University of California Transportation Center

Automobiles impose considerable public costs in the form of emissions and foreign oil dependence. Public policy has thus taken a considerable interest in influencing the technology and fuel economy associated with new vehicles brought to market. In spite of this interest, there is very limited information on the effectiveness of these policies in reducing greenhouse gas emissions or shifting vehicle demands. This is in part due to the fact that modeling the demand for automobiles is wrought with many challenges. These include large choice sets that change frequently over time and significant data collection obstacles. This work proposes a methodology for data development that simplifies many of the challenges associated with data collection in automotive modeling. The methodology explores a technique to merge data on aggregate sales with disaggregate vehicle holdings data to synthesize a complete dataset that preserves the strengths of both. The merged dataset is used to estimate a logit choice model of automotive choice 2 that is applied in evaluating the effectiveness of hybrid tax credits and the gasoline tax in reducing greenhouse gas emissions. Policy simulations suggest that hybrid tax credits have saved an average 1.5 million metric tons of greenhouse gas emissions based on sales between 2006 and 2007. When considered in conjunction with the cost of the policies, the credits appear to have a cost effectiveness ranging between $1000 to $3000 per metric ton of greenhouse gas emissions reduced. Hybrid tax credits are also found to be more effective than a doubling of the gasoline tax in shifting the new vehicle stock towards more fuel efficient vehicles. Finally, the model evaluates the market willingness to pay for fuel cost reduction. The results suggest an average willingness to pay of $522 in purchase price per 1¢ reduction in fuel cost per mile. This means that reasonable circumstances exist in which some buyers will pay more for fuel economy than they save in fuel cost expenses over the life span of their automobiles.