Essays on Environmental and Natural Resource Economics.

This dissertation addresses issues in the economics of the environment and natural resources. The first chapter pertains to the inclusion of environmental objectives into contracts between the government and private firms. In particular, it considers the possibility that conservation restrictions may undermine the goal of fostering competition among private logging firms in timber auctions. Empirically, the policy is costly but is found to be borne primarily by the state without substantial competitive distortions. Importantly, that state can reduce the impact of the policy on revenues by setting reserve prices optimally. The second chapter is joint work with Professor Erich Muehlegger. We use data on Google search activity related to climate change and shocks to local weather to demonstrate that unusual weather increases the salience of climate change as an issue. Further, we find that recent weather shocks have a significant effect on Congressional votes pertaining to environmental regulation. The third chapter makes a methodological contribution to the analysis of auction data. Many auctions have a reserve price, below which the seller simply keeps the object of interest. However, it is typically taken for granted that the object will not be re-auctioned later. Empirical researchers should account for the fact that bidders may respond to this possibility. I present a simple model of repeat auctions, discuss what information can be identified from bidding data, and provide a Monte Carlo simulation of an estimator that addresses this issue. Finally, I examine data on repeat auctions of logging contracts to see whether bidding behavior is consistent with the model. These data could provide a context in which to estimate the model and analyze counterfactual auction policies.PhDEconomicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113433/1/eherrnst_1.pd

Understanding Errors in EIA Projections of Energy Demand

This paper investigates the potential for systematic errors in the Energy Information Administration’s (EIA) widely used Annual Energy Outlook, focusing on the near- to midterm projections of energy demand as measured in physical quantities. Overall, based on an analysis of the EIA’s 22-year projection record, we find a fairly modest but persistent tendency to underestimate total energy demand by an average of 2 percent per year over the one- to five-year projection horizon after controlling for projection errors in gross domestic product, oil prices, and heating/cooling degree days. For the 14 individual fuels/consuming sectors routinely reported by the EIA, we observe a great deal of directional consistency in the error patterns over time, ranging up to 7 percent per year. Electric utility renewables, electric utility natural gas, transportation distillate, and residential electricity all show significant biases, on average, across the full five year projection horizon examined. Projections for certain other fuels/consuming sectors have significant unexplained errors for selected time horizons. Independent evaluation of this type can be useful for validating ongoing analytic efforts and for prioritizing future model revisions.EIA, energy forecasting, bias

www.hks.harvard.edu/m-rcbg/heep Weather, Salience of Climate Change and Congressional Voting

The Harvard Environmental Economics Program (HEEP) develops innovative answers to today’s complex environmental issues, by providing a venue to bring together faculty and graduate students from across Harvard University engaged in research, teaching, and outreach in environmental and natural resource economics and related public policy. The program sponsors research projects, convenes workshops, and supports graduate education to further understanding of critical issues in environmental, natural resource, and energy economics and policy around the world. Acknowledgements The Enel Endowment for Environmental Economics at Harvard University provides major support for HEEP. The Endowment was established in February 2007 by a generous capital gift from Enel SpA, a progressive Italian corporation involved in energy production worldwide. HEEP receives additional support from the affiliated Enel Foundation. HEEP also receives support from the Alfred P. Sloan Foundation, the James M. and Cathleen D. Stone Foundation, Bank of America, Chevron Services Company, Duke Energy Corporation, and Shell. HEEP enjoys an institutional home in and support from the Mossavar-Rahmani Center for Business and Government at the Harvard Kennedy School. HEEP collaborates closely with th

Drilling Deadlines and Oil and Gas Development

Oil and gas leases between mineral owners and extraction firms typically specify a date by which the firm must either drill a well or lose the lease. These deadlines are known as primary terms. Using data from the Louisiana shale boom, we first show that well drilling is substantially bunched just before the primary term deadline. This bunching is not necessarily surplus-reducing: using an estimated model of firms' drilling and input choices, we show that primary terms can increase total surplus by countering the effects of leases' royalties, as royalties are a tax on revenue and delay drilling. These benefits are reduced, however, when production outcomes are sensitive to drilling inputs and when drilling one well indefinitely extends the period of time during which additional wells may be drilled. We enrich the model to consider mineral owners' lease offers and find small effects of primary terms on owners' revenue

Understanding errors in EIA projections of energy demand

This paper investigates the potential for systematic errors in the Energy Information Administration's (EIA) widely used Annual Energy Outlook, focusing on the near- to mid-term projections of energy demand. Based on analysis of the EIA's 22-year projection record, we find a fairly modest but persistent tendency to underestimate total energy demand by an average of 2 percent per year after controlling for projection errors in gross domestic product, oil prices, and heating/cooling degree days. For 14 individual fuels/consuming sectors routinely reported by the EIA, we observe a great deal of directional consistency in the errors over time, ranging up to 7 percent per year. Electric utility renewables, electric utility natural gas, transportation distillate, and residential electricity show significant biases on average. Projections for certain other sectors have significant unexplained errors for selected time horizons. Such independent evaluation can be useful for validating analytic efforts and for prioritizing future model revisions.EIA Energy forecasting Bias