Empirical Characteristics of Legal and Illegal Immigrants in the U.S
We combine the New Immigrant Survey (NIS), which contains information on US legal immigrants, with the American Community Survey (ACS), which contains information on all immigrants to the U.S., legal and illegal ones. Using econometric methodology proposed by Lancaster and Imbens (1996) we compute the probability for each observation in the ACS data to refer to an illegal immigrant, conditional on observed characteristics. The results for illegal versus legal immigrants are novel, since no other work has quanti ed the characteristics of illegal immigrants from a random sample. We nd that, compared to legal immigrants, illegal immigrants are more likely to be less educated, males, and married with spouse not present. These results are heterogeneous across education categories, country of origin (Mexico) and whether professional occupations are included or not in the analysis. Forecasts for the distribution of certain legal and illegal characteristics match those available from other sources, such as aggregate imputations by the Department of Homeland Security for illegal immigrants
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- Lancaster, Tony & Imbens, Guido, 1996.
"Case-control studies with contaminated controls,"
Journal of Econometrics,
Elsevier, vol. 71(1-2), pages 145-160.
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- Imbens, G. & Lancaster, T., 1993. "Case-Control Studies with Contaminated Controls," Papers 9307, Tilburg - Center for Economic Research.
- Imbens, G.W. & Lancaster, T., 1993. "Case-Control Studies with Contaminated Controls," Discussion Paper 1993-7, Tilburg University, Center for Economic Research.
- Nicole Fortin & Thomas Lemieux & Sergio Firpo, 2010.
"Decomposition Methods in Economics,"
NBER Working Papers
16045, National Bureau of Economic Research, Inc.
- Gary Burtless & Audrey Singer, 2011. "The Earnings and Social Security Contributions of Documented and Undocumented Mexican Immigrants," Working Papers, Center for Retirement Research at Boston College wp2011-1, Center for Retirement Research, revised Jan 2011.
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