Federal Social Safety Nets, Single-Mother Households, and Children’s Grade Repetition

Loading...
Thumbnail Image

Date

2016-01-26

Advisors

Gassman-Pines, Anna

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats

238
views
272
downloads

Abstract

Children from single-mother households face increased risks of poverty and poor academic outcomes. This analysis used the National Survey of Children’s Health 2011-2012 data set to examine the correlation between federal social safety net programs – namely SNAP, TANF, and Medicaid/SCHIP – for U.S. single-mother households under the poverty line, and children’s grade repetition. Given the income support and increased access to resources that federal benefits provide, this analysis hypothesized that more receipt of federal benefits would correlate with lower chances of grade repetition. Results from a t-test and a logistic regression were contrary to the hypothesis, and instead suggested that receiving more benefits is associated with greater probability of grade repetition. Selection bias in federal benefit recipients may explain these results, as those who face more poverty may use more federal benefits, and the same poverty depth may contribute to worse child outcomes. When analyzing how each benefit correlated with grade repetition, this analysis found that receipt of public or private healthcare insurance was consistently associated with lower probabilities of grade repetition at marginally statistically-significant levels even after controlling for a broad set of covariates. This result provides encouraging insight into the positive connection between healthcare receipt and child academic outcomes.

Description

Provenance

Citation

Citation

Colorado, Stephanie (2016). Federal Social Safety Nets, Single-Mother Households, and Children’s Grade Repetition. Honors thesis, Duke University. Retrieved from https://hdl.handle.net/10161/11539.


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.