Estimating the Associations between SNAP and Food Insecurity, Obesity, and Food Purchases with Imperfect Administrative Measures of Participation

Administrative data are considered the “gold standard” when measuring program participation, but little evidence exists on their potential problems or implications for econometric estimates. We explore these issues using the FoodAPS, a unique data set containing two different administrative measures...

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Bibliographic Details
Main Authors: Courtemanche, C. (Author), Denteh, A. (Author), Tchernis, R. (Author)
Format: Article
Language:English
Published: Wiley Blackwell 2019
Online Access:View Fulltext in Publisher
LEADER 01740nam a2200157Ia 4500
001 10.1002-soej.12364
008 220511s2019 CNT 000 0 und d
020 |a 00384038 (ISSN) 
245 1 0 |a Estimating the Associations between SNAP and Food Insecurity, Obesity, and Food Purchases with Imperfect Administrative Measures of Participation 
260 0 |b Wiley Blackwell  |c 2019 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1002/soej.12364 
520 3 |a Administrative data are considered the “gold standard” when measuring program participation, but little evidence exists on their potential problems or implications for econometric estimates. We explore these issues using the FoodAPS, a unique data set containing two different administrative measures of Supplemental Nutrition Assistance Program (SNAP) participation and a survey-based measure. We document substantial ambiguity in the two administrative measures and show that they disagree with each other almost as often as they disagree with self-reported participation. Estimated participation and misreporting rates can be meaningfully sensitive to choices made to resolve this ambiguity and disagreement. We explore sensitivity in regression estimates of the associations between SNAP and food insecurity, obesity, and the healthy eating index. The signs are unchanged across the three measures, and the estimates are mostly not statistically different from each other. However, there are some meaningful differences in the magnitudes and levels of statistical significance of the estimates. © 2019 by the Southern Economic Association 
700 1 |a Courtemanche, C.  |e author 
700 1 |a Denteh, A.  |e author 
700 1 |a Tchernis, R.  |e author 
773 |t Southern Economic Journal