The Productivity Consequences of Pollution-Induced Migration in China
时间：2021年12月14日（周二）10:30am-noon
主持人：余淼杰、余昌华
主讲人：Gaurav Khanna, University of California – San Diego (UCSD)
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摘要：This paper studies how migration in response to pollution affects aggregate productivity and welfare in China. We document a robust pattern in which skilled workers emigrate away from polluted cities, more than the unskilled. Their greater sensitivity to air quality holds up in cross-sectional variation across cities, panel variation with individual fixed-effects, and when instrumenting for pollution using distant power-plants upwind of cities, or thermal inversions that trap pollution. Pollution therefore changes the spatial distribution of skilled and unskilled workers, which results in higher returns to skill in cities that the educated migrate away from. We quantify the loss in aggregate productivity due to this re-sorting by estimating a model of demand and supply of skilled and unskilled workers. Counterfactual simulations from the estimated model show that reducing pollution would increase productivity through spatial re-sorting by approximately as much as the direct health benefits of clean air. Physical and institutional restrictions on mobility exacerbate welfare losses. People’s dislike of pollution explains a substantial portion of the wage gap between cities.
主讲人简介：Gaurav is an Assistant Professor of Economics at UCSD's School of Global Policy and Strategy, a faculty affiliate at the Center for Effective Global Action, and a Non-resident Fellow at the Center for Global Development. He mainly works in Development Economics, Education and Labor Economics. His research has been published in several leading journals, including the American Economic Review, the American Economic Journal, the Review of Economics and Statistics, the Journal of Development Economics, the Journal of Labor Economics, etc.
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