Comparison of Vehicle-Ownership Models

Abstract

Empirical studies on household car ownership have used two types of discrete choice modeling structures: ordered and unordered. In ordered response structures, such as the ordered logit and ordered probit models, the choice of the number of household vehicles arises from a unidimensional latent variable that reflects the propensity of a household to own vehicles. Unordered response structures are based on the random utility maximization principle, which assumes a household associates a utility value across different car ownership levels and chooses the one with the maximum utility. The most common unordered response models are the multinomial logit and probit models, but only the multinomial logit has been used in practical applications because of its simple structure and low computational requirements. Consensus among researchers on unordered or ordered structures is still lacking. Empirical studies have reported various models, including the multinomial logit, ordered logit, and ordered probit. An open question remains: Which model would better reflect households’ car ownership choices? This paper compares multinomial logit, ordered logit, and ordered probit car ownership models through a number of formal evaluation measures and empirical analysis of three data sets: the 2001 National Household Travel Survey for the Baltimore [Maryland] Metropolitan Area, the 2005 Dutch National Travel Survey, and the 2000 Osaka [Japan] Metropolitan Person Trip Data. Results show the multinomial logit model should be selected for modeling the level of household car ownership.