Return to search

Fiscal effects of undocumented immigration and amnesty

Master of Arts / Department of Economics / Tracy M. Turner / The report examines the fiscal impact of undocumented persons at the federal, state, and local levels in order to explain the likely effects of an amnesty program. The report first provides background on the population of undocumented persons in the United States and an overview of the laws which govern their status. Details of past and current amnesty legislation are given. The channels through which undocumented immigrants have a fiscal impact on the three levels of government in the United States are explained. The paper discusses the economic theory relating to immigration and its effect on economic growth. Published works on the fiscal impact of the undocumented on state and local budgets and on federal programs such as social security are reviewed. The research reviewed includes an analysis of the long-term fiscal impact of immigrants. Undocumented immigrants impose a net cost at the state and local levels in most cases. However, many undocumented immigrants make income and payroll tax payments and the population of undocumented immigrants imposes a net benefit at the federal level. These sources of information are then used to explain how an amnesty program might change the fiscal impact of the undocumented at the three levels of government. The recent executive order signed by President Obama, known as Deferred Action for Childhood Arrivals (DACA), is an amnesty program that has a strong potential to help the U.S. economy retain young and highly educated workers, who have a positive fiscal impact on government finances. This report draws certain recommendations for the design of a successful amnesty and for implementing other immigration reforms from published research.

Identiferoai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/15067
Date January 1900
CreatorsHisle, William J. III
PublisherKansas State University
Source SetsK-State Research Exchange
Languageen_US
Detected LanguageEnglish
TypeReport

Page generated in 0.0022 seconds