The National School Lunch Program Direct Certification Improvement Study: Analysis of Unmatched Records (Summary)

Quinn Moore, Andrew Gothro, Kevin Conway and Brandon Kyler

Mathematica Policy Research Reports from Mathematica Policy Research

Abstract: An analysis of National School Lunch Program (NSLP) application records and state Supplemental Nutrition Assistance Program (SNAP) participation data revealed characteristics of school-age SNAP participants who are less likely to be matched in direct certification data matching processes. Children with long, uncommon names are less likely to be matched using restrictive deterministic algorithms. These name characteristics correlate with student race and ethnicity, suggesting deterministic matching algorithms might lead to divergent access to school meal benefits by race and ethnicity.

Keywords: SNAP; NSLP; National School Lunch Program; Direct Certification; data matching; deterministic; probabilistic; Nutrition (search for similar items in EconPapers)
Date: 2014-08-29
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