This report explores how public benefit systems can better support young adults by addressing the barriers they face in accessing and maintaining vital services like SNAP, Medicaid, and WIC.
This report offers a detailed assessment of how AI and emerging technologies could impact the Social Security Administration’s disability benefits determinations, recommending guardrails and principles to protect applicant rights, mitigate bias, and promote fairness.
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.
The goal of the brief is to encourage policy makers and employers to consider benefits cliffs as they look to create mandatory wage increases, with a look at a legislative action in NYC.
Data provided by the NYC Mayor’s Office for Economic Opportunity regarding benefit, program, and resource information for over 80 health and human services available to NYC residents in all eleven local law languages.
A modernized public benefits system would better serve program participants, administrators, policy makers, and taxpayers. This paper proposes a set of principles both define the desired future state and outline the values that shape decision making along the way. Practices describe the processes needed to achieve modernization.
This Urban Institute report examines how public investments in children's health, education, and welfare yield significant short- and long-term benefits for both individuals and society.
PolicyEngine is a nonprofit that provides a free, open-source web app enabling users in the US and UK to estimate taxes and benefits at the household level, while also simulating the effects of policy changes. By combining tax and benefits data, PolicyEngine helps individuals and policymakers better understand the impacts of existing policies and proposed reforms, using microsimulation models built from legislation and enhanced survey data.
Benefits Data Trust (BDT) is a nonprofit that connects people to public benefits through a streamlined, phone-based application system called Benefits Launch, which reduces redundant questions and speeds up the process for multiple programs. BDT's approach, supported by a custom-built rules engine, has facilitated over 800,000 benefit enrollments, helping secure over $9 billion for eligible households across seven states.
Professor Don Moynihan discusses how administrative burden is an effective tool to make it difficult for people to access certain types of benefits, noting that this is particularly harmful to communities of color.
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.
