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Should Automobile Fuel Economy Standards be Tightened?

Carolyn Fischer, Winston Harrington and Ian W.H. Parry

Year: 2007
Volume: Volume 28
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol28-No4-1
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This paper develops analytical and numerical models to explain and estimate the welfare effects of raising Corporate Average Fuel Economy (CAFE) standards for new passenger vehicles. The analysis encompasses a wide range of scenarios concerning consumers valuation of fuel economy and the full economic costs of adopting fuel-saving technologies. It also accounts for, and improves estimates of, CAFE's impact on externalities from local and global pollution, oil dependence, traffic congestion and accidents. The bottom line is that it is difficult to make an airtight case either for or against tightening CAFE on pure efficiency grounds, as the magnitude and direction of the welfare change varies across different, plausible scenarios.

The Rebound Effect for Passenger Vehicles

Joshua Linn

Year: 2016
Volume: Volume 37
Number: Number 2
DOI: 10.5547/01956574.37.2.jlin
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The United States and many other countries are dramatically tightening fuel economy standards for passenger vehicles. Higher fuel economy reduces per-mile driving costs and may increase miles traveled, known as the rebound effect. The magnitude of the elasticity of miles traveled to fuel economy is an important parameter in welfare analysis of fuel economy standards, but all previous estimates from micro data impose at least one of three behavioral assumptions: (a) fuel economy is uncorrelated with vehicle and household attributes; (b) for multi-vehicle households, each vehicle can be treated as an independent observation in statistical analysis; and (c) the effect of gasoline prices on vehicle miles traveled is inversely proportional to the effect of fuel economy. Two approaches to relaxing these assumptions yield a large estimate of the rebound effect; a one percent fuel economy increase raises driving 0.2 or 0.4 percent, depending on the approach, but the estimates are not statistically significantly different from one another.

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