Resources and Toolkits

Common policy missteps states may take in efforts to reduce SNAP payment error rates (PERs), such as adopting change reporting, imposing asset tests, or limiting discretionary exemptions, can have unintended effects of increasing error rates. Instead, states should make informed policy choices, such as adopting simplified reporting, waiving asset tests, allowing discretionary exemptions, and implementing…

Workshop examining how predictive analytics and risk scoring can improve SNAP implementation and evaluation, using Conneticut as a case study.

Guidance on state policy chocies that tend to increase SNAP payment error rates include requiring change reporting or monthly reporting, imposing asset tests, and limiting discretionary exemptions. In contrast, states can reduce errors by simplifying reporting requirements, using BBCE, applying exemptions, and using one-month lookbacks to minimize reassessments and ensure coverage for eligible populations.

Workshop to foster collaboration and share modeling practices among state agencies in response to HR1’s new SNAP PER cost share requirements. Gathering encompassed convened a group of nearly 40 research and data analytics staff from across 15 states involved in SNAP QC data modeling.

Key strategies to improve accuracy and efficiency of SNAP program delivery, including evaluating intervention impacts independently, developing strong proxy metrics, watching for unintended consequences, strategically reviewing most error-prone case elements and actions, leveraging new technology for caseworkers, and improving client communication and outreach.