We develop a framework to estimate the marginal cost of air pollution regulation and apply it to assess policy efficiency. We exploit a provision of the Clean Air Act that requires new plants to pay incumbent facilities to reduce emissions. This "offset" policy creates hundreds of local pollution markets, differing by pollutant and location. Theory and transaction data suggest that offset prices reveal marginal abatement costs. We compare these prices to marginal benefits of pollution reduction estimated using leading air quality models and find that, on average, marginal benefits exceed marginal costs by more than a factor of ten.

We investigate how hardships affect rural politics, considering the case of hospital closures. In the last two decades, more than two hundred rural hospitals have closed their doors or drastically reduced their services. Drawing from resource models of voting, our hypothesis is that personal- and community-level deprivations brought about by hospital closures should reduce election turnout. Empirical tests pair geographic information on the location of open and closed hospitals with data from state voter files to create a panel of over 10 million rural residents for the 2016, 2018, and 2020 national elections. Results show that individuals whose nearest hospital closed prior to the proximate election were less likely to vote than their unaffected counterparts. These effects are strongest for older and lower-income residents, but they decay over time so that voting likelihood resembles a pre-closure baseline within 12 months.