Studies in the residential self-selection literature, which use attitudinal factors to model the jointness of residential and travel-related choices, assume a unidirectional impact from attitudes to behavior; however, such an assumption may be violated under several circumstances. In this current study, we allow the error terms of the attitudinal factors to be correlated with the main outcomes as we jointly model residential choice, auto-ownership level, and rank-based modal preferences. In our joint model, we use green lifestyle propensity and luxury lifestyle propensity as the two stochastic latent constructs. The empirical data for this study is drawn from the 2019 multi-city Transformative Technologies in Transportation survey for the city of Austin that elicited information with respect to individuals’ residential location, auto-ownership, and modal preferences through a stated preference experiment in a futuristic autonomous vehicle environment. Results indicate significant unobserved correlations between the latent constructs and the main outcomes; ignoring such endogeneity leads to underestimations of the “true” causal effect of high-density neighborhood (HDN) living on travel-related choices, which can have consequences for policy-making. In our analysis, the “true” causal effect of HDN living on auto-ownership suggests that, on average, the auto-ownership level would reduce by about 29% when an individual is shifted from a non-HDN to a HDN. Furthermore, the probability of using the bicycle mode for non-work pursuits is estimated to increase by 8%, and that of using a private vehicle is estimated to decrease by 3.1%, when individuals are moved from a non-HDN to a HDN.


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    Title :

    Investigating Residential Built Environment Effects on Rank-Based Modal Preferences and Auto-Ownership


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2023-04-04




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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