635 Downey Way, Los Angeles, CA 90089

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Daniel Sullivan

Thursday, January 18 at 3:30pm in VPD 203

 

Abstract: While the costs of environmental policies are generally thought to be regressive, the distribution of benefits is less understood. This paper explores the incidence of an unexpected decrease in air pollution in metropolitan Los Angeles by estimating the resulting change in housing costs and neighborhood demographics. The decrease in air pollution was caused jointly by the California Electricity Crisis of 2000 and the RECLAIM cap-and-trade program for NOx emissions and impacted neighborhoods differentially based on their location relative to major polluters and local wind patterns. I measure local exposure to this pollution shock using a dispersion model developed by atmospheric scientists which calculates the effect of individual firms’ emissions on the air quality of nearby locations. The estimates show that (a) housing rents increase significantly and as much as house prices; (b) 9% of low-income households leave the sample area due to improved air quality; and (c) low-income households are rarely home owners who would benefit from increased housing wealth. I show that a standard residential sorting model predicts that when low-income residents respond to improved amenities by leaving, the distribution of benefits from the improvement is likely regressive. Together, these results suggest that the distribution of benefits from improved air quality likely favors higher-income households.

 

Bio: Daniel M. Sullivan is a fellow at Resources for the Future. His primary fields of research are urban and environmental economics. His work explores how housing markets respond to local air pollution, and how these markets can be used to determine who benefits from environmental regulations. More generally, he analyzes how air pollution affects individuals' health, education, and place of residence. He earned his PhD in economics from Harvard University.

 

Sponsored by:

Solutions Lab for a Sustainable and Equitable Future

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