Estimation of Program Effects from Cross-Sectional Observational Surveys – Case Studies of the Effect on Travel Behavior of the Adoption of (i) Future Mobility Options like Carsharing, and (ii) Telecommuting

This dissertation estimates the 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 nonparticipants; 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 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 results of alternative methods are also compared.


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