Assessment of Fuel Economy Technologies for Medium and Heavy ...

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1. Indirect Costs and Benefits Little, if any, previous research has directly investigated the effects of commercial vehicle fuel economy standards on the factors addressed in these papers. There is a considerable amount of literature that can inform a general assessment of potential effects. The specific effects, however, depend greatly on how the fuel economy regulation is structured, as well as on external issues such as fuel prices, economic trends, and technology development. Therefore, the approach taken in this paper is to develop hypothetical scenarios that allow for examine what would happen given various fuel economy regulation structures and other key factors. The objective is to provide a ―what-if‖ assessment of the impact on fuel economy regulations on performance, congestion, costs, etc., rather than a definitive assessment of impacts. At a minimum, this will help determine whether or not each issue is significant enough to warrant consideration in designing a commercial vehicle fuel economy standard. Each issue is addressed in the following format: Key question – What is the key question of interest that is being investigated Background – What does the literature have to say relevant to this issue Approach – What quantification method was used to estimate potential impacts related to the key question What key assumptions are made in the analysis Findings – What are the results of the analysis under alternative hypothetical scenarios generated for this report – i.e., what impact could commercial vehicle fuel economy standards potentially have on VMT and the rebound effect, vehicle class shifting, etc. (ii) Vehicle-Miles Traveled (VMT) and the Rebound Effect Key Question: If fuel economy improvements reduce vehicle operating costs, will truck traffic volume increase Background: A ―rebound effect‖ in heavy-duty vehicle travel can be characterized as the extent to which cost savings from heavy-duty vehicle fuel efficiency improvements result in increased demand for truck shipping and decreased demand for rail shipping because truck travel is made less expensive per-mile due to reduced fuel costs and therefore reduced truck operating costs. This increased truck travel partially offsets the total fuel savings benefits. The rebound effect has been extensively studied for light-duty (personal) vehicle travel, but somewhat less so for freight truck travel. 1 However, a number of studies have documented relationships between price and demand for truck travel. This literature is focused on long-haul freight truck movements because 1) the effect is likely to be strongest for long-haul movements (due to available modal competition); 2) these movements represent the carriage of a significant volume of the nation‘s freight; and 3) these movements account for the vast majority of the medium- and heavy-duty 1 The National Highway and Traffic Safety Administration (NHTSA), in its preliminary regulatory impact assessment for the CAFE standards rulemaking, selected a value of 15 percent as their best estimate, based on a review of the literature. The assessment also concluded that this effect could plausibly range from 10 to 20 or even 25 percent (NHTSA, 2008). - 4 -
vehicle fuel consumption (78 percent). 2 Little or no research exists to provide information on a rebound effect for medium-duty trucks. The sketch analysis presented herein will focus on long haul trucks, which are generally Class 8 trucks with 53-foot trailers and a gross vehicle weight (GVW) of up to 80,000 pounds. Caution should be exercised when considering the price-demand relationships found in the literature for freight trucks. The results appear to be heavily reliant on factors including the type of demand measures analyzed (vehicle-miles of travel, ton-miles, or tons), analysis geography, trip lengths, markets served, and commodities transported. 3 The literature does not treat differences between short- and long-run effects consistently, and, in general, presents inconsistent results across studies. To provide an envelope of potential effects, the analysis presented herein provides reasonable upper and lower bounds of potential effects as well as a mid-point or ―likely‖ estimate. An additional issue is the difference between the average and marginal per-mile cost of truck shipping. The marginal cost considers only the fuel savings. The average cost also considers any increase in the capital cost of the vehicle, amortized over the lifetime of the vehicle. For the purposes of this assessment it is assumed that vehicle owners will pass these capital costs along to their customers, and therefore it is the average (net) cost or cost savings that is important. The rebound effect in heavy-duty vehicles works in three ways. The first two have been measured and characterized with price elasticities while the third is speculative: An increase in overall demand for truck shipping, if total shipping costs are reduced (the selfprice elasticity effect); A shift of some commodities from other modes (especially rail) to truck due to lower truck shipping costs (the cross-price elasticity effect); and Less efficient utilization of trucks (e.g., lighter loads), because lower costs reduce cost pressures on industry to maximize efficiency. The self-price elasticity provides a measure for describing how the volume of truck shipping (demand) changes with its price while the cross-price elasticity provides a measure for describing how the volume of rail shipping changes with truck price. In general, an elasticity describes the percent change in one variable (e.g. demand for trucking) in response to a percent-change in another (e.g. price of truck operations). For example, a price elasticity of truck demand with respect to truck prices (self-price elasticity) of -0.5 implies that the demand for trucking will grow by 5 percent if truck operations costs decrease by 10 percent (+5 percent change in truck demand/-10 percent change in truck cost = -0.5). Similarly, a cross-price elasticity of rail demand with respect to truck prices (cross-price elasticity) of 0.5 implies that the demand for rail will decrease by 5 percent if truck operations costs decrease by 10 percent (-5 percent change in rail demand/-10 percent change in truck price = 0.5). 2 Oak Ridge National Laboratory, Transportation Energy Data Book, Edition 28, prepared for the US Department of Energy, 2009. See table 5.4 for relevant data. 3 Graham and Glaister, ―Road Traffic Demand Elasticity Estimates: A Review,‖ Transport Reviews Volume 24, 3, pp. 261-274, 2004 and Oum, Waters, and Jong Say Yong, ―A Survey of Recent Estimates of Price Elasticities of Demand for Transport,‖ prepared for the World Bank, Infrastructure and Urban Development Department, January 1990. - 5 -
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