We estimate the effects of immigration on the annual income and employment levels of native-born construction workers in the US. We utilize a so-called "imperfect instrument approach" formalized by Nevo & Rosen (2012) which allows us to derive an upper bound for the effects of immigration on native-born workers. Our partial identification strategy relies on the assumptions that the imperfect instrument is less correlated with the error term than is our endogenous regressor, but that the sign of the correlation is the same. We find negative and significant effects which indicate that immigration has had a harmful impact on native-born construction workers in the US. Our estimates are upper bounds which means that the true effects are likely larger than those that we find.
Ph.D. Student, Agricultural and Resource Economics
Zach Rutledge studys academic journal articles and other relevant material to understand econometric modelling methodology for immigration-related research, use statistical software to process US Census data (including summary statistics, graphs, and regression analysis), develop econometric models to estimate the effect of immigration on wages and employment levels of construction workers in the US, and write research papers. His work consists of lengthy hours reading complicated economic journal articles, sitting at a computer writing computer code to clean and analyze data, and writing reports and research papers.
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Comments from Alexandra Hill, Ph.D. Student, Agricultural and Resource Economics, UC Davis
Broadly, this paper contributes to the understanding of the effects of immigration on the labor market outcomes for native-born workers in the United States. More specifically, the paper examines the impact of changes in the share of foreign-born workers in the construction sector on annual earnings, weekly earnings, number of weeks worked within a year, and unemployment rates for native-born construction workers. To do this, the paper uses 1990 and 2000 U.S. Census data as well as American Community Survey data (ACS) from 2003 to 2011. Because increases in immigration are likely correlated with unobserved demand- pull factors which also affect the income and employment outcomes of natives, the OLS estimator is biased. The authors are the first to use an imperfect instrumental variable (IIV) to partially correct this bias and estimate upper bounds on the impacts of immigration. The authors make substantial contributions to existing literature through their results and the novel application of this methodology. Using the IIV, the authors find estimates of the effects of immigrant share on annual earnings and employment rates for U.S. natives that are negative, significant, and larger in magnitude than previous estimates.