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SNAP is the cornerstone of the nutrition safety net. Mathematica has been working alongside the U.S. Department of Agriculture’s Food and Nutrition Service (FNS) for more than four decades to develop and use microsimulation modeling to support FNS as it assesses proposed changes to SNAP policy, develops annual budgets, and conducts supporting research. Important questions arise when changes to SNAP policy are proposed, including how the proposed change is estimated to affect program costs, SNAP participation and eligibility, and the characteristics of the SNAP caseload. To answer these quick-response requests, Mathematica uses microsimulation modeling to produce simulations and tabulations that help inform the debate over proposed changes to SNAP and enable policymakers to better understand the populations potentially affected by such changes.

Under this project, Mathematica provides quick response analyses and technical support, prepares the annual SNAP Quality Control (SNAP QC) data file, maintains and enhances FNS’s SNAP microsimulation models, and produces annual reports on the characteristics of SNAP households and national and state SNAP participation rates. In addition to these core tasks, Mathematica provides a variety of services as requested by FNS. These have included the following:

• Examining the impact of the reengineered Survey of Income and Program Participation (SIPP) on the MATH SIPP+ microsimulation model. Assessing the quality of the asset data and imputations for low-income households in the 2014 SIPP.
• Examining the characteristics of elderly people participating in or eligible for SNAP and producing detailed state SNAP participation rates for elderly people.
• Convening an expert panel to identify and prioritize research needs related to simulating SNAP eligibility, specifically by the use of Census Bureau survey data linked with state SNAP administrative data. Assessing the quality of and standardizing state administrative data files held by the Census Bureau. Using linked survey and administrative data to improve SNAP eligibility simulations.
• Analyzing the degree of underreporting of program participation for school-age children in households receiving housing assistance, energy assistance, or both compared with those in households receiving SNAP, Temporary Assistance for Needy Families (TANF), and/or Medicaid benefits.
• Providing support for statistical questions and data analysis for the SNAP QC system. Estimating fiscal year 2017 payment error rates for states that FNS found had bias in their SNAP QC system during the fiscal year 2017 review period.