The consumer response to gasoline price changes [electronic resource] : empirical evidence and policy implications

When gasoline prices rise, people notice: the news is filled with reports of pinched household budgets and politicians feeling pressure to do something to ameliorate the burden. Yet, raising the gasoline tax to internalize externalities is widely considered by economists to be among the most economic efficiency-improving policies we could implement in the transportation sector. This dissertation brings new evidence to bear on quantifying the responsiveness to changing gasoline prices, both on the intensive margin (i.e., how much to drive) and the extensive margin (i.e., what vehicles to buy). I assemble a unique and extremely rich vehicle-level dataset that includes all new vehicle registrations in California 2001 to 2009, and all of the mandatory smog check program odometer readings for 2002 to 2009. The full dataset exceeds 49 million observations. Using this dataset, I quantify the responsiveness to gasoline price changes on both margins, as well as the heterogeneity in the responsiveness. I develop a novel structural model of vehicle choice and subsequent utilization, where consumer decisions are modeled in a dynamic setting that explicitly accounts for selection on unobserved driving preference at both the time of purchase and the time of driving. This utility-consistent model allows for the analysis of the welfare implications to consumers and government of a variety of different policies, including gasoline taxes and feebates. I find that consumers are responsive to changing gasoline prices in both vehicle choice and driving decisions, with more responsiveness than in many recent studies in the literature. I estimate a medium-run (i.e., roughly two-year) elasticity of fuel economy with respect to the price of gasoline for new vehicles around 0.1 for California, a response that varies by whether the vehicle manufacturer faces a tightly binding fuel economy standard. I estimate a medium-run elasticity of driving with respect to the price of gasoline around -0.15 for new personal vehicles in the first six years. Older vehicles are driven much less, but tend to be more responsive, with an elasticity of roughly -0.3. I find that the vehicle-level responsiveness in driving to gasoline price changes varies by vehicle class, income, geographic, and demographic groups. I also find that not including controls for economic conditions and not accounting for selection into different types of new vehicles based on unobserved driving preference tend to bias the elasticity of driving away from zero -- implying a greater responsiveness than the true responsiveness. This is an important methodological point, for much of the literature estimating similar elasticities ignores these two issues. These results have significant policy implications for policies to reduce gasoline consumption and greenhouse gas emissions from transportation. The relatively inelastic estimated responsiveness on both margins suggests that a gasoline tax policy may not lead to dramatic reductions in carbon dioxide emissions, but is a relatively non-distortionary policy instrument to raise revenue. When the externalities of driving are considered, an increased gasoline tax may not only be relatively non-distortionary, but even economic efficiency-improving. However, I find that the welfare changes from an increased gasoline tax vary significantly across counties in California, an important consideration for the political feasibility of the policy. Finally, I find suggestive evidence that the ``rebound effect'' of a policy that works only on the extensive margin, such as a feebate or CAFE standards, may be closer to zero than the elasticity of driving with respect to the price of gasoline. This suggestive finding is particularly important for the analysis of the welfare effects of any policy that focuses entirely on the extensive margin.

Keywords: Management Science and Engineering
Advisor: Sweeney James L. primary advisor. Thesis advisor
Goulder Lawrence H. (Lawrence Herbert) advisor. Thesis advisor
Harding Matthew C. advisor. Thesis advisor
Weyant John P. (John Peter) advisor. Thesis advisor