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Topics in Energy Issues

Paper Session

Friday, Jan. 5, 2018 10:15 AM - 12:15 PM

Marriott Philadelphia Downtown, Meeting Room 308
Hosted By: Transportation and Public Utilities Group & American Economic Association
  • Chair: Ian Lange, Colorado School of Mines

Analyzing the Risk of Transporting Crude Oil by Rail

Charles F. Mason
,
University of Wyoming

Abstract

The domestic crude oil industry was witnessed a remarkable expansion over the past ten years. Much of the new production occurs in regions not well serviced by existing oil pipelines, and so firms have increasingly turned to rail as a mode of transport. In turn, this has led to concerns related to safety. In response to these safety concerns, the US Department of Transportation (DOT) adopted a new rule governing rail shipments of oil. These observations point to the importance of understanding the risks associated with rail shipments.

In this paper I provide a careful empirical assessment of the risks associated with shipping a given amount of crude by rail. Using data from the department of Transportation, I construct an empirical model that links rail incidents to the quantity of oil shipped by rail. This data includes monthly observations on the number of carloads of crude oil shipped between January 1, 2009 and December 31, 2014, as well as information on safety incidents associated with these shipments. I find a statistically important link between the number of cars containing crude oil shipped by rail in a given month and the distribution of incidents; in particular, increases in shipments are associated with a rightward-sift in the distribution. I find similar effects relating shipments to the volume of oil spilled as well as the dollar damages from spills. These effects are noticeably more important in states where recent increases in oil production – mainly associated with the deployment of unconventional techniques – has been most pronounced.

Emissions Containment in Response to Carbon Market Prices

Dallas Burtraw
,
Resources for the Future
Karen Palmer
,
Resources for the Future
Anthony Paul
,
Resources for the Future
Charlie Holt
,
University of Virginia
William Shobe
,
University of Virginia

Abstract

In every air emissions trading program, there has been downward pressure on allowance prices, and realized prices have been below expected values. Such low prices erode the payoff to clean energy investors while reducing the incentive for more substantial emissions reductions. This downward pressure on prices has been driven largely by faster than expected emissions reductions, which are in turn caused by a number of factors. These factors include innovation and new mitigation options, the implementation of companion policies promoting clean technology, and the voluntary actions of cities, states, and private entities to further reduce emissions. In the short term, the introduction of companion policies alongside an emissions trading program does not drive additional reductions. Instead, it leads to a reduction in allowance prices, making room under the cap for emissions from other sources. This phenomenon is the so-called “waterbed effect,” where pushing emissions down in one place just leads to emissions going up somewhere else, unless administrative action is taken to adjust the cap downwards.

This paper investigates an emissions containment reserve (ECR) that would institute one or a series of soft price steps (potentially above a hard price floor). Each price step would serve as a reserve price for a quantity of allowances that is distributed through auction into the trading program. If the auction clearing price falls below a price step, the associated quantity of allowances would not be sold. The ECR would not determine the market price, but when prices are lower than expected the ECR would support the price by incrementally constraining the supply of allowances. The paper brings three approaches to an investigation of this new market design: analytical modeling of price formation in allowance markets with an ECR, detailed electricity market simulation modeling and behavioral laboratory experiments around allowance auctions.

Granger Causality of Real Oil Prices After the Great Recession

Szilard Benk
,
National Bank of Hungary
Max Gillman
,
University of Missouri-St. Louis

Abstract

Oil prices (WTI) surged to a sustained high level from 2009 through 2014. The magnitude of this real price "shock" compares to that of the height of the second 1970's "oil shock". Then the US inflation rate was at its highest level since 1946; post-2008 it has been subdued. This at first glance seems to rule out monetary causes of the recent oil shock, making it hard to explain. Yet, this paper shows strong Granger causality of nominal and real oil prices by adjusted measures of the US monetary base, M1 and Divisia M1. Without the adjustment, no causality results. The adjustment is to subtract out the short-lived Central Bank Liquidity Swaps of 2008-2009 from the base, M1 and M1 Divisia. These Swaps constituted Fed temporarily borrowing reserves from other Central Banks when their excess reserves turned negative in 2008, during the investment bank panic. With this adjustment, strong causality results hold for monetary aggregates for the entire post 1947 sample and for various sub-periods, including post-2008. In addition, results show that inflation as measured by the CPIE index also Granger causes the real and nominal oil price. These monetary findings extend those of Gillman and Nakov (2009) and Alquist et al. (2013) in which, contrary to Hamilton (1983), inflation and monetary series are found to Granger cause oil prices. This contributes new robust evidence on nominal factors causing oil prices, including during the recent post-Great Recession oil shock period. These results can be important for oil price forecasting. And the paper extends them to gold prices, the oil to gold price ratio, and the US dollar exchange rate index. This demonstrates the importance of monetary factors for benchmark international commodity markets.

Assessing the External Net Benefits of Wind Energy: The Case of Iowa's Wind Farms

T.J. Rakitan
,
Valparaiso University

Abstract

Wind energy infrastructure is often associated with decreases in nearby property values and increases in local incomes. However, these impacts are measured at different geographic scales, prompting the question of how the external net benefits of wind infrastructure are distributed over space. Using restricted-access income microdata and address-level house value information from county assessor records, I estimate the impact of utility-scale wind energy infrastructure (“wind farms”) on both incomes and property values at the same geographic scale in northwest Iowa. I use a difference-in-differences approach that exploits the staggered installation times of Iowa’s major wind farms, estimating changes in incomes and house values as a function of wind energy infrastructure attributes following the analysis of Roback (1982), Rosen (1979) and others. I find that county-level income effects reported in the literature do not appear to hold at the household level, while house value growth is not significantly different based on proximity to wind farms. This suggests that county- or region-specific attributes correlated with wind energy placement are driving existing results.
Discussant(s)
Richard Melstrom
,
Loyola University Chicago
Lori Bennear
,
Duke University
Jonathan Lee
,
East Carolina University
Matthew Winden
,
University of Wisconsin-Whitewater
JEL Classifications
  • H0 - General
  • Q4 - Energy