In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete-continuous model system formulated in this study explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e., self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components. The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation approaches for joint discrete-continuous model systems. The model system, when applied to simulate the impacts of a doubling in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.

Activity-travel behavior research has hitherto focused on the modeling and understanding of daily time use and activity patterns and resulting travel demand. In this particular paper, an analysis and modeling of weekly activity-travel behavior is presented using a unique multi-week activity-travel behavior data set collected in and around Zurich, Switzerland. The paper focuses on six categories of discretionary activity participation to understand the determinants of, and the inter-personal and intra-personal variability in, weekly activity engagement at a detailed level. A panel version of the Mixed Multiple Discrete Continuous Extreme Value model (MMDCEV) that explicitly accounts for the panel (or repeated-observations) nature of the multi-week activity-travel behavior data set is developed and estimated on the data set. The model also controls for individual-level unobserved factors that lead to correlations in activity engagement preferences across different activity types. To our knowledge, this is the first formulation and application of a panel MMDCEV structure in the econometric literature. The analysis suggests the high prevalence of intra-personal variability in discretionary activity engagement over a multi-week period along with inter-personal variability that is typically considered in activitytravel modeling. In addition, the panel MMDCEV model helped identify the observed socioeconomic factors and unobserved individual specific factors that contribute to variability in multi-week discretionary activity participation.

This paper presents a joint model of residential neighborhood type choice and bicycle ownership. The objective is to isolate the true causal effects of the neighborhood attributes on household bicycle ownership from spurious association due to residential self-selection effects. The joint model accounts for residential self-selection due to both observed socio-demographic characteristics and unobserved preferences. In addition, the model allows for differential residential self-selection effects across different socio-demographic segments. The model is estimated using a sample of more than 5000 households from the San Francisco Bay Area. Further, a policy simulation analysis is carried out to estimate the impact of neighborhood characteristics and socio-demographics on bicycle ownership.The model results show a substantial presence of residential self-selection effects due to observed socio-demographics such as number of children, dwelling type, and house ownership. It is shown for the first time in the self-selection literature that ignoring such observed selfselection effects may not always lead to overestimation of the impact of neighborhood attributes on travel related choices such as bicycle ownership. In the current context, ignoring selfselection due to socio-demographic attributes resulted in an underestimation of the impact of neighborhood attributes on bicycle ownership. In the context of unobserved factors, no significant self-selection effects were found. However, it is recommended to test for such effects as well as heterogeneity in such effects before concluding that there are no unobserved factors contributing to residential self-selection.

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