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.
This resource allows policymakers, employers, benefits providers, and researchers assess benefits performance for constituents and identify opportunities in market and policy innovation to ensure equitable benefits distribution.
This study examines how providing information about administrative burden influences public support for government programs like TANF, showing that awareness of these burdens can increase favorability toward the programs and their recipients.
This guide provides practical insights for benefits administrators on redesigning benefits systems using human-centered design to ensure all eligible residents can access crucial social safety net resources.
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.
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.
ACCESS NYC is an online public screening tool that residents can use to determine the City, State, and Federal health and human service benefit programs for which they are eligible.
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.
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.
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.
