A Structured Logit Model of Auto Ownership and Mode Choice

Abstract

For analysis of many transportation-related policies, it is useful to know the change which a particular policy would induce in the number of autos owned by households and the number of workers who take transit and auto to work. Models of households' choices of how many autos to own (called the auto ownership choice) and workers' choices of mode (called the work-trip mode choice) are intended to provide information about the effects of various policies. This information can be used, along with other information and ideas, in deciding which policies should be implemented. Previous studies of auto ownership and work-trip mode choices have generally been deficient in important ways.' First, most research has not confronted the simultaneity of the choices. Except for Lerman and Ben-Akiva (1975), past researchers have modelled either the auto ownership choice or the work-trip mode choice, not both. When modelling one of the choices, the simultaneity with the other choice has not been satisfactorily incorporated. Of the auto ownership models, Wharton (1977) included an explanatory variable defined as the number of autos the household uses for work trips, but did not adjust its estimation techniques to account for the endogeneity of this variable. None of the other auto ownership models included any variables relating to work-trip mode. In the work-trip mode-choice studies, more emphasis has been placed on the simultaneity of mode choice and auto ownership, but the results have been similarly unsatisfactory. Warner (1962), Lisco (1967), and Quarmby (1967) included auto ownership variables in their models with the (implicit) assumption that the number of autos is exogenous to the mode choice. On the other hand, Lave (1969) recognized that auto ownership is endogeneous and did not include an auto ownership variable on the grounds that his model formulation is a reduced-form equation. Train (1976b) used both approaches, estimating mode choice models with and without an auto ownership variable, and noted the problems inherent in each specification. Aside from the simultaneity problem, previous models have limited usefulness because they include only a few explanatory variables. This fact limits the number of policies and scenarios which can be analysed with the models. For example, in most mode choice models the time spent out of the vehicle (walking, waiting for a bus, and so on) is included as an explanatory variable. Since out-of-vehicle time is not decomposed into time spent waiting for transit and time spent walking to and from transit, the effect of policies trading off these two components cannot be analysed. (An example of such a policy is to place more buses on fewer bus lines, thus decreasing wait times and increasing walk times.) Analogously, most auto ownership models ignore the effect of family structure (household size and number of children, for example) on auto ownership decisions.2 The present study confronts these problems in the previous research. Models of mode choice and auto ownership are developed and estimated with explicit account taken of the interaction between the choices. Numerous explanatory variables are included so that a variety of policies and scenarios can be examined with the models. Throughout the study,