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  5. Participation and Trends in U.S. Transfer Programs and the Social Safety Net
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Participation and Trends in U.S. Transfer Programs and the Social Safety Net

Paper Session

Monday, Jan. 5, 2026 8:00 AM - 10:00 AM (EST)

Philadelphia Convention Center, 204-C
Hosted By: American Economic Association
  • Chair: Robert Moffitt, Johns Hopkins University

Taxes, Transfers, and Inequality at the Bottom of the Income Distribution

Priyanka Anand
,
George Mason University
Robert Moffitt
,
Johns Hopkins University

Abstract

Existing research on income inequality in the US tends to focus on comparing the top income shares with the rest of the distribution. In this paper, we focus on measuring inequality at the bottom end of the income distribution, where social assistance and transfers play an important role. Inequality within the low-income distribution has likely changed over time, in part due to variation in which groups have been targeted by transfer programs, and we seek to produce new statistics to measure these changes. We use 1998 to 2021 data from the Survey of Income and Program Participation and the Medical Expenditure Panel Survey to measure variation over time in inequality at the bottom end of the income distribution, particularly after the Medicaid and Child Tax Credit expansions that occurred in the 2010s and policy developments in the 1990s and 2000s. Our analyses address the well-known problem of underreporting in survey data through a careful imputation method that ensures that our measure of self-reported program receipt matches administrative totals. We also create a comprehensive measure of income that includes personal income and a wide variety of program benefits such as Supplemental Nutrition Assistance Program (SNAP) benefits, Temporary Assistance to Needy Families (TANF), federal disability benefits, Medicaid expenditures, and housing assistance. We then examine distributional trends over time in private income by family structure and measure trends in inequality due to changes in taxes and transfer programs. Our inequality measures will include percentile point ratios and Gini coefficients. Our preliminary results show that over the past 30 years, the U.S. safety net has increasingly provided support to low-income families with higher levels of earnings and income relative to support for the poorest families, thereby increasing inequality within the lower income population.

Multiple Safety Net Program Participation: Incidence and Impacts from Reducing Administrative Burdens

Neil Cholli
,
Cornell University
Derek Wu
,
University of Virginia

Abstract

Multiple program participation among low-income households with children is a critical yet understudied aspect of the U.S. social safety net. Leveraging high-quality administrative records from Virginia, we find that half of program recipients participated in multiple programs despite significant gaps in take-up persisting among eligible populations. We evaluate the causal impact of a technological reform that streamlined applications for SNAP, Medicaid, and TANF via a centralized online platform. Introducing a novel framework that decomposes the reform's effects into “fixed” and “variable” administrative burdens by distance to field office, we employ complementary research designs to identify the impacts of reducing each burden type. The policy reform markedly increased multiple program participation, almost entirely among households with children, and targeted those with increased work histories and fewer criminal offenses. A partial identification analysis of recipient types reveals that a meaningful share of multiple program participation occurred on the intensive margin. Collectively, our results suggest that reductions in administrative burdens to multiple programs can benefit low-income working parents who were previously leaving benefits on the table.

Unintended Consequences: Childless Workers, the EITC, and the Minimum Wage

Ioana Marinescu
,
University of Pennsylvania
Christopher Wodicka
,
University of Pennsylvania

Abstract

This paper examines how state minimum wage increases interact with Earned Income Tax Credit (EITC) eligibility and benefits for childless workers. We use Current Population Survey data to provide new descriptive evidence on how state EITC expansions for childless adults may have unintended consequences when implemented in states with modestly high minimum wages. We focus on EITC eligibility rates among childless workers. We find that state minimum wages above the federal minimum wage of \$7.25 per hour tend to be associated with lower EITC eligibility. However, this relationship is non-linear. The association is concentrated among states with more modest minimum wage levels (\$10 to \$12 per hour) where EITC eligibility is 8\textendash9\% lower than in states with a minimum wage of \$7.25, while the relationship ceases to be negative at the highest minimum wage levels (\$15 per hour). Our findings have important implications for the design and evaluation of anti-poverty policies that target low-income workers without children.

Using Survey-Based Regression Imputation to Address Transfer Underreporting in the CPS ASEC: Implications for Inequality and Poverty 2001-2024

James Ziliak
,
University of Kentucky

Abstract

The paper assesses the extent of transfer program misreporting in the Current Population Survey Annual Social and Economic Supplement (CPS ASEC), and the attendant implications for the level and trends in inequality and poverty over the 2001-2024 survey years. The results suggest that underreporting of participation in Medicaid, Social Security programs, and WIC is most acute, with Medicaid underreporting accelerating after the Affordable Care Act in 2014. Implementing the survey-based regression model to address underreporting of benefit amounts suggests that inequality and poverty are overstated because of transfer misreporting, but this overstatement is small as applied to inequality and relative poverty. Underreporting has a more substantive effect on absolute poverty, with an anchored Supplemental Poverty Measure reduced by an average 1.3 percentage points—or just over 4 million people—after incorporating the regression-based imputations. However, underreporting does not alter the trends in inequality and poverty over time.

Discussant(s)
Chloe East
,
University of Colorado-Boulder
Marianne Bitler
,
University of California-Davis
Jeff Larimore
,
Federal Reserve Board
Christopher Wimer
,
Columbia University
JEL Classifications
  • I3 - Welfare, Well-Being, and Poverty
  • H4 - Publicly Provided Goods