Poverty in the United States Using the Comprehensive Income Dataset

• Activity Number: 491 - Methodology and Utilization of Administrative Data
• Type: Contributed
• Date/Time: Thursday, August 6, 2020 : 10:00 AM to 2:00 PM
• Sponsor: Government Statistics Section
• Author(s): Derek Wu* and Bruce Meyer and Carla Medalia
• Companies: University of Chicago, Harris School of Public Policy and University of Chicago, Harris School of Public Policy and U.S. Census Bureau
• Keywords: Poverty; Data Linkage; Measurement Error; Administrative Data; Government Transfers; Income Distribution

Abstract

This paper provides new estimates of poverty in the U.S. using a groundbreaking set of linked survey and administrative data. The administrative data cover earnings, asset, and retirement income from IRS tax records, as well as transfer income for a myriad of safety net programs including Social Security, SSI, SNAP, housing assistance, and veterans’ benefits. We link these data to the CPS (the source of official poverty and inequality statistics) and the SIPP (the most comprehensive survey of income sources in the U.S.). Linking the administrative data to the surveys is vital given that surveys miss a large and rising share of income. Using the linked data, we find that 55% fewer individuals are in poverty after incorporating taxes and in-kind transfers and correcting for measurement error. We observe a demographic shift in the composition of the poor, with our adjustments leading to significantly more single individuals and fewer families with children in poverty. These estimated reductions in poverty are partly due to surveys underestimating the value of the anti-poverty effects of government programs like SNAP, the EITC, housing assistance, and SSI.