We use a new dataset and a novel identification strategy to analyze the effects on labor market outcomes of residential segregation of migrants in 8 Italian cities. Our data are representative of the population of both legal and illegal migrants, allow us to measure segregation at the very local level (the block) and include measures of housing prices, commuting costs and migrants’ linguistic ability. We find evidence that migrants who reside in areas with a high concentration of non-Italians are less likely to be employed compared to similar migrants who reside in less segregated areas. In our preferred specification, a 10 percentage points increase in residential segregation reduces the probability of being employed by 7 percentage points or about 8% over the average. Additionally, we also show that this effect emerges only above a critical threshold of 15-20% of migrants over the total local population, below which there is no statistically detectable effect. Contrary to common wisdom, in our data migrants seem to be positively selected into segregated areas. A matching model with heterogeneous workers and endogenous sorting into heterogeneous locations rationalizes our findings and is supported by additional empirical results.
Moving to Segregation: Evidence from 8 Italian cities
BOERI, TITO MICHELE;PELLIZZARI, MICHELE
2011
Abstract
We use a new dataset and a novel identification strategy to analyze the effects on labor market outcomes of residential segregation of migrants in 8 Italian cities. Our data are representative of the population of both legal and illegal migrants, allow us to measure segregation at the very local level (the block) and include measures of housing prices, commuting costs and migrants’ linguistic ability. We find evidence that migrants who reside in areas with a high concentration of non-Italians are less likely to be employed compared to similar migrants who reside in less segregated areas. In our preferred specification, a 10 percentage points increase in residential segregation reduces the probability of being employed by 7 percentage points or about 8% over the average. Additionally, we also show that this effect emerges only above a critical threshold of 15-20% of migrants over the total local population, below which there is no statistically detectable effect. Contrary to common wisdom, in our data migrants seem to be positively selected into segregated areas. A matching model with heterogeneous workers and endogenous sorting into heterogeneous locations rationalizes our findings and is supported by additional empirical results.
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