February 13, 2019, 14:00–15:30
Job Market Seminar
Between 2005 and 2014, the US electricity generation sector achieved unprecedented reductions in emissions of local air pollutants. This paper seeks to quantitatively uncover the factors that drove these sharp decreases in emissions and their connections to the cap-and-trade markets introduced by the Clean Air Interstate Rule. To that end, I assemble a comprehensive dataset on power plant operations and costs. In a statistical decomposition of emission reductions at the power plant level, I find that the adoption of capital-intensive abatement technologies constituted the primary factor influencing the emission reductions, accounting for over 50% of the achieved reductions. Switching to cleaner fuel inputs and retiring dirty units also each contributed approximately 20% of the observed reductions. I further demonstrate that the costs incurred due to the adoption of abatement technologies amounted to $45 billion, exceeding ex ante projections. I find that, despite the high costs incurred by power plants, these emission reductions generated net benefits to society. I estimate the health impacts of these emission reductions using novel satellite data to generate spatially continuous pollution measurements that I link to demographic information. A lower-bound estimate of the corresponding health impacts suggests that 19,000 premature infant deaths were avoided during the period considered thanks to the achieved emission reductions. Finally, I estimate the local demand for clean air by studying the impacts of power plant emission reductions on local housing markets. Matching micro-level housing transactions from a proprietary dataset to power plant locations, I find that the emission reductions caused housing prices to increase in cleaned areas, thereby appreciating house values by $8 billion.