The Energy and Environmental Effects of New and Future Mobility: Econometric and Simulation Analysis of Ridesourcing Services Uber and Lyft

This thesis provides an initial understanding of the potentially fundamental changes to the way passenger vehicle transportation in the United States (U.S.) is changing given the introduction of ridesourcing via transportation network companies (TNCs), like Uber and Lyft, and the effects those changes have on energy and environmental outcomes. First, in a set of two complementary studies, I employ real-world data and econometric modeling to assess the impacts that TNCs have already had on U.S. states and urban areas. In the first study (Chapter 2), I focus on thestate level, where relevant data are publicly available to estimate TNC market entry effects on vehicle registrations, gasoline use, vehicle miles traveled, and air pollutant emissions. I find an average decrease in vehicle registrations and no significant effect on other outcomes. In the second study (Chapter 3), I assess TNC effects on vehicle fleet composition (total registrations and fuel economy) and transit ridership at the urban area level and find evidence that TNC entry causes an average 0.7% increase in vehicle registrations and no average effect on overall fleet efficiency or transit ridership. The difference in state- and urban area-level effects on vehicle registrations is due, in part, to heterogeneity in the effects of TNC entry on different cities: I employ heterogeneous treatment effect, clustering, and regression interaction analysis and findsignificant heterogeneity across urban areas. TNC entry tends to increase vehicle ownership in urban areas with higher initial vehicle ownership and lower population growth rates, TNC entry tends to increase vehicle ownership, increase overall fleet efficiency more in urban areas withlower childless household rates, and increase transit ridership more in urban areas with lower average incomes and childless household rates. Where the first two studies look at aggregate past changes to the transportation system attributable to TNCs from the top down using observableindicators at the aggregate state and urban area levels, a third study in Chapter 4 considers a similar set of outcomes but focused at the vehicle level. I propose and apply a framework to quantify the external costs and benefits of TNC disruption to the transportation energy system bysystematically characterizing the avoided cold start emissions and additional non-revenue miles and associated emissions and quantifying the relative size of external benefits and costs from TNC vehicles for several of the largest TNC markets in the U.S. and find that shifting travelfrom private vehicles to TNCs offers net external air pollutant benefits in some areas while incurring a net external cost in others; however, including externalities associated with additional vehicular travel yields net external costs everywhere. Taken together, these three studies confirmthat TNCs have already affected the number and efficiency of vehicles owned and transit ridership rates in the U.S. and that they have done so heterogeneously as a function of preexisting socioeconomic and passenger travel characteristics. And, at the individual TNC trip level, targeted sensitivity and policy analyses to illustrate how transportation and urban planning decisions can increase net external benefits and/or reduce negative external costs.