Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness, and Holes in the Safety Net

• Activity Number: 57
• Type: Invited
• Date/Time: Sunday, August 9, 2015 : 4:00 PM to 5:50 PM
• Sponsor: Government Statistics Section
• Author(s): Bruce Meyer* and Nikolas Mittag
• Companies: Harris School and CERGE-EI/Charles University
• Keywords: Poverty ; Measurement Error ; Administrative Data ; Misreporting

Abstract

We examine the consequences of underreporting of transfer programs in household survey data for prototypical analyses of low-income populations. We link administrative data for food stamps, TANF, General Assistance, and subsidized housing from New York State to the Current Population Survey (CPS) at the individual level. Program receipt in the CPS is missed for over one-third of housing assistance recipients, 40 percent of food stamp recipients and 60 percent of TANF and General Assistance recipients. Dollars of benefits are also undercounted for reporting recipients. We find that the survey data sharply understate the income of poor households. Underreporting in the survey data also severely understates the effects of anti-poverty programs and changes our understanding of program targeting. Using the administrative data, the poverty reducing effect of all programs combined is nearly doubled while the effect of housing assistance is tripled. We also re-examine the coverage of the safety net, finding that using the administrative measures of program receipt rather than the survey ones often reduces the share of single mothers falling through the safety net by one-half or more.