We exploit the introduction of electronic toll collection, (E-ZPass), which greatly reduced both traffic congestion and vehicle emissions near highway toll plazas. We show that the introduction of E-ZPass reduced prematurity and low birth weight among mothers within 2km of a toll plaza by 10.8%...

We examine the distributional effects of changes in local air pollution from driving electric vehicles in the United States. We employ an econometric model to estimate power plant emissions and an integrated assessment model to value damages in air pollution from both electric and gasoline...

Efforts to reduce greenhouse gas emissions in the US have relied on Corporate Average Fuel Economy (CAFE) Standards and Renewable Fuel Standards (RFS). Economists often argue that these policies are inefficient relative to carbon pricing because they ignore existing vehicles and do not...

This paper uses an estimated demand system that accounts for heterogeneity to calculate and compare the lost consumer surplus from a higher tax on gasoline, a tax on distance, or a subsidy for buying a newer car. We introduce a view of cost-effectiveness that compares policies instead of...

Renewable fuel standards, low carbon fuel standards, and ethanol subsidies are popular policies to incentivize ethanol production and reduce emissions from transportation. Compared to carbon trading, these policies lead to large shifts in agricultural activity and unexpected social costs. We...

Household carbon dioxide emissions have been an increasing function of income and distance from the city. Richer suburbanites drive more and consume more electricity and natural gas at home. In recent years, richer people in California have been more likely to buy electric vehicles and to...

We compare the spatial distribution of emissions from Southern California's pollution-trading program with that of a counterfactual command-and-control policy. We develop a normatively significant metric with which to rank the various distributions in a manner consistent with an explicit...