I study how language barriers impact aggregate and distributional economic outcomes using rich microdata from India applied to a quantitative spatial general equilibrium framework. I first document three empirical facts, which are strongest for unskilled workers: first, workers migrate less often to locations where they face high language barriers; second, migrants with high language barriers are employed less often in speaking-intensive occupations; and third migrants with high language barriers get a wage premium. To rationalize these facts, I then develop and estimate a static migration model in which heterogeneous workers sort across occupations and locations by skill and language, with wages accounting for worker selection and adjusting in general equilibrium. I show through the lens of the model how language barriers, by increasing worker sorting and selection, significantly obstruct internal migration, augment the skill premium, and reduce aggregate welfare. Finally, I calibrate costs of both program provision and learning languages to evaluate potential benefits of language programs for unskilled migrants. Using the calibrated model, I argue that welfare benefits of implementing language programs would outweigh costs.
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Amrutha Manjunath
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