An interview with Wendy De La Rosa, assistant professor at the Wharton School at the University of Pennsylvania. De La Rosa discusses how the concept of “psychological ownership” can encourage people to take up benefits they are eligible for.
The IRS is arguably the single most critical benefits administrator in the country, given its responsibility for tax credit-based relief programs, and COVID-19 relief payments. Despite these programs’ incredible progress in reducing poverty, and despite great strides by the IRS to implement them successfully, accessing IRS benefits remains too difficult for many low-income families. This report presents a comprehensive agenda to increase benefit coverage rates, simplify Americans’ interactions with the IRS, and decrease the portion of IRS benefits diverted to third parties.
The Texting Playbook provides guidance and well-researched strategies to help state agencies implement texting in support of Medicaid, SNAP, WIC, and other benefits programs. It provides an overview of how to start texting clients; the types of messages to send, including real examples; Federal Communications Commision (FCC) policy guidance; how to encourage opt-ins and collect consent; how to avoid coming across as spam; and a cost analysis of texting.
This landscape analysis examines data, design, technology, and innovation-enabled approaches that make it easier for eligible people to enroll in, and receive, federally-funded social safety net benefits, with a focus on the earliest adaptations during the COVID-19 pandemic.
The Urban Institute's report outlines actionable approaches for state governments and organizations to enhance the accessibility and retention of public benefit programs, focusing on service delivery, policy reforms, and technological advancements.
This article examines how applying a Racial Equity Framework reveals systemic inequities in the Earned Income Tax Credit (EITC) program, offering insights into barriers faced by marginalized communities and potential solutions.
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.
The Policy Rules Database (PRD), developed by the Federal Reserve Bank of Atlanta and the National Center for Children in Poverty, consolidates complex rules for major U.S. federal and state benefit programs and tax policies into a standardized, easy-to-use format. This database allows researchers to model public assistance impacts, simulate policy changes, and analyze benefits cliffs across various household scenarios using common rules and language across different programming platforms.
MITRE developed the Comprehensive Careers and Supports for Households (CCASH™) tool to help individuals understand and manage federal benefits and employment services, transitioning from a consumer-focused tool to a policy analytics system. By integrating data from sources like the U.S. Census and the Policy Rules Database, MITRE created a model that allows users to analyze and compare benefits eligibility across states, supporting evidence-based policymaking.
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.
The NYC Mayor’s Office for Economic Opportunity (NYC Opportunity) developed the NYC Benefits Platform, including ACCESS NYC, to help residents easily discover and check eligibility for over 80 social programs.
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.
