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Will Corporate Average Fuel Economy (CAFE) Standard help? Modeling CAFE's impact on market share of electric vehicles.

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Title: Will Corporate Average Fuel Economy (CAFE) Standard help? Modeling CAFE's impact on market share of electric vehicles.
Authors: Sen, Burak1, Noori, Mehdi2, Tatari, Omer1 tatari@ucf.edu
Source: Energy Policy. Oct2017, Vol. 109, p279-287. 9p.
Subject Terms: *Energy economics, *Electric vehicles, Traffic safety, Market share
Geographic Terms: United States
Abstract: The purpose of Corporate Average Fuel Economy (CAFE) Standards is to enhance the fuel efficiency of passenger vehicles in the United States. Although these standards had been set constant for years, the National Highway Traffic Safety Administration (NHTSA) set increasing CAFE standards in 2011 based on vehicle's footprint, requiring vehicle manufacturers to improve the fuel economy of the vehicles they produce. This resulting improvement in vehicle fuel economy is likely to influence consumers’ decisions regarding new vehicle purchases, while the stringent CAFE standards are also likely to affect manufacturers’ production costs and benefits. In addition, the government provides various incentives to support the adoption of alternative fuel vehicles (AFVs), including electric vehicles (EVs), which in turn will likewise influences consumers’ decisions regarding purchasing a new vehicle. An agent-based model is developed in this paper to estimate the potential future market shares of EVs considering the existing inherent uncertainties under different policy scenarios, including the footprint-based CAFE regulation. The results show that, if implemented effectively in conjunction with the available government incentives, the CAFE regulation can accelerate EV market penetration and help the U.S. to move away from conventional vehicles, thus reducing fossil fuel dependency. [ABSTRACT FROM AUTHOR]
Copyright of Energy Policy is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: The purpose of Corporate Average Fuel Economy (CAFE) Standards is to enhance the fuel efficiency of passenger vehicles in the United States. Although these standards had been set constant for years, the National Highway Traffic Safety Administration (NHTSA) set increasing CAFE standards in 2011 based on vehicle's footprint, requiring vehicle manufacturers to improve the fuel economy of the vehicles they produce. This resulting improvement in vehicle fuel economy is likely to influence consumers’ decisions regarding new vehicle purchases, while the stringent CAFE standards are also likely to affect manufacturers’ production costs and benefits. In addition, the government provides various incentives to support the adoption of alternative fuel vehicles (AFVs), including electric vehicles (EVs), which in turn will likewise influences consumers’ decisions regarding purchasing a new vehicle. An agent-based model is developed in this paper to estimate the potential future market shares of EVs considering the existing inherent uncertainties under different policy scenarios, including the footprint-based CAFE regulation. The results show that, if implemented effectively in conjunction with the available government incentives, the CAFE regulation can accelerate EV market penetration and help the U.S. to move away from conventional vehicles, thus reducing fossil fuel dependency. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Energy Policy is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.enpol.2017.07.008
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        Text: English
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      – SubjectFull: Electric vehicles
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      – SubjectFull: Traffic safety
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      – SubjectFull: Market share
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              Text: Oct2017
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