Evidence map›Paper›PMID 41583537›Full record

ArticlePopulation research and policy review2026

Do Larger Earned Income Tax Credit and Supplemental Nutrition Assistance Program Benefits Create Complementary Effects on Child Development?

Youngjin Stephanie Hong

Abstract read
In one paragraph

Article in Population research and policy review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Youngjin Stephanie HongDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, WI USA.ORCID 0009-0006-7479-4765

Funding

Health Disparities Research Scholars Training Program-RenewalT32HD049302 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI Maureen S Durkin · 2007 to 2026
$5.6M
NICHD NIH HHS T32 HD049302
6 · The paper itself

Abstract

Poverty is particularly concerning during early childhood and the early school years, as it can negatively impact child development both in the short and long term. To alleviate economic hardship, the U.S. government provides a patchwork of income support policies. This paper examines two of the largest programs, the Supplemental Nutrition Assistance Program (SNAP) and the Earned Income Tax Credit (EITC), which low-income working families often receive simultaneously. This paper is the first to explore whether these benefits interact to influence children's early cognitive development in families receiving both programs. To address endogeneity of program benefits, I use a two-way (child and year) fixed effects model to leverage the variation in the maximum federal and state EITC benefits stemming from changes in the number of children and state EITC policies, as well as the variation in SNAP purchasing power driven by local food prices over time within each child, rather than actual benefit amounts. Using data from the Early Childhood Longitudinal Study-Birth Cohort (which tracks a nationally representative 2001 birth cohort through the kindergarten-entry period), I find new population-level evidence that EITC benefits are effective at improving early math and reading skills when coupled with greater SNAP purchasing power, and vice versa (sample size = 1300). Suggestive evidence is provided on the mechanisms underlying such complementary effects on early cognitive outcomes. The findings highlight the importance of enhancing the reach and generosity of both programs. Supplementary Information: The online version contains supplementary material available at 10.1007/s11113-025-09985-9.

Indexed as

Early cognitive developmentEITCMultiple program participationPovertySafety netSNAPWorking poor

Identifiers

PMID41583537
PMCPMC12827319

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.