Published In

Population Research and Policy Review

Document Type

Article

Publication Date

9-12-2025

Subjects

Immigration Policies -- United States

Abstract

Due to the United States’ decades-long stalemate in federal immigration policy-making, major institutional forecasts of the U.S. population have not included assumptions about changes in immigration policy. However, the 2016 election of President Donald Trump and the COVID-19 pandemic demonstrated just how much policy shifts can affect immigration flows, with substantial implications for the country’s demographic future. We created national-level population and economic projections through 2060 using nine different immigration policy scenarios, reflecting differences in both the scale of immigration allowed and the mix of immigrant visas issued (family reunification versus economic and labor visas). The projections highlight the dramatically divergent outcomes associated with different immigration policy choices. Although even very high levels of immigration do not fully offset population aging, higher levels of immigration are associated with substantial increases in GDP and significant reductions in Social Security deficits. The family-emphasis scenarios produce greater population and economic growth, compared to the labor-emphasis scenarios at similar levels of immigration. Immigration is not the only way to address labor shortages and population aging, but our projections show that immigration restriction, or even the maintenance of moderate levels of immigration, will produce serious social and economic challenges in the future. Although the situation is unfolding, our findings are especially important given that the 2024 re-election of President Trump has resulted in widespread efforts to restrict immigration.

Rights

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Locate the Document

https://doi-org/10.1007/s11113-025-09973-z

DOI

10.1007/s11113-025-09973-z

Persistent Identifier

https://archives.pdx.edu/ds/psu/44124

Publisher

Springer Science and Business Media LLC

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