Abstract: The market for plug-in electric vehicles (EVs) exhibits indirect network effects in that there is interdependence between consumer decision of EV purchase and investor decision of charging station deployment. Through a stylized model, we demonstrate that indirect network effects on both sides of the market lead to feedback loops which could amplify shocks and alter the diffusion process of the new technology. The relative strength of indirect network effects on the two sides of the market has important implications on policy design. Based on quarterly EV sales and charging station deployment in 353 Metro areas from 2011 to 2013, our empirical analysis finds indirect network effects on both sides of the market with those on the EV demand side being stronger. The federal income tax credit of up to $7,500 for EV buyers contributed to 40% of the EV sales during 2011-2013 with feedback loops explaining 40% of that increase. A policy of equal-sized spending but subsidizing charging station deployment would have been more than twice as effective in promoting EV adoption.
"Cars or Trucks? The Impact of Discrete Attribute Basing in Fuel Economic Regulations"(Job Market Paper)
Abstract: Attribute basing is a common regulatory strategy in environmental regulations: in an effort to reduce the externality-generating dimension of a product, regulations impose standards whose stringency is based on a secondary attribute. This study provides empirical evidence of the welfare consequences of attribute basing in the context of U.S. Corporate Average Fuel Economy (CAFE) standards. Throughout the history of CAFE, the policy stringency has been based on a discrete attribute: the classification of vehicles as either passenger cars or light trucks, with the latter being subject to a less stringent target. This differential treatment of cars and trucks has perverse implications as it potentially distorts the fleet composition and increases the tailpipe emissions and accident-related externalities due to a larger market share of light trucks. By estimating a structural model of vehicle demand and supply incorporating CAFE credit trading, this study simulates a counterfactual scenario by removing the standard split and finds that attribute basing results in a 4.9% increase in the sales of light trucks and a corresponding social welfare loss that translates into $2.83 billion in 2014. Attribute basing also leads to welfare redistribution among automakers: the U.S. domestic firms benefit from the attribute basing with a profit increase of 1.8% at the expense of Asian and European automakers with a profit loss of 1.5% and 4.0% respectively.
Abstract: Several alternative fuel vehicle technologies such as flex-fuel vehicles, hybrid vehicles, and plug-in electric vehicles, have been introduced into the mass market during the past two decades amid the heightened concern over the oil dependence and dramatic run-up of gasoline prices. To promote the diffusion of these technologies, governments at various levels in the U.S. and elsewhere have provided incentives to both consumers and automakers such as tax incentives for consumer vehicle purchase and favorable treatment in the compliance of Corporate Average Fuel Economy Standards. There is a now a large body of literature that examines these policies. This article aims to provide a critical review of the recent findings on the impacts of the fiscal policies to promote alternative fuel vehicles with a focus on the U.S. but also drawing evidence from other regions. Particular attention is paid to questions regarding cost-effectiveness, policy design, and comparison with alternative polices such as the gasoline tax.
Abstract: Emissions reductions from incentivizing electric vehicles (EVs) hinge on the emissions of vehicles that EVs replace: the smaller the relative difference in emissions between EVs and vehicles households would have bought in the absence of incentives, the lower the emissions reductions. Estimating the emissions consequences from incentives for EVs therefore depends on how consumers substitute between vehicles of different fuel types and emissions ratings. Using a household-level mixed logit model, we estimate these substitution patterns by combining detailed micro and macro data on new auto- mobile purchases between 2010-2014, a period of rapid growth of EV sales. With our estimates, we show which types of vehicles EVs are replacing, and we estimate how these substitution patterns translate into emissions reductions from various incentives for EVs.
“Who pays to subsidize ZEVs? Examining the welfare impacts of ZEV mandate.” (in progress)
“Local Protection and Subsidy for Electric Vehicles in China.” (in progress)
Jianwei Xing, Assistant Professor of Economics, National School of Development, Peking University