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Project Citation: 

Khanna, Gaurav, Liang, Wenquan, Mobarak, Mushfiq , and Song, Ran. Data and Code For: The Productivity Consequences of Pollution-Induced Migration in China. Nashville, TN: American Economic Association [publisher], 2023. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-06-14. https://doi.org/10.3886/E192181V1

Project Description

Summary:  View help for Summary Summary:  This is replication code and data for the paper "The Productivity Consequences of Pollution-Induced Migration in China."

Abstract
We quantify how pollution affects aggregate productivity and welfare in spatial equilibrium. We document a robust pattern in which skilled workers in China emigrate away from polluted cities, more than the unskilled. These patterns are evident under various empirical specifications, such as when instrumenting for pollution using distant upwind power-plants, or thermal inversions that trap pollutants. Pollution changes the spatial distribution of skilled and unskilled workers, which increases returns-toskill in cities that the educated emigrate from. We quantify the loss in aggregate productivity due to this re-sorting by estimating a spatial equilibrium model. Counterfactual simulations show that reducing pollution increases productivity through spatial re-sorting by approximately as much as the direct health benefits of clean air. We identify a new channel through which pollution lowers aggregate productivity significantly. Hukou mobility restrictions exacerbate welfare losses. Skilled workers’aversion to pollution explains a substantial portion of the wage-gap between cities.

Scope of Project

Subject Terms:  View help for Subject Terms pollution; population migration; productivity
JEL Classification:  View help for JEL Classification
      A10 General Economics: General


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