Abstract:
This paper constructs estimates for the inflow of
undocumented migrants to the United States using survey-based micro
estimates of the number of successful migrations per apprehension and aggregate
apprehensions data reported by U.S. Customs and Border Protection.
The robustness of the constructed data is determined by comparing
the implied stock from the constructed series with previous
estimates of undocumented migrants in the United States. The
estimates are within the unenumerated-correction margin of error of
the post-2000 Census estimates in the literature. Moreover, the analysis in
this paper concurs with Hanson and Spilimbergo (1999) finding that
the inflow of migrants to the United States is responsive to
business cycle conditions.
Immigration and Business Cycle Volatility
Abstract:
This paper finds the responsiveness of a migrant population to
economic shifts increases the volatility of output
and employment in the United States. In a simple business cycle framework, an immigration model is constructed with an additional population variable that is responsive to changes in productivity and wages.
Relative to the classic business cycle model, the model that
incorporates immigration increases the volatility of output by about
2 percent and labor volatility by 3 percent. Empirical analysis
that uses regional variation between migrant localities finds a larger effect than in the theoretical model. An increase in the percent of the
foreign-born labor force increases aggregate employment volatility
by 8 percent and the volatility of the aggregate economic variable by 14 percent.