Driving Intensity in California: Exploring Spatial Variation in VMT and its Relationship to the Built Environment

• Environmental and Resource Economics Workshop

Date and Location

Friday, August 10, 2012, 12:30 PM - 1:30 PM
ARE Conference Room, 2102 Social Sciences and Humanities

Abstract

The use of personal vehicles in the United States accounts for a significant amount of the nation’s energy consumption and is also a major source of carbon emissions. Concerns about air pollution and climate change have prompted many local and regional governments to consider a variety of policies to reduce vehicle dependence, including higher gasoline taxes and changes in urban design. While much effort has been put into understanding how these variables affect travel demand, limitations in data quality and availability have resulted in a lack of convincing empirical conclusions. This paper aims to inform the policy discussion by examining spatial variation in vehicle miles traveled (VMT) and fuel consumption across zip codes in California. The analysis is based on a very large and highly unique dataset containing vehicle-level estimates of VMT. Aggregating these estimates by the home zip code of the vehicle and combining them with data on land use, demographics, fuel prices and other economic variables, a reduced-form analysis is conducted to estimate elasticities for VMT and fuel consumption with respect to fuel prices and the built environment. The zip code level data used in the analysis incorporates estimates of VMT for more than 20 million vehicles in 2005 based on odometer readings from California’s SmogCheck program. These estimates are directly measured rather than reported via survey and also provide insights into the distribution of VMT within each zip code due to the large number of vehicles included. Regression analysis shows that zip codes with higher mean incomes have lower median VMT and fuel consumption on average, while zip codes with newer housing units have higher VMT. To examine the relationship between density and VMT/fuel consumption, multiple measures of density are used, including population density, housing density, vehicle density and spatial development density data from the USGS National Land Cover Database. Controlling for income, region, fuel prices, average commute time and the prevalence of alternative modes of transportation, higher levels of density result in lower median VMT and smaller standard deviations for VMT within zip codes. The final piece of the analysis examines the impact of fuel prices on VMT and fuel consumption and also estimates the effects of a change in the fuel tax.

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