Date of Award


Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)


Resource Economics and Policy


Jonathan Rubin

Second Committee Member

Kathleen P. Bell

Third Committee Member

Mario Teisl


Passenger vehicle use contributes significantly to energy consumption, criteria air pollution and greenhouse gas (GHG) emissions. Recent developments in Geographic Information Systems (GIS) and Vehicle Identification Number (VIN) decoding enable researchers to make use of vehicle registration records to consider the spatial distribution of the vehicle fleet when modeling emissions. In this thesis, these techniques are used to view spatial variation in passenger vehicle attributes and environmental characteristics. The distributions of vehicle type, make and model, size, age, criteria and GHG emission rates, and fuel economy are analyzed. Next, the spatial distribution of private costs and benefits resulting from a hypothetical 30 percent increase in Corporate Average Fuel Economy (CAFE) standards are modeled to demonstrate how spatial information may be used to expand and improve an economic analysis of transportation policy. A complete set of vehicle registration records from the state of Maine, VIN decoding, the EPA Mobile 6.2 emission factor model, and fuel economy technology cost curves are used in conjunction with a GIS to create a series of thematic maps. Spatial variation in vehicle attributes and environmental characteristics is found to lead to significant spatial variation in the impacts resulting from an increase in CAFE standards. Communities that on average receive the greatest net private benefits are typically rural and have lower median household incomes. The spatial distribution of the net present value of the benefits between high and low income areas may be tempered given evidence in the literature that lower income households discount future savings at a higher rate than higher income households. Increasing fuel economy, which reduces the costs of driving, also increases vehicle miles traveled resulting in greater annual criteria emission rates. The largest increase in criteria emission rates are in vehicles from rural towns where the largest increases in fuel economy occur. The significance of the spatial patterns observed are statistically tested using Moran's I and most are found to be significant at the 1% significance level. The finding that the lowest income areas of the state receive the greatest net benefits suggests that increasing CAFE standards may be considered a progressive policy and a better choice than an equivalent gas tax which is generally considered to be regressive.

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