This interactive data visualization uses SNAP quality control data from fiscal year 2016 and microsimulation modeling to provide detailed information on the demographic characteristics of those at risk of losing benefits.
- Microsimulation modeling
- Data visualization
- Data quality
- Statistical analysis
- Human Services
- Nutrition and Food Assistance Programs
Sarah Lauffer specializes in data cleaning and analysis, working primarily with annual nutrition assistance data. She provides statistical programming support and leadership for tasks involving data manipulation and assessment.
Currently, Lauffer manages projects for the U.S. Department of Agriculture (USDA) involving the use of microsimulation to estimate how changes in Supplemental Nutrition Assistance Program (SNAP) policy would affect benefit costs, eligibility, and participation. The projects examine the characteristics of SNAP participants and estimate national and state rates of SNAP participation. As a task lead for USDA contracts, Lauffer has developed expertise in acquiring, validating, and modifying the annual SNAP Quality Control data file, which serves as the primary source for analyses and evaluations of SNAP caseloads.
Lauffer, who joined Mathematica in 2015, has authored annual reports on the characteristics of SNAP households and participants and assisted in drafting annual reports on trends in SNAP participation rates. She holds a B.A. in economics and public policy from the University of North Carolina.