programs.

Governments increasingly use randomized controlled trials (RCTs) to test innovations, yet we know little about how they incorporate results into policymaking. We study 30 US cities that ran 73 RCTs with a national nudge unit. Cities adopt a nudge treatment into their communications in 27% of the cases. We find that the strength of the evidence and key city features do not strongly predict adoption; instead, the largest predictor is whether the RCT was implemented using preexisting communication, as opposed to new communication. We identify organizational inertia as a leading explanation: changes to preexisting infrastructure are more naturally folded into subsequent processes.