Empirical distributions of vehicle use and fuel efficiency across space: Implications of asymmetry for measuring policy incidence

Concerns about local air pollution and climate change have prompted all levels of government to consider a variety of policies to reduce vehicle dependence and fuel consumption, as the transportation sector is one of the largest sources of local and global emissions. Because many of the policy options under consideration are market-based (e.g., gasoline tax, carbon tax), it is important to consider how the impacts would vary across space and affect different subpopulations. Evaluating incidence is relevant for both the expected costs and benefits of a particular policy, however detailed data on vehicle-miles traveled (VMT) and fuel consumption allowing for the distributions of these variables to be estimated at a fine geographic scale is rarely available. This paper uses a unique dataset with more than 20. million vehicles in California to derive estimates of VMT and fuel consumption in order to examine the spatial distribution of impacts for an increase in the price of gasoline as well as the consequences of using different statistics for policy evaluation. Results show that VMT and fuel consumption distributions are not symmetrically distributed and vary significantly within transportation planning regions. To understand the potential implications of this asymmetry, we do a back of the envelope comparison using the mean and mode of the VMT or fuel consumption distribution for policy analysis. We find that assuming a symmetric distribution can lead to a divergence of 20-40% from the estimates based on the empirical distribution. Our results, therefore, introduce caution in interpreting the incidence of policies targeting the transportation sector based on averages.