Estimating The Travel Behavior Effects of Technological Innovations From Cross-Sectional Observed Data: Applications To Carsharing And Telecommuting

This dissertation estimates effects on travel behavior of two specific technological innovations – emerging shared mobility services and telecommuting – using publicly available travel surveys. These surveys are cross-sectional and observational in nature, which leads to the potential for (1) selection bias due to observed and unobserved differences in characteristics between program participants and non-participants; and (2) reverse causality bias arising because of potential influence of the travel behavior outcome of interest on the propensity to enroll in the program. The researcher's methodological framework combines established methods from both statistical and econometric literature to draw causal inferences. The key innovations in this dissertation are the combination of diverse methods to address the joint occurrence of various biases, and their specific empirical applications. The researcher also compares the results of alternative methods.

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