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Social Safety Net

Paper Session

Saturday, Jan. 3, 2026 8:00 AM - 10:00 AM (EST)

Philadelphia Convention Center, 107-AB
Hosted By: American Economic Association
  • Chair: Brendan Cushing-Daniels, Gettysburg College

Comparing the Enrollment and Screening Effects of Asset and Income Tests for Welfare Programs

Jeehoon Han
,
Baylor University
Derek Wu
,
University of Virginia

Abstract

This paper compares the effects of relaxing income and asset tests for welfare programs on eligibility, enrollment, and targeting outcomes. We focus on one of the largest means-tested transfers in the United States: the Supplemental Nutrition Assistance Program (SNAP). We leverage variation in state adoption of Broad-Based Categorical Eligibility (BBCE) policies, which allowed states to expand eligibility by altering gross income, net income, and/or asset thresholds. Using a stacked difference-in-differences design and data from the Survey of Income and Program Participation (SIPP) and SNAP Quality Control (QC) files, we estimate the causal impacts of these three policy levers on the number of newly eligible and enrolled households, as well as on their demographic characteristics and material hardships. We find that both relaxing asset tests and raising income thresholds significantly increase eligibility (by 30% and 15%, respectively), with little to no impact on eligibility of eliminating the net income test. In terms of enrollment, we find that raising gross income thresholds increases the number of non-elderly and non-disabled households by 5%, while relaxing the asset and net income tests tends to bring in more elderly households. Raising gross income thresholds attracts households that are no less disadvantaged than existing eligible households, while relaxing asset tests predominantly brings in households with fewer hardships. Policy simulations suggest that, despite being needier, households eligible due to raised income thresholds qualify for lower benefits than those eligible due to relaxed asset tests. These findings provide insights for policymakers seeking to optimize the design of SNAP and other safety net programs.

From Storefronts to Screens: The Impacts of Online Grocery Shopping on Public Food Assistance Users

Kelsey Pukelis
,
Harvard University

Abstract

Many anti-poverty programs are in-kind, and adoption of new technology can alleviate the challenges associated with redeeming benefits. This project investigates how the availability of online grocery purchasing in public food assistance programs—including SNAP—affects food access, benefit spending patterns, and program participation. Authorization to accept Electronic Benefit Transfer (EBT) payments online was disproportionately adopted by large food retailers in urban areas. Exploiting the staggered roll-out of online purchasing authorization across retailers, I estimate that online exposure led to a $16 increase in monthly online EBT spending per household. Households substitute away from in-store spending at large food retailers. Following a large drop in SNAP benefits, participants decrease online grocery spending more than dollar-for-dollar, suggesting that online grocery shopping is a luxury service and EBT consumers are willing to pay for convenience under higher incomes. Finally, online grocery purchasing availability increases local SNAP participation by 4 percent, primarily by increasing retention of existing participants. These results suggest that policies which reduce benefit redemption frictions can improve the effectiveness of in-kind benefit programs.

The Anatomy and Evolution of Survey Error: Methods

Bruce D. Meyer
,
University of Chicago
Nikolas Mittag
,
CERGE-EI
Derek Wu
,
University of Virginia

Abstract

Survey data increasingly miss dollars for major income sources (Meyer et al. 2015), threatening their reliability as a foundation for research and policy. Previous studies have gone beyond comparisons of aggregates to document measurement error at the individual level, tending to focus on single income sources like retirement income (Bee and Rothbaum 2017) or SNAP (Meyer et al. 2022) over a limited set of states and/or years. We provide a comprehensive assessment of how individual-level measurement error has changed over time, using data for ten income sources spanning more than two decades. We present motivating facts documenting the deterioration of survey quality, including worsening underreporting of both dollars and recipients alongside rising unit non-response, whole imputation, and item imputation rates. We then link the Current Population Survey Annual Social Economic Supplement (CPS) from 1996 and 2017 to administrative records for retirement income (IRS), Social Security (SSA), Old-Age and Survivors Insurance (SSA), Disability Insurance (SSA), Supplemental Security Income (SSA), Unemployment Insurance (IRS), veterans' disability compensation (DVA), SNAP (state agencies), public and subsidized housing (HUD), and Medicaid (CMS). Finally, we describe our approach to decomposing total survey error (in terms of dollars and recipients) into various components for each income source and year.

The Anatomy and Evolution of Survey Error: Estimates

Bruce D. Meyer
,
University of Chicago
Nikolas Mittag
,
CERGE-EI
Derek Wu
,
University of Virginia

Abstract

We document how individual-level measurement error has evolved across ten income sources from 1996 to 2017, using data from the CPS linked to various administrative records. For each income source and year, we quantify four key components of survey error (coverage error, whole imputation error, item non-response error, and measurement error among respondents) and show these components can further be decomposed into false negatives (recipients not reporting receipt), false positives (non-recipients erroneously reporting receipt), and dollar misreporting among true reporting recipients. We show the contribution of each component to total survey error in dollars and recipients, both in net and absolute terms. These estimates have major implications for assessing how income-based measures of poverty, inequality, and program effectiveness are biased at a point in time and have changed over time. They will also form the basis for imputation models to correct for misreporting in survey data, which we plan to share with the research community.

Long-Term Effects of Universal Free School Meal Policies: Evidence from the Community Eligibility Provision

Lexin Cai
,
Cornell University

Abstract

This paper evaluates the short- and long-term effects of the Community Eligibility Provision (CEP), a federal program offering universal school meals, on student academic, behavioral, and economic outcomes. I employ a difference-in-differences research design based on the staggered adoption of CEP in 3,000 Texas schools between 2011 and 2022. To address the limitations of prior research, which has focused on a narrow set of short-term outcomes, I use linked administrative data from Texas that tracks K-12 students through college and into the workforce. The primary outcomes of interest include academic (test scores, ACT/SAT scores, high school graduation, college enrollment), behavioral (meal participation, attendance, suspensions, dropout rates), and economic (employment, earnings) outcomes. Findings from this project will shed light on whether universal free school meals improve student outcomes compared to existing means-tested meal policies.

Attention vs Choice in Welfare Take-up: What Works for WIC?

Lei Wang
,
Ohio State University
Sooa Ahn
,
Ohio State University

Abstract

Incomplete take-up of welfare benefits remains a major policy puzzle. This paper decomposes the causes of incomplete welfare take-up into two mechanisms: inattention, where households do not consider program participation, and active choice, where households consider participation but find it not worthwhile. To capture these two mechanisms, we model households' take-up decision as a two-stage process: attention followed by choice. Applied to NLSY97 data on the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), our model reveals substantial household-level heterogeneity in both attention and choice probabilities. Furthermore, counterfactual simulations predict that choice-nudging policies outperform attention-boosting policies. We test this prediction using data from the WIC2Five pilot program that sent choice-nudging and attention-boosting text messages to different households. Consistent with the counterfactual prediction, choice-nudging messages increased retention much more effectively than attention-boosting messages.
JEL Classifications
  • H5 - National Government Expenditures and Related Policies