Fact check: How does the employment rate of food stamp recipients vary by state?

1. Why state lines change the work picture: markets, waivers and thresholds

State-to-state differences in unemployment rates and waiver use create major variation in employment among SNAP recipients; places with higher unemployment grant more waivers, leaving larger shares of recipients outside work-requirement enforcement, while low-unemployment states more commonly require participation ^{[2] [3]}. Research modeling past recessions under new OBBBA-style thresholds finds many counties would not have met the 10 percent unemployment threshold until deep into recessions, producing uneven impacts across states and counties ^[3]. The result is that policy design interacts with local labor markets to produce the employment-rate differences observed.

2. How often SNAP participants work: competing national snapshots

National analyses give different headline numbers: one 2023 study shows over half of working-age, non-disabled SNAP participants worked in a typical month and 74 percent worked in the surrounding year, emphasizing fluid employment patterns and the program’s role in stabilizing workers ^[1]. Contrastingly, analyses from 2024–2025 report that an average of 38 percent of able-bodied adults on SNAP were employed between 2017–2019, with 62 percent not working in that period, and only 18 percent subject to work rules logging 20+ hours per week, producing a less rosy snapshot ^[5]. These divergent figures reflect differences in definitions, time windows, and populations measured.

3. Who is counted as “work-capable” and why that matters

Differences in employment rates hinge on who is labeled work-capable: many SNAP households include children, seniors, or people with disabilities, and national fact sheets show over 62 percent live in households with children and 37 percent include older adults or disabled people, meaning raw program totals overstate the pool subject to work rules ^[6]. Analyses warning about the effects of stricter work requirements note that caregivers, veterans, and homeless individuals would be disproportionately affected, illustrating that demographics and caregiving responsibilities shape apparent employment rates across states ^{[4] [7]}.

4. Timing and measurement: monthly vs. annual work and policy implications

Studies measuring employment in a single month versus a 12‑month window produce different conclusions; monthly snapshots undercount episodic employment common among low-income workers, while annual measures capture temporary jobs, seasonal work, and churn that show higher cumulative employment. The 2023 finding that 74 percent worked within a year versus the 38 percent monthly employment figure highlights this measurement effect and explains much of the seeming contradiction ^{[1] [5]}. Policy debates that use only one measure risk mischaracterizing the labor-market engagement of SNAP recipients.

5. Policy proposals, time limits, and uneven state impact

Recent reporting and modeling of new SNAP time-limit proposals indicate that stricter federal work rules would disproportionately hit certain states and vulnerable groups, because state unemployment patterns, waiver application, and fiscal choices determine who loses benefits ^{[2] [4]}. Historical simulations applying OBBBA rules to the Great Recession show many counties would have failed the unemployment threshold for waivers for long periods, meaning states with weaker labor markets would have seen larger benefit losses, magnifying geographic inequality in employment and food security ^[3].

6. Political and fiscal responses that reshape state outcomes

States sometimes step in to mitigate federal shortfalls; recent events in late 2025 show several states using state funds to continue SNAP-like assistance during federal funding gaps, an action that temporarily alters the employment/benefit picture and demonstrates that state political choices and budget capacity affect how employment rates among recipients translate into benefit receipt ^[8]. Governors’ decisions to extend aid, or to implement stricter eligibility locally, create variance in observed employment rates tied to program participation rather than labor-market behavior.

7. Bottom line: heterogeneity and what’s omitted from simple claims

The accurate takeaway is that state-level employment rates among SNAP recipients are heterogeneous because of labor markets, measurement windows, demographic composition, waiver rules, and state policy responses; single statistics (e.g., “38% employed” or “most work-capable work”) omit these contexts and thus can mislead ^{[1] [5] [2]}. Evaluations should use comparable definitions, report monthly and annual measures, and account for exemptions and state-level policies to portray how employment among SNAP recipients truly varies across states ^{[6] [3]}.