An opportunity to join our fantastic research team at the California Department of Social Services!
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Many thanks to the data curation team at ICPSR for helping make this data available and user-friendly
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This dataset is for researchers, policymakers, and anyone interested in how SNAP works.
Let me know how you use it — or if you’re interested in building on this work!
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For example, the new county-level enrollment data includes enrollment across all calendar months, rather than just January and July.
And the new state-level enrollment data contains more detailed information, subject to state availability.
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I compiled enrollment data from individual state websites, which is often more comprehensive and detailed than enrollment data from USDA’s SNAP Data Tables.
www.fns.usda.gov/pd/supplemen...
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This dataset release includes:
✅ Monthly state-level SNAP policy data (Mar 2020–Jun 2023)
✅ County-level enrollment figures
✅ State-level enrollment details, including breakdowns by apps, recerts, and demographics for select states
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States increased benefit amounts, simplified application & recertification processes, and extended certification periods through policy waivers.
And we now have the data to study all of this in depth.
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Why does this matter?
SNAP enrollment remained elevated for years following COVID-19. An important question is: why?
Was it the economy, or the new policies?
This data — and my analysis — shows: it was mostly *policy*
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I compiled a comprehensive dataset capturing these pandemic-era SNAP changes across states and over time.
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Between 2020–2023 in response to COVID-19, the U.S. overhauled how the Supplemental Nutrition Assistance Program (SNAP) worked — more benefits, simplified enrollment processes, and huge policy flexibility for states.
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🚨 🚨 New dataset 🚨 🚨
I'm excited to share a new dataset + companion paper covering SNAP policy changes & enrollment data, with a focus on COVID-19-era reforms.
📊https://www.icpsr.umich.edu/web/sbeccc/studies/39331
📄https://kelseypukelis.com/files/Pukelis_SNAPcovid.pdf
A thread🧵
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