Abstract: How Does Raising the Minimum Wage Affect SNAP Participation? Evidence from Washington State Administrative Data (Society for Social Work and Research 27th Annual Conference - Social Work Science and Complex Problems: Battling Inequities + Building Solutions)

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How Does Raising the Minimum Wage Affect SNAP Participation? Evidence from Washington State Administrative Data

Schedule:
Sunday, January 15, 2023
Laveen B, 2nd Level (Sheraton Phoenix Downtown)
* noted as presenting author
Callie Freitag, MA, MS, PhD Candidate, University of Washington, Lynnwood, WA
Jennifer Romich, PhD, Associate Professor, University of Washington, Seattle, WA
Elizabeth Pelletier, MA, MS, PhD Student, University of Washington, WA
Heather Hill, PhD, Associate Professor, University of Washington, Seattle, WA
Scott Allard, PhD, Professor, University of Washington, Seattle, WA
Background and Purpose: In 2014, the Seattle City Council voted to raise the minimum wage from $9.47 per hour to $15 per hour over three years (2015-2017). Yet, many low-income workers combine earnings with means-tested benefits like the Supplemental Nutrition Assistance Program (SNAP), which decreases when earnings increase, to make ends meet. We examine how raising Seattle’s minimum wage between 2015 and 2017 affected SNAP receipt. We hypothesize that raising the minimum wage could affect SNAP use in two ways: (1) workers might earn more, resulting in decreased or a total loss of benefits, or (2) employers might eliminate jobs, leading to newly unemployed workers claiming SNAP. Both possibilities raise important issues for policymakers and undermine key goals of raising the minimum wage.

Methods: Data and Samples: We use linked administrative data from multiple Washington state agencies to construct a two longitudinal cohorts of low-wage Washington workers and benefit users (2010-2017). In the first cohort, we select workers earning below $13 per hour in Seattle in the first quarter of 2015. For the second cohort, we only look at workers in the first cohort who were also using SNAP in the first quarter of 2015. For both cohorts, we use the same strategy to identify treatment and control groups. “Treated” workers are those working in Seattle in the first quarter of 2015. The comparison groups for each cohort are workers in Washington state outside of Seattle, selected using nearest-neighbor and exact matching to minimize observable differences.

Analytic Approach: We take a triple-difference estimation strategy using logistic regression to estimate the causal effect of Seattle’s minimum wage increases on SNAP usage. We also conduct a path analysis to determine if changes in SNAP usage were driven by changes in employment or earnings.

Results: Our preliminary triple difference results suggest that the Seattle minimum wage increases reduced SNAP participation among treated workers, though the estimated effects are less pronounced than simple difference-in-difference estimates suggest. The differences in the strength of results for the low-wage worker and SNAP worker cohorts suggests two possibilities: that the general population of low-wage workers and the SNAP-using population of low-wage workers are differently affected by increases to the minimum wage, or that the household size matching strategy used to create the SNAP worker cohort eliminates a critical source of bias in the effect estimates. Both possibilities are likely. We anticipate our sensitivity and path analyses will provide insights into the mechanisms driving SNAP loss following a higher minimum wage.

Conclusions and implications: Our overall findings suggest that for low-wage workers who use means-tested benefits like SNAP, raising the minimum wage achieves a key policy goal of transitioning workers from public assistance to earnings. Policymakers considering raising the minimum wage should also consider a complementary set of policies raising income eligibility for means-tested programs to ensure low-income families do not lose essential resources for making ends meet.