During a presentation titled "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness, and Holes in the Safety Net," Meyer shared the findings of a study he conducted with Nikolas Mittag.
For the study, they combined data from the Current Population Survey (CPS)--the government's source of official poverty and inequality statistics--with New York administrative records for four public assistance programs to better measure the receipt of government transfers and the effect of the programs on reducing the nation's poverty rate. The studied programs are the Supplemental Nutrition Assistance Program (SNAP), more commonly called food stamps; Temporary Assistance for Needy Families (TANF); General Assistance; and Housing and Urban Development Housing Assistance.
Meyer is professor of economics in The University of Chicago's Harris School of Public Policy Studies; Mittag is assistant professor of economics at Charles University in Prague, Czech Republic.
The response rates of household surveys, which are the source of official rates of unemployment, poverty, health insurance coverage, inflation and other statistics that guide public-policy decisions, are in decline. Individuals have become reticent to answer surveys, and those who respond are less likely to answer certain questions or give accurate answers. To combat this worrying trend, federal statistical agencies are looking to administrative data as a way to maintain the quality of their survey products.
To obtain a better measure of government transfers to families in need, Meyer and Mittag linked household survey data from the New York state sample of the 2008-2013 Current Population Survey Annual Social and Economic Supplement with administrative records from the New York State Office of Temporary and Disability Assistance (OTDA) and administrative data on housing assistance programs under the U.S. Department of Housing and Urban Development's purview.
The former contained records of monthly payments from SNAP, TANF and General Assistance for all individuals in the state from 2007 through 2012. The latter contained data on all recipients of federal housing assistance such as addresses, number and ages of family members and rent paid by the tenant from April 2008 to March 2012. Administrative data were matched to the CPS survey data by the U.S. Census Bureau using social security numbers and provided to Meyer and Mittag without personal identifiers. The data were analyzed at a secure data center and the results were screened to prevent disclosure of personal information.
Their analysis identified widespread underreporting of social welfare program payments in the CPS household survey data and a significant understatement of the impact of these programs on reducing the nation's poverty rate. Meyer cited the following examples in his presentation:
More than one-third of housing assistance recipients did not report receipt. 40 percent of food stamp recipients underreported. 60 percent of TANF and General Assistance recipients did not report receipt. Government transfer payments from the four programs are underreported by more than $1,400 per person in the CPS. The four programs moved a much larger faction of people out of poverty than the CPS suggests: 5.3% found by the study versus 2.8% reported in the CPS. The four programs combined account for a 10 percentage point reduction and 18 percentage point reduction in the poverty rate of disabled and single mother-headed households, respectively. As a share of the baseline poverty rates for these two groups, reductions were approximately 50% in both cases, while the survey captured a 19% reduction in poverty for single mothers and a 30% reduction for the disabled. The study shows the poverty rate for the elderly was reduced by 38% versus the 24% reduction suggested by the CPS results. The overall safety net reaches far more people in need than CPS data suggest; the study shows the share of single mothers who neither work nor receive any cash transfers is overstated in the CPS by 50%.
The results show using administrative data combined with survey data sharply alters the picture of well-being at the bottom of the income distribution and the effects of transfer programs. "Inaccurate reporting has badly distorted the understanding of policymakers of income distribution, poverty and the effectiveness of federal government antipoverty programs," said Meyer.
"Correcting for misreporting sharply changes key results derived from only using survey data. By linking the survey and administrative data, poverty and inequality are better than officially reported, program effects are larger and fewer individuals have fallen through the public safety net."
Meyer added that although the study is limited to New York state, it is likely the results carry over to the entire country. "This study's findings on the importance of underreporting of SNAP benefits and the understatement of the value of public assistance almost certainly will apply to the rest of the United States," he said.
In making the case for linking administrative and survey data to improve policymaker opinions of poverty and inequality statistics, Meyer said: "The most productive step toward improving the quality of data available for social science research and policy decisions is to increase the availability of administrative data sets and find ways to link these to household survey data."
INFORMATION:
JSM 2015 is being held August 8-13 at the Washington State Convention Center in Seattle. More than 6,000 statisticians--representing academia, business and industry, as well as national, state and local governments--from numerous countries are attending North America's largest statistical science gathering.
About JSM 2015
JSM, which has been held annually since 1974, is being conducted jointly this year by the American Statistical Association (http://www.amstat.org), International Biometric Society (http://www.biometricsociety.org/) (ENAR [http://www.enar.org/] and WNAR [http://wnar.org/]) (http://www.biometricsociety.org/), Institute of Mathematical Statistics (http://imstat.org/en/index.html), Statistical Society of Canada (http://www.ssc.ca/en/whats-new), International Chinese Statistical Association (http://www.icsa.org/), International Indian Statistical Association (http://www.intindstat.org/), Korean International Statistical Society (http://www.statkiss.org/Home.php), International Society for Bayesian Analysis (http://bayesian.org/), Royal Statistical Society (https://www.rss.org.uk/), and International Statistical Institute (http://www.isi-web.org/). JSM activities include oral presentations, panel sessions, poster presentations, professional development courses, an exhibit hall, a career service, society and section business meetings, committee meetings, social activities and networking opportunities. Click here for more information about JSM 2015 (http://www.amstat.org/meetings/jsm/2015/index.cfm).
About the American Statistical Association
The ASA is the world's largest community of statisticians and the second-oldest continuously operating professional society in the United States. Its members serve in industry, government and academia in more than 90 countries, advancing research and promoting sound statistical practice to inform public policy and improve human welfare. For additional information, please visit the ASA website at http://www.amstat.org.
@AmstatNews
#JSM2015 END
