Distributional Impacts of WIC on Child Dietary Quality: Evidence from a Regression Discontinuity Design

Monday, June 11, 2018: 8:20 AM
Oak Amphitheater - Garden Level (Emory Conference Center Hotel)

Presenter: Pourya Valizadeh

Co-Author: Travis Smith;

Discussant: Chelsea J. Crain


Poor dietary quality in childhood may impair growth and development and affect dietary behaviors in adulthood. Subsequently, longer-term poor nutrition is associated with major causes of cardiovascular disease, type 2 diabetes, and cancer. The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is designed to support the health and nutrition of low-income pregnant, postpartum, and breastfeeding women who are nutritionally at risk, as well as low-income infants and children. This study evaluates the causal impact of WIC on dietary quality of children, who comprise over half of all WIC participants. A major concern in evaluating the causal effect of the WIC program is the absence of a strong identification strategy. WIC participants self-select into the program and might be different than WIC non-participants in systematic ways, leading to biased estimates of the impact of the program.

In this study, we use an empirical strategy that allows us to make causal inferences pertaining to the impact of WIC on child dietary quality, as quantified by the Healthy Eating Index (HEI). According to federal WIC eligibility criteria, children can remain on WIC up to their fifth birthday. Using a regression discontinuity design (RDD), we exploit this age-related discontinuity in WIC participation and estimate changes in diet quality of children as they become age-ineligible for WIC. Like previous studies using alternative identification strategies, we find little impact of WIC on the average quality of diets.

When then ask, does WIC affect children who are prone to low-quality diets (perhaps due to parental or environmental factors) differently than those who are prone to higher-quality diets? That is, we take a distributional approach and allow for heterogeneous outcomes. Specifically, we use a fuzzy RDD within a quantile regression framework to estimate the impact of aging out of WIC at different points in the dietary quality distribution. Our data are drawn from the continuous waves of the National Health and Nutrition Examination Survey (NHANES), covering 1999-2014. Preliminary analysis indicates that the impacts of becoming age-ineligible for WIC are more detrimental for children falling in the lowest portion of diet quality distribution. This is a policy-relevant finding because WIC appears to have the largest benefits for children prone to the lowest quality diets.