Panel: Using Administrative Data for SNAP Policy Research
(Poverty and Income Policy)

Saturday, November 10, 2018: 8:30 AM-10:00 AM
8222 - Lobby Level (Marriott Wardman Park)

*Names in bold indicate Presenter

Panel Chairs:  Agustina Laurito, University of Illinois, Chicago
Discussants:  Jonathan Cantor, RAND Corporation and Laura Wheaton, Urban Institute


The Poverty Reduction Due to Social Security and Means-Tested Transfers
Bruce Meyer and Derek Wu, University of Chicago



Program Recertification Costs: Evidence from SNAP
Tatiana Homonoff, New York University and Jason Somerville, Cornell University



Long Run Effects of Food Assistance and Early Human Capital Programs
Theodore Figinski, U.S. Department of the Treasury and Marianne P. Bitler, University of California, Davis


This panel includes four papers which leverage the use of administrative data to answer a wide variety of policy questions related to the Supplemental Nutritional Assistance Program (SNAP) as well as other means-tested programs. The first two papers use survey data linked to administrative data sets to determine the effect of self-reporting of outcome measures on policy estimates; the second two papers use administrative data sets to estimate determinants of SNAP participation and subsequent impacts of the program. The first paper considers the sensitivity of estimates of the impact of SNAP on food consumption – food spending, diet quality, and food security – to reporting errors using household survey data linked to administrative records of SNAP participation in the FoodAPS data set. The second paper links administrative Social Security data to survey data from the SIPP to estimate the effect of several means-tested programs on poverty reduction. The third paper uses administrative data from San Francisco’s CalFresh program to determine the effect of seemingly trivial recertification components – specifically, the randomly assigned recertification interview date – on continued program participation. The fourth paper uses administrative data on earnings and SSI linked to county-level program roll-out data to determine the long-run effect of SNAP and Head Start.


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