Identifying the Effects of SNAP (Food Stamps) on Child Health Outcomes When Participation Is Endogenous and Misreported

Abstract

The literature assessing the efficacy of the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp Program, has long puzzled over positive associations between SNAP receipt and various undesirable health outcomes such as food insecurity. Assessing the causal impacts of SNAP, however, is hampered by two key identification problems: endogenous selection into participation and extensive systematic underreporting of participation status. Using data from the National Health and Nutrition Examination Survey (NHANES), we extend partial identification bounding methods to account for these two identification problems in a single unifying framework. Specifically, we derive informative bounds on the average treatment effect (ATE) of SNAP on child food insecurity, poor general health, obesity, and anemia across a range of different assumptions used to address the selection and classification error problems. In particular, to address the selection problem, we apply relatively weak nonparametric assumptions on the latent outcomes, selected treatments, and observed covariates. To address the classification error problem, we formalize a new approach that uses auxiliary administrative data on the size of the SNAP caseload to restrict the magnitudes and patterns of SNAP reporting errors. Layering successively stronger assumptions, an objective of our analysis is to make transparent how the strength of the conclusions varies with the strength of the identifying assumptions. Under the weakest restrictions, there is substantial ambiguity; we cannot rule out the possibility that SNAP increases or decreases poor health. Under stronger but plausible assumptions used to address the selection and classification error problems, we find that commonly cited relationships between SNAP and poor health outcomes provide a misleading picture about the true impacts of the program. Our tightest bounds identify favorable impacts of SNAP on child health.

Food Insecurity, Neighborhood Food Access, and Food Assistance in Philadelphia

“…25 In addition, prior research suggests that individuals do not reliably disclose whether they participate in SNAP on surveys, meaning our analysis likely underestimates true rates of food assistance coverage. 26,27 Those receiving WIC, or both SNAP and WIC, had similar odds of food insecurity to those receiving no food assistance. There are several possible interpretations of this finding.…”

Food insecurity and housing instability in vulnerable families

“…Consequently, cuts in the program, through budget decreases or termination of eligibility, before the economy recovers would lead to families experience even greater hardships. Examining the effectiveness of SNAP, Kreider et al (2012) argue that findings from previous studies of deleterious impacts of the SNAP program on health are driven by the endogeneity and misreporting of SNAP participation. Using a partial identification bounding methods, they find that the program at least alleviates food security and poor health outcomes.…”

Partial identification of the long-run causal effect of food security on child health

“…The probabilities are conditioned on observed covariates denoted by X 2 with values in the set . In this approach, conditioning on covariates only helps to de…ne subpopulations of interest (Kreider et al 2012). For notational simplicity, X 2 is dropped in the following derivations.…”

“…The nonparametric partial identi…cation method of Kreider et al (2012) provides sharp bounds on the average treatment e¤ect (ATE) of very low food security when food security is non-random and potentially measured with error. These bounds require weaker assumptions than those of an instrumental variable (IV), classical measurement error, or linear response model while addressing both selection and measurement error in food security status.…”

“…In the …rst stage, we assess the nature of selection into food insecurity status. In the second stage, we use the nonparametric partial identi…cation method proposed in Kreider et al (2012) to account for both non-random selection and measurement error in food security status in a single unifying framework. We then turn to a younger sample of children obtained from the Early Childhood Longitudinal Study -Birth Cohort (ECLS-B).…”