%0 Report %1 meyer2017using %A Meyer, Bruce D. %A Mittag, Nikolas %C Bonn %D 2017 %K socdes statistik %N 10943 %T Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net %U https://www.iza.org/publications/dp/10943/using-linked-survey-and-administrative-data-to-better-measure-income-implications-for-poverty-program-effectiveness-and-holes-in-the-safety-net %X We examine the consequences of underreporting of transfer programs in household survey data for several prototypical analyses of low-income populations. We focus on the Current Population Survey (CPS), the source of official poverty and inequality statistics. We link administrative data for food stamps, TANF, General Assistance, and subsidized housing from New York State to the CPS at the household level. Program receipt in the CPS is missed for over one-third of housing assistance recipients, over 40 percent of food stamp recipients and over 60 percent of TANF and General Assistance recipients. Dollars of benefits are also undercounted for reporting recipients, particularly for TANF, General Assistance and housing benefits. We find that the survey sharply understates the income of poor households. Underreporting in the survey data also greatly understates the effects of anti-poverty programs and changes our understanding of program targeting, often making it seem that welfare programs are less targeted to both the very poorest and middle-income households than they are. Using the combined data rather than survey data alone, the poverty reducing effect of all programs together is nearly doubled while the effect of housing assistance is tripled. We also re-examine the coverage of the safety net, specifically the share of people without work or program receipt. 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.

@techreport{meyer2017using, abstract = { We examine the consequences of underreporting of transfer programs in household survey data for several prototypical analyses of low-income populations. We focus on the Current Population Survey (CPS), the source of official poverty and inequality statistics. We link administrative data for food stamps, TANF, General Assistance, and subsidized housing from New York State to the CPS at the household level. Program receipt in the CPS is missed for over one-third of housing assistance recipients, over 40 percent of food stamp recipients and over 60 percent of TANF and General Assistance recipients. Dollars of benefits are also undercounted for reporting recipients, particularly for TANF, General Assistance and housing benefits. We find that the survey sharply understates the income of poor households. Underreporting in the survey data also greatly understates the effects of anti-poverty programs and changes our understanding of program targeting, often making it seem that welfare programs are less targeted to both the very poorest and middle-income households than they are. Using the combined data rather than survey data alone, the poverty reducing effect of all programs together is nearly doubled while the effect of housing assistance is tripled. We also re-examine the coverage of the safety net, specifically the share of people without work or program receipt. 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.}, added-at = {2018-02-27T10:56:41.000+0100}, address = {Bonn}, author = {Meyer, Bruce D. and Mittag, Nikolas}, biburl = {https://www.bibsonomy.org/bibtex/2b44e7fad716e3ad6ce41d9835d6428f1/dirtyhawk}, institution = {IZA Institute of Labor Economics}, interhash = {0bf0a711f462b50d6308e33f74f0c536}, intrahash = {b44e7fad716e3ad6ce41d9835d6428f1}, keywords = {socdes statistik}, month = {08}, number = 10943, timestamp = {2018-09-19T18:10:30.000+0200}, title = {Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net}, type = {IZA Discussion Paper}, url = {https://www.iza.org/publications/dp/10943/using-linked-survey-and-administrative-data-to-better-measure-income-implications-for-poverty-program-effectiveness-and-holes-in-the-safety-net}, urldate = {2018-02-27}, year = 2017 }