This report details findings and lessons from a project to develop a calculator to help people anticipate how a change in earnings from employment would affect their net income and information on their estimated effective marginal tax rate.
U.S. Department of Health and Human Services (HHS)
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.
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.
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.
The team introduced an AI assistant for benefits navigators to streamline the process and improve outcomes by quickly assessing client eligibility for benefits programs.
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 report examines how the U.S. federal government can enhance the efficiency and equity of benefit delivery by simplifying eligibility rules and using a Rules as Code approach for digital systems.
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 guide consolidates learning and spotlights principles, insights, and emerging practices to guide municipal leaders and public-private partnerships interested in designing basic income programs that are ethical, equitable, rigorous, informative, and consequential for local, state and national 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 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.
This explores how tax credit systems can be redesigned to better meet the needs of families, especially those facing systemic barriers to filing and receiving benefits.
