Association for Public Policy Analysis & Management

We investigate the relationship between the Supplemental Nutrition Assistance Program (SNAP), and the National School Lunch Program (NSLP). We examine how SNAP and the timing of SNAP payments affects participation in school lunch, and children’s food consumption in and outside of school. To be precise, we explore how school lunch might ameliorate the decline in food consumption at the end of the SNAP benefit cycle. To do so, we use rich and detailed data on individuals, households, and food acquisitions from FoodAPS.

We identify children in SNAP and non-SNAP households, and calculate the number of days since SNAP payment for each day in the FoodAPS week. FoodAPS collects detailed data on food acquisitions and purchases for all members of participating households during seven days. Our empirical strategy takes advantage of the timing of FoodAPS data collection relative to the SNAP payment cycle. We select a sample of children in households that received SNAP payments during the data collection week, allowing us to compare food acquisitions and lunch participation right at the end and at the beginning of the SNAP payment cycle. This strategy yields unbiased estimates if the timing of SNAP payments within the data collection window is random. Further, in most states the date of SNAP benefit receipt is assigned based on the social security number, case number, or first letter of recipient’s last name, and so it is plausibly random. We also investigate differences in the effect of SNAP payments on lunch participation during the summer months, when school is not in session

We use various measures of lunch participation (at school, any lunch, outside of school) and other meal acquisitions (snacks and breakfast). We also construct the healthy eating index (HEI) to investigate variations in diet quality before and after SNAP payments. Finally, we explore heterogeneity in the relationship between SNAP and school lunch by gender, race/ethnicity, age, and school level. Results from this paper will contribute to our understanding of how households use SNAP and school lunch at different times of the SNAP payment cycle, and provide insights into whether there is substitution between the two programs.