Selected Working Papers
- “Market Power in Coal Shipping and Implications for U.S. Climate Policy”
Economists have widely endorsed pricing CO2 emissions to internalize climate change-related externalities. Doing so would significantly affect coal, which is the most carbon-intensive major energy source. However, U.S. coal markets exhibit an additional distortion, as the railroads that transport coal to power plants can exert market power. This upstream distortion can mute the price signal of a corrective tax, due to changes in markups or incomplete tax pass-through. In this paper, I provide the first empirical estimates of how coal-by-rail markups respond to changes in coal demand. I find that rail carriers reduce coal markups when downstream power plant demand changes, due to a decrease in the price of natural gas (a competing fuel). I estimate markup changes that vary substantially across coal plants, resulting from a combination of heterogeneous transportation market structure and plant-specific demand shocks. Since low natural gas prices and a CO2 emissions tax similarly disadvantage coal, observed decreases in coal markups imply that pass-through of a federal carbon tax to coal power plants may be heterogeneous and incomplete. This could substantially erode the environmental benefits of a price-based climate policy. My results suggest that decreases in coal markups have increased recent climate damages by $2.3 billion, compared to a counterfactual where markups do not change.
- “Panel Data and Experimental Design”
[Stata package: type - ssc describe pcpanel - in Stata console]
(with Fiona Burlig and Matt Woerman; revise & resubmit, Journal of Development Economics)
How should researchers design panel data experiments? We analytically derive the variance of panel estimators, informing power calculations in panel data settings. We generalize Frison and Pocock (1992) to fully arbitrary error structures, thereby extending McKenzie (2012) to allow for non-constant serial correlation. Using Monte Carlo simulations and real-world panel data, we demonstrate that failing to account for arbitrary serial correlation ex ante yields experiments that are incorrectly powered under proper inference. By contrast, our “serial-correlation-robust” power calculations achieve correctly powered experiments in both simulated and real data. We discuss the implications of these results, and introduce a new software package to facilitate proper power calculations in practice.
- “Out of the Darkness and Into the Light? Development Effects of Rural Electrification”
(with Fiona Burlig; revise & resubmit, Journal of Political Economy)
Over 1 billion people lack electricity access. Developing countries are investing billions of dollars in rural electrification, targeting economic growth and poverty reduction, despite limited empirical evidence. We estimate the effects of rural electrification on economic development in the context of India’s national electrification program, which reached over 400,000 villages. We use a regression discontinuity design and high-resolution geospatial data to identify medium-run economic impacts of electrification. We find a substantial increase in electricity use, but reject effects larger than 0.26 standard deviations across numerous measures of economic development, suggesting that rural electrification may be less beneficial than previously thought.
- “Spatial Externalities in Groundwater Extraction: Evidence from California Agriculture”
[preliminary draft available upon request] [Forbes piece]
(with Fiona Burlig and Matt Woerman)
Groundwater is a common-pool resource essential for agricultural production. When farmers extract a marginal unit of groundwater, this lowers nearby groundwater levels and increases their neighbors’ groundwater pumping costs. This paper estimates farmers’ elasticity of demand for groundwater, in order to empirically investigate the magnitude of this spatial “pumping cost” externality. We assemble a novel dataset that combines (i) detailed microdata on farmers’ electricity consumption, (ii) rich data from technical audits of these farmers’ pump efficiencies, and (iii) publicly available measurements of groundwater depths in California aquifers. Using exogenous variation in electricity prices, we estimate farmers’ price elasticities of demand for both electricity (–1.17) and groundwater (–1.12) to be much larger than previous estimates in the literature. We then calculate the extent to which each farm lowers its neighbors’ economic surplus by removing water from their shared aquifer. Our preliminary results suggest that the magnitude of the “pumping cost” externality is likely smaller than farmers’ private costs of groundwater pumping.
- “Environmental and Technology Policy Options in the Electricity Sector: Are We Deploying Too Many?”
Journal of the Association of Environmental and Resource Economists 4 (4): 959–984. 2017.
(with Carolyn Fischer and Richard Newell)
- “Combining Policies for Renewable Energy: Is the Whole Less Than the Sum of Its Parts?”
International Review of Environmental and Resource Economics 4 (1): 51–92. 2010.
(with Carolyn Fischer)