Immigration, Beneficiary Assumptions, and Welfare Support

Hang Qi

Review of Policy Research2026https://doi.org/10.1111/ropr.70083article
AJG 2
Weight
0.50

What the paper says

Previous research demonstrates that assumptions and perceptions about who benefits from welfare programs and the deservingness of those welfare beneficiaries play a considerable role in shaping individuals' welfare attitudes. However, a holistic understanding of how these assumptions and perceptions are formed remains limited. In this study, I indicate that elements of welfare policy design (e.g., means‐testing rules) can shape native citizens' assumptions about immigrants as welfare beneficiaries. Through an original survey experiment on Cint Theorem, I find that including a means‐testing rule makes respondents more likely to assume a welfare program benefits immigrants to the exclusion of native‐born Americans. Such a rule also appears to increase assumptions that these programs primarily benefit low‐skilled immigrants and newcomers from less developed countries, though the magnitude of these effects varies across policy domains. In the Pell Grant experiment, the effects are statistically stronger, whereas the corresponding effects in the Child Tax Credit experiment—though pointing in the same direction—are smaller and only marginally significant. Moreover, while certain assumptions—such as the exclusion assumption—are more strongly associated with welfare opposition among those with stronger anti‐immigration views.

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https://doi.org/https://doi.org/10.1111/ropr.70083

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@article{hang2026,
  title        = {{Immigration, Beneficiary Assumptions, and Welfare Support}},
  author       = {Hang Qi},
  journal      = {Review of Policy Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/ropr.70083},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.