By Natisha Bartlett

Faculty Mentor: Don Lee

Abstract

Immigration is a very polarized topic today in the media, amongst families and friends, and in the workplace. I intend to objectively research the effect immigration has on U.S unemployment.The United States is a perfect country to give a depiction of what impact immigration has on unemployment because it is a country known for being a host country for the largest numbers of international immigrants. This is not surprising since immigration has been the cornerstone for the establishment of the U.S, economic growth, and international relevancy. America still welcomes migrants today but what are the benefits and costs? Previous literature has concluded that there is a positive effect of immigration to the United States on unemployment rate in the long run showing that while there is no statistically significant relationship between the two variables in the short run, an increase in the immigrant population increases the unemployment rate by 0.14 percent in the long run (Aslan, Altinöz 2020). This is in contrast to the findings of Ekrame Boubtane, Dramane Coulibaly, and Christophe Rault who’s results provided evidence of migration contribution to host economic prosperity such as a positive impact on GDP per capita and a negative impact on aggregate unemployment, native- and foreign-born unemployment rates (Boubtane, et al. 2013).I contribute to this literature by examining the impact of immigration on U.S unemployment rates utilizing state level time series data. I will be utilizing panel data for my dynamic model using state level data from 2013-2020. In this model the unemployment rate for each state will be my dependent variable and immigration, measured in thousands, will be my main independent variable. I will follow the literature in that I will lag the dependent variable to account for the effects over time that may be vital to the data. I will also run another model with the immigration variable lagged to see if that has a major effect on the coefficients and showing any significance while accounting for any serial correlation.