David L. Greene

Energy efficiency and consumption : the rebound effect : a survey

Abstract Technology policies are one of the options available for the reduction of carbon emissions and the usage of energy. However, gains in the efficiency of energy consumption will result in an effective reduction in the per unit price of energy services. As a result, consumption of energy services should increase (i.e., “rebound” or “take-back”), partially offsetting the impact of the efficiency gain in fuel use. Definitions of the “rebound” effect vary in the literature and among researchers. Depending on the boundaries used for the effect, the size or magnitude of this behavioral response may vary. This review of some of the relevant literature from the US offers definitions and identifies sources including direct, secondary, and economy-wide sources. We then offer a summary of the available empirical evidence for the effect for various sources. For the energy end uses for which studies are available, we conclude that the range of estimates for the size of the rebound effect is very low to moderate.

Why CAFE worked

The 1975 Energy Policy and Conservation Act established mandatory fuel economy standards for passenger cars and light trucks sold in the US. Since that time the Corporate Average Fuel Economy (CAFE) standards have often been criticized as costly, inefficient, and even unsafe, despite the general absence of direct empirical evidence to support such claims. This paper reviews empirical evidence on the impacts of the CAFE standards and explains why properly designed and executed fuel economy regulations may be preferable to other policies for reducing petroleum dependence and carbon emissions. It appears that the standards substantially achieved their objective of restraining US oil consumption without producing significant negative side-effects because they were set at levels that could be achieved by cost-effective or nearly cost-effective technological innovations.

Vehicles and E85 Stations Needed to Achieve Ethanol Goals

An analysis of the number of stations and vehicles necessary to achieve future goals for sales of ethanol fuel (E85) is presented. Issues related to the supply of ethanol, which may turn out to be of even greater concern, are not analyzed here. A model of consumers’ decisions to purchase E85 versus gasoline based on prices, availability, and refueling frequency is derived, and preliminary results for 2010, 2017, and 2030 consistent with the presidents 2007 biofuels program goals are presented. A limited sensitivity analysis is carried out to indicate key uncertainties in the trade-off between the number of stations and fuels. The analysis indicates that to meet a 2017 goal of 26 billion gallons of E85 sold, on the order of 30% to 80% of all stations may need to offer E85 and that 125 to 200 million flexible-fuel vehicles (FFVs) may need to be on the road, even if oil prices remain high. These conclusions are tentative for three reasons: there is considerable uncertainty about key parameter values, such as the price elasticity of choice between E85 and gasoline; the future prices of E85 and gasoline are uncertain; and the method of analysis used is highly aggregated—it does not consider the potential benefits of regional strategies or the possible existence of market segments predisposed to purchase E85. Nonetheless, the preliminary results indicate that the 2017 biofuels program goals are ambitious and will require a massive effort to produce enough FFVs and ensure widespread availability of E85.

Promoting the Market for Plug-In Hybrid and Battery Electric Vehicles: Role of Recharge Availability

Much recent attention has been drawn to providing adequate recharge availability as a means to promote the battery electric vehicle (BEV) and plug-in hybrid electric vehicle (PHEV) market. The possible role of improved recharge availability in developing the BEV-PHEV market and the priorities that different charging options should receive from the government require better understanding. This study reviews the charging issue and conceptualizes it into three interactions between the charge network and the travel network. With travel data from 3,755 drivers in the National Household Travel Survey, this paper estimates the distribution among U.S. consumers of (a) PHEV fuel-saving benefits by different recharge availability improvements, (b) range anxiety by different BEV ranges, and (c) willingness to pay for workplace and public charging in addition to home recharging. With the Oak Ridge National Laboratory MA3T model, the impact of three recharge improvements is quantified by the resulting increase in BEV-PHEV sales. Compared with workplace and public recharging improvements, home recharging improvement appears to have a greater impact on BEV-PHEV sales. The impact of improved recharging availability is shown to be amplified by a faster reduction in battery cost.

Fuel Economy: The Case for Market Failure

This chapter argues that uncertainty combined with loss aversion by consumers is sufficient to explain the failure to adopt cost effective energy efficiency improvements in the market for automotive fuel economy, although other market failures appear to be present as well. Consumers are known to be loss averse as a general rule. Furthermore, consumers’ preferences for future fuel savings versus present wealth are certain to be “fuzzy” as required by the theory of loss aversion. The net present value of an investment of an investment in fuel economy is indeed uncertain, and the uncertainty is enhanced by the fact that net value is the difference of two uncertain quantities. The chapter describes how there is evidence that other types of market failures are also present in the market for fuel economy. Nonetheless, it appears that uncertainty plus loss aversion alone are sufficient to induce a significant underinvestment in energy efficiency. Other market failures, such as imperfect information and bounded rationality, almost certainly contribute to or exacerbate the uncertainty/loss aversion market deficiency. External costs, especially carbon dioxide emissions and oil dependence, are critically important market failures because they constitute society’s motivation for seeking solutions to the fuel economy market failure.

The outlook for US oil dependence

Abstract Oil dependence is defined as a dynamic problem of short- and long-run market power. The potential monopoly power of an oil cartel depends on its market share and the elasticities of oil supply and demand, while the economic vulnerability of oil-consuming states depends most directly on the quantity of oil imported and the oil cost share of gross domestic product (GDP). Of these factors, only the market share of the Organization of Petroleum Exporting Countries (OPEC) cartel and the rate of growth of world oil demand are clearly different than they were 25 years ago. OPEC still holds the majority of world oil and, in the future, will regain market share. A hypothetical 2-year supply reduction in 2005–2006, similar in size to those of 1973–1974 or 1979–1980, illustrates the potential benefits to OPEC and harm to the US economy of a future oil price shock. OPECs revenues are estimated to increase by roughly

Future Potential of Hybrid and Diesel Powertrains in the U.S. Light-Duty Vehicle Market

0.7 trillion, while the US economy loses about

TAFV Alternative Fuels and Vehicles Choice Model Documentation

0.5 trillion. Strategic petroleum reserves seem ineffective against a determined, multi-year supply curtailment. Increasing the markets price responsiveness by improving the technologies of oil supply and oil demand can greatly reduce the costs of oil dependence. Each element of this interpretation of the oil dependence problem is well supported by previous studies. This papers contribution is to unite these elements into a coherent explanation and to point out the enormously important implications for energy policy.

Energy futures for the US transport sector

Diesel and hybrid technologies each have the potential to increase light-duty vehicle fuel economy by a third or more without loss of performance, yet these technologies have typically been excluded from technical assessments of fuel economy potential on the grounds that hybrids are too expensive and diesels cannot meet Tier 2 emissions standards. Recently, hybrid costs have come down and the few hybrid makes available are selling well. Diesels have made great strides in reducing particulate and nitrogen oxide emissions, and are likely though not certain to meet future standards. In light of these developments, this study takes a detailed look at the market potential of these two powertrain technologies and their possible impacts on light-duty vehicle fuel economy. A nested multinomial logit model of vehicle choice was calibrated to 2002 model year sales of 930 makes, models and engine- transmission configurations. Based on an assessment of the status and outlook for the two technologies, market shares were predicted for 2008, 2012 and beyond, assuming no additional increase in fuel economy standards or other new policy initiatives. Current tax incentives for hybrids are assumed to be phased out by 2008. Given announced and likely introductions by 2008, hybrids could capture 4-7% and diesels 2-4% of the light-duty market. Based on our best guesses for further introductions, these shares could increase to 10-15% for hybrids and 4- 7% for diesels by 2012. The resulting impacts on fleet average fuel economy would be about +2% in 2008 and +4% in 2012. If diesels and hybrids were widely available across vehicle classes, makes, and models, they could capture 40% or more of the light-duty vehicle market.

Effect of Fuel Economy on Automobile Safety: A Reexamination

A model for predicting choice of alternative fuel and among alternative vehicle technologies for light-duty motor vehicles is derived. The nested multinomial logit (NML) mathematical framework is used. Calibration of the model is based on information in the existing literature and deduction based on assuming a small number of key parameters, such as the value of time and discount rates. A spreadsheet model has been developed for calibration and preliminary testing of the model.