This webpage provides state agency resources and policy memos detailing how the One Big Beautiful Bill Act (H.R. 1) of 2025 affects SNAP implementation.
This report catalogs the policy choices, demonstration projects, and waivers each state uses to administer SNAP, highlighting how states adapt federal rules to local needs.
Created for use in the Digital Doorways research project, this design stimuli shows the steps of submitting an application, sharing personal information, and verifying identity for Arizona's integrated online application that includes SNAP and Medicaid.
Created for use in the Digital Doorways research project, this design stimuli shows the steps of submitting an application, sharing personal information, and verifying identity for Massachusetts' online application for SNAP benefits.
This blog analyzes how the One Big Beautiful Bill Act (OBBBA) will dramatically shift SNAP costs onto state governments, projecting massive budget increases and fiscal strain.
Innovators inside and outside of government are working to improve access to the social safety net using data, technology, and design. This report highlights innovations carried out by The Rockefeller Foundation’s Data and Technology grantees from 2018 to 2021, including extraordinary efforts to meet the challenges of the pandemic. Those grantees are: Benefits Data Trust, Code for America, Georgetown University’s Beeck Center for Social Impact and Innovation, U.S. Digital Response, and the Digital Innovation and Governance Initiative at New America. In 2020, these projects secured more than $200 million in benefits for close to 100,000 people across at least 36 states, and helped millions more through policy change, training, and guidance.
This paper describes results from fieldwork conducted at a social services site where the workers evaluate citizens' applications for food and medical assistance submitted via an e-government system. These results suggest value tensions that result - not from different stakeholders with different values - but from differences among how stakeholders enact the same shared value in practice.
CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
PolicyEngine US is a Python-based microsimulation model of the US tax and benefit system. It models federal individual income taxes (including credits), major benefit programs, and state income taxes (currently in six states). The PolicyEngine US package can be used as a Python package, via the PolicyEngine API, or via the policyengine.org web app.
Applicants to federal aid programs face numerous barriers in accessing benefits they are eligible for. The Centers for Medicaid and Medicare conducted an extensive qualitative user research study to better understand applicant experience in enrolling in public assistance programs. Based on the results, the study emphasizes the need for simplified, streamlined and less burdensome application processes.
Github repository for Policy Rules Database, which encodes up-to-date rules and provisions for all major federal and state public assistance programs, taxes, and tax credits.
In this report, the U.S. Chamber of Commerce Foundation examines benefits cliffs – the loss of eligibility for public safety-net programs and benefits they provide as income rises above eligibility limits.
