Take-up and Targeting

Matt Notowidigdo (Northwestern)

Abstract:

We develop a framework for welfare analysis of interventions designed to increase take-up of social safety net programs in the presence of potential behavioral biases. We calibrate the key parameters using a randomized field experiment in which 30,000 elderly individuals not enrolled in – but likely eligible for – the Supplemental Nutrition Assistance Program (SNAP) are either provided with information that they are likely eligible, provided with this information and also offered assistance in applying, or are in a “status quo” control group. Only 6 percent of the control group enrolls in SNAP over the next 9 months, compared to 11 percent of the Information Only group and 18 percent of the Information Plus Assistance group. The individuals who apply or enroll in response to either intervention receive lower benefits and are less sick than the average enrollee in the control group. We present evidence consistent with the existence of optimization frictions that are greater for needier individuals, which suggests that the poor targeting properties of the interventions reduce their welfare benefits.