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To reduce local air pollution and greenhouse gas emissions from the transportation sector, governments in the U.S. and elsewhere have introduced various policy instruments including taxes, subsidies, and technology standards to reduce oil consumption from passenger transport. My dissertation aims to empirically evaluate the cost-effectiveness of certain programs that intend to increase the fleet fuel economy including consumer subsidies for adopting alternative fuel vehicles (AVFs) and the Corporate Average Fuel Economy (CAFE) Standards imposed on manufacturers. The dissertation is comprised of three chapters. Chapter 1 studies the impact of income tax credit for electric vehicle (EV) purchases and compare its cost-effectiveness with an alternative policy that subsidies charging stations when indirect network effects exist in the market. Chapter 2 estimates consumer vehicle demand using random coefficient discrete choice model and examines the substitution pattern of EVs with other fuel types, which helps assessing the environmental benefits of policies that subsidize EVs. Chapter 3 investigates the differential treatment between light trucks and passenger cars in CAFE standards and estimates to what extent does the standard split undermine the policy goal of increasing the average fleet fuel economy while achieving the redistributional goals.

Plug-in electric vehicles (EVs) offer great potential in reducing local air pollution and carbon emissions and in alleviating dependency on fossil fuel. However, there are significant barriers to the diffusion process of this new technology. The EV market features indirect network effects (or the chicken-and-egg problem) in that consumers may be reluctant to adopt EVs with the lack of public charging stations while investors are less willing to build charging stations when the installed base of EVs is small. Indirect network effects could amplify shocks whether negative or positive through feedback loops and therefore could slow down or speed up the diffusion process. Using a data set of quarterly EV sales in 353 metro areas from 2011 to 2013, this paper provides the first empirical analysis on the importance of indirect network effects in this market: a 10% increase in the number of charging stations would increase the EV sales by 10.8% while a 10% growth in the EV stock would lead to a 5.8% increase in the number of charging stations. Our simulation results find that the current federal tax credits of up to $7,500 have contributed to 48.5% of the EV sales during 2011-2013, with indirect network effect explaining 42% of that sales increase. The total tax credit of $1.05 billion given out during these three years brought about $0.23 billion in long-term environmental benefits, while a policy of equal-size spending but subsidizing charging station building would be several times more effective.