Conference Agenda

This paper quantifies the long-term economic costs of ambient air pollution by constructing novel measures of individual lifetime exposure to emissions from French fossil fuel power plants over 1950–2022, accounting for residential mobility. Exploiting quasi-experimental variation generated by France's 1980s government-led transition to nuclear energy and subsequent phase-out of coal- and oil-fired power plants, we estimate the effects of early-life and cumulative electricity-related pollution exposure on adult employment, earnings, and health. We find that greater long-run exposure significantly reduces career-average annual earnings, with effects partly mediated by adverse health impacts from exposure before age five. The implied gains from this early French fossil phase-out are substantial: within 80 kilometers of plants, individuals born after 1985 are predicted to earn 2.2 percent higher wages than those born before 1965.

The health consequences of sectoral transitions are theoretically ambiguous. Reductions in industrial activity and associated pollution may improve health, while local economic deterioration may worsen it. This paper examines these competing forces in the context of coal’s decline. Linking restricted-access mortality data with detailed records of coal-fired power plant and mine activity from 2004 to 2019, we find that power-sector contractions reduce pollution-related mortality among older adults, while coal mining contractions increase mortality and overdose deaths among working-age adults. These results indicate that the health consequences of coal’s decline depend not only on pollution reductions, but also the uneven economic disruptions experienced by coal-dependent communities.

A common strategy to reduce exposure to pollutants during critical air quality events in Latin America is to temporarily adjust transportation policies. Medellín, Colombia's second-largest city, and the Aburrá Valley Metropolitan Area implemented a short-term driving restriction plan in 2017. Unlike other cities, this plan not only banned cars but also restricted motorcycles and trucks. The restrictions quickly became stricter for older vehicles. We use a two-way fixed effects model to empirically evaluate the effectiveness of this plan between 2017 and 2019. We assess the impact on pollutant concentrations, vehicle trips, noise, and changes in regular on-road tests of vehicle environmental performance. Our results show the plan reduced air pollution by 3% to 26% for several pollutants. Red alerts, which implemented the strictest bans, showed the largest improvement in air quality, especially for particulate matter. Reductions in air pollutants appear greater when restrictions apply to trucks, older vehicles, or when bans include additional license plate numbers, rather than using generalized restrictions. Vehicle trips and noise also declined. Additionally, we found an increase in on-road vehicle testing. Unlike regular driving restriction programs that provide mixed evidence regarding their effectiveness, our findings suggest that differentiated restrictions are effective. Focusing the strictest bans on the most polluting vehicles reduces air pollution during short-term episodes of poor air quality.

We study the benefits, abatement costs, and distributional outcomes of the EPA’s NOx Budget Program, a seasonal cap-and-trade market for NOx emissions. Using a new empirical approach, we recover source-specific marginal abatement cost curves and combine them with source-specific air pollution damages to quantify market outcomes. We find that abatement costs under the market are roughly one-sixth those of an abatement-equivalent non-market policy. Despite these large differences in aggregate costs, the market and the non-market policy yield similar air quality benefits, both in overall magnitude and across demographic groups. We show that these results reflect the weak correlation between source-specific marginal damages and abatement behavior.