Environmental amenities play an important role in residential location decisions, which in turn affect the concentration of consumption and production activities. In this paper, I develop and estimate a spatial general equilibrium model to examine how environmental amenities affect the spatial distribution of urban economic activities and their welfare consequences. The model characterizes household location and consumption decisions, production decisions, as well as urban agglomeration and dispersion forces. The empirical analysis leverages a natural experiment of pollution monitoring and information disclosure program and recovers key underlying parameters using fine-scale travel data on commuting and consumption trips and environmental amenities. The analysis shows that job access, residential amenities, and consumption access account for 49%, 30% and 21% of overall attractiveness of a residential location, respectively. A one-standard-deviation change in air quality leads to a 0.24-standard-deviation change in individuals’ perceived amenity level. Counterfactual simulations suggest an 8.4% welfare gain if individuals were to fully incorporate environmental amenities into their decisions, compared to the scenario of not incorporating their impacts. The welfare difference is driven by changes in residential and workplace locations, as well as consumption and production decisions.

Can the enhanced mobility created by transportation infrastructure investments help people to avoid environmental extremes? We use transaction records from China’s card payment system to measure experienced pollution exposure (EPE) - that is, exposure based on the pollution levels at travelers’ actual locations - and evaluate how EPE was affected by the country’s high-speed railway network, even while holding pollution itself constant. Our estimates imply a reduction in EPE that corresponds to a mortality benefit of 21.3 million life-years saved, primarily due to travelers changing their destinations towards locations with predictably cleaner air.

This paper exploits the universe of credit- and debit-card transactions in China during 2013-2015 and provides the first nationwide analysis of the healthcare cost of PM2.5 for a developing country. We leverage spatial spillovers of PM2.5 from long-range transport to generate exogenous variation in local pollution and employ a flexible distributed lag model to capture semiparametrically the dynamic response of pollution exposure. We find significant impacts of PM2.5 on healthcare spending in both the short and medium terms. A 10 µg/m3 decrease in PM2.5 would reduce annual healthcare spending by over $9.2 billion, about 1.5% of China’s annual healthcare expenditure.