Empirical studies on household car ownership have used two types of modeling structures, the ordered and the unordered. In ordered structures such as the ordered logit and ordered probit models, the choice of the number of household-vehicles arises from a uni-dimensional latent index that reflects the propensity of a household to own vehicles. Unordered response models, on the other hand, are based on the random utility maximization principle, under which a household associates a utility value across different car ownership levels and chooses the one with the maximum utility. The multinomial logit and probit models are representatives of the unordered response models, but only the multinomial logit has been used extensively because of its simple structure and low computational requirements. Following Bhat and Pulugurta's (1998) comparative study between the multinomial logit and ordered logit models, consensus among researchers is still lacking and empirical studies have reported car ownership model based on the multinomial logit, ordered logit as well as ordered probit models. It is apparent that there is an open question to be addressed: Which of the aforementioned models would reflect better households' car ownership choices? This paper provides an empirical comparison of multinomial logit, ordered logit and ordered probit car ownership models by introducing a number of formal evaluation measures and using three datasets; the 2001 National Household Travel Survey (NHTS) for the metropolitan area of Baltimore, the 2005 Dutch National Travel Survey (NTS) and the 2000 Osaka Metropolitan Person Trip Data. Results show that the multinomial logit model is the one to be selected for modeling the level of household car ownership over ordered logit and ordered probit.
Abstract