Immigration, local crowd-out and undercoverage bias
Using decadal census data since 1960, I cannot reject the hypothesis that new immigrants crowd out existing residents from US commuting zones and states one-for-one. My estimate accounts explicitly for dynamic local adjustment, it is statistically precise and robust to numerous specifications, and I show how it can be reconciled with apparently conflicting results in the literature. Exploiting my model's structure, I attribute 30% of the observed effect to mismeasurement, specifically undercoverage of new immigrants in the census. Based on a remarkably simple decomposition (and after adjusting for undercoverage), I show that population mobility accounts for 90% of local labor market adjustment (following an immigration shock), and labor demand the remainder. These results have important methodological implications for the estimation of immigration effects.
13 January 2020 Paper Number CEPDP1669
Download PDF - Immigration, local crowd-out and undercoverage bias
This CEP discussion paper is published under the centre's Labour markets programme.